BACKGROUND OF THE INVENTION

Glaucoma is a disease affecting over 2.2 million in the United States and is expected to affect 3.4 million by the year 2020 (Friedman et al., Arch Ophthalmol 122, 532 (2004)). Glaucoma is the second most prevalent cause of blindness with 60 million cases worldwide (Resnikoff et al., Bull World Health Organ 82, 844 (2004)). Glaucoma is characterized by progressive loss of vision, and is painless and asymptomatic until late in the disease. The pathophysiology of glaucoma is poorly understood. Therefore, an understanding of its pathogenesis and complications is needed to face the challenge of providing improved risk assessment and better treatment. Glaucoma is a heterogeneous group of eye disorders, which share a progressive degeneration of retinal ganglion cells and their axons, resulting in the appearance of optic disc and a concomitant pattern of visual loss. In most populations open angle glaucoma (OAG), characterized by painless loss of vision, constitutes the majority of glaucoma cases and is defined as a progressive loss of optic disc neuroretinal rim tissue and consequent excavation of the optic disc with corresponding loss of visual field (Foster, R. et al., Br J Ophthalmol 86, 238 (2002); Jonasson, F. et ai, Eye 17, 747 (2003)). Open angle glaucoma may be divided into primary open angle glaucoma (POAG) and secondary glaucoma. POAG is without an identifiable cause of aqueous outflow resistance, whereas in secondary glaucoma the outflow resistance is of a known cause and in exfoliation glaucoma (XFG) it is considered to be due to the exfoliative material from which the exfoliation syndrome (XFS) derives its name. POAG is often associated with an elevated intraocular pressure (IOP) (Hollows & Graham, Br J Ophthalmol 50, 570 (1966)). POAG is highly familial and age-related (Hewitt, et al, CHn Experiment Ophthalmol 34, 472 (2006)), and its risk indicators, vertical optic disc, vertical optic cup, vertical optic cup-to-disc ration and IOP parameters are have high heritability (Klein & Lee, Invest Ophthalmol Vis Sci 45, 59 (2004)).

A number of genetic loci for congenital and Juvenal glaucoma have been reported (Hewitt et al., CHn Experiment Ophthalmol 34, 472 (2006)). However, in adult glaucoma only the MYOC gene, encoding for myocillin, has been shown to confer considerable impact to the disease (Stone et al., Science 275, 668 (1997)). The MYOC has a mutation prevalence of 2-4% in POAG, with over 40 different mutations reported to date, and over 10% in juvenile open angle glaucoma (JOAG). Mutations in the MYOC gene cause dysfunctions in the trabecular meshwork, and genotype-phenotype correlations are strong.

No common genetic variants are known that predispose to common forms of glaucoma, in particular primary open angle glaucoma (POAG). Common genetic variants predisposing to exfoliation glaucoma (XFG) have however been discovered (Thorleifsson, G. et al. Science 317: 1397-1400 (2007)). The risk of developing glaucoma increases with several known risk factors. Thus, increased intraocular pressure with increasing age is a major contributor to increased risk of developing glaucoma (Sommer et al., Arch. Ophthalmol. 109: 1090-95 (1991); Mitchell et al., Ophthalmol. 103: 1661-69 (1996)). Other risk factors include visual field abnormalities that are observed in otherwise baseline visual field examinations (Kass et al, Arch. Ophthalmol. 120:701-13 (2002); Gordon et al., Arch Ophthalmol. 120: 714-20 (2002)), high myopia and family history of glaucoma (Wolfs et ai, Arch Ophthalmol 116: 1640-45 (1998); Tielsch et al., Arch Ophthalmol. 112: 69-73 (1994)), thin cornea (central corneal thickness of less than 556μm) and a vertical or horizontal cup-to-disc ratio of greater than 0.4 (Kass et al, Arch. Ophthalmol. 120:701-13 (2002); Gordon et al., Arch Ophthalmol. 120: 714-20 (2002)). More recently, additional risk factors have been identified, including systemic hypertension, cardiovascular disease, migraine headache, and peripheral vasospasm.

Genetic risk is conferred by subtle differences in the genome among individuals in a population. Variations in the human genome are most frequently due to single nucleotide polymorphisms (SNPs), although other variations are also important. SNPs are located on average every 1000 base pairs in the human genome. Accordingly, a typical human gene containing 250,000 base pairs may contain 250 different SNPs. Only a minor number of SNPs are located in exons and alter the amino acid sequence of the protein encoded by the gene. Most SNPs may have little or no effect on gene function, while others may alter transcription, splicing, translation, or stability of the mRNA encoded by the gene. Additional genetic polymorphisms in the human genome are caused by insertions, deletions, translocations or inversion of either short or long stretches of DNA. Genetic polymorphisms conferring disease risk may directly alter the amino acid sequence of proteins, may increase the amount of protein produced from the gene, or may decrease the amount of protein produced by the gene. As genetic polymorphisms conferring risk of common diseases are uncovered, genetic testing for such risk factors is becoming increasingly important for clinical medicine. Examples are apolipoprotein E testing to identify genetic carriers of the apoE4 polymorphism in dementia patients for the differential diagnosis of Alzheimer's disease, and of Factor V Leiden testing for predisposition to deep venous thrombosis. More importantly, in the treatment of cancer, diagnosis of genetic variants in tumor cells is used for the selection of the most appropriate treatment regime for the individual patient. In breast cancer, genetic variation in estrogen receptor expression or heregulm type 2 (Her2) receptor tyrosine kinase expression determine if anti-estrogenic drugs (tamoxifen) or anti-Her2 antibody (Herceptin) will be incorporated into the treatment plan. In chronic myeloid leukemia (CML) diagnosis of the Philadelphia chromosome genetic translocation fusing the genes encoding the Bcr and AbI receptor tyrosine kinases indicates that Gleevec (STI571), a specific inhibitor of the Bcr-Abl kinase should be used for treatment of the cancer. For CML patients with such a genetic alteration, inhibition of the Bcr- Abl kinase leads to rapid elimination of the tumor cells and remission from leukemia.

Furthermore, genetic testing services are now available, providing individuals with information about their disease risk based on the discovery that certain SNPs have been associated with risk of many of the common diseases.

SUMMARY OF THE INVENTION The present invention relates to applications of the surprising finding that certain genetic markers on chromosome 7q31 are predictive of risk of glaucoma in humans. The invention provides diagnostic methods, kits, medium and apparati useful for determining risk of glaucoma, as well as therapeutic uses and treatments that involve use of markers in the human caveolln-1 and/or caveolin-2 genes. In a first aspect, the invention provides a method of determining a susceptibility to glaucoma in a human individual, the method comprising (i) obtaining sequence data about a human individual identifying at least one allele of at least one polymorphic marker, wherein different alleles of the at least one polymorphic marker are associated with different susceptibilities to glaucoma in humans, and (ii)determining a susceptibility to glaucoma from the sequence data, wherein the at least one polymorphic marker is a marker associated with the human caveolin-1 gene and/or the human caveolin-2 gene. In certain embodiments, markers that are associated with the human caveolin-1 and/or caveolin-2 genes are markers that are in linkage

disequilibrium (LD) with at least one of the caveolin-1 and/or caveolin-2 genes. Markers in linkage disequilibrium with these genes can for example be markers that are in linkage disequilibrium with at least one marker within the genes.

Identifying at least one allele of a marker in general means that it is determined whether a particular allele is present or absence at a particular position in the sequence. In certain embodiments, the sequence data is nucleic acid sequence data. In certain other embodiments, the sequence data is amino acid sequence data. For single nucleotide polymorphisms (SNPs), this means determining the identity of the identity of a nucleotide at a particular position in the genome of an individual. In one embodiment, identifying at least one allele has the meaning that the absence of presence of at least one allele is determined. For example, the absence or presence of allele A of the marker rs4236601 (SEQ ID NO:2) may be determined.

The invention also relates to a method of determining a susceptibility to glaucoma in a human individual, the method comprising (i) obtaining sequence data about a human individual identifying at least one allele of at least one polymorphic marker, wherein different alleles of the at least one polymorphic marker are associated with different susceptibilities to glaucoma, and (M) determining a susceptibility to glaucoma from the sequence data, wherein the at least one polymorphic marker is selected from the group consisting of rs4236601, and markers in linkage disequilibrium therewith. In a related aspect, the invention provides a method for determining a susceptibility to glaucoma in a human individual, comprising (i) obtaining a nucleic acid sample from the individual; and (ii) determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual, wherein the at least one polymorphic marker is selected from the group consisting of rs4236601, and markers in linkage disequilibrium therewith, and wherein determination of the presence of the at least one allele is indicative of a susceptibility to glaucoma. Yet another related aspect relates to a method of assessing a susceptibility to glaucoma in a human individual, comprising (i) obtaining sequence information about the individual for at least one polymorphic marker selected from the group consisting of rs4236601, and markers in linkage disequilibrium therewith, wherein different alleles of the at least one polymorphic marker are associated with different

susceptibilities to glaucoma in humans, and (ii) identifying the presence or absence of at least one allele in the at least one polymorphic marker that correlates with increased occurrence of glaucoma in humans; wherein determination of the presence of the at least one allele identifies the individual as having elevated susceptibility to glaucoma, and wherein determination of the absence of the at least one allele identifies the individual as not having the elevated

susceptibility. Yet another aspect relates to a method of determining a susceptibility to glaucoma in a human individual, the method comprising (i) obtaining sequence data about a human individual identifying at least one allele of at least one polymorphic marker, wherein different alleles of the at least one polymorphic marker are associated with different

susceptibilities to glaucoma in humans, and (ii) determining a susceptibility to glaucoma from the sequence data, wherein the at least one polymorphic marker is a marker within LD block C07 as set forth in SEQ ID NO: 1.

The invention further provides methods for identifying markers that are useful for determining risk of glaucoma in humans. Thus, in one aspect, the invention provides a method of identification of a marker for use in assessing susceptibility to glaucoma in human individuals, the method comprising (i) identifying at least one polymorphic marker in linkage disequilibrium with rs4236601; (ii) obtaining sequence information about the at least one polymorphic marker in a group of individuals diagnosed with glaucoma; and (iii) obtaining sequence information about the at least one polymorphic marker in a group of control individuals; wherein

determination of a significant difference in frequency of at least one allele in the at least one polymorphism in individuals diagnosed with glaucoma as compared with the frequency of the at least one allele in the control group is indicative of the at least one polymorphism being useful for assessing susceptibility to glaucoma. In certain embodiments, determination of an increase in frequency of the at least one allele in the at least one polymorphism in individuals diagnosed with glaucoma, as compared with the frequency of the at least one allele in the control group, is indicative of the at least one polymorphism being useful for assessing increased susceptibility to glaucoma; and determination of a decrease in frequency of the at least one allele in the at least one polymorphism in individuals diagnosed with glaucoma, as compared with the frequency of the at least one allele in the control group, is indicative of the at least one polymorphism being useful for assessing decreased susceptibility to, or protection against, glaucoma. In certain applications of the invention, genetic markers are useful for predicting medical prognosis and/or response. Thus, in one aspect, the invention further provides a method of predicting prognosis of an individual diagnosed with glaucoma, the method comprising: (i) obtaining sequence data about a human individual identifying at least one allele of at least one polymorphic marker selected from the group consisting of rs4236601, and markers in linkage disequilibrium therewith, wherein different alleles of the at least one polymorphic marker are associated with different susceptibilities to glaucoma in humans, and (ii) predicting prognosis of glaucoma from the sequence data. The invention also provides a method of assessing probability of response of a human individual to a therapeutic agent for preventing, treating and/or ameliorating symptoms associated with glaucoma comprising (i) obtaining sequence data about a human individual identifying at least one allele of at least one polymorphic marker selected from the group consisting of rs4236601, and markers in linkage disequilibrium therewith, wherein different alleles of the at least one polymorphic marker are associated with different probabilities of response to the therapeutic agent in humans, and (ii) determining the probability of a positive response to the therapeutic agent from the sequence data.

Kits are also provided. In one such aspect, the kit comprises (ι) reagents for selectively detecting at least one allele of at least one polymorphic marker in the genome of the individual, wherein the polymorphic marker is selected from the group consisting of rs4236601, and markers in linkage disequilibrium therewith, and (ii) a collection of data comprising correlation data between the at least one polymorphism and susceptibility to glaucoma. The collection of data may be stored on any suitable medium. In one embodiment, the data is on a computer- readable medium.

The invention also provides use of probes for manufacturing diagnostic reagents for diagnosing, or aiding in the diagnosis of, glaucoma. In one such aspect, the probe is capable of hybridizing to a segment of a nucleic acid with sequence as set forth in SEQ ID NO: 1, and wherein the segment is 15-500 nucleotides in length. The probe may suitable comprise a polymorphic site, as set forth herein.

Computer-implemented aspects are also provided. One aspect relates to a computer-readable medium having computer executable instructions for determining susceptibility to glaucoma, the computer readable medium comprising (i) data indicative of at least one polymorphic marker; and (ii) a routine stored on the computer readable medium and adapted to be executed by a processor to determine risk of developing glaucoma for the at least one polymorphic marker; wherein the at least one polymorphic marker is selected from the group consisting of rs4236601, and markers in linkage disequilibrium therewith. Another computer-implemented aspect relates to an apparatus (e.g., a computer) for determining a genetic indicator for glaucoma in a human individual, comprising (i) a processor; (ii) a computer readable memory having computer executable instructions adapted to be executed on the processor to analyze genotype data for at least one human individual with respect to at least one polymorphic marker associated with the human caveolin-1 gene and/or the human caveolin-2 gene, and generate an output based on the genotype data, wherein the output comprises a risk measure for the at least one marker as a genetic indicator of glaucoma for the human individual. The polymorphic markers described herein may also be useful for predicting whether certain individuals are likely to develop increased intraocular pressure when treated with a glucocorticoid therapeutic agent. Thus, in one aspect, the invention provides a method of determining whether a human individual is at risk for developing elevated intraocular pressure and/or glaucoma as a complication of being treated with a glucocorticoid therapeutic agent, the method comprising obtaining sequence data about a human individual identifying at least one allele of at least one polymorphic marker selected from the group consisting of rs4236601, and markers in linkage disequilibrium therewith, wherein different alleles of the at least one polymorphic marker are associated with different susceptibilities to glaucoma in humans; wherein determination of the presence of the at least one allele is indicative of an increased risk of developing elevated intraocular pressure and/or glaucoma as a complication of being treated with a glucocorticoid therapeutic agent. In preferred embodiments, the glucocorticoid therapeutic agent is selected from the group consisting of the agents set forth in the Agent Table II herein.

The invention also provides methods of treatment. In one aspect, a method of prophylaxis therapy for glaucoma is provided, comprising (a) selecting a human subject at risk for glaucoma; and (b) administering to the subject a therapeutically effective amount of a composition comprising a therapeutic agent for glaucoma, wherein the selecting comprises (i) analyzing sequence data about the human subject identifying at least one allele of at least one polymorphic marker associated with the human caveolin 1 gene and/or the human caveolin 2 gene, wherein different alleles of the at least one polymorphic marker are associated with different

susceptibilities to glaucoma in humans, (ii) determining a susceptibility to glaucoma from the sequence data, and (iii) selecting for prophylaxis therapy a human individual who is at increased risk for glaucoma. In certain embodiments, the therapeutic agent is selected from the group consisting of the agents set forth in the Agent Table I herein. Preferably, the at least one polymorphic marker is selected from rs4236601, and markers in linkage disequilibrium therewith.

Also provided is a therapeutic agent for glaucoma for treating a human subject with a variant associated with the human caveolin-1 gene and/or the human caveolin-2 gene that correlates with an increased risk for glaucoma in humans. Alternatively, a use of a therapeutic agent for glaucoma is provided, for the manufacture of a medicament for treating glaucoma in a human subject with a variant associated with the human caveolin-1 gene and/or the human caveolin-2 gene that correlates with an increased risk for glaucoma.

Certain embodiments of the invention relate to marker rs4236601, or markers in linkage disequilibrium therewith. Certain embodiments relate to markers within LD block C07, as set forth in SEQ ID NO: 1. Certain embodiments of the invention relate to primary open angle glaucoma (POAG). Thus, in such embodiments, the glaucoma is primary open angle glaucoma.

It should be understood that all combinations of features described herein are contemplated, even if the combination of feature is not specifically found in the same sentence or paragraph herein. This includes in particular the use of all markers disclosed herein, alone or in combination, for analysis individually or in haplotypes, in all aspects of the invention as described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features and advantages of the invention will be apparent from the following more particular description of preferred embodiments of the invention.

FIG 1 provides a diagram illustrating a computer-implemented system utilizing risk variants as described herein.

FIG 2 shows the human chromosome 7q31.2 region that contains variants that associate with risk of glaucoma and that also contains the human caveolin-1 and caveolin-2 genes.

FIG 3 (A) The pair-wise correlation structure in a 600 kb interval (115.65 - 116.25 Mb, NCBI B36) on chromosome 7. The upper plot shows pair-wise D' for 533 common SNPs (with minor allele frequency (MAF) > 5%) from the Utah (CEU) HapMap(r22) samples. The lower plot shows the corresponding r ² values. (B) Estimated sex-averaged recombination rates (saRR) in cM / Mb from the HapMap Phase II data. (C) Location of known genes in the region. (D) Schematic view of the association with POAG for all 70 markers tested in the GWA in the region. All panels use the same horizontal scale shown in panel D.

DETAILED DESCRIPTION Definitions

Unless otherwise indicated, nucleic acid sequences are written left to right in a 5' to 3' orientation. Numeric ranges recited within the specification are inclusive of the numbers defining the range and include each integer or any non-integer fraction within the defined range. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by the ordinary person skilled in the art to which the invention pertains.

The following terms shall, in the present context, have the meaning as indicated: A "polymorphic marker", sometime referred to as a "marker", as described herein, refers to a genomic polymorphic site. Each polymorphic marker has at least two sequence variations characteristic of particular alleles at the polymorphic site. Thus, genetic association to a polymorphic marker implies that there is association to at least one specific allele of that particular polymorphic marker. The marker can comprise any allele of any variant type found in the genome, including SNPs, mini- or microsatellites, translocations and copy number variations (insertions, deletions, duplications). Polymorphic markers can be of any measurable frequency in the population. For mapping of disease genes, polymorphic markers with population frequency higher than 5-10% are in general most useful. However, polymorphic markers may also have lower population frequencies, such as 1-5% frequency, or even lower frequency, in particular copy number variations (CNVs). The term shall, in the present context, be taken to include polymorphic markers with any population frequency.

An "allele" refers to the nucleotide sequence of a given locus (position) on a chromosome. A polymorphic marker allele thus refers to the composition (i.e., sequence) of the marker on a chromosome. Genomic DNA from an individual contains two alleles (e.g., allele-specific sequences) for any given polymorphic marker, representative of each copy of the marker on each chromosome. An allele is represented by its identity in the context of a marker, e.g., rs4236601[A], rs4236601 A, A rs4236601, or rs4236601 allele A, which are all equivalent representations of the identity of an A allele at marker rs4236601. Sequence codes for nucleotides used herein are: A = 1, C = 2, G = 3, T = 4. For microsatellite alleles, the CEPH sample (Centre d'Etudes du Polymorphisme Humain, genomics repository, CEPH sample 1347- 02) is used as a reference, the shorter allele of each microsatellite in this sample is set as 0 and all other alleles in other samples are numbered in relation to this reference. Thus, e.g. , allele 1 is 1 bp longer than the shorter allele in the CEPH sample, allele 2 is 2 bp longer than the shorter allele in the CEPH sample, allele 3 is 3 bp longer than the lower allele in the CEPH sample, etc., and allele -1 is 1 bp shorter than the shorter allele in the CEPH sample, allele -2 is 2 bp shorter than the shorter allele in the CEPH sample, etc.

Sequence conucleotide ambiguity as described herein is as proposed by IUPAC-IlIB. These codes are compatible with the codes used by the EMBL, GenBank, and PIR databases.

A nucleotide position at which more than one sequence is possible in a population (either a natural population or a synthetic population, e.g., a library of synthetic molecules) is referred to herein as a "polymorphic site". A "Single Nucleotide Polymorphism" or "SNP" is a DNA sequence variation occurring when a single nucleotide at a specific location in the genome differs between members of a species or between paired chromosomes in an individual. Most SNP polymorphisms have two alleles. Each individual is in this instance either homozygous for one allele of the polymorphism (i.e. both chromosomal copies of the individual have the same nucleotide at the SNP location), or the individual is heterozygous (i.e. the two sister chromosomes of the individual contain different nucleotides). The SNP nomenclature as reported herein refers to the official Reference SNP (rs) ID identification tag as assigned to each unique SNP by the National Center for Biotechnological Information (NCBI).

A "variant", as described herein, refers to a segment of DNA that differs from the reference DNA. A "marker" or a "polymorphic marker", as defined herein, is a variant. Alleles that differ from the reference are referred to as "variant" alleles.

A "microsatellite" is a polymorphic marker that has multiple small repeats of bases that are 2-8 nucleotides in length (such as CA repeats) at a particular site, in which the number of repeat lengths varies in the general population. An "indel" is a common form of polymorphism comprising a small insertion or deletion that is typically only a few nucleotides long.

A "haplotype," as described herein, refers to a segment of genomic DNA that is characterized by a specific combination of alleles arranged along the segment. For diploid organisms such as humans, a haplotype comprises one member of the pair of alleles for each polymorphic marker or locus along the segment. In a certain embodiment, the haplotype can comprise two or more alleles, three or more alleles, four or more alleles, or five or more alleles. Haplotypes are described herein in the context of the marker name and the allele of the marker in that haplotype, e.g., "1 rs4236601" refers to the 1 allele of marker rs4236601 being in the haplotype, and is equivalent to "rs4236601 allele 1". Furthermore, allelic codes in haplotypes are as for individual markers, i.e. I = A, 2 = C, 3 = G and 4 = T. The term "susceptibility", as described herein, refers to the proneness of an individual towards the development of a certain state {e.g., a certain trait, phenotype or disease), or towards being less able to resist a particular state than the average individual . The term encompasses both increased susceptibility and decreased susceptibility. Thus, particular alleles at polymorphic markers and/or haplotypes of the invention as described herein may be characteristic of increased susceptibility (i.e., increased risk) of glaucoma, as characterized by a relative risk (RR) or odds ratio (OR) of greater than one for the particular allele or haplotype. Alternatively, the markers and/or haplotypes of the invention are characteristic of decreased susceptibility (i.e., decreased risk) of glaucoma, as characterized by a relative risk of less than one.

The term "and/or" shall in the present context be understood to indicate that either or both of the items connected by it are involved. In other words, the term herein shall be taken to mean "one or the other or both".

The term "look-up table", as described herein, is a table that correlates one form of data to another form, or one or more forms of data to a predicted outcome to which the data is relevant, such as phenotype or trait. For example, a look-up table can comprise a correlation between allelic data for at least one polymorphic marker and a particular trait or phenotype, such as a particular disease diagnosis, that an individual who comprises the particular allelic data is likely to display, or is more likely to display than individuals who do not comprise the particular allelic data. Look-up tables can be multidimensional, i.e. they can contain information about multiple alleles for single markers simultaneously, or they can contain information about multiple markers, and they may also comprise other factors, such as particulars about diseases diagnoses, racial information, biomarkers, biochemical measurements, therapeutic methods or drugs, etc.

A "computer-readable medium", is an information storage medium that can be accessed by a computer using a commercially available or custom-made interface. Exemplary computer- readable media include memory (e.g., RAM, ROM, flash memory, etc.), optical storage media (e.g., CD-ROM), magnetic storage media {e.g., computer hard drives, floppy disks, etc.), punch cards, or other commercially available media. Information may be transferred between a system of interest and a medium, between computers, or between computers and the computer- readable medium for storage or access of stored information. Such transmission can be electrical, or by other available methods, such as IR links, wireless connections, etc. A "nucleic acid sample" as described herein, refers to a sample obtained from an individual that contains nucleic acid (DNA or RNA). In certain embodiments, i.e. the detection of specific polymorphic markers and/or haplotypes, the nucleic acid sample comprises genomic DNA. Such a nucleic acid sample can be obtained from any source that contains genomic DNA, including a blood sample, sample of amniotic fluid, sample of cerebrospinal fluid, or tissue sample from skin, muscle, buccal or conjunctival mucosa, placenta, gastrointestinal tract or other organs.

The term "glaucoma therapeutic agent" refers to an agent that can be used to ameliorate or prevent symptoms associated with glaucoma.

The term "glaucoma-associated nucleic acid", as described herein, refers to a nucleic acid that has been found to be associated to glaucoma. This includes, but is not limited to, the markers and haplotypes described herein and markers and haplotypes in strong linkage disequilibrium (LD) therewith. In one embodiment, a glaucoma-associated nucleic acid refers to an LD-block found to be associated with glaucoma through at least one polymorphic marker located within the LD block.

The term "antisense agent" or "antisense oligonucleotide" refers, as described herein, to molecules, or compositions comprising molecules, which include a sequence of purine an pyrimidine heterocyclic bases, supported by a backbone, which are effective to hydrogen bond to a corresponding contiguous bases in a target nucleic acid sequence. The backbone is composed of subunit backbone moieties supporting the purine and pyrimidine hetercyclic bases at positions which allow such hydrogen bonding. These backbone moieties are cyclic moieties of 5 to 7 atoms in size, linked together by phosphorous-containing linkage units of one to three atoms in length. In certain preferred embodiments, the antisense agent comprises an oligonucleotide molecule.

The term "LD Block C07", as described herein, refers to the Linkage Disequilibrium (LD) block on Chromosome 7 between position 115,779,669 and 116,000,047 of NCBI (National Center for Biotechnology Information) Build 36 (SEQ ID NO: 1).

Variants associated with human caveolin-1 and human caveolin-2 are associated with glaucoma

The present inventors have for the first time shown that variants on chromosome 7q31 associated with human caveolin-1 and caveolin-2 are indicative of risk of glaucoma in humans. As described in more detail herein, a segment on chromosome 7q31 has been found to associate with risk of glaucoma. Polymorphic markers in this region that show association to glaucoma include rs4236601 (SEQ ID NO:2), rs8940 and rsl052990 (SEQ ID NO:3), which are all strongly associated with risk of glaucoma. Further variants associated with risk of glaucoma are shown in Table 5 herein. Particular alleles at these markers {e.g., allele A of marker rs4236601, allele G of rs8940 and allele G of marker rsl052990) are found more frequently in individuals with glaucoma than in the general population. These markers are therefore predictive of risk of glaucoma, i.e. individuals carrying the particular at-risk alleles are at increased risk of developing glaucoma compared with the general population. Markers that are in linkage disequilibrium with these markers are also predictive of risk of glaucoma, as described in more detail herein. The signal in the 7q31 region appears to be captured by marker rs4236601. In other words, other markers in the regions showing association to glaucoma appear to do so because they are in linkage disequilibrium with rs4236601. The association in the region is thus tagged by

I-S4236601.

The LD block containing rs4236601 and correlated markers contains two known genes CAVl and CAV2 and few uncharacterized ESTs. CAVl and CAV2 are members of the caveolin gene family that also includes the muscle-specific CAV3 gene. CAVl and CAV2 are expressed in most human cell types, including tissues such as the scleral spur cells (Tamm, E. R., Exp Eye Res 88:648-55 (2009), trabecular meshwork (Gonzalez, P. et al. Invest Ophthalmol Vis Sci 41:3678-93 (2000)) and retinal ganglion cells (Berta, A. I., et al. MoI Vis 13:881-6 (2007)) of the eye, but alterations in these tissues are thought to play a role in the pathology of POAG, leading to loss of retinal ganglion cell axons, along with supportive glia and vasculature. Interestingly, under

experimental conditions, CAVl showed consistent up-regulation in the trabecular meshwork after one hour of increased IOP (Borras, T., Prog Rβtm Eye Res 22:435-63 (2003)).

Caveolae are pits of 60-80nm with a flask shape, and are localized in the plasma membrane (reviewed in Parton, R. G. & Simons, K., Nat Rev MoI Cell Biol 8: 185-194 (2007)). Caveolins are major structural components of the caveolae; caveolin 1 appears to be essential for formations of caveolae (Couet, J., et al. Adv Drug Deliv Rev 49: 223-235 (2001)). Caveolae are implicated in a variety of cellular functions, including endoctyosis, transcytosis, calcium signalling and other signal transduction events. Caveolae have also been implicated in several human diseases, including cancer, atherosclerosis and vasculoproliferative diseases, cardiac hypertrophy and heart failure, degenerative muscular dystrophies and diabetes mellitus (Schwenke, C, et al. Cardiovasc Res 70:42-49 (2006)). Knockout experiments in mice lead to development of dilated cariomyopathy with an enlarged left ventricular diameter, wall thinning and decreased contractility, and Cav-1 -/- (homozygous knockouts) display markedly increased pulmonary artery pressure and hypertrophied right ventricles (Zhao, Y-J., et al. Proc Natl Acad Sci USA 99: 11375-80 (2002)).

Three human caveolin genes are known, caveolin-1, caveolιn-2, both localized on chromosome 7q31, and caveolin-3, localized on chromosome 3p26. The region on chromsome 7q that harbors the caveolin-1 and caveolin-2 genes is frequently lost in malignant tumors. However, variants in these genes have to date not been associated with any common human trait.

The CAVl and CAV2 genes are involved in the formation of caveolae, specialized invaginations of the plasma membrane, rich in cholesterol and other lipids and take part in transcytosis.

However, the role of caveolae in signal transduction through interaction with signaling molecules has been most extensively studied. Caveolae recruit and compartmentalize various signaling molecules through direct physical interaction mediated by the scaffolding domain in CAVl (CSD). This interaction generally results in inhibition of signaling (Couet, ]., et al. Adv Drug Deliv Rev 49:223-35 (2001); Hnasko, R. & Lisanti, M. P., MoI Interv 3:445-64 (2003); Patel, H. H., et al. Annu Rev Pharmacol Toxicol 48: 359-91 (2008); Parat, M.O. Int Rev Cell MoI Biol. 273: 117-62 (2009)). Interestingly, caveolins have been suggested as regulators of adult neural stem cell proliferation as evident by increased proliferation of adult neural stem cells in Cav-1, Cav-2 and Cav-3 knockout mice (Jasmin, J. F. et al. Cell Cycle 8: 3978-83 (2009)). The regulation by CAVl of the endothelial nitric-oxide synthase (eNOS), an enzyme that produces nitric oxide (NO), is well documented, but their interaction leads to eNOS inactivation (Ju, H., et al. J Biol Chem

272: 18522-5 (1997); Garcia-Cardena, G. et al. J Biol Chem 272:25437-40 (1997)) and reduced NO production. NO plays an important role in the regulation of many physiological functions in the cardiovascular system and the central and peripheral nervous systems. NO produced in excessive amounts exerts cytotoxicity, neurodegeneration, apoptotic cell death, and circulatory failure. In addition to NO signaling, CAVl has also been shown to be an important regulator of TGF-β signaling through interaction with TGF-β type 1 receptor. Both NO and TGF-β signaling have been implicated as culprits in the pathogenesis of POAG (Fuchshofer, R. & Tamm, E. R. Exp Eye Res 88:683-8 (2009); Toda, N. & Nakanishi-Toda, M. Prog Retin Eye Res 26: 205-38 (2007)).

It is notable that while rs4236601[A] confers relative risk of 1.27 for POAG in populations of European descent it does not seem to have major effects on known risk factors for POAG such as IOP and central corneal thickness suggesting that the variant acts through biochemical pathways independent of those associated with IOP or central corneal thickness (CCT). Furthermore, it does not act through diseases such as T2D, hypertension or myopia that are all independent risk factors of POAG. The CAVl and CAV2 genes with their involvement in regulation of NO and/or TGF-β signaling raises the possibility of new prevention and treatment options for POAG. The frequency of the POAG variant differs between ethnicities; in particular its frequency is much lower in East Asian populations while the estimated risk is higher than in individuals of European descent. These data highlight the importance of considering the genetic component of the risk of common complex diseases in the context of geographic ancestry.

The finding that common variants associated with the caveoliπ-1 and caveoliπ-2 genes are significantly associated with risk of glaucoma is greatly surprising. The present invention relates to this surprising finding, which opens up a number of diagnostic applications utilizing variants as described herein. Furthermore, the invention provides possibilities for therapeutic intervention for glaucoma, as described in more detail in the following.

Methods of determining susceptibility to glaucoma

Accordingly, in one aspect the invention provides a method of determining a susceptibility to glaucoma in a human individual, the method comprising analyzing sequence data about a human individual for at least one polymorphic marker associated with the human caveolin-1 gene and/or the human caveolin-2 gene, wherein different alleles of the at least one polymorphic marker are associated with different susceptibilities to glaucoma in humans, and determining a susceptibility to glaucoma from the sequence data. In certain embodiments, the glaucoma is primary open angle glaucoma (POAG). Certain embodiments relate to normal pressure glaucoma, i.e. glaucoma in the absence of elevated intraocular pressure.

In certain embodiments, the sequence data is nucleic acid sequence data. Nucleic acid sequence data identifying particular alleles of polymorphic markers is sometimes also referred to as genotype data. Nucleic acid sequence data can be obtained for example by analyzing sequence of the at least one polymorphic marker in a biological sample from the individual. Alternatively, nucleic acid sequence data can be obtained in a genotype dataset from the human individual and analyzing sequence of the at least one polymorphic marker in the dataset. Such analysis in certain embodiments comprises determining the presence or absence of a particular allele of specific polymorphic markers. Identification of particular alleles in general terms should be taken to mean that determination of the presence or absence of the allele(s) is made. Thus, the analyzing may in certain embodiments relate to determining the presence or absence of at least one allele of the at least one polymorphic marker. Usually, determination of both allelic copies in the genome of an individual is performed, by determining the occurrence of all possible alleles of the particular polymorphism in a particular individual (for SNPs, each of the two possible nucleotides possible for the allelic site). It is also possible to determine whether only particular alleles are present or not. For example, in certain embodiments, determination of the presence or absence of certain alleles that have been shown to associate with risk of glaucoma is made, but not necessarily other alleles of the particular marker, and a determination of susceptibility is made based on such determination. In certain embodiments, sequence data about at least two polymorphic markers is obtained. In certain embodiments, obtaining nucleic acid sequence data comprises a method that includes at least one procedure selected from amplifying nucleic acid from the biological sample; and performing a hybridization assay using a nucleic acid probe and nucleic acid, or amplified nucleic acid, from the sample.

In certain embodiments, the at least one polymorphic marker associated with the human caveolin-1 gene and/or the human caveolin-2 gene is a marker within LD block C07, as set forth in SEQ ID NO: 1. In certain embodiments, the marker is selected from the group consisting of rs4236601, and markers in linkage disequilibrium therewith.

In particular embodiments, markers in linkage disequilibrium with rs4236601 are suitably selected from the group consisting of rsl0808180, s.115639367, rs3807958, rsl7138624, rsll80289, rsll982034, rsl633714, s.115809902, s.115812308, rsll80293, rsll772856, s.115822680, s.115822757, rsl2535567, s.115823136, rsl633731, s.115823881, rsll80286, rs58217805, s.115829658, rsl0252986, rsl633728, rsl918923, rsl918924, rsl0247635, rsl0247800, rsl0226352, rslO255816, s.115837158, s.115837213, s.115837220, s.115837228, s.115837231, rslO237417, s.115844941, s.115845073, s.115845156, rs6952334, rs66910042, s.115852616, s.115853434, rsl0256207, rsl0228039, rsl0227962, rs4540346, rsl7138684, rs6963408, rslO282315, rslO261897, rs6466577, rslO225153, s.115869741, rsll971849, rslO215761, rslO215954, rs7796627, s.115874386, s.115875537, s.115876493, rs73454998, rs73454999, rs4273775, rs9656238, rs73455001, s.115885256, rs35421698, s.115887401, s.115890028, rs768107, s.115897291, s.115898314, rs717957, s.115900980, s.115903500, S.115904029, s.115904171, s.115904290, rs926197, s.115906984, s.115907049, rs879211, rs6976316, s.115913401, s.115914118, s.115914208, s.115914539, rsl2538592, s.115916238, s.115916241, s.115916324, rs6954077, s.115916526, s.115916936, rsl0282556, s.115918221, rsl0487350, rslO228178, rs6973611, rs6974053, rsl7515508, rsl0273272, s.115921458, s.115922252, s.115922359, rsl7138755, rsl7138756, s.115922928, s.115924118, s.115924242, rsl7138765, rs4730742, rs2191500, s.115926151, s.115926168, s.115926213, rs2270188, s.115927852, s.115928000, rs28503222, rs3779511, s.115929066, s.115929696, s.115929698, rsl l980719, rsl0233003, s.115931038, rs67933359, rsl0253097, rsl2668473, rs28587043, rsl0271007, s.115933173, rs4730743, rs8940, rsl0278782, rsl0249656, s.115934973, rs4727833, rsl052990, rsl0224685, rsl7515960, s.115937080, rsl2536639, rsl0258482, rsl0262524, rs6466579, rslO281637, rs3919515, rs2024211, rslO281661, rsl7588172, s.115941422, rs6466580, rs6969706, s.115943204, rsl0261304, s.115943215, rs59454355, rs7811851, rs7795510, rsl2540035, s.115947197, rs4730745, rs55883210, rs6950798, rs6950964, rsl0227696, rslO257125, s.115949855, s.115950221, rs4385407, s.115951190, rs926198, rs917664, rs4730748, rsll973363, s.115957431, rs3779512, rs9649394, rslO256914, s.115967515, rs4730751, rsl0270569, rslO241283, rs66916956, rs9886215, rs9886219, rs2109516, rslO22436, s.115984089, rs6466587, rslO49314, rs8713, rs6867, rslO49337, s.115989209, rs6961215, rs6961388, s.115990167, s.115990177, rsl0280730, rsl0232369, rs6959106, rs7802124, rs7802438, rsll979486, rsl0273326, s.115996983, s.115996984, rs7801180, rsl2535567, rsl633731, rsll80286, rsl0252986, rsl633728, rsl918923, rsl918924, rsl0247635, rsl0247800, rslO237417, rs6952334, rsl0228039, rsl0227962, rs4540346, rsl7138684, rs6963408, rslO282315, rs6466577, rs7796627, rs4273775, rs9656238, rs768107, rs717957, rs926197, rs879211, rs6976316, rsl2538592, rs6954077, rsl0487350, rslO228178, rsl7138749, rsl7515508, rsl0273272, rsl7138756, rsl7138765, rs4730742, rs2270188, rsll980719, rsl0253097, rsl0271007, rs4730743, rs8940, rsl0278782, rs4727833, rsl052990, rsl7515960, rsl0258482, rsl0262524, rs6466579, rslO281637, rs3919515, rs2024211, rsl7588172, rs6466580, rs6969706, rsl0227696, rs4236601, rs926198, rs917664, rs4730748, rs3779512, rs9649394, rslO256914, rs4730751, rsl0270569, rs9886215, rs9886219, rs2109516, rs6466587, rslO49314, rs8713, rs6867, rs6961215, rs6961388, rsl0280730, and rsl0232369, which are the markers listed in Table 1 (A and B).

In certain embodiments, markers in linkage disequilibrium with rs4236601 are selected from the group consisting of rsl2535567, rsl633731, rsl 180286, rsl0252986, rsl633728, rsl918923, rsl918924, rsl0247635, rsl0247800, rslO237417, rs6952334, rsl0228039, rsl0227962, rs4540346, rsl7138684, rs6963408, rslO282315, rs6466577, rs7796627, rs4273775, rs9656238, rs768107, rs717957, rs926197, rs879211, rs6976316, rsl2538592, rs6954077, rsl0487350, rslO228178, rsl7138749, rsl7515508, rsl0273272, rsl7138756, rsl7138765, rs4730742, rs2270188, rsl 1980719, rsl0253097, rsl0271007, rs4730743, rs8940, rsl0278782, rs4727833, rsl052990, rsl7515960, rsl0258482, rsl0262524, rs6466579, rslO281637, rs3919515, rs2024211, rsl7588172, rs6466580, rs6969706, rsl0227696, rs4236601, rs926198, rs917664, rs4730748, rs3779512, rs9649394, rslO256914, rs4730751, rsl0270569, rs9886215, rs9886219, rs2109516, rs6466587, rslO49314, rs8713, rs6867, rs6961215, rs6961388, rsl0280730, rsl0232369, which are the markers listed in Table IA.

In another embodiment, markers in linkage disequilibrium with rs4236601 are selected from the group consisting of rsl0808180, s.115639367, rs3807958, rsl7138624, rsll80289, rsll982034, rsl633714, s.115809902, s.115812308, rsll80293, rsll772856, s.115822680, s.115822757, rsl2535567, s.115823136, rsl633731, s.115823881, rsll80286, rs58217805, s.115829658, rsl0252986, rsl633728, rsl918923, rsl918924, rsl0247635, rsl0247800, rsl0226352, rslO255816, s.115837158, s.115837213, s.115837220, s.115837228,

S.115837231, rslO237417, s.115844941, s.115845073, S.115845156, rs6952334, rs66910042, s.115852616, s.115853434, rsl0256207, rsl0228039, rsl0227962, rs4540346, rsl7138684, rs6963408, rslO282315, rslO261897, rs6466577, rslO225153, s.115869741, rsll971849, rslO215761, rslO215954, rs7796627, s.115874386, S.115875537, s.115876493, rs73454998, rs73454999, rs4273775, rs9656238, rs73455001, s.115885256, rs35421698, s.115887401, S.115890028, rs768107, s.115897291, s.115898314, rs717957, s.115900980, S.115903500, s.115904029, s.115904171, s.115904290, rs926197, s.115906984, s.115907049, rs879211, rs6976316, s.115913401, s.115914118, s.115914208, s.115914539, rsl2538592, s.115916238, S.115916241, s.115916324, rs6954077, s.115916526, S.115916936, rsl0282556, s.115918221, rsl0487350, rslO228178, rs6973611, rs6974053, rsl7515508, rsl0273272, s.115921458, s.115922252, s.115922359, rsl7138755, rsl7138756, s.115922928, s.115924118,

S.115924242, rsl7138765, rs4730742, rs2191500, S.115926151, S.115926168, S.115926213, rs2270188, s.115927852, s.115928000, rs28503222, rs3779511, s.115929066, s.115929696, s.115929698, rsl l980719, rsl0233003, s.115931038, rs67933359, rsl0253097, rsl2668473, rs28587043, rsl0271007, s.115933173, rs4730743, rs8940, rsl0278782, rsl0249656, s.115934973, rs4727833, rsl052990, rsl0224685, rsl7515960, s.115937080, rsl2536639, rsl0258482, rsl0262524, rs6466579, rslO281637, rs3919515, rs2024211, rslO281661, rsl7588172, s.115941422, rs6466580, rs6969706, s.115943204, rsl0261304, s.115943215, rs59454355, rs7811851, rs7795510, rsl2540035, s.115947197, rs4730745, rs55883210, rs6950798, rs6950964, rsl0227696, rslO257125, s.115949855, s.115950221, rs4385407, s.115951190, rs926198, rs917664, rs4730748, rsll973363, s.115957431, rs3779512, rs9649394, rslO256914, s.115967515, rs4730751, rsl0270569, rslO241283, rs66916956, rs9886215, rs9886219, rs2109516, rslO22436, s.115984089, rs6466587, rslO49314, rs8713, rs6867, rslO49337, s.115989209, rs6961215, rs6961388, s.115990167, s.115990177, rsl0280730, rsl0232369, rs6959106, rs7802124, rs7802438, rsll979486, rsl0273326, s.115996983, s.115996984, rs7801180, which are the markers listed in Table IB.

In one preferred embodiment, the at least one polymorphic marker is selected from the group consisting of rs4236601, rsl052990, rs4730742, rs6976316, rsl2530912, rs6466587, rs3779512, rs2191502, rs729949, rs3815412, rsl7138756, rs926198, rsl0235210, rslO 11441, rsl0464649, rsll80286, rs6963408, rs2402061, rsl528243, rs760444, rsll772856, rs7806219, rs4540346, rs7796627, rslO49337, rs2204679, rs2402091, and rs926201.

In another preferred embodiment, the at least one polymorphic marker is selected from the group consisting of rs4236601, rsl052990 and rs8940. Most preferably, the at least one polymorphic marker is rs4236601. In one embodiment, the at least one polymorphic marker is selected from the group consisting of rsl2535567, rs6976316, rsl2530912, rs6466587, rs9886215, rslO49314, rs8713, rs6867, rs6961215, rs6961388, rsl0280730, rsl0232369, rs3779512, rs6955882, rs6959106, rs7802124, rsl0273272, rs7802438, rsl0273326, rsll979486, rs2191502, rs729949, rs3815412, rsl7138756, rs926198, rsl0235210, rslO11441, rsl0464649, rsl l80286, rs6963408, rs2402061, rs760444, rsl528243, rsll772856, rs7806219, rs4540346, rs7796627, rslO49337, rs2204679, rs2402091, rs926201, rsl052990, rsl0253097, rs8940, rsl0227696, rsl0258482, rslO256914, rs4730751, rs4236601, rsl0262524, rslO281637, rs2024211, rs6969706, rs4730742, rsl2538592, rsl0270569, rs879211, which are markers as listed in Table 5 with statistically significant P-values of association to glaucoma (P-values < 0.05).

In yet another embodiment, the at least one polymorphic marker is selected from the group consisting of rsl2535567, rs6976316, rsl2530912, rs6466587, rs9886215, rslO49314, rs8713, rs6867, rs6961215, rs6961388, rsl0280730, rsl0232369, rs3779512, rs729949, rs3815412, rs926198, rsl0235210, rslO11441, rsl0464649, rsll80286, rs2402061, rs760444, rsl528243, rsll772856, rs4540346, rs7796627, rslO49337, rs2204679, rs2402091, rs926201, rsl052990, rsl0258482, rslO256914, rs4730751, rs4236601, rsl0262524, rslO281637, rs2024211, rs6969706, and rsl0270569.

Surrogate markers in linkage disequilibrium with particular key markers can be selected based on certain values of the linkage disequilibrium measures D' and r ² , as described further herein. For example, markers that are in linkage disequilibrium with rs4236601 are exemplified by the markers listed in Table 1 A and B herein, but the skilled person will appreciate that other markers in linkage disequilibrium with these markers may also be used in the diagnostic applications described herein. Further, as also described in more detail herein, the skilled person will appreciate that since linkage disequilibrium is a continuous measure, certain values of the LD measures D' and r ² may be suitably chosen to define markers that are useful as surrogate markers in LD with the markers described herein. Numeric values of D' and r ² may thus in certain embodiments be used to define marker subsets that fulfill certain numerical cutoff values of D' and/or r ² . In one embodiment, markers in linkage disequilibrium with a particular anchor marker {e.g., rs4236601) are in LD with the anchor marker characterized by numerical values of D' of greater than 0.8 and/or numerical values of r ² of greater than 0.2. In one embodiment, markers in linkage disequilibrium with a particular anchor marker are in LD with the anchor marker characterized by numerical values of of r ² of greater than 0.2. The markers provided in Table 1 provideexemplary markers that fulfill this criterion. In other embodiments, markers in linkage disequilibrium with a particular anchor marker are in LD with the anchor marker characterized by numerical values of of r ² of greater than 0.3, greater than 0.4, greater than 0.5, greater than 0.6, greater than 0.7, greater than 0.8, greater than 0.9, greater than 0.95. Other numerical values of r ² and/or D' may also be suitably selected to select markers that are in LD with the anchor marker. The stronger the LD, the more similar the association signal and/or the predictive risk by the surrogate marker will be to that of the anchor marker. Markers with values of r ² = 1 to the anchor marker are perfect surrogates of the anchor marker and will provide identical association and risk prediction data. The skilled person will realize that although the table shows identity of a single allele that is associated [i.e. in LD) with allele A of rs4236601, the compliment allele may of course also be detected. For example, allele G of rsl2535567 is correlated with allele A of rs4236601. However, the C complement of allele G of rsl2535567 is of course also correlated, and may suitably also be detected instead of the G allele. In other words, both strands of DNA (+ and - strands) provide identical genetic information.

Association data presented in Table 9 illustrate that surrogate markers are indeed associated with glaucoma. Surrogate markers give different association signals depending on how strongly they are correlated with the underlying signal. Consider, for example, the markers rsl7138765, rsl0278782 and rsl0233003, which are all surrogate markers of rs4236601. The strongest association signal is observed for rsl0233003 (OR 1.38, P-value 2.1E-10; see Table 9), while weaker association is observed for rsl0278782 (OR 1.35, P-value 1.1E-7) and rsl7138765 (OR 1.25, P-value 0.0033). All three are surrogates ofrs4236601, but capture the underlying association signal to a varying degree - correlation values of r ² to rs4236601 are 1.0, 0.56 and 0.23, respectively, for rsl0233003, rsl0278782 and rsl7138765. It should also be noted that sample size also has an effect of the power to detect an underlying association. This power is exemplified by the apparent P-value of association determined using the particular sample. This does not mean that the inherent strength of each surrogate marker is affected, but is rather a manifestation of the relative strength of such markers in capturing the underlying association. The weaker the correlation to the anchor marker, the large a sample size will be needed to capture the underlying association with a particular statistical certainty.

Thus, in certain embodiments, markers in linkage disequilibrium with rs4236601 are selected from the group consisting of rsl0258482, rsl0262524, rslO281637, rs2024211, rs6969706, rslO281661, s.115943204, s.115943215, rs59454355, rsl2540035, rs4730745, rs6950798, rs6950964, rslO257125, rs4385407, rsl0233003, rs67933359, s.115941422, rs7811851, rs28587043, rsl2668473, rsll980719, rsl7588172, rs6466580, s.115931038, rs3779511, rsl052990, rs4730751, rslO256914, rsl0270569, rsl0253097, rsl0227696, rsl0224685, rsl0249656, rsl2536639, rs4730748, rsll973363, rs28503222, rsl0278782, rs8940, rsl0261304, rs7795510, s.115947197, rs55883210, rs4727833, rs4730743, rsl0271007, rs3919515, rs6466579, rs2270188, s.115950221, s.115927852, rs4730742, s.115906984, rsl2538592, s.115904290, rs879211, s.115916526, rsl0282556, s.115903500, s.115897291, s.115898314, s.115900980, s.115913401, s.115914118, s.115922252, s.115924242, s.115989209, rsl2535567, rs8713, rslO241283, rslO22436, rs6466587, rs3779512, rs717957, rs6954077, rslO228178, rs9886215, rs9886219, rslO49314, rs6867, rs6961215, rs6961388, rsl0280730, rsl0232369, rs926197, rs6976316, s.115957431, rs66916956, rs2109516, rs9649394, s.115837213, rs6959106, s.115990177, s.115809902, s.115812308, s.115822680, rs7802124, rs7802438, rsl l979486, rsl0273326, rs7801180, rsl0273272, s.115996983, S.115845073, rs6973611, S.115822757, s.115823136, S.115829658, S.115844941,

s.115852616, rs768107, s.115874386, rsll971849, s.115904029, s.115907049, s.115914208, S.115914539, rsl7515508, S.115916324, s.115916936, S.115918221, rs6974053, rs66910042, rsl0256207, rsl0487350, rs917664, s.115926151, s.115926168, s.115921458, s.115922359, rsl7138756, s.115922928, s.115924118, rs926198, rs9656238, rsl7138765, s.115837158, rslO215954, rslO215761, rslO261897, rs6466577, s.115875537, rslO237417, rs6963408, rsll80286, rs58217805, rsl0252986, s.115933173, s.115937080, rs35421698, s.115929066, s.115949855, s.115951190, rslO282315, s.115928000, rsl633728, rs6952334, rsl0228039, rsl0227962, rsl633731, rsl0247800, rsl7138755, rsl918923, rsl918924, rsl7515960, rslO255816, rs4540346, rs7796627, rsl7138684, s.115926213, s.115885256, s.115996984, rsl7138749, rsl0247635, s.115904171, rs4273775, s.115887401, rs2191500, rs73455001, rs73454999, rsll772856, rs73454998, and rslO225153, which are the markers provided in Table 9 that have been shown to be significantly associated with glaucoma.

The sequence data that is obtained may in certain embodiments, be amino acid sequence data. Polymorphic markers can result in alterations in the amino acid sequence of encoded polypeptide or protein sequence. For example, the polymorphic markers may result in amino acid changes selected from I18M, A87D and V155I in a human CAVl protein, or the polymorphic markers may result in amino acid changes selected from Q130E, A67G, and T146M in a human CAV2 protein.

In a preferred embodiment, the sequence data obtained by the claimed method is amino acid sequence data, wherein the presence of a Q130E and/or A67G substitution in human CAV2 is indicative of increased susceptibility of glaucoma in the individual from whom the sequence data originates. The Q130E substitution is in this context a substitution in position 130 of CAV2 isoforms a and/or b (Refseq NP_001224), while the A67G substitution is a substitution in position 67 of CAV2 isoform c (Refseq NP_937855).

In certain embodiments, the analysis of amino acid sequence data comprises determining the presence or absence of an amino acid substitution in the amino acid encoded by the at least one polymorphic marker. Sequence data can in certain embodiments be obtained by analyzing the amino acid sequence encoded by the at least one polymorphic marker in a biological sample obtained from the individual. In certain embodiments, the at least one polymorphic marker that is assessed is an amino acid substitution in a polypeptide encoded by the human caveolin-1 gene and/or the human caveolln-2 gene. In other words, the marker may be an amino acid substitution in a human caveolin-1 or human caveolin-2 polypeptide. In certain embodiments of the invention, determination of the presence of particular marker alleles is predictive of an increased susceptibility of glaucoma in humans. In certain

embodiments, determination of the presence of a marker allele selected from the group consisting of rsl2535567 allele G, rsl633731 allele G, rsll80286 allele C, rsl0252986 allele A, rsl633728 allele G, rsl918923 allele G, rsl918924 allele T, rsl0247635 allele T, rsl0247800 allele A, rslO237417 allele G, rs6952334 allele G, rsl0228039 allele A, rsl0227962 allele G, rs4540346 allele T, rsl7138684 allele G, rs6963408 allele G, rslO282315 allele G, rs6466577 allele A, rs7796627 allele T, rs4273775 allele T, rs9656238 allele G, rs768107 allele C, rs717957 allele G, rs926197 allele C, rs879211 allele T, rs6976316 allele G, rsl2538592 allele T, rs6954077 allele G, rsl0487350 allele T, rslO228178 allele G, rsl7138749 allele C, rsl7515508 allele C, rsl0273272 allele A, rsl7138756 allele G, rsl7138765 allele A, rs4730742 allele G, rs2270188 allele G, rsll980719 allele A, rsl0253097 allele C, rsl0271007 allele A, rs4730743 allele A, rs8940 allele G, rsl0278782 allele G, rs4727833 allele C, rsl052990 allele G, rsl7515960 allele G, rsl0258482 allele A, rsl0262524 allele A, rs6466579 allele T, rslO281637 allele C, rs3919515 allele G, rs2024211 allele C, rsl7588172 allele G, rs6466580 allele C, rs6969706 allele T, rsl0227696 allele A, rs4236601 allele A, rs926198 allele C, rs917664 allele A, rs4730748 allele G, rs3779512 allele T, rs9649394 allele A, rslO256914 allele C, rs4730751 allele A, rsl0270569 allele T, rs9886215 allele G, rs9886219 allele T, rs2109516 allele G, rs6466587 allele G, rslO49314 allele A, rs8713 allele C, rs6867 allele A, rs6961215 allele T, rs6961388 allele G, rsl0280730 allele T, rsl0232369 allele A, rsl0808180 allele A, s.115639367 allele C, rs3807958 allele C, rsl7138624 allele A, rsl l80289 allele T, rsll982034 allele T, rsl633714 allele T, s.115809902 allele A, s.115812308 allele G, rsll80293 allele G, rsl l772856 allele C, s.115822680 allele T, s.115822757 allele A, s.115823136 allele C, s.115823881 allele T, rs58217805 allele C, s.115829658 allele A, rsl0226352 allele G, rslO255816 allele T, s.115837158 allele C, s.115837213 allele C, s.115837220 allele T, s.115837228 allele A, s.115837231 allele A, s.115844941 allele G, s.115845073 allele G, s.115845156 allele G, rs66910042 allele T, s.115852616 allele A, s.115853434 allele A, rsl0256207 allele C, rslO261897 allele C, rslO225153 allele C, s.115869741 allele C, rsl l971849 allele C, rslO215761 allele T, rslO215954 allele T, s.115874386 allele G, s.115875537 allele G, s.115876493 allele T, rs73454998 allele G, rs73454999 allele A, rs73455001 allele C, s.115885256 allele C, rs35421698 allele T, s.115887401 allele G, s.115890028 allele A, s.115897291 allele A, s.115898314 allele G, s.115900980 allele C, s.115903500 allele G, s.115904029 allele A, s.115904171 allele T, s.115904290 allele C, s.115906984 allele A, s.115907049 allele C, s.115913401 allele C, s.115914118 allele A, s.115914208 allele G, s.115914539 allele A, s.115916238 allele A, s.115916241 allele T, s.115916324 allele T, s.115916526 allele C, s.115916936 allele T, rsl0282556 allele G, s.115918221 allele G, rs6973611 allele G, rs6974053 allele A, s.115921458 allele A, s.115922252 allele G,

s.115922359 allele A, rsl7138755 allele C, s.115922928 allele A, s.115924118 allele A, s.115924242 allele G, rs2191500 allele C, s.115926151 allele T, s.115926168 allele C, s.115926213 allele C, s.115927852 allele A, s.115928000 allele A, rs28503222 allele C, rs3779511 allele G, s.115929066 allele T, s.115929696 allele C, s.115929698 allele G, rsl0233003 allele A, s.115931038 allele T, rs67933359 allele A, rsl2668473 allele T, rs28587043 allele A, s.115933173 allele A, rsl0249656 allele T, s.115934973 allele G, rsl0224685 allele C, s.115937080 allele T, rsl2536639 allele A, rslO281661 allele G, s.115941422 allele G, s.115943204 allele G, rsl0261304 allele C, s.115943215 allele C, rs59454355 allele G, rs7811851 allele T, rs7795510 allele T, rsl2540035 allele A, s.115947197 allele G, rs4730745 allele T, rs55883210 allele G, rs6950798 allele C, rs6950964 allele C, rslO257125 allele T, s.115949855 allele G, s.115950221 allele T, rs4385407 allele A, s.115951190 allele G, rsll973363 allele G, s.115957431 allele T, s.115967515 allele A, rslO241283 allele G, rs66916956 allele T, rslO22436 allele G, s.115984089 allele A, rslO49337 allele C, s.115989209 allele G, s.115990167 allele G, s.115990177 allele G, rs6959106 allele C, rs7802124 allele C, rs7802438 allele A, rsl 1979486 allele G, rsl0273326 allele C, s.115996983 allele A, s.115996984 allele A, and rs7801180 allele C is indicative of an increased risk of glaucoma in the individual. In certain preferred embodiments, determination of the presence of a marker allele selected from the group consisting of the A allele of rs4236601, the G allele of rs8940 and/or the G allele of rsl052990 is indicative of increased risk of glaucoma in the individual.

Determination of the absence of at-risk alleles in an individual is indicative of a decreased risk of glaucoma. For example, individuals who are determined not to be carrying the at-risk alleles rs4236601 allele A, rs8940 allele G and rsl052990 allele G are at a decreased risk of glaucoma compared with carriers of these alleles, or a random sample from the population. For SNPs, which only have two alleles, this means that the individuals are homozygous for the alternate allele of the particular SNP {e.g., rs4236601 allele G, rs8940 allele C and rsl052990 allele T), which is also called the protective allele. Individuals who are heterozygous for at-risk alleles, also heterozygous for the protective allele in the case of SNPs, are at-risk compared with non- carriers of the at-risk allele. Individuals who are homozygous for at-risk alleles or haplotypes are at particularly high risk of developing glaucoma, since their genome includes two copies of the at-risk variant. Thus, certain embodiments relate to determination of the presence of two copies of the particular at- risk allele or haplotype in the individual. Individuals who are homozygous for protective alleles (non-carriers of at-risk alleles for SNPs) are at particularly low risk of developing glaucoma. Measures of susceptibility or risk include measures such as relative risk (RR), odds ratio (OR), and absolute risk (AR), as described in more detail herein.

In certain embodiments, increased susceptibility is reported as a risk of at least 1.25, at least 1.26, at least 1.27, at least 1.28, at least 1.29, at least 1.30, at least 1.31, at least 1.32, at least 1.33, at least 1.34, at least 1.35, at least 1.36, at least 1.37, at least 1.38, at least 1.39, at least 1.40, at least 1.45, at least 1.50, at least 1.55, at least 1.60, at least 1.65, at least 1.70, at least 1.75, and at least 1.80. Other numerical non-integer values between 0 and 1 are also possible to characterize the risk, and such numerical values are also within scope of the invention.

Certain embodiments relate to homozygous individuals for a particular markers, i.e. individuals who carry two copies of the same allele in their genome. One embodiment relates to individuals who are homozygous carriers of allele A of rs4236601, or a marker allele in linkage

disequilibrium therewith.

In certain other embodiments, determination of the presence of particular marker alleles or particular haplotypes is predictive of a decreased susceptibility of glaucoma in humans. For SNP markers with two alleles, the alternate allele to an at-risk allele will be in decreased frequency in patients compared with controls. Thus, determination of the presence of the alternate allele is indicative of a decreased susceptibility of glaucoma. Individuals who are homozygous for the alternate (protective) allele are at particularly decreased susceptibility or risk. To identify markers that are useful for assessing susceptibility to glaucoma, it may be useful to compare the frequency of markers alleles in individuals with glaucoma to control individuals. The control individuals may be a random sample from the general population, i.e. a population cohort. The control individuals may also be a sample from individuals that do are disease-free, e.g. individuals who have been confirmed not to have glaucoma. In one embodiment, an increase in frequency of at least one allele in at least one polymorphism in individuals diagnosed with glaucoma, as compared with the frequency of the at least one allele in the control group is indicative of the at least one allele being useful for assessing increased susceptibility to glaucoma. In another embodiment, a decrease in frequency of at least one allele in at least one polymorphism in individuals diagnosed with glaucoma, as compared with the frequency of the at least one allele in the control sample is indicative of the at least one allele being useful for assessing decreased susceptibility to, or protection against, glaucoma.

In general, sequence data can be obtained by analyzing a sample from an individual, or by analyzing information about specific markers in a database, for example a genotype database or a sequence database. The sample is in certain embodiments a nucleic acid sample. Analyzing a sample from an individual may in certain embodiments include steps of isolating genomic nucleic acid from the sample, amplifying a segment of the genomic nucleic acid that contains at least one polymorphic marker, and determine sequence information about the at least one polymorphic marker. Amplification is preferably performed by Polymerase Chain Reaction (PCR) techniques. In certain embodiments, sequence data can be obtained through nucleic acid sequence information or amino acid sequence information from a preexisting record. Such a preexisting record can be any documentation, database or other form of data storage containing such information.

Determination of a susceptibility or risk of a particular individual in general comprises comparison of the genotype information (sequence information) to a record or database providing a correlation about particular polymorphic marker(s) and susceptibility to glaucoma. Thus, in specific embodiments, determining a susceptibility comprises comparing the sequence data to a database containing correlation data between the at least one polymorphic marker and susceptibility to glaucoma. In certain embodiments, the database comprises at least one measure of susceptibility to glaucoma for the at least one polymorphic marker. In certain embodiments, the database comprises a look-up table comprising at least one measure of susceptibility to glaucoma for the at least one polymorphic marker. The measure of

susceptibility may in the form of relative risk (RR), absolute risk (AR), percentage (%) or other convenient measure for describing genetic susceptibility of individuals.

Certain embodiments of the invention relate to markers associated with the human caveolin-1 gene and/or the human caveolin-2 gene. Markers that are associated with these genes are in certain embodiments markers that are in linkage disequilibrium (LD) with at least one genetic marker within the genes. In certain embodiments, the markers are located within the genomic segment LD block C07, with sequence as set forth in SEQ ID NO: 1. In certain embodiments, markers associated with the caveolin-1 gene are selected from the markers within the human caveolin-1 gene. In certain embodiments, markers associated with the caveolin-2 gene are selected from the markers within the human caveolin-2 gene.

Certain embodiments of the invention relate to markers located within the LD Block C07 as defined herein. It is however also contemplated that surrogate markers useful for determining susceptibility to glaucoma may be located outside the LD Block C07 as defined in physical terms (genomic locations). Thus, certain embodiments of the invention are not limited to surrogate markers located within the physical boundaries of the C07 LD block as defined, but also include useful surrogate markers outside the physical boundaries of the LD block asa defined, due to the surrogate markers being in LD with one or more of the markers within C07 shown herein to be associated with risk of glaucoma.

In certain embodiments of the invention, more than one polymorphic marker is analyzed. In certain embodiments, at least two polymorphic markers are analyzed. Thus, in certain embodiments, nucleic acid data about at least two polymorphic markers is obtained. In certain embodiments, a further step of analyzing at least one haplotype comprising two or more polymorphic markers is included.

In one aspect, the invention relates to a method for determining a susceptibility to glaucoma in a human individual, comprising determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual, or in a genotype dataset from the individual, wherein the at least one polymorphic marker is selected from the group consisting of rs4236601, and markers in linkage disequilibrium therewith, and wherein determination of the presence of the at least one allele is indicative of a susceptibility to glaucoma. Determination of the presence of an allele that correlates with glaucoma is indicative of an increased susceptibility to glaucoma. Individuals who are homozygous for such alleles are particularly susceptible to glaucoma. On the other hand, individuals who do not carry such at- risk alleles are at a decreased susceptibility of developing glaucoma. For SNPs, such individuals will be homozygous for the alternate (protective) allele of the polymorphism. Determination of susceptibility is in some embodiments reported by a comparison with non- carriers of the at-risk allele(s) of polymorphic markers. In certain embodiments, susceptibility is reported based on a comparison with the general population, e.g. compared with a random selection of individuals from the population. In certain embodiments of the invention, the determining of the presence or absence of particular alleles at particular markers comprises analyzing nucleic acid in the sample using a method that includes at least one procedure selected from amplifying nucleic acid from the nucleic acid sample; and performing a hybridization assay using a nucleic acid probe and nucleic acid from the nucleic acid sample, or from the amplifying. In another embodiment, a further step is included comprising displaying results from the analyzing of the sequence data indicative of a susceptibility to glaucoma on a visual display selected from the group consisting of an electronic display and a printed report.

In certain embodiments, polymorphic markers are detected by sequencing technologies.

Obtaining sequence information about an individual identifies particular nucleotides in the context of a nucleic acid sequence. For SNPs, sequence information about a single unique sequence site is sufficient to identify alleles at that particular SNP. For markers comprising more than one nucleotide, sequence information about the genomic region of the individual that contains the polymorphic site identifies the alleles of the individual for the particular site. The sequence information can be obtained from a sample from the individual. In certain

embodiments, the sample is a nucleic acid sample. In certain other embodiments, the sample is a protein sample.

Various methods for obtaining nucleic acid sequence are known to the skilled person, and all such methods are useful for practicing the invention. Sanger sequencing is a well-known method for generating nucleic acid sequence information. Recent methods for obtaining large amounts of sequence data have been developed, and such methods are also contemplated to be useful for obtaining sequence information. These include pyrosequencing technology (Ronaghi, M. et al. Anal Biochem 267:65-71 (1999); Ronaghi, et al. Biotechniques 25 :876-878 (1998)), e.g. 454 pyrosequencing (Nyren, P., et al. Anal Biochem 208: 171-175 (1993)), Illumina/Solexa sequencing technology (http://www.illumina.com; see also Strausberg, RL, et al Drug Disc Today 13: 569-577 (2008)), and Supported Oligonucleotide Ligation and Detection Platform (SOLiD) technology (Applied Biosystems, http://www.appliedbiosystems.com); Strausberg, RL, et al Drug Disc Today 13:569-577 (2008).

Providing risk assessment results

Results of determination and/or analysis of sequence data from an individual are suitably reported in a convenient format. In certain embodiments, a report is prepared containing nucleic acid sequence data for at least one marker. Such a report may be provided written in a computer readable medium, printed on paper, or displayed on a visual display. The visual display may be an electronic display or it may be in the form of a printed visual report. Assessment for markers and haplotypes

The genomic sequence within populations is not identical when individuals are compared.

Rather, the genome exhibits sequence variability between individuals at many locations in the genome. Such variations in sequence are commonly referred to as polymorphisms, and there are many such sites within each genome. For example, the human genome exhibits sequence variations which occur on average every 500 base pairs. The most common sequence variant consists of base variations at a single base position in the genome, and such sequence variants, or polymorphisms, are commonly called Single Nucleotide Polymorphisms ("SNPs"). These SNPs are believed to have occurred in a single mutational event, and therefore there are usually two possible alleles possible at each SNPsite; the original allele and the mutated allele. Due to natural genetic drift and possibly also selective pressure, the original mutation has resulted in a polymorphism characterized by a particular frequency of its alleles in any given population. Many other types of sequence variants are found in the human genome, including mini- and microsatellites, and insertions, deletions and inversions (also called copy number variations (CNVs)). A polymorphic microsatellite has multiple small repeats of bases (such as CA repeats, TG on the complimentary strand) at a particular site in which the number of repeat lengths varies in the general population. In general terms, each version of the sequence with respect to the polymorphic site represents a specific allele of the polymorphic site. These sequence variants can all be referred to as polymorphisms, occurring at specific polymorphic sites characteristic of the sequence variant in question. In general, polymorphisms can comprise any number of specific alleles within the population, although each human individual has two alleles at each polymorphic site - one maternal and one paternal allele. Thus in one embodiment of the invention, the polymorphism is characterized by the presence of two or more alleles in any given population. In another embodiment, the polymorphism is characterized by the presence of three or more alleles in a population. In other embodiments, the polymorphism is characterized by four or more alleles, five or more alleles, six or more alleles, seven or more alleles, nine or more alleles, or ten or more alleles. All such polymorphisms can be utilized in the methods and kits of the present invention, and are thus within the scope of the invention.

Due to their abundance, SNPs account for a majority of sequence variation in the human genome. Over 6 million human SNPs have been validated to date

(http://www.ncbi. nlm.nih.gov/projects/SNP/snp_summary.cgi). However, CNVs are receiving increased attention. These large-scale polymorphisms (typically lkb or larger) account for polymorphic variation affecting a substantial proportion of the assembled human genome; known CNVs covery over 15% of the human genome sequence (Estivill, X Armengol; L., PIoS Genetics 3: 1787-99 (2007); http://projects.tcag. ca/variation/). Most of these polymorphisms are however very rare, and on average affect only a fraction of the genomic sequence of each individual. CNVs are known to affect gene expression, phenotypic variation and adaptation by disrupting gene dosage, and are also known to cause disease (microdeletion and

microduplication disorders) and confer risk of common complex diseases, including HIV-I infection and glomerulonephritis (Redon, R., et al. Nature 23:444-454 (2006)). It is thus possible that either previously described or unknown CNVs represent causative variants in linkage disequilibrium with the disease-associated markers described herein. Methods for detecting CNVs include comparative genomic hybridization (CGH) and genotyping, including use of genotyping arrays, as described by Carter (Nature Genetics 39:S16-S21 (2007)). The Database of Genomic Variants (http://projects.tcag.ca/vanation/) contains updated information about the location, type and size of described CNVs. The database currently contains data for over 21,000 CNVs.

In some instances, reference is made to different alleles at a polymorphic site without choosing a reference allele. Alternatively, a reference sequence can be referred to for a particular polymorphic site. The reference allele is sometimes referred to as the "wild-type" allele and it usually is chosen as either the first sequenced allele or as the allele from a "non -affected" individual (e.g., an individual that does not display a trait or disease phenotype).

Alleles for SNP markers as referred to herein refer to the bases A, C, G or T as they occur at the polymorphic site. The allele codes for SNPs used herein are as follows: 1= A, 2=C, 3=G, 4=T. Since human DNA is double-stranded, the person skilled in the art will realise that by assaying or reading the opposite DNA strand, the complementary base can in each case be measured. Thus, for a polymorphic site (polymorphic marker) characterized by an A/G polymorphism, the methodologyemployed to detect the marker may be designed to specifically detect the presence of one or both of the two bases possible, i.e. A and G. Alternatively, by designing an assay that is designed to detect the complimentary strand on the DNA template, the presence of the complementary bases T and C can be measured. Quantitatively (for example, in terms of risk estimates), identical results would be obtained from measurement of either DNA strand (+ strand or - strand).

Typically, a reference sequence is referred to for a particular sequence. Alleles that differ from the reference are sometimes referred to as "variant" alleles. A variant sequence, as used herein, refers to a sequence that differs from the reference sequence but is otherwise substantially similar. Alleles at the polymorphic genetic markers described herein are variants. Variants can include changes that affect a polypeptide. Sequence differences, when compared to a reference nucleotide sequence, can include the insertion or deletion of a single nucleotide, or of more than one nucleotide, resulting in a frame shift; the change of at least one nucleotide, resulting in a change in the encoded amino acid; the change of at least one nucleotide, resulting in the generation of a premature stop codon; the deletion of several nucleotides, resulting in a deletion of one or more amino acids encoded by the nucleotides; the insertion of one or several nucleotides, such as by unequal recombination or gene conversion, resulting in an interruption of the coding sequence of a reading frame; duplication of all or a part of a sequence; transposition; or a rearrangement of a nucleotide sequence,. Such sequence changes can alter the polypeptide encoded by the nucleic acid. For example, if the change in the nucleic acid sequence causes a frame shift, the frame shift can result in a change in the encoded amino acids, and/or can result in the generation of a premature stop codon, causing generation of a truncated polypeptide. Alternatively, a polymorphism can be a synonymous change in one or more nucleotides [i.e. , a change that does not result in a change in the amino acid sequence). Such a polymorphism can, for example, alter splice sites, affect the stability or transport of mRNA, or otherwise affect the transcription or translation of an encoded polypeptide. It can also alter DNA to increase the possibility that structural changes, such as amplifications or deletions, occur at the somatic level. The polypeptide encoded by the reference nucleotide sequence is the "reference" polypeptide with a particular reference amino acid sequence, and polypeptides encoded by variant alleles are referred to as "variant" polypeptides with variant amino acid sequences.

A haplotype refers to a single-stranded segment of DNA that is characterized by a specific combination of alleles arranged along the segment. For diploid organisms such as humans, a haplotype comprises one member of the pair of alleles for each polymorphic marker or locus . In a certain embodiment, the haplotype can comprise two or more alleles, three or more alleles, four or more alleles, or five or more alleles, each allele corresponding to a specific polymorphic marker along the segment. Haplotypes can comprise a combination of various polymorphic markers, e.g., SNPs and microsatellites, having particular alleles at the polymorphic sites. The haplotypes thus comprise a combination of alleles at various genetic markers.

Detecting specific polymorphic markers and/or haplotypes can be accomplished by methods known in the art for detecting sequences at polymorphic sites. For example, standard techniques for genotyping for the presence of SNPs and/or microsatellite markers can be used, such as fluorescence-based techniques [e.g., Chen, X. et ai., Genome Res. 9(5): 492-98 (1999); Kutyavin et ai., Nucleic Acid Res. 34:el28 (2006)), utilizing PCR, LCR, Nested PCR and other techniques for nucleic acid amplification. Specific commercial methodologies available for SNP genotyping include, but are not limited to, TaqMan genotyping assays and SNPIex platforms (Applied Biosystems), gel electrophoresis (Applied Biosystems), mass spectrometry [e.g., MassARRAY system from Sequenom), minisequencing methods, real-time PCR, Bio-Plex system (BioRad), CEQ and SNPstream systems (Beckman), array hybridization technology(e.g. , Affymetrix GeneChip; Perlegen), BeadArray Technologies [e.g., Illumina GoldenGate and Infinium assays), array tag technology [e.g., Parallele), and endonuclease-based fluorescence hybridization technology (Invader; Third Wave) . Some of the available array platforms, including Affymetrix SNP Array 6.0 and Illumina CNV370-Duo and IM BeadChips, include SNPs that tag certain CNVs. This allows detection of CNVs via surrogate SNPs included in these platforms. Thus, by use of these or other methods available to the person skilled in the art, one or more alleles at polymorphic markers, including microsatellites, SNPs or other types of polymorphic markers, can be identified. In certain embodiments, polymorphic markers are detected by sequencing technologies.

Obtaining sequence information about an individual identifies particular nucleotides in the context of a sequence. For SNPs, sequence information about a single unique sequence site is sufficient to identify alleles at that particular SNP. For markers comprising more than one nucleotide, sequence information about the nucleotides of the individual that contain the polymorphic site identifies the alleles of the individual for the particular site. The sequence information can be obtained from a sample from the individual. In certain embodiments, the sample is a nucleic acid sample. In certain other embodiments, the sample is a protein sample.

Various methods for obtaining nucleic acid sequence are known to the skilled person, and all such methods are useful for practicing the invention. Sanger sequencing is a well-known method for generating nucleic acid sequence information. Recent methods for obtaining large amounts of sequence data have been developed, and such methods are also contemplated to be useful for obtaining sequence information. These include pyrosequencing technology (Ronaghi, M. et al. Anal Biochem 267:65-71 (1999); Ronaghi, et al. Biotechniques 25 :876-878 (1998)), e.g. 454 pyrosequencing (Nyren, P., et al. Anal Biochem 208: 171-175 (1993)), Illumina/Solexa sequencing technology (http://www.illumina.com; see also Strausberg, RL, et al Drug Disc Today 13: 569-577 (2008)), and Supported Oligonucleotide Ligation and Detection Platform (SOLiD) technology (Applied Biosystems, http://www.appliedbiosystems.com); Strausberg, RL, et al Drug Disc Today 13:569-577 (2008). It is possible to impute or predict genotypes for un-genotyped relatives of genotyped individuals. For every un-genotyped case, it is possible to calculate the probability of the genotypes of its relatives given its four possible phased genotypes. In practice it may be preferable to include only the genotypes of the case's parents, children, siblings, half-siblings (and the half-sibling's parents), grand-parents, grand-children (and the grand-children's parents) and spouses. It will be assumed that the individuals in the small sub-pedigrees created around each case are not related through any path not included in the pedigree. It is also assumed that alleles that are not transmitted to the case have the same frequency - the population allele frequency. Let us consider a SNP marker with the alleles A and G. The probability of the genotypes of the case's relatives can then be computed by: P

where θ denotes the A allele's frequency in the cases. Assuming the genotypes of each set of relatives are independent, this allows us to write down a likelihood function for θ:

This assumption of independence is usually not correct. Accounting for the dependence between individuals is a difficult and potentially prohibitively expensive computational task. The likelihood function in (*) may be thought of as a pseudolikelihood approximation of the full likelihood function for θ which properly accounts for all dependencies. In general, the genotyped cases and controls in a case-control association study are not independent and applying the case-control method to related cases and controls is an analogous approximation. The method of genomic control (Devlin, B. et al., Nat Genet 36, 1129-30; author reply 1131 (2004)) has proven to be successful at adjusting case-control test statistics for relatedness. We therefore apply the method of genomic control to account for the dependence between the terms in our

pseudolikelihood and produce a valid test statistic.

Fisher's information can be used to estimate the effective sample size of the part of the pseudolikelihood due to un-genotyped cases. Breaking the total Fisher information, I, into the part due to genotyped cases, I ₉ , and the part due to ungenotyped cases, I _Ul I = I ₉ + I _u , and denoting the number of genotyped cases with Λ/, the effective sample size due to the ungenotyped cases is estimated by

In the present context, an individual who is at an increased susceptibility (i.e., increased risk) for a disease, is an individual in whom at least one specific allele at one or more polymorphic marker or haplotype conferring increased susceptibility (increased risk) for the disease is identified (i.e., at-risk marker alleles or haplotypes). The at-risk marker or haplotype is one that confers an increased risk (increased susceptibility) of the disease. In one embodiment, significance associated with a marker or haplotype is measured by a relative risk (RR). In another embodiment, significance associated with a marker or haplotye is measured by an odds ratio (OR). In a further embodiment, the significance is measured by a percentage. In one embodiment, a significant increased risk is measured as a risk (relative risk and/or odds ratio) of at least 1.2, including but not limited to: at least 1.2, at least 1.3, at least 1.4, at least 1.5, at least 1.6, at least 1.7, at least 1.8, at least 1.9, and at least 2.0. In a particular embodiment, a risk (relative risk and/or odds ratio) of at least 1.2 is significant. In another particular embodiment, a risk of at least 1.3 is significant. In yet another embodiment, a risk of at least 1.4 is significant. In a further embodiment, a relative risk of at least 1.5 is significant. In another further embodiment, a significant increase in risk is at least 1.7 is significant. However, other cutoffs are also contemplated, e.g., at least 1.15, 1.25, 1.35, and so on, and such cutoffs are also within scope of the present invention. In other embodiments, a significant increase in risk is at least about 20%, including but not limited to about 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, 150%, and 200%. In one particular embodiment, a significant increase in risk is at least 20%. In other embodiments, a significant increase in risk is at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% and at least 100%. Other cutoffs or ranges as deemed suitable by the person skilled in the art to characterize the invention are however also contemplated, and those are also within scope of the present invention. In certain embodiments, a significant increase in risk is characterized by a p-value, such as a p-value of less than 0.05, less than 0.01, less than 0.001, less than 0.0001, less than 0.00001, less than 0.000001, less than 0.0000001, less than 0.00000001, or less than 0.000000001.

An at-risk polymorphic marker or haplotype as described herein is one where at least one allele of at least one marker or haplotype is more frequently present in an individual at risk for the disease (or trait) (affected), or diagnosed with the disease, compared to the frequency of its presence in a comparison group (control), such that the presence of the marker or haplotype is indicative of susceptibility to the disease. The control group may in one embodiment be a population sample, i.e. a random sample from the general population. In another embodiment, the control group is represented by a group of individuals who are disease-free. Such disease- free controls may in one embodiment be characterized by the absence of one or more specific disease-associated symptoms. Alternatively, the disease-free controls are those that have not been diagnosed with the disease. In another embodiment, the disease-free control group is characterized by the absence of one or more disease-specific risk factors. Such risk factors are in one embodiment at least one environmental risk factor. Representative environmental factors are natural products, minerals or other chemicals which are known to affect, or contemplated to affect, the risk of developing the specific disease or trait. Other environmental risk factors are risk factors related to lifestyle, including but not limited to food and drink habits, geographical location of main habitat, and occupational risk factors. In another embodiment, the risk factors comprise at least one additional genetic risk factor. As an example of a simple test for correlation would be a Fisher-exact test on a two by two table. Given a cohort of chromosomes, the two by two table is constructed out of the number of chromosomes that include both of the markers or haplotypes, one of the markers or haplotypes but not the other and neither of the markers or haplotypes. Other statistical tests of association known to the skilled person are also contemplated and are also within scope of the invention. The person skilled in the art will appreciate that for markers with two alleles present in the population being studied (such as SNPs), and wherein one allele is found in increased frequency in a group of individuals with a trait or disease in the population, compared with controls, the other allele of the marker will be found in decreased frequency in the group of individuals with the trait or disease, compared with controls. In such a case, one allele of the marker (the one found in increased frequency in individuals with the trait or disease) will be the at-risk allele, while the other allele will be a protective allele.

Thus, in other embodiments of the invention, an individual who is at a decreased susceptibility (i.e., at a decreased risk) for a disease or trait is an individual in whom at least one specific allele at one or more polymorphic marker or haplotype conferring decreased susceptibility for the disease or trait is identified. The marker alleles and/or haplotypes conferring decreased risk are also said to be protective. In one aspect, the protective marker or haplotype is one that confers a significant decreased risk (or susceptibility) of the disease or trait. In one embodiment, significant decreased risk is measured as a relative risk (or odds ratio) of less than 0.9, including but not limited to less than 0.9, less than 0.8, less than 0.7, less than 0.6, less than 0.5, less than 0.4, less than 0.3, less than 0.2 and less than 0.1. In one particular embodiment, significant decreased risk is less than 0.7. In another embodiment, significant decreased risk is less than 0.5. In yet another embodiment, significant decreased risk is less than 0.3. In another embodiment, the decrease in risk (or susceptibility) is at least 20%, including but not limited to at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95% and at least 98%. In one particular embodiment, a significant decrease in risk is at least about 30%. In another embodiment, a significant decrease in risk is at least about 50%. In another embodiment, the decrease in risk is at least about 70%. Other cutoffs or ranges as deemed suitable by the person skilled in the art to characterize the invention are however also contemplated, and those are also within scope of the present invention.

A genetic variant associated with a disease or a trait can be used alone to predict the risk of the disease for a given genotype. For a biallelic marker, such as a SNP, there are 3 possible genotypes: homozygote for the at risk variant, heterozygote, and non carrier of the at risk variant. Risk associated with variants at multiple loci can be used to estimate overall risk. For multiple SNP variants, there are k possible genotypes k = 3" χ 2 ^P ; where n is the number autosomal loci and p the number of gonosomal (sex chromosomal) loci. Overall risk assessment calculations for a plurality of risk variants usually assume that the relative risks of different genetic variants multiply, I.e. the overall risk (e.g., RR or OR) associated with a particular genotype combination is the product of the risk values for the genotype at each locus. If the risk presented is the relative risk for a person, or a specific genotype for a person, compared to a reference population with matched gender and ethnicity, then the combined risk is the product of the locus specific risk values and also corresponds to an overall risk estimate compared with the population. If the risk for a person is based on a comparison to non-carriers of the at risk allele, then the combined risk corresponds to an estimate that compares the person with a given combination of genotypes at all loci to a group of individuals who do not carry risk variants at any of those loci. The group of non-carriers of any at risk variant has the lowest estimated risk and has a combined risk _^ compared with itself (i.e. , non-carriers) of 1.0, but has an overall risk, compare with the population, of less than 1.0. It should be noted that the group of non-carriers can potentially be very small, especially for large number of loci, and in that case, its relevance is correspondingly small.

The multiplicative model is a parsimonious model that usually fits the data of complex traits reasonably well. Deviations from multiplicity have been rarely described in the context of common variants for common diseases, and if reported are usually only suggestive since very large sample sizes are usually required to be able to demonstrate statistical interactions between loci.

By way of an example, let us consider the case where a total of eight variants that have been associated with a disease. One such example is provided by prostate cancer (Gudmundsson, J., et al., Nat Genet 39:631-7 (2007), Gudmundsson, J., et al., Nat Genet 39:977-83 (2007);

Yeager, M., et al, Nat Genet 39:645-49 (2007), Amundadottir, L., el al., Nat Genet 38:652-8 (2006); Haiman, CA. , et al., Nat Genet 39:638-44 (2007)). Seven of these loci are on autosomes, and the remaining locus is on chromosome X. The total number of theoretical genotypic combinations is then 3 ⁷ x 2 ¹ = 4374. Some of those genotypic classes are very rare, but are still possible, and should be considered for overall risk assessment. It is likely that the multiplicative model applied in the case of multiple genetic variant will also be valid in conjugation with non-genetic risk variants assuming that the genetic variant does not clearly correlate with the "environmental" factor. In other words, genetic and non-genetic at- risk variants can be assessed under the multiplicative model to estimate combined risk, assuming that the non-genetic and genetic risk factors do not interact.

Using the same quantitative approach, the combined or overall risk associated with any plurality of variants associated with glaucoma may be assessed.

Linkage Disequilibrium

The natural phenomenon of recombination, which occurs on average once for each chromosomal pair during each meiotic event, represents one way in which nature provides variations in sequence (and biological function by consequence). It has been discovered that recombination does not occur randomly in the genome; rather, there are large variations in the frequency of recombination rates, resulting in small regions of high recombination frequency (also called recombination hotspots) and larger regions of low recombination frequency, which are commonly referred to as Linkage Disequilibrium (LD) blocks (Myers, S. et al., Biochem Soc Trans 34: 526- 530 (2006); Jeffreys, AJ., et al., Nature Genet 29:217-222 (2001); May, CA. , et al., Nature Genet 31:272-275(2002)).

Linkage Disequilibrium (LD) refers to a non-random assortment of two genetic elements. For example, if a particular genetic element (e.g., an allele of a polymorphic marker, or a haplotype) occurs in a population at a frequency of 0.50 (50%) and another element occurs at a frequency of 0.50 (50%), then the predicted occurrance of a person's having both elements is 0.25 (25%), assuming a random distribution of the elements. However, if it is discovered that the two elements occur together at a frequency higher than 0.25, then the elements are said to be in linkage disequilibrium, since they tend to be inherited together at a higher rate than what their independent frequencies of occurrence (e.g., allele or haplotype frequencies) would predict. Roughly speaking, LD is generally correlated with the frequency of recombination events between the two elements. Allele or haplotype frequencies can be determined in a population by genotyping individuals in a population and determining the frequency of the occurence of each allele or haplotype in the population. For populations of diploids, e.g., human populations, individuals will typically have two alleles or allelic combinations for each genetic element {e.g. , a marker, haplotype or gene).

Many different measures have been proposed for assessing the strength of linkage disequilibrium (LD; reviewed in Devlin, B. & Risch, N., Genomics 29:311-22 (1995)). Most capture the strength of association between pairs of biallelic sites. Two important pairwise measures of LD are r ² (sometimes denoted Δ ² ) and | D'| (Lewontin, R., Genetics 49:49-67 (1964); Hill, W. G. &

Robertson, A. Theor. Appl. Genet. 22:226-231 (1968)). Both measures range from 0 (no disequilibrium) to 1 ('complete' disequilibrium), but their interpretation is slightly different. | D' is defined in such a way that it is equal to 1 if just two or three of the possible haplotypes for two markers are present, and it is < 1 if all four possible haplotypes are present. Therefore, a value of | D'| that is < 1 indicates that historical recombination may have occurred between two sites (recurrent mutation can also cause | D'| to be <1, but for single nucleotide polymorphisms (SNPs) this is usually regarded as being less likely than recombination). The measure r ² represents the statistical correlation between two sites, and takes the value of 1 if only two haplotypes are present.

The r ² measure is arguably the most relevant measure for association mapping, because there is a simple inverse relationship between r ² and the sample size required to detect association between susceptibility loci and SNPs. These measures are defined for pairs of sites, but for some applications a determination of how strong LD is across an entire region that contains many polymorphic sites might be desirable (e.g., testing whether the strength of LD differs significantly among loci or across populations, or whether there is more or less LD in a region than predicted under a particular model). Roughly speaking, r measures how much recombination would be required under a particular population model to generate the LD that is seen in the data. This type of method can potentially also provide a statistically rigorous approach to the problem of determining whether LD data provide evidence for the presence of recombination hotspots. For the methods described herein, a significant r ² value between markers indicative of the markers bein in linkage disequilibrium can be at least 0.1, such as at least 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50, 0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97, 0.98, or at least 0.99. In one preferred embodiment, the significant r ² value can be at least 0.2. Alternatively, markers in linkage disequilibrium are characterized by values of | D'| of at least 0.2, such as 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.85, 0.9, 0.95, 0.96, 0.97, 0.98, or at least 0.99. Thus, linkage disequilibrium represents a correlation between alleles of distinct markers. In certain embodiments, linkage disequilibrium is defined in terms of values for both the r ² and I D'l measures. In one such embodiment, a significant linkage disequilibrium is defined as r ² > 0.1 and | D'| >0.8, and markers fulfilling these criteria are said to be in linkage disequilibrium. In another embodiment, a significant linkage disequilibrium is defined as r ² > 0.2 and | D'| >0.9. Other combinations and permutations of values of r ² and | D'|for determining linkage

disequilibrium are also contemplated, and are also within the scope of the invention. Linkage disequilibrium can be determined in a single human population, as defined herein, or it can be determined in a collection of samples comprising individuals from more than one human population. In one embodiment of the invention, LD is determined in a sample from one or more of the HapMap populations (Caucasian, African (Yuroban), Japanese, Chinese), as defined (http://www.hapmap.org). In one such embodiment, LD is determined in the CEU population of the HapMap samples (Utah residents with ancestry from northern and western Europe) . In another embodiment, LD is determined in the YRI population of the HapMap samples (Yuroba in Ibadan, Nigeria). . In another embodiment, LD is determined in the CHB population of the HapMap samples (Han Chinese from Beijing, China). In another embodiment, LD is determined in the JPT population of the HapMap samples (Japanese from Tokyo, Japan). In yet another embodiment, LD is determined in samples from the Icelandic population. If all polymorphisms in the genome were independent at the population level {i.e., no LD), then every single one of them would need to be investigated in association studies, to assess all the different polymorphic states. However, due to linkage disequilibrium between polymorphisms, tightly linked polymorphisms are strongly correlated, which reduces the number of

polymorphisms that need to be investigated in an association study to observe a significant association. Another consequence of LD is that many polymorphisms may give an association signal due to the fact that these polymorphisms are strongly correlated.

Genomic LD maps have been generated across the genome, and such LD maps have been proposed to serve as framework for mapping disease-genes (Risch, N. & Merkiangas, K, Science 273: 1516-1517 (1996); Maniatis, N., et al., Proc Natl Acad Sci USA 99:2228-2233 (2002); Reich, DE et al, Nature 411 : 199-204 (2001)) .

It is now established that many portions of the human genome can be broken into series of discrete haplotype blocks containing a few common haplotypes; for these blocks, linkage disequilibrium data provides little evidence indicating recombination (see, e.g., Wall., J . D. and Pritchard, J. K., Nature Reviews Genetics 4: 587-597 (2003); Daly, M. et al., Nature Genet.

29:229-232 (2001); Gabriel, S. B. et al., Science 296:2225-2229 (2002); Patil, N. et al., Science 294: 1719-1723 (2001); Dawson, E. et al., Nature 4JS: 544-548 (2002); Phillips, M.S. et al., Nature Genet. 33:382-387 (2003)).

There are two mam methods for defining these haplotype blocks: blocks can be defined as regions of DNA that have limited haplotype diversity (see, e.g., Daly, M. et al., Nature Genet. 29:229-232 (2001); Patil, N. et al., Science 294: 1719-1723 (2001); Dawson, E. et al., Nature 418: 544-548 (2002); Zhang, K. et al., Proc. Natl. Acad. Sci. USA 99: 7335-7339 (2002)), or as regions between transition zones having extensive historical recombination, identified using linkage disequilibrium (see, e.g., Gabriel, S. B. et al., Science 296: 2225-2229 (2002); Phillips, M.S. et al., Nature Genet. 33:382-387 (2003); Wang, N. et al., Am. J. Hum. Genet. 71 : 1227- 1234 (2002); Stumpf, M. P., and Goldstein, D. B., Curr. Biol. 13: 1-8 (2003)). More recently, a fine-scale map of recombination rates and corresponding hotspots across the human genome has been generated (Myers, S., et al., Science 310:321-32324 (2005); Myers, S. et al., Biochem Soc Trans 34: 526530 (2006)). The map reveals the enormous variation in recombination across the genome, with recombination rates as high as 10-60 cM/Mb in hotspots, while closer to 0 in intervening regions, which thus represent regions of limited haplotype diversity and high LD. The map can therefore be used to define haplotype blocks/LD blocks as regions flanked by recombination hotspots. As used herein, the terms "haplotype block" or "LD block" includes blocks defined by any of the above described characteristics, or other alternative methods used by the person skilled in the art to define such regions.

Haplotype blocks (LD blocks) can be used to map associations between phenotype and haplotype status, using single markers or haplotypes comprising a plurality of markers. The main haplotypes can be identified in each haplotype block, and then a set of "tagging" SNPs or markers (the smallest set of SNPs or markers needed to distinguish among the haplotypes) can then be identified. These tagging SNPs or markers can then be used in assessment of samples from groups of individuals, in order to identify association between phenotype and haplotype. Markers shown herein to be associated with glaucoma are such tagging markers. If desired, neighboring haplotype blocks can be assessed concurrently, as there may also exist linkage disequilibrium among the haplotype blocks.

It has thus become apparent that for any given observed association to a polymorphic marker in the genome, additional markers in the genome also show association. This is a natural consequence of the uneven distribution of LD across the genome, as observed by the large variation in recombination rates. The markers used to detect association thus in a sense represent "tags" for a genomic region (i.e., a haplotype block or LD block) that is associating with a given disease or trait, and as such are useful for use in the methods and kits of the present invention. One or more causative (functional) variants or mutations may reside within the region found to be associating to the disease or trait. The functional variant may be another SNP, a tandem repeat polymorphism (such as a minisatellite or a microsatellite), a transposable element, or a copy number variation, such as an inversion, deletion or insertion. Such variants in LD with the variants described herein may confer a higher relative risk (RR) or odds ratio (OR) than observed for the tagging markers used to detect the association. The present invention thus refers to the markers used for detecting association to the disease, as described herein, as well as markers in linkage disequilibrium with the markers. Thus, in certain embodiments of the invention, markers that are in LD with the markers originally used to detect an association may be used as surrogate markers. The surrogate markers have in one embodiment relative risk (RR) and/or odds ratio (OR) values smaller than originally detected. In other embodiments, the surrogate markers have RR or OR values greater than those initially determined for the markers initially found to be associating with the disease. An example of such an embodiment would be a rare, or relatively rare (such as < 10% allelic population frequency) variant in LD with a more common variant (> 10% population frequency) initially found to be associating with the disease. Identifying and using such surrogate markers for detecting the association can be performed by routine methods well known to the person skilled in the art, and are therefore within the scope of the present invention.

Determination of haplotype frequency

The frequencies of haplotypes in patient and control groups can be estimated using an expectation-maximization algorithm (Dempster A. et al., J. R. Stat. Soc. B, 39: 1-38 (1977)). An implementation of this algorithm that can handle missing genotypes and uncertainty with the phase can be used. Under the null hypothesis, the patients and the controls are assumed to have identical frequencies. Using a likelihood approach, an alternative hypothesis is tested, where a candidate at-risk-haplotype, which can include the markers described herein, is allowed to have a higher frequency in patients than controls, while the ratios of the frequencies of other haplotypes are assumed to be the same in both groups. Likelihoods are maximized separately under both hypotheses and a corresponding 1-df likelihood ratio statistic is used to evaluate the statistical significance.

To look for at-risk and protective markers and haplotypes within a susceptibility region, for example within an LD block, association of all possible combinations of genotyped markers within the region is studied. The combined patient and control groups can be randomly divided into two sets, equal in size to the original group of patients and controls. The marker and haplotype analysis is then repeated and the most significant p-value registered is determined. This randomization scheme can be repeated, for example, over 100 times to construct an empirical distribution of p-values. In a preferred embodiment, a p-value of <0.05 is indicative of a significant marker and/or haplotype association.

Haplotype Analysis

One general approach to haplotype analysis involves using likelihood-based inference applied to NEsted MOdels (Gretarsdottir S., et al., Nat. Genet. 35: 131-38 (2003)). The method is implemented in the program NEMO, which allows for many polymorphic markers, SNPs and microsatellites. The method and software are specifically designed for case-control studies where the purpose is to identify haplotype groups that confer different risks. It is also a tool for studying LD structures. In NEMO, maximum likelihood estimates, likelihood ratios and p-values are calculated directly, with the aid of the EM algorithm, for the observed data treating it as a missing-data problem. Even though likelihood ratio tests based on likelihoods computed directly for the observed data, which have captured the information loss due to uncertainty in phase and missing genotypes, can be relied on to give valid p-values, it would still be of interest to know how much information had been lost due to the information being incomplete. The information measure for haplotype analysis is described in Nicolae and Kong (Technical Report 537, Department of Statistics, University of Statistics, University of Chicago; Biometrics, 60(2) :368-75 (2004)) as a natural extension of information measures defined for linkage analysis, and is implemented in NEMO.

Association analysis

For single marker association to a disease, the Fisher exact test can be used to calculate two- sided p-values for each individual allele. Correcting for relatedness among patients can be done by extending a variance adjustment procedure previously described (Risch, N. & Teng, J.

Genome Res., 8: 1273-1288 (1998)) for sibships so that it can be applied to general familial relationships. The method of genomic controls (Devlin, B. & Roeder, K. Biometrics 55 :997 (1999)) can also be used to adjust for the relatedness of the individuals and possible stratification. For both single-marker and haplotype analyses, relative risk (RR) and the population attributable risk (PAR) can be calculated assuming a multiplicative model (haplotype relative risk model) (Terwilliger, J. D. & Ott, ]., Hum. Hered. 42:337-46 (1992) and FaIk, CT. & Rubinstein, P, Ann. Hum. Genet 51 (Pt 3):227-33 (1987)), i.e., that the risks of the two alleles/haplotypes a person carries multiply. For example, if RR is the risk of A relative to a, then the risk of a person homozygote AA will be RR times that of a heterozygote Aa and RR ² times that of a homozygote aa. The multiplicative model has a nice property that simplifies analysis and computations— haplotypes are independent, i.e., in Hardy-Weinberg equilibrium, within the affected population as well as within the control population. As a consequence, haplotype counts of the affecteds and controls each have multinomial distributions, but with different haplotype frequencies under the alternative hypothesis. Specifically, for two haplotypes, h, and h _j , risk(h _i ,)/risk(h _j ) =

(f _i l P _i )/(f _j /P _j ), where f and p denote, respectively, frequencies in the affected population and in the control population. While there is some power loss if the true model is not multiplicative, the loss tends to be mild except for extreme cases. Most importantly, p-values are always valid since they are computed with respect to null hypothesis.

An association signal detected in one association study may be replicated in a second cohort, ideally from a different population (e.g., different region of same country, or a different country) of the same or different ethnicity. The advantage of replication studies is that the number of tests performed in the replication study is usually quite small, and hence the less stringent the statistical measure that needs to be applied. For example, for a genome-wide search for susceptibility variants for a particular disease or trait using 300,000 SNPs, a correction for the 300,000 tests performed (one for each SNP) can be performed. Since many SNPs on the arrays typically used are correlated {i.e., in LD), they are not independent. Thus, the correction is conservative. Nevertheless, applying this correction factor requires an observed P-value of less than 0.05/300,000 = 1.7 x 10 ^"7 for the signal to be considered significant applying this conservative test on results from a single study cohort. Obviously, signals found in a genome- wide association study with P-values less than this conservative threshold {i.e., more significant) are a measure of a true genetic effect, and replication in additional cohorts is not necessarily from a statistical point of view. Importantly, however, signals with P-values that are greater than this threshold may also be due to a true genetic effect. The sample size in the first study may not have been sufficiently large to provide an observed P-value that meets the conservative threshold for genome-wide significance, or the first study may not have reached genome-wide significance due to inherent fluctuations due to sampling. Since the correction factor depends on the number of statistical tests performed, if one signal (one SNP) from an initial study is replicated in a second case-control cohort, the appropriate statistical test for significance is that for a single statistical test, i.e., P-value less than 0.05. Replication studies in one or even several additional case-control cohorts have the added advantage of providing assessment of the association signal in additional populations, thus simultaneously confirming the initial finding and providing an assessment of the overall significance of the genetic variant(s) being tested in human populations in general.

The results from several case-control cohorts can also be combined to provide an overall assessment of the underlying effect. The methodology commonly used to combine results from multiple genetic association studies is the Mantel-Haenszel model (Mantel and Haenszel, J Natl Cancer Inst 22: 719-48 (1959)). The model is designed to deal with the situation where association results from different populations, with each possibly having a different population frequency of the genetic variant, are combined. The model combines the results assuming that the effect of the variant on the risk of the disease, a measured by the OR or RR, is the same in all populations, while the frequency of the variant may differ between the poplations. Combining the results from several populations has the added advantage that the overall power to detect a real underlying association signal is increased, due to the increased statistical power provided by the combined cohorts. Furthermore, any deficiencies in individual studies, for example due to unequal matching of cases and controls or population stratification will tend to balance out when results from multiple cohorts are combined, again providing a better estimate of the true underlying genetic effect.

Risk assessment and Diagnostics

Within any given population, there is an absolute risk of developing a disease or trait, defined as the chance of a person developing the specific disease or trait over a specified time-period. For example, a woman's lifetime absolute risk of breast cancer is one in nine. That is to say, one woman in every nine will develop breast cancer at some point in their lives. Risk is typically measured by looking at very large numbers of people, rather than at a particular individual. Risk is often presented in terms of Absolute Risk (AR) and Relative Risk (RR). Relative Risk is used to compare risks associating with two variants or the risks of two different groups of people. For example, it can be used to compare a group of people with a certain genotype with another group having a different genotype. For a disease, a relative risk of 2 means that one group has twice the chance of developing a disease as the other group. The risk presented is usually the relative risk for a person, or a specific genotype of a person, compared to the population with matched gender and ethnicity. Risks of two individuals of the same gender and ethnicity could be compared in a simple manner. For example, if, compared to the population, the first individual has relative risk 1.5 and the second has relative risk 0.5, then the risk of the first individual compared to the second individual is 1.5/0.5 = 3.

Risk Calculations The creation of a model to calculate the overall genetic risk involves two steps: i) conversion of odds-ratios for a single genetic variant into relative risk and ii) combination of risk from multiple variants in different genetic loci into a single relative risk value.

Deriving risk from odds-ratios

Most gene discovery studies for complex diseases that have been published to date in authoritative journals have employed a case-control design because of their retrospective setup. These studies sample and genotype a selected set of cases (people who have the specified disease condition) and control individuals. The interest is in genetic variants (alleles) which frequency in cases and controls differ significantly.

The results are typically reported in odds ratios, that is the ratio between the fraction

(probability) with the risk variant (carriers) versus the non-risk variant (non-carriers) in the groups of affected versus the controls, i.e. expressed in terms of probabilities conditional on the affection status:

OR = (Pr(c|A)/Pr(nc|A)) / (Pr(c|C)/Pr(nc| Q)

Sometimes it is however the absolute risk for the disease that we are interested in, i.e. the fraction of those individuals carrying the risk variant who get the disease or in other words the probability of getting the disease. This number cannot be directly measured in case-control studies, in part, because the ratio of cases versus controls is typically not the same as that in the general population. However, under certain assumption, we can estimate the risk from the odds ratio.

It is well known that under the rare disease assumption, the relative risk of a disease can be approximated by the odds ratio. This assumption may however not hold for many common diseases. Still, it turns out that the risk of one genotype variant relative to another can be estimated from the odds ratio expressed above. The calculation is particularly simple under the assumption of random population controls where the controls are random samples from the same population as the cases, including affected people rather than being strictly unaffected individuals. To increase sample size and power, many of the large genome-wide association and replication studies use controls that were neither age-matched with the cases, nor were they carefully scrutinized to ensure that they did not have the disease at the time of the study.

Hence, while not exactly, they often approximate a random sample from the general population. It is noted that this assumption is rarely expected to be satisfied exactly, but the risk estimates are usually robust to moderate deviations from this assumption.

Calculations show that for the dominant and the recessive models, where we have a risk variant carrier, "c", and a non-carrier, "nc", the odds ratio of individuals is the same as the risk ratio between these variants:

OR = Pr(A|c)/Pr(A| nc) = r And likewise for the multiplicative model, where the risk is the product of the risk associated with the two allele copies, the allelic odds ratio equals the risk factor:

OR = Pr(A|aa)/Pr(A| ab) = Pr(A|ab)/Pr(A| bb) = r

Here "a" denotes the risk allele and "b" the non-risk allele. The factor "r" is therefore the relative risk between the allele types. For many of the studies published in the last few years, reporting common variants associated with complex diseases, the multiplicative model has been found to summarize the effect adequately and most often provide a fit to the data superior to alternative models such as the dominant and recessive models. The risk relative to the average population risk

It is most convenient to represent the risk of a genetic variant relative to the average population since it makes it easier to communicate the lifetime risk for developing the disease compared with the baseline population risk. For example, in the multiplicative model we can calculate the relative population risk for variant "aa" as: RR(aa) = Pr(A|aa)/Pr(A) = (Pr(A| aa)/Pr(A| bb))/(Pr(A)/Pr(A| bb)) = r ² /(Pr(aa) r ² + Pr(ab) r + Pr(bb)) = r ² /(p ² r ² + 2pq r + q ² ) = r ² /R

Here "p" and "q" are the allele frequencies of "a" and "b" respectively. Likewise, we get that RR(ab) = r/R and RR(bb) = 1/R. The allele frequency estimates may be obtained from the publications that report the odds-ratios and from the HapMap database. Note that in the case where we do not know the genotypes of an individual, the relative genetic risk for that test or marker is simply equal to one.

As an example, in glaucoma risk, allele A of the disease associated marker rs4236601 on chromosome 7q31 has an allelic OR of 1.36 and a frequency (p) around 0.23 in white populations. The genotype relative risk compared to genotype GG are estimated based on the multiplicative model.

For AA it is 1.36x 1.36 = 1.85; for AG it is simply the OR 1.36, and for GG it is 1.0 by definition.

The frequency of allele G is q = l - p = l - 0.23 = 0.77. Population frequency of each of the three possible genotypes at this marker is:

Pr(AA) = p ² = 0.05, Pr(AG) = 2pq = 0.35, and Pr(GG) = q ² = 0.59 The average population risk relative to genotype GG (which is defined to have a risk of one) is: R = 0.05x 1.85 + 0.35 x 1.37 + 0.59x 1 = 1.16

Therefore, the risk relative to the general population (RR) for individuals who have one of the following genotypes at this marker is:

RR(AA) = 1.36/1.16 = 1.17, RR(AG) = 1.36/1.16 = 1.17, RR(GG) = 1/1.16 = 0.86. Combining the risk from multiple markers

When genotypes of many SNP variants are used to estimate the risk for an individual a multiplicative model for risk can generally be assumed. This means that the combined genetic risk relative to the population is calculated as the product of the corresponding estimates for individual markers, e.g. for two markers gl and g2:

RR(gl,g2) = RR(gl)RR(g2)

The underlying assumption is that the risk factors occur and behave independently, i.e. that the joint conditional probabilities can be represented as products:

Pr(A|gl,g2) = Pr(A|gl)Pr(A| g2)/Pr(A) and Pr(gl,g2) = Pr(gl)Pr(g2) Obvious violations to this assumption are markers that are closely spaced on the genome, i.e. in linkage disequilibrium, such that the concurrence of two or more risk alleles is correlated. In such cases, we can use so called haplotype modeling where the odds-ratios are defined for all allele combinations of the correlated SNPs.

As is in most situations where a statistical model is utilized, the model applied is not expected to be exactly true since it is not based on an underlying bio-physical model. However, the multiplicative model has so far been found to fit the data adequately, i.e. no significant deviations are detected for many common diseases for which many risk variants have been discovered.

As an example, an individual who has the following genotypes at 4 hypothetical markers associated with a particular disease along with the risk relative to the population at each marker:

Combined, the overall risk relative to the population for this individual is: 1.03x 1.30x 0.88x 1.54 = 1.81.

Adjusted life-time risk

The lifetime risk of an individual is derived by multiplying the overall genetic risk relative to the population with the average life-time risk of the disease in the general population of the same ethnicity and gender and in the region of the individual's geographical origin. As there are usually several epidemiologic studies to choose from when defining the general population risk, we will pick studies that are well-powered for the disease definition that has been used for the genetic variants. For example, for a disease, if the overall genetic risk relative to the population is 1.8 for a white individual, and if the average life-time risk of the disease for individuals of the same

demographic is 20%, then the adjusted lifetime risk for the individual is 20% x 1.8 = 36%.

Note that since the average RR for a population is one, this multiplication model provides the same average adjusted life-time risk of the disease. Furthermore, since the actual life-time risk cannot exceed 100%, there must be an upper limit to the genetic RR.

Risk assessment for glaucoma

As described herein, certain polymorphic markers and haplotypes comprising such markers are found to be useful for risk assessment of glaucoma. Risk assessment can involve the use of the markers for determining a susceptibility to glaucoma. Particular alleles of certain polymorphic markers are found more frequently in individuals with glaucoma, than in individuals without diagnosis of glaucoma. Therefore, these marker alleles have predictive value for detecting glaucoma, or a susceptibility to glaucoma, in an individual. Tagging markers in linkage disequilibrium with at-risk variants (or protective variants) described herein can be used as surrogates for these markers (and/or haplotypes). Such surrogate markers can be located within a particular haplotype block or LD block (e.g., LD block C07). Such surrogate markers can also sometimes be located outside the physical boundaries of such a haplotype block or LD block, either in close vicinity of the LD block/haplotype block, but possibly also located in a more distant genomic location. Long-distance LD can for example arise if particular genomic regions {e.g., genes) are in a functional relationship. For example, if two genes encode proteins that play a role in a shared metabolic pathway, then particular variants in one gene may have a direct impact on observed variants for the other gene. Let us consider the case where a variant in one gene leads to increased expression of the gene product. To counteract this effect and preserve overall flux of the particular pathway, this variant may have led to selection of one (or more) variants at a second gene that confers decreased expression levels of that gene. These two genes may be located in different genomic locations, possibly on different chromosomes, but variants within the genes are in apparent LD, not because of their shared physical location within a region of high LD, but rather due to evolutionary forces. Such LD is also contemplated and within scope of the present invention. The skilled person will appreciate that many other scenarios of functional gene-gene interaction are possible, and the particular example discussed here represents only one such possible scenario.

Markers with values of r ² equal to 1 are perfect surrogates for the at-risk variants (anchor variants), i.e. genotypes for one marker perfectly predicts genotypes for the other. Preferred embodiments of the methods described herein therefore relate to any suitable marker with values of r ² to rs4236601 equal to 1. Markers with smaller values of r ² than 1 can also be surrogates for the at-risk variant, or alternatively represent variants with relative risk values as high as or possibly even higher than the at-risk variant. In certain preferred embodiments, markers with values of r ² to the at-risk anchor variant are useful surrogate markers. The at-risk variant identified may not be the functional variant itself, but is in this instance in linkage disequilibrium with the true functional variant. The functional variant may be a SNP, but may also for example be a tandem repeat, such as a minisatellite or a microsatellite, a transposable element (e.g., an AIu element), or a structural alteration, such as a deletion, insertion or inversion (sometimes also called copy number variations, or CNVs). The present invention encompasses the assessment of such surrogate markers for the markers as disclosed herein. Such markers are annotated, mapped and listed in public databases, as well known to the skilled person, or can alternatively be readily identified by sequencing the region or a part of the region identified by the markers of the present invention in a group of individuals, and identify polymorphisms in the resulting group of sequences. As a consequence, the person skilled in the art can readily and without undue experimentation identify and genotype surrogate markers in linkage disequilibrium with the markers and/or haplotypes as described herein. The tagging or surrogate markers in LD with the at-risk variants detected also have predictive value. The present invention can in certain embodiments be practiced by assessing a sample comprising genomic DNA from an individual for the presence of certain variants described herein to be associated with glaucoma. Such assessment typically steps that detect the presence or absence of at least one allele of at least one polymorphic marker, using methods well known to the skilled person and further described herein, and based on the outcome of such assessment, determine whether the individual from whom the sample is derived is at increased or decreased risk {i.e., increased or decreased susceptibility) of glaucoma. Detecting particular alleles of polymorphic markers can in certain embodiments be done by obtaining nucleic acid sequence data about a particular human individual, that identifies at least one allele of at least one polymorphic marker. Different alleles of the at least one marker are associated with different susceptibility to the disease in humans. Obtaining nucleic acid sequence data can comprise nucleic acid sequence at a single nucleotide position, which is sufficient to identify alleles at SNPs. The nucleic acid sequence data can also comprise sequence at any other number of nucleotide positions, in particular for genetic markers that comprise multiple nuclotide positions, and can be anywhere from two to hundreds of thousands, possibly even millions, of nucleotides (in particular, in the case of copy number variations (CNVs)).

In certain embodiments, the invention can be practiced utilizing a dataset comprising information about the genotype status of at least one polymorphic marker associated with glaucoma (or markers in linkage disequilibrium with at least one marker associated with glaucoma). In other words, a dataset containing information about such genetic status, for example in the form of genotype counts at a certain polymorphic marker, or a plurality of markers (e.g., an indication of the presence or absence of certain at-risk alleles), or actual genotypes for one or more markers, can be queried for the presence or absence of certain at-risk alleles at certain polymorphic markers shown by the present inventors to be associated with glaucoma. A positive result for a variant {e.g., marker allele) associated with glaucoma, is indicative of the individual from which the dataset is derived is at increased susceptibility (increased risk) of glaucoma. In certain embodiments of the invention, a polymorphic marker is correlated to a disease by referencing genotype data for the polymorphic marker to a database, such as a look-up table, that comprises correlation data between at least one allele of the polymorphism and the disease. In some embodiments, the table comprises a correlation for one polymorphism. In other embodiments, the table comprises a correlation for a plurality of polymorphisms. In both scenarios, by referencing to a look-up table that gives an indication of a correlation between a marker and the disease, a risk for the disease, or a susceptibility to the disease, can be identified in the individual from whom the sample is derived. In some embodiments, the correlation is reported as a statistical measure. The statistical measure may be reported as a risk measure, such as a relative risk (RR), an absolute risk (AR) or an odds ratio (OR).

Risk markers may be useful for risk assessment and diagnostic purposes, either alone or in combination. Results of disease risk assessment based on the markers described herein can also be combined with data for other genetic markers or risk factors for the disease, to establish overall risk. Thus, even in cases where the increase in risk by individual markers is relatively modest, e.g. on the order of 10-30%, the association may have significant implications when combined with other risk markers. Thus, relatively common variants may have significant contribution to the overall risk (Population Attributable Risk is high), or combination of markers can be used to define groups of individual who, based on the combined risk of the markers, is at significant combined risk of developing the disease. Thus, in certain embodiments of the invention, a plurality of variants (genetic markers, biomarkers and/or haplotypes) is used for overall risk assessment. These variants are in one embodiment selected from the variants as disclosed herein. Other embodiments include the use of the variants of the present invention in combination with other variants known to be useful for determining a susceptibility to glaucoma. In such embodiments, the genotype status of a plurality of markers and/or haplotypes is determined in an individual, and the status of the individual compared with the population frequency of the associated variants, or the frequency of the variants in clinically healthy subjects, such as age-matched and sex-matched subjects. Methods known in the art, such as multivariate analyses or joint risk analyses, such as those described herein, or other methods known to the skilled person, may subsequently be used to determine the overall risk conferred based on the genotype status at the multiple loci.

Assessment of risk based on such analysis may subsequently be used in the methods, uses and kits of the invention, as described herein.

Study population

In a general sense, the methods and kits described herein can be utilized from samples containing nucleic acid material (DNA or RNA) from any source and from any individual, or from genotype or sequence data derived from such samples. In preferred embodiments, the individual is a human individual. The individual can be an adult, child, or fetus. The nucleic acid source may be any sample comprising nucleic acid material, including biological samples, or a sample comprising nucleic acid material derived therefrom. The present invention also provides for assessing markers and/or haplotypes in individuals who are members of a target population. Such a target population is in one embodiment a population or group of individuals at risk of developing the disease, based on other genetic factors, biomarkers, biophysical parameters, or general health and/or lifestyle parameters (e.g., family history of glaucoma or related eye diseases).

The invention provides for embodiments that include individuals from specific age subgroups, such as those over the age of 40, over age of 45, or over age of 50, 55, 60, 65, 70, 75, 80, or 85. Other embodiments of the invention pertain to other age groups, such as individuals aged less than 85, such as less than age 80, less than age 75, or less than age 70, 65, 60, 55, 50, 45, 40, 35, or age 30. Other embodiments relate to individuals with age at onset of glaucoma in any of the age ranges described in the above. It is also contemplated that a range of ages may be relevant in certain embodiments, such as age at onset at more than age 45 but less than age 60. Other age ranges are however also contemplated, including all age ranges bracketed by the age values listed in the above. The invention furthermore relates to individuals of either gender, males or females.

The Icelandic population is a Caucasian population of Northern European ancestry. A large number of studies reporting results of genetic linkage and association in the Icelandic population have been published in the last few years. Many of those studies show replication of variants, originally identified in the Icelandic population as being associating with a particular disease, in other populations (Sulem, P., et al. Nat Genet May 17 2009 (Epub ahead of print); Rafnar, T., et al. Nat Genet 41 :221-7 (2009); Gretarsdottir, S., et al. Ann Neurol 64:402-9 (2008); Stacey, S. N., et al. Nat Genet 40: 1313-18 (2008); Gudbjartsson, D. F., et al. Nat Genet 40:886-91 (2008); Styrkarsdottir, U., et al. N Engl J Med 358: 2355-65 (2008); Thorgeirsson, T., et al. Nature 452:638-42 (2008); Gudmundsson, J., et al. Nat Genet. 40:281-3 (2008); Stacey, S. N., et al., Nat Genet. 39:865-69 (2007); Helgadottir, A., et al., Science 316: 1491-93 (2007);

Steinthorsdottir, V., et al., Nat Genet. 39:770-75 (2007); Gudmundsson, J., et al., Nat Genet. 39:631-37 (2007); Frayling, TM, Nature Reviews Genet 8:657-662 (2007); Amundadottir, L.T., et al., Nat Genet. 38: 652-58 (2006); Grant, S. F., et al., Nat Genet. 38:320-23 (2006)). Thus, genetic findings in the Icelandic population have in general been replicated in other populations, including populations from Africa and Asia.

It is thus believed that the markers described herein to be associated with risk of glaucoma will show similar association in other human populations. Particular embodiments comprising individual human populations are thus also contemplated and within the scope of the invention. Such embodiments relate to human subjects that are from one or more human population including, but not limited to, Caucasian populations, European populations, American

populations, Eurasian populations, Asian populations, Central/South Asian populations, East Asian populations, Middle Eastern populations, African populations, Hispanic populations, and Oceanian populations. European populations include, but are not limited to, Swedish, Norwegian, Finnish, Russian, Danish, Icelandic, Irish, Kelt, English, Scottish, Dutch, Belgian, French, German, Spanish, Portuguese, Italian, Polish,

The racial contribution in individual subjects may also be determined by genetic analysis.

Genetic analysis of ancestry may be carried out using unlinked microsatellite markers such as those set out in Smith et al. [Am J Hum Genet 74, 1001-13 (2004)).

The person skilled in the art will appreciate that measures of linkage disequilibrium (LD) may give different results when applied to different populations. This is due to different population history of different human populations as well as differential selective pressures that may have led to differences in LD in specific genomic regions. It is also well known to the person skilled in the art that certain markers, e.g. SNP markers, have different population frequency in different populations, or are polymorphic in one population but not in another. The person skilled in the art will however apply the methods available and as thought herein to practice the present invention in any given human population. This may include assessment of polymorphic markers in the LD region of the present invention, so as to identify those markers that give strongest association within the specific population. Thus, the at-risk variants of the present invention may reside on different haplotype background and in different frequencies in various human populations. However, utilizing methods known in the art and the markers of the present invention, the invention can be practiced in any given human population.

Utility of Genetic Testing The person skilled in the art will appreciate and understand that the variants described herein in general do not, by themselves, provide an absolute identification of individuals who will develop a particular disease {e.g., glaucoma). The variants described herein do however indicate increased and/or decreased likelihood that individuals carrying the at-risk or protective variants of the invention will develop glaucoma. The present inventors have discovered that certain variants confer increase risk of developing glaucoma, as supported by the statistically significant results presented in the Exemplification herein. This information is extremely valuable in itself, as outlined in more detail in the below, as it can be used to, for example, initiate preventive measures at an early stage, perform regular physical exams to monitor the progress and/or appearance of symptoms, or to schedule exams at a regular interval to identify early symptoms, so as to be able to apply treatment at an early stage.

The knowledge about a genetic variant that confers a risk of developing or glaucoma offers the opportunity to apply a genetic test to distinguish between individuals with increased risk of developing glaucoma (i.e. carriers of the at-risk variant) and those with decreased risk of developing glaucoma (i.e. carriers of the protective variant, or non-carriers of an at-risk variant). The core values of genetic testing, for individuals belonging to both of the above mentioned groups, are the possibilities of being able to diagnose glaucoma, or a predisposition to glaucoma, at an early stage and provide information to the clinician about prognosis/aggressiveness of the disease in order to be able to apply the most appropriate treatment at an early stage. Individuals with a family history of glaucoma and carriers of at-risk variants may benefit from genetic testing since the knowledge of the presence of a genetic risk factor, or evidence for increased risk of being a carrier of one or more risk factors, may aid the clinician in selecting the best treatment options and medication for each individual. Further, individuals who are carriers of the at-risk variants of the invention are likely to benefit from regular monitoring from the clinician, so as to minimize the risk of developing glaucoma and/or apply treatment at an early stage.

The present invention furthermore relates to risk assessment for glaucoma, including diagnosing whether an individual is at risk for developing glaucoma. The polymorphic markers of the present invention can be used alone or in combination, as well as in combination with other factors, including other genetic risk factors or biomarkers, for risk assessment of an individual for glaucoma. Certain factors known to affect the predisposition of an individual towards glaucoma are known to the person skilled in the art and can be utilized in such assessment. These include, but are not limited to, increased intraocular pressure, age, visual field abnormalities that are observed in otherwise baseline visual field examinations, high myopia, family history of glaucoma, thin cornea (central corneal thickness of less than 556μm), a vertical or horizontal cup-to-disc ratio of greater than 0.4, systemic hypertension, cardiovascular disease, migraine headache, and peripheral vasospasm.

Yet another utility lies on the use of genetic markers to determine whether to apply particular treatment modalities. Thus, based on the carrier status of particular markers as described herein to be associated with risk of glaucoma, a particular treatment is administered. This can for example be done by first determining whether an individual is carrying at least one particular risk allele of one or more markers, or by determining the carrier status of the indiviudal with respect to at least one particular haplotype. Based on the result of the genetic analysis, the particular treatment modality is administered. The treatment modality can for example be a therapeutic agent for glaucoma, as described herein, or a therepeutic agent for lowering intraocular pressure.

Methods known in the art can be used for such assessment, including multivariate analyses or logistic regression. Diagnostic and screening methods

In certain embodiments, the present invention pertains to methods of diagnosing, or aiding in the diagnosis of, glaucoma or a susceptibility to glaucoma, by detecting particular alleles at genetic markers that appear more frequently in glaucoma subjects or subjects who are susceptible to glaucoma. In particular embodiments, the invention is a method of determining a susceptibility to glaucoma by detecting at least one allele of at least one polymorphic marker (e.g., the markers described herein). In other embodiments, the invention relates to a method of determining a susceptibility to glaucoma by detecting at least one allele of at least one polymorphic marker. The present invention describes methods whereby detection of particular alleles of particular markers or haplotypes is indicative of a susceptibility to glaucoma. Such prognostic or predictive assays can also be used to determine prophylactic treatment of a subject prior to the onset of symptoms of glaucoma.

The present invention pertains in some embodiments to methods of clinical applications of diagnosis, e.g., diagnosis performed by a medical professional. In other embodiments, the invention pertains to methods of diagnosis or methods of determination of a susceptibility performed by a layman. The layman can be the customer of a genotyping service. The layman may also be a genotype service provider, who performs genotype analysis on a DNA sample from an individual, in order to provide service related to genetic risk factors for particular traits or diseases, based on the genotype status of the individual {i.e., the customer). Recent technological advances in genotyping technologies, including high-throughput genotyping of SNP markers, such as Molecular Inversion Probe array technology (e.g., Affymetrix GeneChip), and BeadArray Technologies {e.g., Illumina GoldenGate and Infinium assays) have made it possible for individuals to have their own genome assessed for up to one million SNPs simultaneously, at relatively little cost. The resulting genotype information, which can be made available to the individual, can be compared to information about disease or trait risk associated with various SNPs, including information from public literature and scientific publications. The diagnostic application of disease-associated alleles as described herein, can thus for example be performed by the individual, through analysis of his/her genotype data, by a health professional based on results of a clinical test, or by a third party, including the genotype service provider. The third party may also be service provider who interprets genotype information from the customer to provide service related to specific genetic risk factors, including the genetic markers described herein. In other words, the diagnosis or determination of a susceptibility of genetic risk can be made by health professionals, genetic counselors, third parties providing genotyping service, third parties providing risk assessment service or by the layman {e.g., the individual), based on information about the genotype status of an individual and knowledge about the risk conferred by particular genetic risk factors {e.g., particular SNPs). In the present context, the term "diagnosing", "diagnose a susceptibility" and "determine a susceptibility" is meant to refer to any available diagnostic method, including those mentioned above. In certain embodiments, a sample containing genomic DNA from an individual is collected. Such sample can for example be a buccal swab, a saliva sample, a blood sample, or other suitable samples containing genomic DNA, as described further herein. The genomic DNA is then analyzed using any common technique available to the skilled person, such as high-throughput array technologies. Results from such genotyping are stored in a convenient data storage unit, such as a data carrier, including computer databases, data storage disks, or by other convenient data storage means. In certain embodiments, the computer database is an object database, a relational database or a post-relational database. The genotype data is subsequently analyzed for the presence of certain variants known to be susceptibility variants for a particular human conditions, such as the genetic variants described herein. Genotype data can be retrieved from the data storage unit using any convenient data query method. Calculating risk conferred by a particular genotype for the individual can be based on comparing the genotype of the individual to previously determined risk (expressed as a relative risk (RR) or and odds ratio (OR), for example) for the genotype, for example for an heterozygous carrier of an at-risk variant for a particular disease or trait. The calculated risk for the individual can be the relative risk for a person, or for a specific genotype of a person, compared to the average population with matched gender and ethnicity. The average population risk can be expressed as a weighted average of the risks of different genotypes, using results from a reference population, and the appropriate calculations to calculate the risk of a genotype group relative to the population can then be performed. Alternatively, the risk for an individual is based on a comparison of particular genotypes, for example heterozygous carriers of an at-risk allele of a marker compared with non-carriers of the at-risk allele. Using the population average may in certain embodiments be more convenient, since it provides a measure which is easy to interpret for the user, i.e. a measure that gives the risk for the individual, based on his/her genotype, compared with the average in the population. The calculated risk estimated can be made available to the customer via a website, preferably a secure website.

In certain embodiments, a service provider will include in the provided service all of the steps of isolating genomic DNA from a sample provided by the customer, performing genotyping of the isolated DNA, calculating genetic risk based on the genotype data, and report the risk to the customer. In some other embodiments, the service provider will include in the service the interpretation of genotype data for the individual, i.e. , risk estimates for particular genetic variants based on the genotype data for the individual. In some other embodiments, the service provider may include service that includes genotyping service and interpretation of the genotype data, starting from a sample of isolated DNA from the individual (the customer).

Overall risk for multiple risk variants can be performed using standard methodology. For example, assuming a multiplicative model, i.e. assuming that the risk of individual risk variants multiply to establish the overall effect, allows for a straight-forward calculation of the overall risk for multiple markers.

In addition, in certain other embodiments, the present invention pertains to methods of determining a decreased susceptibility to glaucoma, by detecting particular genetic marker alleles or haplotypes that appear less frequently in glaucoma patients than in individual not diagnosed with glaucoma or in the general population.

As described and exemplified herein, particular marker alleles or haplotypes are associated with risk of glaucoma. In one embodiment, the marker allele or haplotype is one that confers a significant risk or susceptibility to glaucoma. In another embodiment, the invention relates to a method of determining a susceptibility to glaucoma in a human individual, the method comprising determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual. In another embodiment, the invention pertains to methods of determining a susceptibility to glaucoma in a human individual, by screening for at least one marker allele or haplotype as described herein. In another embodiment, the marker allele or haplotype is more frequently present in a subject having, or who is susceptible to, glaucoma (affected), as compared to the frequency of its presence in a healthy subject (control, such as population controls) . In certain embodiments, the significance of association of the at least one marker allele or haplotype is characterized by a p value < 0.05. In other embodiments, the significance of association is characterized by smaller p-values, such as < 0.01, <0.001, <0.0001, <0.00001, <0.000001, <0.0000001, <0.00000001 or

<0.000000001.

In these embodiments, determination of the presence of the at least one marker allele or haplotype is indicative of a susceptibility to glaucoma. These diagnostic methods involve determining whether particular alleles or haplotypes that are associated with risk of glaucoma are present in particular individuals. The detection of particular genetic marker alleles can be performed by a variety of methods described herein and/or known in the art. For example, genetic markers can be detected at the nucleic acid level {e.g., by direct nucleotide sequencing, or by other genotyping means known to the skilled in the art) or at the amino acid level if the genetic marker affects the coding sequence of a protein {e.g. , by protein sequencing or by immunoassays using antibodies that recognize such a protein). The marker alleles or haplotypes correspond to fragments of a genomic segments (e.g., genes) associated with glaucoma. Such fragments encompass the DNA sequence of the polymorphic marker or haplotype in question, but may also include DNA segments in strong LD (linkage disequilibrium) with the marker or haplotype. In one embodiment, such segments comprises segments in LD with the marker or haplotype as determined by a value of r ² greater than 0.2 and/or | D'| > 0.8).

In one embodiment, determination of a susceptibility to glaucoma can be accomplished using hybridization methods, (see Current Protocols in Molecular Biology, Ausubel, F. et al., eds., John Wiley & Sons, including all supplements). The presence of a specific marker allele can be indicated by sequence-specific hybridization of a nucleic acid probe specific for the particular allele. The presence of more than one specific marker allele or a specific haplotype can be indicated by using several sequence-specific nucleic acid probes, each being specific for a particular allele. A sequence-specific probe can be directed to hybridize to genomic DNA, RNA, or cDNA. A "nucleic acid probe", as used herein, can be a DNA probe or an RNA probe that hybridizes to a complementary sequence. One of skill in the art would know how to design such a probe so that sequence specific hybridization will occur only if a particular allele is present in a genomic sequence from a test sample. The invention can also be reduced to practice using any convenient genotyping method, including commercially available technologies and methods for genotyping particular polymorphic markers.

To determine a susceptibility to glaucoma, a hybridization sample can be formed by contacting the test sample, such as a genomic DNA sample, with at least one nucleic acid probe. A non- limiting example of a probe for detecting mRNA or genomic DNA is a labeled nucleic acid probe that is capable of hybridizing to mRNA or genomic DNA sequences described herein. The nucleic acid probe can be, for example, a full-length nucleic acid molecule, or a portion thereof, such as an oligonucleotide of at least 15, 30, 50, 100, 250 or 500 nucleotides in length that is sufficient to specifically hybridize under stringent conditions to appropriate mRNA or genomic DNA. In certain embodiments, the oligonucleotide is from about 15 to about 100 nucleotides in length. In certain other embodiments, the oligonucleotide is from about 20 to about 50 nucleotides in length. The nucleic acid probe can comprise all or a portion of the nucleotide sequence of LD Block C07, as described herein, optionally comprising at least one allele of a marker described herein, or at least one haplotype described herein, or the probe can be the complementary sequence of such a sequence. In a particular embodiment, the nucleic acid probe is a portion of the nucleotide sequence of LD Block C07, as described herein (SEQ ID NO: 1), optionally comprising at least one allele of a marker described herein, or at least one allele of one polymorphic marker or haplotype comprising at least one polymorphic marker described herein, or the probe can be the complementary sequence of such a sequence. Other suitable probes for use in the diagnostic assays of the invention are described herein. Hybridization can be performed by methods well known to the person skilled in the art (see, e.g., Current Protocols in Molecular Biology, Ausubel, F. et ai, eds., John Wiley & Sons, including all supplements). In one embodiment, hybridization refers to specific hybridization, i.e., hybridization with no mismatches (exact hybridization). In one embodiment, the hybridization conditions for specific hybridization are high stringency. Specific hybridization, if present, is detected using standard methods. If specific hybridization occurs between the nucleic acid probe and the nucleic acid in the test sample, then the sample contains the allele that is complementary to the nucleotide that is present in the nucleic acid probe. The process can be repeated for any markers of the present invention, or markers that make up a haplotype of the present invention, or multiple probes can be used concurrently to detect more than one marker alleles at a time. It is also possible to design a single probe containing more than one marker alleles of a particular haplotype (e.g., a probe containing alleles complementary to 2, 3, 4, 5 or all of the markers that make up a particular haplotype). Detection of the particular markers of the haplotype in the sample is indicative that the source of the sample has the particular haplotype (e.g., a haplotype) and therefore is susceptible to glaucoma.

In one preferred embodiment, a method utilizing a detection oligonucleotide probe comprising a fluorescent moiety or group at its 3' terminus and a quencher at its 5' terminus, and an enhancer oligonucleotide, is employed, as described by Kutyavin et al. (Nucleic Acid Res. 34:el28 (2006)). The fluorescent moiety can be Gig Harbor Green or Yakima Yellow, or other suitable fluorescent moieties. The detection probe is designed to hybridize to a short nucleotide sequence that includes the SNP polymorphism to be detected. Preferably, the SNP is anywhere from the terminal residue to -6 residues from the 3' end of the detection probe. The enhancer is a short oligonucleotide probe which hybridizes to the DNA template 3' relative to the detection probe. The probes are designed such that a single nucleotide gap exists between the detection probe and the enhancer nucleotide probe when both are bound to the template. The gap creates a synthetic abasic site that is recognized by an endonuclease, such as Endonuclease IV. The enzyme cleaves the dye off the fully complementary detection probe, but cannot cleave a detection probe containing a mismatch. Thus, by measuring the fluorescence of the released fluorescent moiety, assessment of the presence of a particular allele defined by nucleotide sequence of the detection probe can be performed.

The detection probe can be of any suitable size, although preferably the probe is relatively short. In one embodiment, the probe is from 5-100 nucleotides in length. In another embodiment, the probe is from 10-50 nucleotides in length, and in another embodiment, the probe is from 12-30 nucleotides in length. Other lengths of the probe are possible and within scope of the skill of the average person skilled in the art.

In a preferred embodiment, the DNA template containing the SNP polymorphism is amplified by Polymerase Chain Reaction (PCR) prior to detection. In such an embodiment, the amplified DNA serves as the template for the detection probe and the enhancer probe.

Certain embodiments of the detection probe, the enhancer probe, and/or the primers used for amplification of the template by PCR include the use of modified bases, including modified A and modified G. The use of modified bases can be useful for adjusting the melting temperature of the nucleotide molecule (probe and/or primer) to the template DNA, for example for increasing the melting temperature in regions containing a low percentage of G or C bases, in which modified A with the capability of forming three hydrogen bonds to its complementary T can be used, or for decreasing the melting temperature in regions containing a high percentage of G or C bases, for example by using modified G bases that form only two hydrogen bonds to their complementary C base in a double stranded DNA molecule. In a preferred embodiment, modified bases are used in the design of the detection nucleotide probe. Any modified base known to the skilled person can be selected in these methods, and the selection of suitable bases is well within the scope of the skilled person based on the teachings herein and known bases available from commercial sources as known to the skilled person.

Alternatively, a peptide nucleic acid (PNA) probe can be used in addition to, or instead of, a nucleic acid probe in the hybridization methods described herein. A PNA is a DNA mimic having a peptide-like, inorganic backbone, such as N-(2-aminoethyl)glycine units, with an organic base (A, G, C, T or U) attached to the glycine nitrogen via a methylene carbonyl linker (see, for example, Nielsen, P., et al., Bioconjug. Chem. 5: 3-7 (1994)). The PNA probe can be designed to specifically hybridize to a molecule in a sample suspected of containing one or more of the marker alleles that are associated with glaucoma.

In one embodiment of the invention, a test sample containing genomic DNA obtained from the subject is collected and the polymerase chain reaction (PCR) is used to amplify a fragment comprising one ore more markers or haplotypes of the present invention. As described herein, identification of a particular marker allele or haplotype can be accomplished using a variety of methods {e.g., sequence analysis, analysis by restriction digestion, specific hybridization, single stranded conformation polymorphism assays (SSCP), electrophoretic analysis, etc.). In another embodiment, diagnosis is accomplished by expression analysis, for example by using

quantitative PCR (kinetic thermal cycling). This technique can, for example, utilize commercially available technologies, such as TaqMan ^® (Applied Biosystems, Foster City, CA) . The technique can assess the presence of an alteration in the expression or composition of a polypeptide or splicing variant(s). Further, the expression of the variant(s) can be quantified as physically or functionally different.

In another embodiment of the methods of the invention, analysis by restriction digestion can be used to detect a particular allele if the allele results in the creation or elimination of a restriction site relative to a reference sequence. Restriction fragment length polymorphism (RFLP) analysis can be conducted, e.g., as described in Current Protocols in Molecular Biology, supra. The digestion pattern of the relevant DNA fragment indicates the presence or absence of the particular allele in the sample.

Sequence analysis can also be used to detect specific alleles or haplotypes. Therefore, in one embodiment, determination of the presence or absence of a particular marker alleles or haplotypes comprises sequence analysis of a test sample of DNA or RNA obtained from a subject or individual. PCR or other appropriate methods can be used to amplify a portion of a nucleic acid that contains a polymorphic marker or haplotype, and the presence of specific alleles can then be detected directly by sequencing the polymorphic site (or multiple polymorphic sites in a haplotype) of the genomic DNA in the sample.

In another embodiment, arrays of oligonucleotide probes that are complementary to target nucleic acid sequence segments from a subject, can be used to identify particular alleles at polymorphic sites. For example, an oligonucleotide array can be used. Oligonucleotide arrays typically comprise a plurality of different oligonucleotide probes that are coupled to a surface of a substrate in different known locations. These arrays can generally be produced using mechanical synthesis methods or light directed synthesis methods that incorporate a combination of photolithographic methods and solid phase oligonucleotide synthesis methods, or by other methods known to the person skilled in the art (see, e.g., Bier, F. F., et al. Adv Biochem Eπg Biotechnol 109:433-53 (2008); Hoheisel, J. D., Nat Rev Genet 7:200-10 (2006); Fan, J. B., et al. Methods Enzymol 410: 57-73 (2006); Raqoussis, J. & Elvidge, G., Expert Rev MoI Dlagn 6: 145-52 (2006); Mockler, T. C, et al Genomics 85: 1-15 (2005), and references cited therein, the entire teachings of each of which are incorporated by reference herein). Many additional descriptions of the preparation and use of oligonucleotide arrays for detection of polymorphisms can be found, for example, in US 6,858,394, US 6,429,027, US 5,445,934, US 5,700,637, US

5,744,305, US 5,945,334, US 6,054,270, US 6,300,063, US 6,733,977, US 7,364,858, EP 619 321, and EP 373 203, the entire teachings of which are incorporated by reference herein.

Other methods of nucleic acid analysis that are available to those skilled in the art can be used to detect a particular allele at a polymorphic site. Representative methods include, for example, direct manual sequencing (Church and Gilbert, Proc. Natl. Acad. Sci. USA, 81 : 1991-1995 (1988); Sanger, F., et al. , Proc. Natl. Acad. Sci. USA, 74: 5463-5467 (1977); Beavis, et al., U.S. Patent No. 5,288,644); automated fluorescent sequencing; single-stranded conformation polymorphism assays (SSCP); clamped denaturing gel electrophoresis (CDGE); denaturing gradient gel electrophoresis (DGGE) (Sheffield, V., et al., Proc. Natl. Acad. Sci. USA, 86:232-236 (1989)), mobility shift analysis (Orita, M., et al. , Proc. Natl. Acad. Sci. USA, 86:2766-2770 (1989)), restriction enzyme analysis (Flavell, R., et al., Cell, 15: 25-41 (1978); Geever, R., et al., Proc. Natl. Acad. Sci. USA, 78: 5081-5085 (1981)); heteroduplex analysis; chemical mismatch cleavage (CMC) (Cotton, R., et al., Proc. Natl. Acad. Sci. USA, 85:4397-4401 (1985)); RNase protection assays (Myers, R., et al., Science, 230: 1242-1246 (1985); use of polypeptides that recognize nucleotide mismatches, such as E. coli mutS protein; and allele-specific PCR.

In another embodiment of the invention, determination of a susceptibility to glaucoma can be made by examining expression and/or composition of a polypeptide encoded by a nucleic acid associated with glaucoma in those instances where the genetic marker(s) or haplotype(s) of the present invention result in a change in the composition or expression of the polypeptide. Thus, determination of a susceptibility to glaucoma can be made by examining expression and/or composition of one of these polypeptides, or another polypeptide encoded by a nucleic acid associated with glaucoma, in those instances where the genetic marker or haplotype of the present invention results in a change in the composition or expression of the polypeptide. The markers described herein may thus affect expression of nearby genes (e.g., caveolin-1 and/or caveolin-2). It is well known that regulatory element affecting gene expression may be located far away, even as far as tenths or hundreds of kilobases away, from the promoter region of a gene. By assaying for the presence or absence of at least one allele of at least one polymorphic marker of the present invention, it is thus possible to assess the expression level of such nearby genes. Possible mechanisms affecting these genes include, e.g., effects on transcription, effects on RNA splicing, alterations in relative amounts of alternative splice forms of mRNA, effects on RNA stability, effects on transport from the nucleus to cytoplasm, and effects on the efficiency and accuracy of translation.

A variety of methods can be used for detecting protein expression levels, including enzyme linked immunosorbent assays (ELISA), Western blots, immunoprecipitations and

immunofluorescence. A test sample from a subject is assessed for the presence of an alteration in the expression and/or an alteration in composition of the polypeptide encoded by a particular nucleic acid. An alteration in expression of a polypeptide encoded by the nucleic acid can be, for example, an alteration in the quantitative polypeptide expression (i.e., the amount of polypeptide produced). An alteration in the composition of a polypeptide encoded by the nucleic acid is an alteration in the qualitative polypeptide expression (e.g., expression of a mutant polypeptide or of a different splicing variant). In one embodiment, diagnosis of a susceptibility to glaucoma is made by detecting a particular splicing variant encoded by a nucleic acid associated with glaucoma, or a particular pattern of splicing variants. Both such alterations (quantitative and qualitative) can also be present. An "alteration" in the polypeptide expression or composition, as used herein, refers to an alteration in expression or composition in a test sample, as compared to the expression or composition of the polypeptide in a control sample. A control sample is a sample that corresponds to the test sample (e.g. , is from the same type of cells), and is from a subject who is not affected by, and/or who does not have a susceptibility to, glaucoma. In one embodiment, the control sample is from a subject that does not possess a marker allele associated with glaucoma, as described herein. Similarly, the presence of one or more different splicing variants in the test sample, or the presence of significantly different amounts of different splicing variants in the test sample, as compared with the control sample, can be indicative of a susceptibility to glaucoma. An alteration in the expression or composition of the polypeptide in the test sample, as compared with the control sample, can be indicative of a specific allele in the instance where the allele alters a splice site relative to the reference in the control sample. Various means of examining expression or composition of a polypeptide encoded by a nucleic acid are known to the person skilled in the art and can be used, including spectroscopy, colorimetry, electrophoresis, isoelectric focusing, and immunoassays (e.g., David et al., U.S. Pat. No. 4,376,110) such as immunoblotting (see, e.g., Current Protocols in Molecular Biology, particularly chapter 10, supra).

For example, in one embodiment, an antibody (e.g., an antibody with a detectable label) that is capable of binding to a polypeptide encoded by a nucleic acid associated with glaucoma can be used (e.g, an antibody against caveolin-1 and/or caveolin-2 polypeptides). Antibodies can be polyclonal or monoclonal. An intact antibody, or a fragment thereof (e.g., Fv, Fab, Fab', F(ab') ₂ ) can be used. The term "labeled", with regard to the probe or antibody, is intended to encompass direct labeling of the probe or antibody by coupling (i.e., physically linking) a detectable substance to the probe or antibody, as well as indirect labeling of the probe or antibody by reactivity with another reagent that is directly labeled. Examples of indirect labeling include detection of a primary antibody using a labeled secondary antibody (e.g., a fluorescently-labeled secondary antibody) and end-labeling of a DNA probe with biotin such that it can be detected with fluorescently-labeled streptavidin.

In one embodiment of this method, the level or amount of a polypeptide in a test sample is compared with the level or amount of the polypeptide in a control sample. A level or amount of the polypeptide in the test sample that is higher or lower than the level or amount of the polypeptide in the control sample, such that the difference is statistically significant, is indicative of an alteration in the expression of the polypeptide encoded by the nucleic acid, and is diagnostic for a particular allele or haplotype responsible for causing the difference in expression. Alternatively, the composition of the polypeptide in a test sample is compared with the composition of the polypeptide in a control sample. In another embodiment, both the level or amount and the composition of the polypeptide can be assessed in the test sample and in the control sample. In another embodiment, determination of a susceptibility to glaucoma is made by detecting at least one marker or haplotype of the present invention, in combination with an additional protein-based, RNA-based or DNA-based assay.

Kits Kits useful in the methods of the invention comprise components useful in any of the methods described herein, including for example, primers for nucleic acid amplification, hybridization probes, restriction enzymes (e.g., for RFLP analysis), allele-specific oligonucleotides, antibodies that bind to an altered polypeptide encoded by a nucleic acid of the invention as described herein (e.g., a genomic segment comprising at least one polymorphic marker and/or haplotype of the present invention) or to a non-altered (native) polypeptide encoded by a nucleic acid of the invention as described herein, means for amplification of a nucleic acids, means for analyzing the nucleic acid sequence of a nucleic acid, means for analyzing the amino acid sequence of a polypeptide, etc. The kits can for example include necessary buffers, nucleic acid primers for amplifying nucleic acids of the invention (e.g., a nucleic acid segment comprising one or more of the polymorphic markers as described herein), and reagents for allele-specific detection of the fragments amplified using such primers and necessary enzymes (e.g. , dna polymerase).

Additionally, kits can provide reagents for assays to be used in combination with the methods of the present invention, e.g., reagents for use with other diagnostic assays for glaucoma.

In one embodiment, the invention pertains to a kit for assaying a sample from a subject to detect a susceptibility to glaucoma in a subject, wherein the kit comprises reagents necessary for selectively detecting at least one allele of at least one polymorphism of the present invention in the genome of the individual. In a particular embodiment, the reagents comprise at least one contiguous oligonucleotide that hybridizes to a fragment of the genome of the individual comprising at least one polymorphism of the present invention. In another embodiment, the reagents comprise at least one pair of oligonucleotides that hybridize to opposite strands of a genomic segment obtained from a subject, wherein each oligonucleotide primer pair is designed to selectively amplify a fragment of the genome of the individual that includes at least one polymorphism associated with glaucoma risk. In one such embodiment, the polymorphism is selected from the group consisting of rs4236601, and polymorphic markers in linkage disequilibrium therewith. In yet another embodiment the fragment is at least 20 base pairs in size. Such oligonucleotides or nucleic acids (e.g., oligonucleotide primers) can be designed using portions of the nucleic acid sequence flanking the polymorphisms (e.g., SNPs or microsatellites). In another embodiment, the kit comprises one or more labeled nucleic acids capable of allele- specific detection of one or more specific polymorphic markers or haplotypes, and reagents for detection of the label. Suitable labels include, e.g., a radioisotope, a fluorescent label, an enzyme label, an enzyme co-factor label, a magnetic label, a spin label, an epitope label.

In particular embodiments, the polymorphic marker to be detected by the reagents of the kit comprises one or more markers, two or more markers, three or more markers, four or more markers or five or more markers. In another embodiment, the marker to be detected comprises at least one marker from the group consisting of markers in strong linkage disequilibrium, as defined by values of r ² greater than 0.2, to rs4236601. In another embodiment, the marker or haplotype to be detected is selected from the group consisting of rsl0808180, s.115639367, rs3807958, rsl7138624, rsl l80289, rsll982034, rsl633714, s.115809902, s.115812308, rsll80293, rsll772856, s.115822680, s.115822757, rsl2535567, s.115823136, rsl633731, s.115823881, rsl l80286, rs58217805, s.115829658, rsl0252986, rsl633728, rsl918923, rsl918924, rsl0247635, rsl0247800, rsl0226352, rslO255816, s.115837158, s.115837213, s.115837220, s.115837228, s.115837231, rslO237417, s.115844941, s.115845073,

S.115845156, rs6952334, rs66910042, s.115852616, S.115853434, rsl0256207, rsl0228039, rsl0227962, rs4540346, rsl7138684, rs6963408, rslO282315, rslO261897, rs6466577, rslO225153, s.115869741, rsll971849, rslO215761, rslO215954, rs7796627, s.115874386, s.115875537, s.115876493, rs73454998, rs73454999, rs4273775, rs9656238, rs73455001, s.115885256, rs35421698, s.115887401, s.115890028, rs768107, s.115897291, s.115898314, rs717957, s.115900980, s.115903500, s.115904029, s.115904171, s.115904290, rs926197, S.115906984, s.115907049, rs879211, rs6976316, S.115913401, S.115914118, S.115914208, s.115914539, rsl2538592, s.115916238, s.115916241, s.115916324, rs6954077, s.115916526, s.115916936, rsl0282556, s.115918221, rsl0487350, rslO228178, rs6973611, rs6974053, rsl7515508, rsl0273272, s.115921458, s.115922252, s.115922359, rsl7138755, rsl7138756, s.115922928, s.115924118, s.115924242, rsl7138765, rs4730742, rs2191500, s.115926151, S.115926168, S.115926213, rs2270188, S.115927852, s.115928000, rs28503222, rs3779511, s.115929066, s.115929696, s.115929698, rsll980719, rsl0233003, s.115931038, rs67933359, rsl0253097, rsl2668473, rs28587043, rsl0271007, s.115933173, rs4730743, rs8940, rsl0278782, rsl0249656, s.115934973, rs4727833, rsl052990, rsl0224685, rsl7515960, s.115937080, rsl2536639, rsl0258482, rsl0262524, rs6466579, rslO281637, rs3919515, rs2024211, rslO281661, rsl7588172, s.115941422, rs6466580, rs6969706, s.115943204, rsl0261304, s.115943215, rs59454355, rs7811851, rs7795510, rsl2540035, s.115947197, rs4730745, rs55883210, rs6950798, rs6950964, rsl0227696, rslO257125, s.115949855, s.115950221, rs4385407, s.115951190, rs926198, rs917664, rs4730748, rsl l973363, s.115957431, rs3779512, rs9649394, rslO256914, s.115967515, rs4730751, rsl0270569, rslO241283, rs66916956, rs9886215, rs9886219, rs2109516, rslO22436, s.115984089, rs6466587, rslO49314, rs8713, rs6867, rslO49337, s.115989209, rs6961215, rs6961388, s.115990167, s.115990177, rsl0280730, rsl0232369, rs6959106, rs7802124, rs7802438, rsll979486, rsl0273326, s.115996983, s.115996984, rs7801180, rsl2535567, rsl633731, rsll80286, rsl0252986, rsl633728, rsl918923, rsl918924, rsl0247635, rsl0247800, rslO237417, rs6952334, rsl0228039, rsl0227962, rs4540346, rsl7138684, rs6963408, rslO282315, rs6466577, rs7796627, rs4273775, rs9656238, rs768107, rs717957, rs926197, rs879211, rs6976316, rsl2538592, rs6954077, rsl0487350, rslO228178, rsl7138749, rsl7515508, rsl0273272, rsl7138756, rsl7138765, rs4730742, rs2270188, rsll980719, rsl0253097, rsl0271007, rs4730743, rs8940, rsl0278782, rs4727833, rsl052990, rsl7515960, rsl0258482, rsl0262524, rs6466579, rslO281637, rs3919515, rs2024211, rsl7588172, rs6466580, rs6969706, rsl0227696, rs4236601, rs926198, rs917664, rs4730748, rs3779512, rs9649394, rslO256914, rs4730751, rsl0270569, rs9886215, rs9886219, rs2109516, rs6466587, rslO49314, rs8713, rs6867, rs6961215, rs6961388, rsl0280730, and rsl0232369.

In a preferred embodiment, the DNA template containing the SNP polymorphism is amplified by Polymerase Chain Reaction (PCR) prior to detection, and primers for such amplification are included in the reagent kit. In such an embodiment, the amplified DNA serves as the template for the detection probe and the enhancer probe.

In one embodiment, the DNA template is amplified by means of Whole Genome Amplification (WGA) methods, prior to assessment for the presence of specific polymorphic markers as described herein. Standard methods well known to the skilled person for performing WGA may be utilized, and are within scope of the invention. In one such embodiment, reagents for performing WGA are included in the reagent kit.

In a further aspect of the present invention, a pharmaceutical pack (kit) is provided, the pack comprising a therapeutic agent and a set of instructions for administration of the therapeutic agent to humans tested for one or more variants of the present invention, as disclosed herein. The therapeutic agent can be a small molecule drug, an antibody, a peptide, an antisense or rnai molecule, or other therapeutic molecules. In one embodiment, an individual identified as a carrier of at least one variant of the present invention is instructed to take a prescribed dose of the therapeutic agent. In one such embodiment, an individual identified as a homozygous carrier of at least one variant of the present invention is instructed to take a prescribed dose of the therapeutic agent. In another embodiment, an individual identified as a non-carrier of at least one variant of the present invention is instructed to take a prescribed dose of the therapeutic agent.

In certain embodiments, the kit further comprises a set of instructions for using the reagents comprising the kit. In certain embodiments, the kit further comprises a collection of data comprising correlation data between the polymorphic markers assessed by the kit and susceptibility to glaucoma. The collection of data may be provided on any suitable format. In one embodiment, the collection of data is provided on a computer-readable format.

Potential for utilization of variants in the development of improved therapies for glaucoma Most cases of glaucoma are not discovered until vision has been permanently lost, because clinical signs of the disease are subtle. However, the loss of vision caused by glaucoma could be limited or prevented by currently available therapies. It is therefore imperative to characterize and utilize the risk factors associated with increased risk of the disease. The present invention provides markers that can be used to identify those individuals that are at increased risk of developing symptoms associated with glaucoma. The present invention thus provides methods and kits for detecting and identifying those individuals who are at increased risk of developing glaucoma. Thus, the present invention provides methods for providing a more efficient and cost- effective way of identifying individuals likely to develop the disease. Using measurements of intraocular pressure to screen populations for glaucoma is not an effective method (Weinreb & Khaw, Lancet 363: 1711-20 (2004)). The most widely method used, Goldmann tonometry, underestimates the true intraocular pressure of patients with thin corneas and overestimates the pressure in patients with thick ones. Furthermore, half of all patients with primary open-angle glaucoma have pressure below 22 mm Hg (Mitchell et al., Ophthalmol 103: 1661-69 (1996)). In addition, most individuals with raised pressure do not have, and may never develop, optic nerve damage. Therefore, current methods need to rely on assessment of the optic disc, retinal nerve fibre layer and visual function, in addition to pressure.

The additional application of genetic risk factors may thus facilitate the development of more cost-effective and reliable prevention programs that are aimed at detecting eye disorders such as glaucoma at an early stage. Such programs may provide individuals who are at risk of developing glaucoma, or individuals with early symptoms of the disease, a hope for a successful therapeutic intervention based, in part, on the result of the genetic testing. Thus, individuals positive for the genetic test may be selected for more rigorous or frequent examination, or, if they also present with early symptoms of the disease, may undergo more aggressive therapeutic intervention. Also, the variants of the invention may be used to screen for those individuals who are most likely to benefit from irridectomy, which is an invasive medical procedure. A number of medications for glaucoma and lowering intraocular pressure have been developed. Prostaglandin analogs and prostamides, including latanoprost, travoprost, unoprostone and bimatoprost, reduce intraocular pressure by increasing the outflow of aqueous humour, and have in general become the first line of treatment. Some prostaglandins activate matrix

metallproteinases, which then remodel extracellular matrix and reduce outflow resistance, allowing the aqueous humour to flow out through this route. Other types of medications for reducing intraocular pressure include α2 adrenergic agonists, such as brimonidine and apraclonidine, carbonic anhydrase inhibitors, such as dorzolamide, brinzolamide, acetazolamide and methozolamide, β-blockers such as betaxolol, carteolol, levobunolol, metipranolol and timolol, and cholinergic agonists, for example pilocarpine and carbachol. Further information on glaucoma medications is provided in Agent Table I. Lowering intraocular pressure can, on average, reduce the number of ocular hypertensive patients progressing to glaucoma by one- half, and can also prevent progression in patients with pre-existing glaucoma. However, early intervention is of great importance.

Recently, drug delivery to the eye by means of intraocular injections has been marketed.

Examples of successful therapeutic applications include Lucentis (ranibizumab injection) and Macugen (pegaptanib sodium injection), both of which are prescribed for the treatment of wet age-related macular degeneration.

Laser treatment for glaucoma is also available, the most widely-used form for open-angle glaucoma being laser trabeculoplasty, whereby laser light is directed at the trabecular meshwork to reduce the resistance to aqueous humour outflow. Another procedure is laser diode cyclophotocoagulation, used in more advanced cases, and has a more temporary effect. Surgical methods have also been developed, including trabeculectomy, in which a small portion of the trabecular meshwork is excised.

Therapeutic agents

The variants (markers and/or haplotypes) disclosed herein can be useful in the identification of novel therapeutic targets for glaucoma. For example, genes containing, or in linkage

disequilibrium with, one or more of these variants (e.g., caveolin-1 and/or caveolin-2), or their products, as well as genes or their products that are directly or indirectly regulated by or interact with these variant genes or their products, can be targeted for the development of therapeutic agents for glaucoma. Therapeutic agents may comprise one or more of, for example, small nonprotein and non-nucleic acid molecules, proteins, peptides, protein fragments, nucleic acids (DNA, RNA), PNA (peptide nucleic acids), or their derivatives or mimetics which can modulate the function and/or levels of the target genes or their gene products.

It is contemplated that in certain embodiments, a useful therapeutic measure may comprise delivery of a caveolin-1 and/or caveolin-2 protein In vivo. Delivery of caveolin-1 and/or caveolin- 2 protein to a person in need thereof, either a person diagnosed with glaucoma, or a person at risk for developing glaucoma, may ameliorate or prevent the symptoms associated with the disease.

The nucleic acids and/or variants described herein, or nucleic acids comprising their

complementary sequence, may also be used as antisense constructs to control gene expression in cells, tissues or organs. The methodology associated with antisense techniques is well known to the skilled artisan, and is for example described and reviewed in AntisenseDrug Technology: Principles, Strategies, and Applications, Crooke, ed., Marcel Dekker Inc., New York (2001). In general, antisense agents (antisense oligonucleotides) are comprised of single stranded oligonucleotides (RNA or DNA) that are capable of binding to a complimentary nucleotide segment. By binding the appropriate target sequence, an RNA-RNA, DNA-DNA or RNA-DNA duplex is formed. The antisense oligonucleotides are complementary to the sense or coding strand of a gene. It is also possible to form a triple helix, where the antisense oligonucleotide binds to duplex DNA.

Several classes of antisense oligonucleotide are known to those skilled in the art, including cleavers and blockers. The former bind to target RNA sites, activate intracellular nucleases (e.g., RnaseH or Rnase L), that cleave the target RNA. Blockers bind to target RNA, inhibit protein translation by steric hindrance of the ribosomes. Examples of blockers include nucleic acids, morpholino compounds, locked nucleic acids and methylphosphonates (Thompson, Drug

Discovery Today, 7:912-917 (2002)). Antisense oligonucleotides are useful directly as therapeutic agents, and are also useful for determining and validating gene function, for example by gene knock-out or gene knock-down experiments. Antisense technology is further described in Lavery et al., Curr. Opin. Drug Discov. Devel. 6: 561-569 (2003), Stephens et al., Curr. Opin. MoI. Ther. 5: 118-122 (2003), Kurreck, Eur. J. Biochem. 270: 1628-44 (2003), Dias et al., MoI. Cancer Ten 1 :347-55 (2002), Chen, Methods MoI. Med. 75:621-636 (2003), Wang et al., Curr. Cancer Drug Targets 1 : 177-96 (2001), and Bennett, Antisense Nucleic Acid Drug.Dev. 12:215- 24 (2002).

In certain embodiments, the antisense agent is an oligonucleotide that is capable of binding to a particular nucleotide segment. In certain embodiments, the nucleotide segment comprises the caveolin-1 and/or the caveolin-2 gene, or biologically active fragments thereof. In certain other embodiments, the antisense nucleotide is capable of binding to a nucleotide segment as set forth in SEQ ID NO: 1. Antisense nucleotides can be from 5-500 nucleotides in length, including 5-200 nucleotides, 5-100 nucleotides, 10-50 nucleotides, and 10-30 nucleotides. In certain preferred embodiments, the antisense nucleotides is from 14-50 nucleotides in length, includign 14-40 nucleotides and 14-30 nucleotides. .

The variants described herein can also be used for the selection and design of antisense reagents that are specific for particular variants. Using information about the variants described herein, antisense oligonucleotides or other antisense molecules that specifically target mRNA molecules that contain one or more variants of the invention can be designed. In this manner, expression of mRNA molecules that contain one or more variant of the present invention (i.e. certain marker alleles and/or haplotypes) can be inhibited or blocked. In one embodiment, the antisense molecules are designed to specifically bind a particular allelic form (i.e., one or several variants (alleles and/or haplotypes)) of the target nucleic acid, thereby inhibiting translation of a product originating from this specific allele or haplotype, but which do not bind other or alternate variants at the specific polymorphic sites of the target nucleic acid molecule. As antisense molecules can be used to inactivate mRNA so as to inhibit gene expression, and thus protein expression, the molecules can be used for disease treatment. The methodology can involve cleavage by means of ribozymes containing nucleotide sequences complementary to one or more regions in the mRNA that attenuate the ability of the mRNA to be translated. Such mRNA regions include, for example, protein-coding regions, in particular protein-coding regions corresponding to catalytic activity, substrate and/or ligand binding sites, or other functional domains of a protein. The phenomenon of RNA interference (RNAi) has been actively studied for the last decade, since its original discovery in C. βlβgans (Fire βt al., Nature 391 :806-11 (1998)), and in recent years its potential use in treatment of human disease has been actively pursued (reviewed in Kim & Rossi, Nature Rev. Genet. 8: 173-204 (2007)). RNA interference (RNAi), also called gene silencing, is based on using double-stranded RNA molecules (dsRNA) to turn off specific genes. In the cell, cytoplasmic double-stranded RNA molecules (dsRNA) are processed by cellular complexes into small interfering RNA (siRNA). The siRNA guide the targeting of a protein-RNA complex to specific sites on a target mRNA, leading to cleavage of the mRNA (Thompson, Drug Discovery Today, 7:912-917 (2002)). The siRNA molecules are typically about 20, 21, 22 or 23 nucleotides in length. Thus, one aspect of the invention relates to isolated nucleic acid molecules, and the use of those molecules for RNA interference, i.e. as small interfering RNA molecules (siRNA). In one embodiment, the isolated nucleic acid molecules are 18-26 nucleotides in length, preferably 19-25 nucleotides in length, more preferably 20-24 nucleotides in length, and more preferably 21, 22 or 23 nucleotides in length.

Another pathway for RNAi-mediated gene silencing originates in endogenously encoded primary microRNA (pri-miRNA) transcripts, which are processed in the cell to generate precursor miRNA (pre-miRNA). These miRNA molecules are exported from the nucleus to the cytoplasm, where they undergo processing to generate mature miRNA molecules (miRNA), which direct translational inhibition by recognizing target sites in the 3' untranslated regions of mRNAs, and subsequent mRNA degradation by processing P-bodies (reviewed in Kim & Rossi, Nature Rev. Genet. 8: 173-204 (2007)).

Clinical applications of RNAi include the incorporation of synthetic siRNA duplexes, which preferably are approximately 20-23 nucleotides in size, and preferably have 3' overlaps of 2 nucleotides. Knockdown of gene expression is established by sequence-specific design for the target mRNA. Several commercial sites for optimal design and synthesis of such molecules are known to those skilled in the art.

Other applications provide longer siRNA molecules (typically 25-30 nucleotides in length, preferably about 27 nucleotides), as well as small hairpin RNAs (shRNAs; typically about 29 nucleotides in length). The latter are naturally expressed, as described in Amarzguioui et al. (FEBS Lett. 579: 5974-81 (2005)). Chemically synthetic siRNAs and shRNAs are substrates for in vivo processing, and in some cases provide more potent gene-silencing than shorter designs

(Kim et al., Nature Biotechnol. 23: 222-226 (2005); Siolas et al. _f Nature Biotechnol. 23:227-231 (2005)). In general siRNAs provide for transient silencing of gene expression, because their intracellular concentration is diluted by subsequent cell divisions. By contrast, expressed shRNAs mediate long-term, stable knockdown of target transcripts, for as long as transcription of the shRNA takes place (Marques et al., Nature Biotechnol. 23 :559-565 (2006); Brummelkamp et al., Science 296: 550-553 (2002)).

Since RNAi molecules, including siRNA, miRNA and shRNA, act in a sequence-dependent manner, the variants presented herein can be used to design RNAi reagents that recognize specific nucleic acid molecules comprising specific alleles and/or haplotypes (e.g., the alleles and/or haplotypes of the present invention), while not recognizing nucleic acid molecules comprising other alleles or haplotypes. These RNAi reagents can thus recognize and destroy the target nucleic acid molecules. As with antisense reagents, RNAi reagents can be useful as therapeutic agents (i.e., for turning off disease-associated genes or disease-associated gene variants), but may also be useful for characterizing and validating gene function (e.g., by gene knock-out or gene knockdown experiments).

Delivery of RNAi may be performed by a range of methodologies known to those skilled in the art. Methods utilizing non-viral delivery include cholesterol, stable nucleic acid-lipid particle (SNALP), heavy-chain antibody fragment (Fab), aptamers and nanoparticles. Viral delivery methods include use of lentivirus, adenovirus and adeno-associated virus. The siRNA molecules are in some embodiments chemically modified to increase their stability. This can include modifications at the 2' position of the ribose, including 2'-O-methylpurines and 2'- fluoropyrimidines, which provide resistance to Rnase activity. Other chemical modifications are possible and known to those skilled in the art.

The following references provide a further summary of RNAi, and possibilities for targeting specific genes using RNAi : Kim & Rossi, Nat. Rev. Genet. 8: 173-184 (2007), Chen & Rajewsky, Nat. Rev. Genet. 8: 93-103 (2007), Reynolds, et al., Nat. Biotechnol. 22: 326-330 (2004), Chi et al., Proc. Natl. Acad. Sci. USA 100:6343-6346 (2003), Vickers et al., J. Biol. Chem. 278:7108- 7118 (2003), Agami, Curr. Opin. Chem. Biol. 6:829-834 (2002), Lavery, et al., Curr. Opin. Drug Discov. Devel. 6: 561-569 (2003), Shi, Trends Genet. 19:9-12 (2003), Shuey et al., Drug Discov. Today 7: 1040-46 (2002), McManus et al., Nat. Rev. Genet. 3: 737-747 (2002), Xia et al., Nat. Biotechnol. 20: 1006-10 (2002), Plasterk et al., curr. Opin. Genet. Dev. 10: 562-7 (2000), Bosher et al., Nat. Cell Biol. 2: E31-6 (2000), and Hunter, Curr. Biol. 9: R440-442 (1999). Inihibitory agents, including antisense, small molecule drugs and RNAi, can also be used to perturb cellular expression control so as to increase the expression of the caveolin-2 and/or caveolin-2 genes. Thus, inhibitory agents can be used to target inhibitory transcriptional regulators of one or both of these genes. Alleviation or reduction of the activity of such regulators will then lead to an increase in the transcription of the gene. Thus, the present invention also relates to the use of inhibitory agents that target transcriptional regulators of the caveolin-2 and/or caveolin-2 genes. It is also contemplated that gene products located upstream in a cellular pathway leading to, or affecting, the caveolin-2 and/or caveolin-2 genes, can be targets for such inhibitory agents. Such inhibitory agents may lead to the inhibition of the expression of the caveolin-2 and/or caveolin-2 genes, or they may lead to an increase in the expression of the caveolin-2 and/or caveolin-2 genes, depending on the normal biological function of the gene product in question.

The eye is a relatively isolated tissue compartment, making it ideal for protein therapy or gene therapy, including utilization of RNAi molecules. Local delivery to the eye by intraocular injection limits exposure to the rest of the body, and reduces the amount of therapeutic agent needed. For example, the amount of siRNA used in ocular delivery is small compared to systemic application. This allows local silencing of a gene, with little chance of affecting the gene in tissues outside of the eye. Several applications of ocular administration of siRNA have been reported, as reviewed by Campochiaro (Gene Therapy 13: 559-62 (2006)).

A genetic defect leading to increased predisposition or risk for development of glaucoma, or a defect causing glaucoma, may be corrected permanently by administering to a subject carrying the defect a nucleic acid fragment that incorporates a repair sequence that supplies the normal/wild-type nucleotide(s) at the site of the genetic defect. Such site-specific repair sequence may concompass an RNA/DNA oligonucleotide that operates to promote endogenous repair of a subject's genomic DNA. The administration of the repair sequence may be performed by an appropriate vehicle, such as a complex with polyethelenimine, encapsulated in anionic liposomes, a viral vector such as an adenovirus vector, or other pharmaceutical compositions suitable for promoting intracellular uptake of the adminstered nucleic acid. The genetic defect may then be overcome, since the chimeric oligonucleotides induce the incorporation of the normal sequence into the genome of the subject, leading to expression of the normal/wild-type gene product. The replacement is propagated, thus rendering a permanent repair and alleviation of the symptoms associated with the disease or condition.

Variant gene expression in a patient can be assessed by expression of a variant-containing nucleic acid sequence (e.g., caveolin-1 and/or caveolin-2), or by altered expression of a normal/wild-type nucleic acid sequence due to variants affecting the level or pattern of expression of the normal transcripts, for example variants in the regulatory or control region of the gene. Assays for gene expression include direct nucleic acid assays (mRNA), assays for expressed protein levels, or assays of collateral compounds involved in a pathway, for example a signal pathway. Furthermore, the expression of genes that are up- or down-regulated in response to the signal pathway can also be assayed. One embodiment includes operably linking a reporter gene, such as luciferase, to the regulatory region of the gene(s) of interest.

Modulators of gene expression can in one embodiment be identified when a cell is contacted with a candidate compound or agent, and the expression of mRNA is determined. The expression level of mRNA in the presence of the candidate compound or agent is compared to the expression level in the absence of the compound or agent. Based on this comparison, candidate compounds or agents for treating glaucoma can be identified as those modulating the gene expression of the variant gene. When expression of mRNA or the encoded protein is statistically significantly greater in the presence of the candidate compound or agent than in its absence, then the candidate compound or agent is identified as a stimulator or up-regulator of expression of the nucleic acid. When nucleic acid expression or protein level is statistically significantly less in the presence of the candidate compound or agent than in its absence, then the candidate compound is identified as an inhibitor or down-regulator of the nucleic acid expression.

The invention further provides methods of treatment using a compound identified through drug (compound and/or agent) screening as a gene modulator (i.e. stimulator and/or inhibitor of gene expression).

Methods of assessing probability of response to therapeutic agents, methods of monitoring progress of treatment and methods of treatment

As is known in the art, individuals can have differential responses to a particular therapy (e.g., a therapeutic agent or therapeutic method). Pharmacogenomics addresses the issue of how genetic variations (e.g., the variants (markers and/or haplotypes) of the present invention) affect drug response, due to altered drug disposition and/or abnormal or altered action of the drug. Thus, the basis of the differential response may be genetically determined in part. Clinical outcomes due to genetic variations affecting drug response may result in toxicity of the drug in certain individuals {e.g., carriers or non-carriers of the genetic variants of the present invention), or therapeutic failure of the drug. Therefore, the variants of the present invention may determine the manner in which a therapeutic agent and/or method acts on the body, or the way in which the body metabolizes the therapeutic agent.

Accordingly, in one embodiment, the presence of a particular allele at a polymorphic site or haplotype is indicative of a different response, e.g. a different response rate, to a particular treatment modality. This means that a patient diagnosed with glaucoma, and carrying a certain allele at a particular polymorphic site would respond better to, or worse to, a specific

therapeutic, drug and/or other therapy used to treat glaucoma. Therefore, the presence or absence of the marker allele or haplotype could aid in deciding what treatment should be used for a the patient. For example, for a newly diagnosed patient, the presence of a marker or haplotype of the present invention may be assessed (e.g., through testing DNA derived from a blood sample, as described herein). If the patient is positive for a marker allele or haplotype at (that is, at least one specific allele of the marker, or haplotype, is present), then the physician recommends one particular therapy, while if the patient is negative for the at least one allele of a marker, or a haplotype, then a different course of therapy may be recommended (which may include recommending that no immediate therapy, other than serial monitoring for progression of the disease, be performed). Thus, the patient's carrier status could be used to help determine whether a particular treatment modality should be administered. The value lies within the possibilities of being able to diagnose the disease at an early stage, to select the most appropriate treatment, and provide information to the clinician about prognosis/aggressiveness of the disease in order to be able to apply the most appropriate treatment. This type of selection of individuals who would especially benefit froma particular treatment modality is contemplated to be applicable to a wide range of therapeutic agents for glaucoma, including the therapeutic agents listed in Agent Table I herein.

Another aspect of the invention relates to methods of select individuals suitable for a particular treatment modality, based on the their likelihood of developing particular complications or side effects of the particular treatment. It is well known that most therapeutic agents can lead to certain unwanted complications or side effects. Likewise, certain therapeutic procedures or operations may have complications associated with them. Complications or side effects of these particular treatments or associated with specific therapeutic agents can, just as diseases do, have a genetic component. It is therefore contemplated that selection of the appropriate treatment or therapeutic agent can in part be performed by determining the genotype of an individual, and using the genotype status of the individual to decide on a suitable therapeutic procedure or on a suitable therapeutic agent to treat the particular disease. It is therefore contemplated that the polymorphic markers of the present invention can be used in this manner. In particular, the polymorphic markers of the present invention can be used to determine whether administration of a particular therapeutic agent or treatment modality or method is suitable for the individual, based on estimating the likelihood that the individual will glaucoma or a related condition (e.g., elevated intraocular pressure) as a consequence of being administered the particular therapeutic agent or treatment modality or method. Indescriminate use of a such therapeutic agents or treatment modalities may lead to unnecessary and needless blindness in individuals due to the adverse complications.

In one embodiment of this aspect, the genetic markers of the invention are used to select individuals suitable for receiving intravitreal steroid injections. Intravitreal corticosteroids are commonly used to treat inflammation in the eye caused by various edematous and neovascular intraocular conditions, including macular edema secondary to diabetes, pseudophakia, central retinal vein occlusion, and uveitis, as well as radiation-induced edema, macular edema associated with retinitis pigmentosa, systoid macular edema secondary to birdshot

retinochoroidopathy, and also exudative age-related macular degeneration, proliferative diabetic retionapthy, neovascular glaucoma, proliferative vitreaoretinopathy, chronic uveitis, acquired parafoveral teleangiectasia, choroidal neovascularization in ocular histoplasmosis syndrome, sympathetic ophthalmia, prephthisical ocular hypotony, and serous retinal detachment in Vogt- Koyanagi-Harada syndrome (Reichle, M. Optometry 76: 450-460 (2005)). Topical and systemic corticosteroids are known to be associated with increased intraocular pressure (IOP) in 30 - 40% of the general population and in about 60% of first-degree relatives of people with primary open angle glaucoma (POAG) (Reichle, M. Optometry 76: 450-460 (2005); Krishnadas, R. &

Ramakrishnan, R., Community Eye Health 14: 40-42 (2001); Wordinger, RJ. & Clark, A. F., Progr Retinal Eye Research 18:629-667 (1999)). Increased IOP is known to be associated with exfoliation syndrome and glaucoma, and thus increased IOP due to steroid administration may lead to increased predisposition to exfoliation syndrome. In particular, it is noteworthy that exfoliation material characteristic of exfoliation syndrome is known to accumulate in the trabecular meshwork, and that the amount of the material correlates inversely with axon count in the eye, indicating a direct causative relationship between the buildup of the exfoliation material in the meshwork and the development of disease symptoms (Ritch, et ai., Progr Retinal Eye Research 22: 253-275 (2003)).

Exemplary corticosteroids are provided by the glucorticoids set forth in Agent Table II.

Identification of those individuals at highest risk of developing complications due to steroid administration prior to selection of appropriate therapy could significantly decrease unnecessary blindness caused by corticosteroids. As the polymorphic markers of the present invention can be used to determine whether an individual is at increased (or decreased) risk of developing glaucoma and symptoms associated therewith, including elevated intraocular pressure, it is contemplated that the markers may also be used to determine whether an individual is at an increased risk of developing elevated IOC and/or glaucoma as a consequence of being administered naturally occurring or synthetic corticosteroids. Thus, in one embodiment, the invention relates to a method of determining whether a human individual is at risk for developing elevated intraocular pressure and/or glaucoma as a complication of being treated with a glucocorticoid therapeutic agent, the method comprising determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual, wherein the at least one polymorphic marker is associated with the human caveolin-1 and/or caveolin-2 gene, and wherein the presence of the at least one allele is indicative of an increased risk of developing elevated intraocular pressure and/or glaucoma as a complication of being treated with a glucocorticoid therapeutic agent. In certain embodiments, individuals who are carriers of the allele A of rs4236601, or a variant in linkage disequilibrium therewith, are contemplated to be especially vulnerable to such complications. Furthermore, individuals who are homozygous for at least one such at-risk variant (marker or haplotype) are contemplated to be especially vulnerable. Such individuals are therefore contemplated to be especially vulnerable to developing elevated intraocular pressure and/or glaucoma as a complication of being treated with a glucocorticoid therapeutic agent. Corticosteroid therapeutic agents that are commonly used for delivery to the eye include, but are not limited to, betamethoasone, clobetasone butyrate, dexamethasone, fluorometholone, hydrocortisone acetate, prednisolone, rimexolone, loteprednol, and medrysone.

Individuals who carry protective variants, e.g., the protective allele of the polymorphic markers of the invention may be suitable for administration of corticosteroid therapy, due to a decreased risk of developing elevated intraocular pressure and/or glaucoma as a complication of being treated with a glucocorticoid therapeutic agent. Protective variants include allele G of rs4236601, and marker alleles in linkage disequilibrium therewith. Particularly suitable individuals are those that carry two copies of allele G of rs4236601, and marker alleles in linkage disequilibrium therewith.. Thus, individuals suitable for receiving particular therapy, i.e. corticosteroid therapy, are in certain embodiments those individuals who do not carry the at-risk variants of the invention in their genome, or those who are heterozygous carriers, including those individuals who are homozygous for the protective variants of the SNP markers or haplotypes of the invention.

The present invention also relates to methods of monitoring progress or effectiveness of a treatment for glaucoma. This can be done based on the genotype status of the markers as described herein, i.e., by assessing the absence or presence of at least one allele of at least one polymorphic marker as disclosed herein, or by monitoring expression of genes that are associated with the variants (markers and haplotypes) of the present invention (e.g., the human caveolin-1 and/or caveolin-2 genes). The risk gene mRNA or the encoded polypeptide can be measured in a tissue sample (e.g., a peripheral blood sample, or a biopsy sample). Expression levels and/or mRNA levels can thus be determined before and during treatment to monitor its effectiveness. Alternatively, or concomitantly, the genotype and/or haplotype status of at least one risk variant for glaucoma as presented herein is determined before and during treatment to monitor its effectiveness.

Alternatively, biological networks or metabolic pathways related to the markers and haplotypes of the present invention can be monitored by determining mRNA and/or polypeptide levels. This can be done for example, by monitoring expression levels or polypeptides for several genes belonging to the network and/or pathway, in samples taken before and/or during treatment. Alternatively, metabolites belonging to the biological network or metabolic pathway can be determined before and during treatment. Effectiveness of the treatment is determined by comparing observed changes in expression levels/metabolite levels during treatment to corresponding data from healthy subjects. In a further aspect, the markers of the present invention can be used to increase power and effectiveness of clinical trials. Thus, individuals who are carriers of at least one at-risk variant of the present invention, i.e. individuals who are carriers of at least one allele of at least one polymorphic marker conferring increased risk of developing glaucoma may be more likely to respond to a particular treatment modality. In one embodiment, individuals who carry at-πsk variants for gene(s) in a pathway and/or metabolic network for which a particular treatment (e.g., small molecule drug) is targeting (e.g., the human caveolin-1 and/or caveolin-2 genes), are more likely to be responders to the treatment. In another embodiment, individuals who carry at-risk variants for a gene, which expression and/or function is altered by the at-risk variant, are more likely to be responders to a treatment modality targeting that gene, its expression or its gene product. This application can improve the safety of clinical trials, but can also enhance the chance that a clinical trial will demonstrate statistically significant efficacy, which may be limited to a certain sub-group of the population. Thus, one possible outcome of such a trial is that carriers of certain genetic variants, e.g., the markers and haplotypes of the present invention, are statistically significantly likely to show positive response to the therapeutic agent, i.e. experience alleviation of symptoms associated glaucoma when taking the therapeutic agent or drug as prescribed.

In a further aspect, the markers and haplotypes of the present invention can be used for targeting the selection of pharmaceutical agents for specific individuals. Personalized selection of treatment modalities, lifestyle changes or combination of the two, can be realized by the utilization of the at-risk variants of the present invention. Thus, the knowledge of an individual's status for particular markers of the present invention, can be useful for selection of treatment options that target genes or gene products affected by the at-risk variants of the invention. Certain combinations of variants may be suitable for one selection of treatment options, while other gene variant combinations may target other treatment options. Such combination of variant may include one variant, two variants, three variants, or four or more variants, as needed to determine with clinically reliable accuracy the selection of treatment module.

Computer-implemented aspects

As understood by those of ordinary skill in the art, the methods and information described herein may be implemented, in all or in part, as computer executable instructions on known computer readable media. For example, the methods described herein may be implemented in hardware. Alternatively, the method may be implemented in software stored in, for example, one or more memories or other computer readable medium and implemented on one or more processors. As is known, the processors may be associated with one or more controllers, calculation units and/or other units of a computer system, or implanted in firmware as desired. If implemented in software, the routines may be stored in any computer readable memory such as in RAM, ROM, flash memory, a magnetic disk, a laser disk, or other storage medium, as is also known.

Likewise, this software may be delivered to a computing device via any known delivery method including, for example, over a communication channel such as a telephone line, the Internet, a wireless connection, etc., or via a transportable medium, such as a computer readable disk, flash drive, etc.

More generally, and as understood by those of ordinary skill in the art, the various steps described above may be implemented as various blocks, operations, tools, modules and techniques which, in turn, may be implemented in hardware, firmware, software, or any combination of hardware, firmware, and/or software. When implemented in hardware, some or all of the blocks, operations, techniques, etc. may be implemented in, for example, a custom integrated circuit (IC), an application specific integrated circuit (ASIC), a field programmable logic array (FPGA), a programmable logic array (PLA), etc.

When implemented in software, the software may be stored in any known computer readable medium such as on a magnetic disk, an optical disk, or other storage medium, in a RAM or ROM or flash memory of a computer, processor, hard disk drive, optical disk drive, tape drive, etc. Likewise, the software may be delivered to a user or a computing system via any known delivery method including, for example, on a computer readable disk or other transportable computer storage mechanism. Fig. 1 illustrates an example of a suitable computing system environment 100 on which a system for the steps of the claimed method and apparatus may be implemented. The computing system environment 100 is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the method or apparatus of the claims. Neither should the computing environment 100 be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary operating environment 100. The steps of the claimed method and system are operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known computing systems, environments, and/or configurations that may be suitable for use with the methods or system of the claims include, but are not limited to, personal computers, server computers, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.

The steps of the claimed method and system may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The methods and apparatus may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In both integrated and distributed computing environments, program modules may be located in both local and remote computer storage media including memory storage devices.

With reference to Fig. 1, an exemplary system for implementing the steps of the claimed method and system includes a general purpose computing device in the form of a computer 110.

Components of computer 110 may include, but are not limited to, a processing unit 120, a system memory 130, and a system bus 121 that couples various system components including the system memory to the processing unit 120. The system bus 121 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus also known as Mezzanine bus.

Computer 110 typically includes a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer 110 and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media and

communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by computer 110. Communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media.

Combinations of the any of the above should also be included within the scope of computer readable media.

The system memory 130 includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM) 131 and random access memory (RAM) 132. A basic input/output system 133 (BIOS), containing the basic routines that help to transfer information between elements within computer 110, such as during start-up, is typically stored in ROM 131. RAM 132 typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit 120. By way of example, and not limitation, Fig. 1 illustrates operating system 134, application programs 135, other program modules 136, and program data 137.

The computer 110 may also include other removable/non-removable, volatile/nonvolatile computer storage media. By way of example only, Fig. 1 illustrates a hard disk drive 140 that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive 151 that reads from or writes to a removable, nonvolatile magnetic disk 152, and an optical disk drive 155 that reads from or writes to a removable, nonvolatile optical disk 156 such as a CD ROM or other optical media. Other removable/non-removable, volatile/nonvolatile computer storage media that can be used in the exemplary operating environment include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like. The hard disk drive 141 is typically connected to the system bus 121 through a non-removable memory interface such as interface 140, and magnetic disk drive 151 and optical disk drive 155 are typically connected to the system bus 121 by a removable memory interface, such as interface 150.

The drives and their associated computer storage media discussed above and illustrated in Fig. 1, provide storage of computer readable instructions, data structures, program modules and other data for the computer 110. In Fig. 1, for example, hard disk drive 141 is illustrated as storing operating system 144, application programs 145, other program modules 146, and program data 147. Note that these components can either be the same as or different from operating system 134, application programs 135, other program modules 136, and program data 137. Operating system 144, application programs 145, other program modules 146, and program data 147 are given different numbers here to illustrate that, at a minimum, they are different copies. A user may enter commands and information into the computer 20 through input devices such as a keyboard 162 and pointing device 161, commonly referred to as a mouse, trackball or touch pad. Other input devices (not shown) may include a microphone, joystick, game pad, satellite dish, scanner, or the like. These and other input devices are often connected to the processing unit 120 through a user input interface 160 that is coupled to the system bus, but may be connected by other interface and bus structures, such as a parallel port, game port or a universal serial bus (LJSB). A monitor 191 or other type of display device is also connected to the system bus 121 via an interface, such as a video interface 190. In addition to the monitor, computers may also include other peripheral output devices such as speakers 197 and printer 196, which may be connected through an output peripheral interface 190.

The computer 110 may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 180. The remote computer 180 may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer 110, although only a memory storage device 181 has been illustrated in Fig. 1. The logical connections depicted in Fig. 1 include a local area network (LAN) 171 and a wide area network (WAN) 173, but may also include other networks. Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets and the Internet. When used in a LAN networking environment, the computer 110 is connected to the LAN 171 through a network interface or adapter 170. When used in a WAN networking environment, the computer 110 typically includes a modem 172 or other means for establishing communications over the WAN 173, such as the Internet. The modem 172, which may be internal or external, may be connected to the system bus 121 via the user input interface 160, or other appropriate mechanism. In a networked environment, program modules depicted relative to the computer 110, or portions thereof, may be stored in the remote memory storage device. By way of example, and not limitation, Fig. 1 illustrates remote application programs 185 as residing on memory device 181. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers may be used. Although the forgoing text sets forth a detailed description of numerous different embodiments of the invention, it should be understood that the scope of the invention is defined by the words of the claims set forth at the end of this patent. The detailed description is to be construed as exemplary only and does not describe every possibly embodiment of the invention because describing every possible embodiment would be impractical, if not impossible. Numerous alternative embodiments could be implemented, using either current technology or technology developed after the filing date of this patent, which would still fall within the scope of the claims defining the invention.

While the risk evaluation system and method, and other elements, have been described as preferably being implemented in software, they may be implemented in hardware, firmware, etc., and may be implemented by any other processor. Thus, the elements described herein may be implemented in a standard multi-purpose CPU or on specifically designed hardware or firmware such as an application-specific integrated circuit (ASIC) or other hard-wired device as desired, including, but not limited to, the computer 110 of Fig. 1. When implemented in software, the software routine may be stored in any computer readable memory such as on a magnetic disk, a laser disk, or other storage medium, in a RAM or ROM of a computer or processor, in any database, etc. Likewise, this software may be delivered to a user or a diagnostic system via any known or desired delivery method including, for example, on a computer readable disk or other transportable computer storage mechanism or over a communication channel such as a telephone line, the internet, wireless communication, etc. (which are viewed as being the same as or interchangeable with providing such software via a transportable storage medium).

Thus, many modifications and variations may be made in the techniques and structures described and illustrated herein without departing from the spirit and scope of the present invention. Thus, it should be understood that the methods and apparatus described herein are illustrative only and are not limiting upon the scope of the invention.

Accordingly, the invention relates to computer-implemented applications using the polymorphic markers and haplotypes described herein, and genotype and/or disease-association data derived therefrom. Such applications can be useful for storing, manipulating or otherwise analyzing genotype data that is useful in the methods of the invention. One example pertains to storing genotype information derived from an individual on readable media, so as to be able to provide the genotype information to a third party (e.g., the individual, a guardian of the individual, a health care provider or genetic analysis service provider), or for deriving information from the genotype data, e.g., by comparing the genotype data to information about genetic risk factors contributing to increased susceptibility to the disease, and reporting results based on such comparison.

In certain embodiments, computer-readable media suitably comprise capabilities of storing (i) identifier information for at least one polymorphic marker or a haplotype (e.g., rs-names of particular markers), as described herein; (ii) an indicator of the identity (e.g., presence or absence) of at least one allele of said at least one marker, or a haplotype, in individuals with the disease; and (iii) an indicator of the risk associated with the marker allele or haplotype.

The markers and haplotypes described herein to be associated with increased susceptibility (increased risk) of glaucoma, are in certain embodiments useful for interpretation and/or analysis of genotype data. Thus in certain embodiments, determination of the presence of an at- risk allele for glaucoma, as shown herein, or determination of the presence of an allele at a polymorphic marker in LD with any such risk allele, is indicative of the individual from whom the genotype data originates is at increased risk of glaucoma. In one such embodiment, genotype data is generated for at least one polymorphic marker shown herein to be associated with glaucoma, or a marker in linkage disequilibrium therewith. The genotype data is subsequently made available to a third party, such as the individual from whom the data originates, his/her guardian or representative, a physician or health care worker, genetic counsellor, or insurance agent, for example via a user interface accessible over the internet, together with an interpretation of the genotype data, e.g., in the form of a risk measure (such as an absolute risk (AR), risk ratio (RR) or odds ratio (OR)) for the disease. In another embodiment, at-risk markers identified in a genotype dataset derived from an individual are assessed and results from the assessment of the risk conferred by the presence of such at-risk variants in the dataset are made available to the third party, for example via a secure web interface, or by other communication means. The results of such risk assessment can be reported in numeric form (e.g., by risk values, such as absolute risk, relative risk, and/or an odds ratio, or by a percentage increase in risk compared with a reference), by graphical means, or by other means suitable to illustrate the risk to the individual from whom the genotype data is derived.

Nucleic acids and polypeptides

The nucleic acids and polypeptides described herein can be used in methods and kits of the present invention. An "isolated" nucleic acid molecule, as used herein, is one that is separated from nucleic acids that normally flank the gene or nucleotide sequence (as in genomic sequences) and/or has been completely or partially purified from other transcribed sequences (e.g., as in an RNA library). For example, an isolated nucleic acid of the invention can be substantially isolated with respect to the complex cellular milieu in which it naturally occurs, or culture medium when produced by recombinant techniques, or chemical precursors or other chemicals when chemically synthesized. In some instances, the isolated material will form part of a composition (for example, a crude extract containing other substances), buffer system or reagent mix. In other circumstances, the material can be purified to essential homogeneity, for example as determined by polyacrylamide gel electrophoresis (PAGE) or column chromatography (e.g., HPLC). An isolated nucleic acid molecule of the invention can comprise at least about 50%, at least about 80% or at least about 90% (on a molar basis) of all macromolecular species present. With regard to genomic DNA, the term "isolated" also can refer to nucleic acid molecules that are separated from the chromosome with which the genomic DNA is naturally associated. For example, the isolated nucleic acid molecule can contain less than about 250 kb, 200 kb, 150 kb, 100 kb, 75 kb, 50 kb, 25 kb, 10 kb, 5 kb, 4 kb, 3 kb, 2 kb, 1 kb, 0.5 kb or 0.1 kb of the nucleotides that flank the nucleic acid molecule in the genomic DNA of the cell from which the nucleic acid molecule is derived.

The nucleic acid molecule can be fused to other coding or regulatory sequences and still be considered isolated. Thus, recombinant DNA contained in a vector is included in the definition of "isolated" as used herein. Also, isolated nucleic acid molecules include recombinant DNA molecules in heterologous host cells or heterologous organisms, as well as partially or substantially purified DNA molecules in solution. "Isolated" nucleic acid molecules also encompass in vivo and in vitro RNA transcripts of the DNA molecules of the present invention. An isolated nucleic acid molecule or nucleotide sequence can include a nucleic acid molecule or nucleotide sequence that is synthesized chemically or by recombinant means. Such isolated nucleotide sequences are useful, for example, in the manufacture of the encoded polypeptide, as probes for isolating homologous sequences (e.g. , from other mammalian species), for gene mapping (e.g., by in situ hybridization with chromosomes), or for detecting expression of the gene in tissue {e.g., human tissue), such as by Northern blot analysis or other hybridization techniques.

The invention also pertains to nucleic acid molecules that hybridize under high stringency hybridization conditions, such as for selective hybridization, to a nucleotide sequence described herein (e.g., nucleic acid molecules that specifically hybridize to a nucleotide sequence containing a polymorphic site associated with a marker or haplotype described herein). Such nucleic acid molecules can be detected and/or isolated by allele- or sequence-specific hybridization (e.g., under high stringency conditions). Stringency conditions and methods for nucleic acid hybridizations are well known to the skilled person (see, e.g. , Current Protocols in Molecular Biology, Ausubel, F. et al, John Wiley & Sons, (1998), and Kraus, M. and Aaronson, S., Methods Enzymol., 200: 546-556 (1991), the entire teachings of which are incorporated by reference herein.

The percent identity of two nucleotide or amino acid sequences can be determined by aligning the sequences for optimal comparison purposes (e.g. , gaps can be introduced in the sequence of a first sequence). The nucleotides or amino acids at corresponding positions are then compared, and the percent identity between the two sequences is a function of the number of identical positions shared by the sequences (i.e., % identity = # of identical positions/total # of positions x 100). In certain embodiments, the length of a sequence aligned for comparison purposes is at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or at least 95%, of the length of the reference sequence. The actual comparison of the two sequences can be accomplished by well-known methods, for example, using a mathematical algorithm. A non-limiting example of such a mathematical algorithm is described in Karlin, S. and Altschul, S., Proc. Natl. Acad. ScL USA, 90: 5873-5877 (1993). Such an algorithm is incorporated into the NBLAST and XBLAST programs (version 2.0), as described in Altschul, S. et al., Nucleic Acids Res., 25: 3389-3402 (1997). When utilizing BLAST and Gapped BLAST programs, the default parameters of the respective programs (e.g., NBLAST) can be used. See the website on the world wide web at ncbi.nlm.nih.gov. In one embodiment, parameters for sequence comparison can be set at score=100, wordlength = 12, or can be varied (e.g. , W=5 or W=20). Another example of an algorithm is BLAT (Kent, WJ. Genome Res. 12: 656-64 (2002)).

Other examples include the algorithm of Myers and Miller, CABIOS (1989), ADVANCE and ADAM as described in Torellis, A. and Robotti, C, Comput. Appl. Biosci. 10:3-5 (1994); and FASTA described in Pearson, W. and Lipman, D., Proc. Natl. Acad. Sci. USA, 85:2444-48 (1988).

In another embodiment, the percent identity between two amino acid sequences can be accomplished using the GAP program in the GCG software package (Accelrys, Cambridge, UK).

The present invention also provides isolated nucleic acid molecules that contain a fragment or portion that hybridizes under highly stringent conditions to a nucleic acid that comprises, or consists of, the nucleotide sequence of LD Block C07, or a nucleotide sequence comprising, or consisting of, the complement of the nucleotide sequence of LD Block C07 as set forth in SEQ ID NO: 1, wherein the nucleotide sequence comprises at least one polymorphic allele contained in the markers and haplotypes described herein. The nucleic acid fragments of the invention are at least about 15, at least about 18, 20, 23 or 25 nucleotides, and can be 30, 40, 50, 100, 200, 500, 1000, 10,000 or more nucleotides in length.

The nucleic acid fragments of the invention are used as probes or primers in assays such as those described herein. "Probes" or "primers" are oligonucleotides that hybridize in a base- specific manner to a complementary strand of a nucleic acid molecule. In addition to DNA and RNA, such probes and primers include polypeptide nucleic acids (PNA), as described in Nielsen, P. et ai , Science 254: 1497-1500 (1991). A probe or primer comprises a region of nucleotide sequence that hybridizes to at least about 15, typically about 20-25, and in certain embodiments about 40, 50 or 75, consecutive nucleotides of a nucleic acid molecule. In one embodiment, the probe or primer comprises at least one allele of at least one polymorphic marker or at least one haplotype described herein, or the complement thereof. In particular embodiments, a probe or primer can comprise 100 or fewer nucleotides; for example, in certain embodiments from 6 to 50 nucleotides, or, for example, from 12 to 30 nucleotides. In other embodiments, the probe or primer is at least 70% identical, at least 80% identical, at least 85% identical, at least 90% identical, or at least 95% identical, to the contiguous nucleotide sequence or to the complement of the contiguous nucleotide sequence. In another embodiment, the probe or primer is capable of selectively hybridizing to the contiguous nucleotide sequence or to the complement of the contiguous nucleotide sequence. Often, the probe or primer further comprises a label, e.g., a radioisotope, a fluorescent label, an enzyme label, an enzyme co-factor label, a magnetic label, a spin label, an epitope label.

The nucleic acid molecules of the invention, such as those described above, can be identified and isolated using standard molecular biology techniques well known to the skilled person. The amplified DNA can be labeled (e.g., radiolabeled, fluorescently labeled) and used as a probe for screening a cDNA library derived from human cells. The cDNA can be derived from mRNA and contained in a suitable vector. Corresponding clones can be isolated, DNA obtained following in vivo excision, and the cloned insert can be sequenced in either or both orientations by art- recognized methods to identify the correct reading frame encoding a polypeptide of the appropriate molecular weight. Using these or similar methods, the polypeptide and the DNA encoding the polypeptide can be isolated, sequenced and further characterized.

Antibodies

The invention also provides antibodies which bind to an epitope comprising either a variant amino acid sequence (e.g., comprising an amino acid substitution, e.g. a substitution in a caveolin-1 or caveolin-2 protein) encoded by a variant allele or the reference amino acid sequence encoded by the corresponding non-variant or wild-type allele. The term "antibody" as used herein refers to immunoglobulin molecules and immunologically active portions of immunoglobulin molecules, i.e., molecules that contain antigen-binding sites that specifically bind an antigen. A molecule that specifically binds to a polypeptide of the invention is a molecule that binds to that polypeptide or a fragment thereof, but does not substantially bind other molecules in a sample, e.g., a biological sample, which naturally contains the polypeptide. Examples of immunologically active portions of immunoglobulin molecules include F(ab) and F(ab') ₂ fragments which can be generated by treating the antibody with an enzyme such as pepsin. The invention provides polyclonal and monoclonal antibodies that bind to a polypeptide of the invention. The term "monoclonal antibody" or "monoclonal antibody composition", as used herein, refers to a population of antibody molecules that contain only one species of an antigen binding site capable of immunoreacting with a particular epitope of a polypeptide of the invention. A monoclonal antibody composition thus typically displays a single binding affinity for a particular polypeptide of the invention with which it immunoreacts.

Polyclonal antibodies can be prepared as described above by immunizing a suitable subject with a desired immunogen, e.g., polypeptide of the invention or a fragment thereof. The antibody titer in the immunized subject can be monitored over time by standard techniques, such as with an enzyme linked immunosorbent assay (ELISA) using immobilized polypeptide. If desired, the antibody molecules directed against the polypeptide can be isolated from the mammal (e.g., from the blood) and further purified by well-known techniques, such as protein A

chromatography to obtain the IgG fraction. At an appropriate time after immunization, e.g., when the antibody titers are highest, antibody-producing cells can be obtained from the subject and used to prepare monoclonal antibodies by standard techniques, such as the hybridoma technique originally described by Kohler and Milstein, Nature 256:495-497 (1975), the human B cell hybridoma technique (Kozbor et al., Immunol. Today 4: 72 (1983)), the EBV-hybridoma technique (Cole et al., Monoclonal Antibodies and Cancer Therapy, Alan R. Liss,1985, Inc., pp. 77-96) or trioma techniques. The technology for producing hybridomas is well known (see generally Current Protocols in Immunology (1994) Coligan et al., (eds.) John Wiley & Sons, Inc., New York, NY). Briefly, an immortal cell line (typically a myeloma) is fused to lymphocytes (typically splenocytes) from a mammal immunized with an immunogen as described above, and the culture supernatants of the resulting hybridoma cells are screened to identify a hybridoma producing a monoclonal antibody that binds a polypeptide of the invention.

Any of the many well known protocols used for fusing lymphocytes and immortalized cell lines can be applied for the purpose of generating a monoclonal antibody to a polypeptide of the invention (see, e.g., Current Protocols in Immunology, supra; Galfre et al. , Nature 266: 55052 (1977); R. H. Kenneth, in Monoclonal Antibodies: A New Dimension In Biological Analyses, Plenum Publishing Corp., New York, New York (1980); and Lemer, Yale J. Biol. Med. 54: 387-402 (1981)). Moreover, the ordinarily skilled worker will appreciate that there are many variations of such methods that also would be useful.

Alternative to preparing monoclonal antibody-secreting hybridomas, a monoclonal antibody to a polypeptide of the invention can be identified and isolated by screening a recombinant combinatorial immunoglobulin library (e.g. , an antibody phage display library) with the polypeptide to thereby isolate immunoglobulin library members that bind the polypeptide. Kits for generating and screening phage display libraries are commercially available (e.g., the Pharmacia Recombinant Phage Antibody System, Catalog No. 27-9400-01; and the Stratagene SurfZAP™ Phage Display Kit, Catalog No. 240612). Additionally, examples of methods and reagents particularly amenable for use in generating and screening antibody display library can be found in, for example, U.S. Patent No. 5,223,409; PCT Publication No. WO 92/18619; PCT Publication No. WO 91/17271 ; PCT Publication No. WO 92/20791; PCT Publication No. WO 92/15679; PCT Publication No. WO 93/01288; PCT Publication No. WO 92/01047; PCT

Publication No. WO 92/09690; PCT Publication No. WO 90/02809; Fuchs et al. , Bio/Technology 9: 1370-1372 (1991); Hay et al., Hum. Antibod. Hybridomas 3:81-85 (1992); Huse et al., Science 246: 1275-1281 (1989); and Griffiths et al., EMBO J. 12:725-734 (1993).

Additionally, recombinant antibodies, such as chimeric and humanized monoclonal antibodies, comprising both human and non-human portions, which can be made using standard recombinant DNA techniques, are within the scope of the invention. Such chimeric and humanized monoclonal antibodies can be produced by recombinant DNA techniques known in the art.

In general, antibodies of the invention (e.g., a monoclonal antibody) can be used to isolate a polypeptide of the invention by standard techniques, such as affinity chromatography or immunoprecipitation. A polypeptide-specific antibody can facilitate the purification of natural polypeptide from cells and of recombinantly produced polypeptide expressed in host cells.

Moreover, an antibody specific for a polypeptide of the invention can be used to detect the polypeptide (e.g., in a cellular lysate, cell supernatant, or tissue sample) in order to evaluate the abundance and pattern of expression of the polypeptide. Antibodies can be used diagnostically to monitor protein levels in tissue as part of a clinical testing procedure, e.g., to, for example, determine the efficacy of a given treatment regimen. The antibody can be coupled to a detectable substance to facilitate its detection. Examples of detectable substances include various enzymes, prosthetic groups, fluorescent materials, luminescent materials,

bioluminescent materials, and radioactive materials. Examples of suitable enzymes include horseradish peroxidase, alkaline phosphatase, beta-galactosidase, or acetylcholinesterase; examples of suitable prosthetic group complexes include streptavidin/biotin and avidin/biotin; examples of suitable fluorescent materials include umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansyl chloride or phycoerythrin; an example of a luminescent material includes luminol; examples of bioluminescent materials include luciferase, luciferin, and aequorin, and examples of suitable radioactive material include ¹²⁵ I, ¹³¹ I, ³⁵ S Or ³ H.

Antibodies may also be useful in pharmacogenomic analysis. In such embodiments, antibodies against variant proteins encoded by nucleic acids according to the invention, such as variant proteins that are encoded by nucleic acids that contain at least one polymorpic marker of the invention, can be used to identify individuals that require modified treatment modalities.

Antibodies can furthermore be useful for assessing expression of variant proteins in disease states, such as in active stages of a disease, or in an individual with a predisposition to a disease related to the function of the protein {e.g., caveolin-1 or caveolin-2 protein. Antibodies specific for a variant protein of the present invention that is encoded by a nucleic acid that comprises at least one polymorphic marker or haplotype as described herein can be used to screen for the presence of the variant protein, for example to screen for a predisposition to glaucoma as indicated by the presence of the variant protein. Antibodies can be used in other methods. Thus, antibodies are useful as diagnostic tools for evaluating proteins, such as variant proteins of the invention, in conjunction with analysis by electrophoretic mobility, isoelectric point, tryptic or other protease digest, or for use in other physical assays known to those skilled in the art. Antibodies may also be used in tissue typing. In one such embodiment, a specific variant protein has been correlated with expression in a specific tissue type, and antibodies specific for the variant protein can then be used to identify the specific tissue type.

Subcellular localization of proteins, including variant proteins, can also be determined using antibodies, and can be applied to assess aberrant subcellular localization of the protein in cells in various tissues. Such use can be applied in genetic testing, but also in monitoring a particular treatment modality. In the case where treatment is aimed at correcting the expression level or presence of the variant protein or aberrant tissue distribution or developmental expression of the variant protein, antibodies specific for the variant protein or fragments thereof can be used to monitor therapeutic efficacy.

Antibodies are further useful for inhibiting variant protein function, for example by blocking the binding of a variant protein to a binding molecule or partner. Such uses can also be applied in a therapeutic context in which treatment involves inhibiting a variant protein's function. An antibody can be for example be used to block or competitively inhibit binding, thereby modulating (i.e., agonizing or antagonizing) the activity of the protein. Antibodies can be prepared against specific protein fragments containing sites required for specific function or against an intact protein that is associated with a cell or cell membrane. For administration in vivo, an antibody may be linked with an additional therapeutic payload, such as radionuclide, an enzyme, an immunogenic epitope, or a cytotoxic agent, including bacterial toxins (diphtheria or plant toxins, such as ricin). The in vivo half-life of an antibody or a fragment thereof may be increased by pegylation through conjugation to polyethylene glycol. The present invention further relates to kits for using antibodies in the methods described herein. This includes, but is not limited to, kits for detecting the presence of a variant protein in a test sample. One preferred embodiment comprises antibodies such as a labelled or labelable antibody and a compound or agent for detecting variant proteins in a biological sample, means for determining the amount or the presence and/or absence of variant protein in the sample, and means for comparing the amount of variant protein in the sample with a standard, as well as instructions for use of the kit.

The present invention will now be exemplified by the following non-limiting examples.

EXAMPLE 1

Patient cohorts

Iceland

An Icelandic cohort of individuals diagnosed with Primary Open Angle Glaucoma (POAG) was recruited. All individuals signed an informed consent. Diagnosis of primary open angle glaucoma (POAG) was as described in Jonasson et al. (Eye 17: 747-753 (2003).

Sweden

Patients were recruited from the out-patient clinic at the Department of Opthalmology, University Hospital, Uppsala, and the Department of Ophthalmology, Tierps Hospital, Tierp, located close to Uppsala. After obtaining informed consent, samples of peripheral blood were collected from 200 unrelated patients diagnosed with POAG and 200 unrelated patients with exfoliative glaucoma. Diagnostic criteria included increased IOP and glaucomatous damage to the optic nerve head and/or glaucomatous damage to the visual field. Diagnoses were obtained from the patients' medical records. The grading of the optic nerve head damage, therefore, had been performed by the patients' treating and examining physician. Correspondingly, many different perimetric methods for visual field testing were used, and the grading of the fields was based on the examining physicians' evaluation. At the two clinics involved in this study, dilation of the pupils and gonioscopy are standard procedures for the diagnosis of glaucoma. The presence of exfoliative material on, e.g. the iris or lens was needed for the diagnosis of exfoliation glaucoma. None of the patients in the POAG and the exfoliation glaucoma groups were related. An additional 200 samples were collected from control individuals matched for age, sex, and geographic and ethnic origin, in whom glaucoma had been excluded using IOP measurements and ophthalmoscopy of the optic disc. The study was approved by the local Research Ethics Committee and performed according to the Declaration of Helsinki.

Illumlna Genome-Wide Genotyplng

All Icelandic case and control samples were assayed with the Illumina HumanHap300 or HumanHapCNV370 bead chips (Illumina, SanDiego, CA, USA), containing 317,503 and 370,404 SNPs derived from phase I of the International HapMap project. Only SNPs present on both chips were included in the analysis and SNPs were excluded if they had (a) yield lower than 95% in cases or controls, (b) minor allele frequency less than 1% in the population, or (c) showed significant deviation from Hardy-Weinberg equilibrium in the controls (P < 0.001). Any samples with a call rate below 98% were excluded from the analysis. The final analysis included 303,117 SNPs. Single SNP Genotyping

Single SNP genotyping for all samples was carried out at deCODE genetics in Reykjavik, Iceland, applying the same platform to all populations studied. All single SNP genotyping was carried out using the Centaurus (Nanogen) platform (Kutyavin, LV. et al. Nucleic Adds Res 34, el28 (2006)). The quality of each Centaurus SNP assay was evaluated by genotyping each assay on the CEU samples and comparing the results with the HapMap data. All assays had mismatch rate <0.5%. Additionally, all markers were re-genotyped on more than 10% of samples typed with the Illumina platform resulting in an observed mismatch in less than 0.5% of samples.

Association Analysis

For association analysis we utilized a standard likelihood ratio statistic, implemented in the NEMO software (Gretarsdottir, S. et al. Nat Genet 35, 131-8 (2003).) to calculate two-sided P values and odds ratios (ORs) for each individual allele, assuming a multiplicative model for risk, i.e. that the risk of the two alleles a person carries multiplies (Rice, J. A. in Mathematical Statistics and Data Analysis, Wadsworth Inc., Belmont, CA, (1995)). Allelic frequencies, rather than carrier frequencies are presented for the markers and P values are given after adjustment for the relatedness of the subjects. When estimating genotype specific OR, genotype frequencies in the population were estimated assuming Hardy-Weinberg equilibrium.

In general, allele and haplotype frequencies are estimated by maximum likelihood and tests of differences between cases and controls are performed using a generalized likelihood ratio test (Mantel, /V. S Haenszel, W., J Natl Cancer Inst 22: 719-48 (1959)). This method is particularly useful in situations where there are some missing genotypes for the marker of interest and genotypes of another marker, which is in strong LD with the marker of interest, are used to provide some partial information. This was used in the association tests presented in Table 3 to ensure that the comparison of the highly correlated markers was done using the same number of individuals. To handle uncertainties with phase and missing genotypes, maximum likelihood estimates, likelihood ratios and P values are computed directly for the observed data, and hence the loss of information due to uncertainty in phase and missing genotypes is automatically captured by the likelihood ratios.

Results from multiple case-control groups were combined using a Mantel-Haenszel model (Mantel, N. & Haenszel, W., J Natl Cancer Inst 22:719-48 (1959)) in which the groups were allowed to have different population frequencies for alleles, haplotypes and genotypes but were assumed to have common relative risks. The correlation between the sequence variants and the various biochemical traits was done by regressing the individual trait values on the number of copies of the at-risk variant an individual carries. To obtain effect estimates the regression was done using unadjusted trait values as response variables, while to estimate the significance of the correlation the regression was done using sex and age adjusted and standardized (by an inverse normal transform) trait values as response values to eliminate the effect of non-normality of the distribution of trait values. For the regression between bone mineral density and the sequence variants, both the effect estimate and the P values were calculated by regressing standardized age, sex and weight adjusted trait values on the number of copies of the risk variant an individual carries. Correction for Relatedπess of the Subjects and Genomic Control

Some of the individuals in both the Icelandic patient and control groups are related to each other, causing the chi-square test statistic to have a mean >1 and median >0.675. We estimated the inflation factor for the genome-wide association by calculating the average of the 303,117 chi-square statistics, which was a method of genomic control (Devlin B, & Roeder, K., Biometrics 55:997-1004 (1999)) to adjust for both relatedness and potential population stratification. The inflation factor was estimated as 1.182 and the results presented are based on adjusting the chi-square statistics by dividing each of them by 1.182. To adjust the association results for the Icelandic replication sample set, and the combined replication and discovery sample set, where association results for a genome-wide set of SNPs is not available, we used a previously described procedure where we simulated genotypes through the genealogy of

708,683 Icelanders to estimate the adjustment factor (Stefansson, H. et al. Nat Genet 37, 129- 37 (2005)).

RESULTS Genome-wide association study

To search for genetic variants that confer risk of POAG we conducted a genome-wide association study on 1,263 POAG cases and 34,877 population controls from Iceland . After quality filtering 303,117 SNPs, typed with the Illumina HumanHap300 and HumanHapCNV370 bead chips, were tested for association to POAG. The results were adjusted for relatedness using the method of genomic controls (Devlin et.al. Biometrics 55:997-1004 (1999)) by dividing the χ ² statistic by 1.182.

Two SNPs reached the genome-wide significance level of P < 1.6χlO ^"7 (rsl052990 and rs4236601 ; Table 2 and Table 3). For these variants, rs4236601 [A] and rsl052990[G] were found to have an odds ratio (OR) = 1.36 and P = 5.OxIO ^"10 and OR = 1.32 and P = l.lxlO ^"9 , respectively. The two variants are located between the CAVl and CAV2 (caveolin 1 and 2) genes on 7q31 and are highly correlated (r ² = 0.64 based on the HapMap CEU dataset), and after adjusting for the observed association with rs4236601[A] neither rsl052990[G] or any other variant in the 7q31 region showed significant association with POAG.

To replicate the observed association, we typed rs4236601 in 200 POAG cases and 194 controls from Sweden and in 404 POAG cases and 1,650 controls from the United Kingdom. In both sets, rs4236601[A] conferred similar risk of POAG as observed in the Icelandic case-control analysis: OR = 1.33 (P = 0.092) in the Swedish set and OR = 1.31 (P = 0.002) in the UK set (Table 2). Combined, the two replication sets give OR = 1.32 (95 CI = 1.13-1.54) and a corresponding P = 0.00043, and combining all the three case-controls sets gives OR =1.35 (95 CI = 1.24-1.47) and P = 9.5x10 ¹³ . The estimated population frequency of rs4236601[A] ranges from 0.207 to 0.240 for the three sets studied and the corresponding population attributed risk is 13% - 15%.

EXAMPLE 2

In order to search for variants in the sequence of the genome that confer risk of POAG we conducted a genome-wide association study on 1,263 POAG cases diagnosed by Icelandic ophthalmologists using established glaucoma criteria ¹² and 34,877 population controls from Iceland. After quality filtering 303,117 SNPs, typed with the Illumina HumanHap300 or

HumanHapCNV370 bead chips, were tested for association with POAG. The results were adjusted for relatedness using the method of genomic controls ¹³ by dividing the χ ² statistic by 1.182.

Two highly correlated SNPs, rs4236601[A] and rsl052990[G] (r ² = 0.64 based on the Utah (CEU) HapMap(r22) samples), reached genome-wide significance of P < 1.6χlO ^~7 . These variants, with an odds ratio (OR) = 1.36 and P = 5.0x10 ¹⁰ and OR = 1.32 and P = l.lxlO ^"9 , respectively, are located within the same LD block between the CAVl and CAV2 (caveolin 1 and 2) genes on 7q31 (Table 4 and Figure 3). After adjusting for the observed association with rs4236601[A] neither rsl052990[G] nor any other variant in the 7q31 region showed significant association with POAG (Table 5).

In an attempt to replicate the association we typed rs4236601 in 200 POAG cases and 194 controls from Sweden, in 871 POAG cases and 865 controls from Leicester and from

Southampton, United Kingdom, and in 1,104 POAG cases and 1,001 controls from Australia. In the Swedish set rs4236601 [A] confers similar risk of POAG as observed in the Icelandic case- control analysis: OR = 1.33 (P = 0.092), while the estimated risk is less in the two UK sets, OR = 1.14 (P = 0.2) and OR = 1.04 (P = 0.75) (Table 4). The Australian sample consists of three studies, from Tasmania (GIST), from South-Australia (ANZRAG) and the Blue Mountains Eye Study (BMES), that individually have estimated risks of OR = 1.17 (P = 0.29), 1.25 (P = 0.038), 1.26 (P = 0.13), respectively, and combined an OR = 1.20 (P = 0.018). Combined, the replication sets give OR =1.18 (95% CI = 1.06-1.31) and P = 0.0015, and including the discovery set yields a combined OR = 1.27 (95% CI = 1.18-1.36) and P = 2.2x10 ⁿ . There is heterogeneity in the effect estimates among the study populations (P _het = 0.048), in particular the estimated effect in the samples from Southampton is low. POAG is a heterogeneous disease and therefore this heterogeneity is not surprising. In the Southampton samples the risk was confined to a small subset of normal pressure glaucoma cases while no risk was observed for the majority of the cases diagnosed with high-pressure glaucoma (Table 6). Higher risk in normal pressure cases is also observed, although not consistently, in the POAG cases from Iceland and Australia: sample sets that also include a mixture of normal and high pressure cases.

The estimated population frequency of rs4236601[A] ranges from 0.207 to 0.281 in the four populations studied and the corresponding population attributed risk percentage is about 12% using the mean of the population frequencies and the estimated OR = 1.27. About 6% of the populations carry two copies of the risk allele and their risk of developing POAG is 1.6 times greater than those carrying no risk variant. The frequency of the risk variant rs4236601[A] differs between ethnicities. In the HapMap populations the estimated frequency ranges from 45% in the Yoruba and 28% in the Utah Ceph population to 2% in the Han Chinese and the variant was not detected in 60 individuals from Japan. We tested the variant for association with POAG in 299 cases and 580 unaffected controls of Chinese origin from Hong Kong and Shantou (Table 4). Although the variant is very rare, about 1.8% in cases and less than 0.4% in controls, the association is significant with OR = 5.42 and P = 0.0021. We also tested the variant in 1,207 population controls from Hong Kong where the frequency of rs4236601[A] is slightly higher than in the unaffected controls or 0.7%. Including these controls in the analysis the association still remained significant although the effect is weaker.

The greater risk and lower frequency of rs4236601[A] in the Chinese population than in

European populations raises the possibility that it tags some rare unknown causative variant through linkage disequilibrium that is stronger in the Chinese population than in European populations. In support of this notion, we note that in the Chinese (CHB) HapMap(r22) samples 32 SNP alleles, spread across 174kb, are perfect surrogates (r ² = 1) of rs4236601, whereas in the Utah (CEU) sample there are only five such SNP alleles, covering only 12.6kb. Of the 32 CHB surrogate SNPs, we tested 31 that are polymorphic the CEU samples for association in the Icelandic sample set (Table 5). Several of those SNPs showed similar association with POAG as rs4236601, in particular rsl0258483, however, all of those SNPs are highly correlated with rs4236601 and none is significant after adjusting for the effect of rs4326601. Thus, we are left either with the conclusion that the risk attributable to this locus differs in European and Hong Kong populations or that there remains an undetected rare causative variant that is not well tagged by existing SNPs in the Utah (CEU) HapMap samples.

We tested rs4236601[A] for association with exfoliation glaucoma in 190 XFG cases and 34,839 controls from Iceland and 198 XFG cases and 198 controls from Sweden. Neither sample set yielded association (P = 0.87 in Iceland and P = 0.30 in Sweden; Table 4).

In order to refine the association signal and to search for protein coding mutations we sequenced the promoter region, exons and exon and intron boundaries of the CAVl and CAV2 genes in 280 POAG cases and 358 controls from Iceland. SNPs identified through this effort were then imputed into the remaining Icelandic POAG case and control samples using recently developed methods of long-range phasing of haplotypes in sets of related individuals ¹⁴ . Furthermore two of the identified SNPs, a non-synonomous coding variant rs8940 and rsl052990, located in the 3'UTR end of CAV2, were genotyped in the samples from Australia and Sweden. Several of the identified variants show significant association with POAG, however, after adjusting for the effect of rs4236601[A] none of the tested SNPs remain significant (Tables 7 and 8). The converse is not true as none of the other variants accounts for the association of rs4236601[A] with POAG. This indicates that rs4236601 is unlikely to tag mutations within the coding region of the CAVl or the CAV2 genes. To evaluate whether the 7q31 variant predisposes to POAG through known risk factors we tested for association of rs4236601[A] with IOP, CCT, hypertension, type 2 diabetes (T2D) and myopia. For IOP, CCT and myopia we used 1,713 samples from the Twins Eye Study in Tasmania (TEST) ¹⁵ , in addition to 691 Australian POAG cases and 439 controls with IOP measurements and 316 samples with IOP and CCT measurements without glaucoma from the Reykjavik Eye Study. For myopia we also had 883 individuals from Iceland with spherical equivalent refraction error of -3 diopters or higher. The association of rs4236601[A] with T2D and hypertension was evaluated in Icelandic sample sets of 2,251 cases and 34,647 controls for T2D and 7,007 cases and 31,521 controls for hypertension. Of the six traits tested, nominally significant association was only observed for increased IOP (P = 0.034).

References:

1. Resπikoff, S., et al. Global data on visual impairment in the year 2002. Bull World Health Organ 82, 844-851 (2004).

2. Allingham, R. R., Liu, Y. & Rhee, DJ. The genetics of primary open-angle glaucoma : a review.

Exp Eye Res 88, 837-844 (2009).

3. Fan, BJ., Wang, D. Y., Lam, D. S. & Pang, CP. Gene mapping for primary open angle

glaucoma. Clin Biochem 39, 249-258 (2006).

4. Stone, E. M., et al. Identification of a gene that causes primary open angle glaucoma. Science

275, 668-670 (1997).

5. Rezaie, T., et al. Adult-onset primary open-angle glaucoma caused by mutations in optineurin.

Science 295, 1077-1079 (2002).

6. Monemi, S., et al. Identification of a novel adult-onset primary open-angle glaucoma (POAG) gene on 5q22.1. Hum MoI Genet 14, 725-733 (2005).

7. Pasutto, F., et al. Heterozygous NTF4 mutations impairing neurotrophin-4 signaling in patients with primary open-angle glaucoma. Am J Hum Genet 85, 447-456 (2009).

8. Thorleifsson, G., et al. Common sequence variants in the LOXLl gene confer susceptibility to exfoliation glaucoma. Science 317, 1397-1400 (2007).

9. Liu, Y., et al. Lack of association between LOXLl variants and primary open-angle glaucoma in three different populations. Invest Ophthalmol Vis ScI 49, 3465-3468 (2008).

10. Nakano, M., et al. Three susceptible loci associated with primary open-angle glaucoma

identified by genome-wide association study in a Japanese population. Proc Natl Acad ScI U S

A 106, 12838-12842 (2009).

11. Rao, K. N., Kaur, I. & Chakrabarti, S. Lack of association of three primary open-angle

glaucoma-susceptible loci with primary glaucomas in an Indian population. Proc Natl Acad ScI

U S A 106, E125-126; author reply E127 (2009).

12. Jonasson, F., et al. Prevalence of open-angle glaucoma in Iceland : Reykjavik Eye Study. Eye

(Lond) 17, 747-753 (2003).

13. Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997 (1999).

14. Kong, A., et al. Detection of sharing by descent, long-range phasing and haplotype

imputation. Nat Genet 40, 1068-1075 (2008).

15. Mackey, D.A., et al. Twins eye study in tasmania (TEST): rationale and methodology to recruit and examine twins. Twin Res Hum Genet 12, 441-454 (2009).

16. Tamm, E. R. The trabecular meshwork outflow pathways: structural and functional aspects.

Exp Eye Res 88, 648-655 (2009).

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trabecular meshwork using single-pass sequencing of 1060 clones. Invest Ophthalmol Vis Sci

41, 3678-3693 (2000).

18. Berta, A. I., et al. Different caveolin isoforms in the retina of melanoma malignum affected human eye. MoI Vis 13, 881-886 (2007).

19. Borras, T. Gene expression in the trabecular meshwork and the influence of intraocular

pressure. Prog Retin Eye Res 22, 435-463 (2003).

20. Couet, J., Belanger, M. M., Roussel, E. & Drolet, M. C. Cell biology of caveolae and caveolin. Adv Drug Deliv Rev 49, 223-235 (2001).

21. Hnasko, R. & Lisanti, M. P. The biology of caveolae: lessons from caveolin knockout mice and implications for human disease. MoI Interv 3, 445-464 (2003). 22. Patel, H. H., Murray, F. & Insel, P. A. Caveolae as organizers of pharmacologically relevant signal transduction molecules. Annu Rev Pharmacol Toxicol 48, 359-391 (2008).

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25. Ju, H., Zou, R., Venema, V.J. & Venema, R. C. Direct interaction of endothelial nitric-oxide synthase and caveolin-1 inhibits synthase activity. J Biol Chem 272, 18522-18525 (1997). 26. Garcia-Cardena, G _v et al. Dissecting the interaction between nitric oxide synthase (NOS) and caveolin. Functional significance of the nos caveolin binding domain in vivo. J Biol Chem 272, 25437-25440 (1997).

27. Fuchshofer, R. & Tamm, E. R. Modulation of extracellular matrix turnover in the trabecular meshwork. Exp Eye Res 88, 683-688 (2009).

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retinopathy. Prog Retin Eye Res 26, 205-238 (2007).

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Nature 449, 851-861 (2007).

EXAMPLE 3

Methods

Subjects from Iceland

The Icelandic glaucoma sample set was created by joining two lists of glaucoma patients. A list of participants in the Reykjavik Eye Study ¹ and a list compiled by Icelandic ophthalmologists in 2008 including patients 55-86 years old at the time of diagnosis, all meeting either structural (glaucomatous optic neuropathy) or functional (glaucomatous visual field defects) criteria of glaucoma or both. For visual fields measurements, we used the Octopus 123 perimeter (Haag- Streit AG, Kδniz Switzerland). Intra ocular pressure (IOP) was not a part of the definition. On gonioscopy the angles were found to be open and normal in appearance. This list included 492 individuals, 234 men and 258 women. Exfoliation syndrome (XFS) was specifically looked for and if detected the participant was excluded from this study.

The second list including 771 individuals, 348 men and 423 women compiled by Icelandic ophthalmologists working in the glaucoma clinic from 1977 - 2000. In addition to including persons with criteria described above, IOP > 22mmHg could be used as one of two criteria, namely together with either glaucomatous optic neuropathy or glaucomatous visual field defect. Various perimeters were used. All were followed up and treated for some years. Exfoliation syndrome was not specifically looked for and documented by all ophthalmologists. One of the authors (FJ) who worked in the glaucoma clinic from 1978-2000 and participated in creating the list, examined it and removed those individuals where any documentation could be found in any files, of exfoliation syndrome in either eye. Considering population based studies from Iceland ¹ , less than 10% of the remaining list may have had or later developed exfoliation glaucoma.

The Icelandic control group of 34,887 individuals was selected among individuals that had participated in the various genetic programs at deCODE genetics and have been genotyped with either the Illumina HumanHap300 or the HumanHapCNV370 bead chip. Individuals with reported history of glaucoma were excluded from the control group.

The study was approved by the Icelandic National Bioethics Committee and by the Icelandic Data Protection Authority. Informed consent was obtained from all participants. The study was conducted in accordance with revised Declaration of Helsinki. Subjects from the United Kingdom

The glaucoma sample set from Leicester consisted of 416 POAG subjects (216 males, 200 females), recruited between 1999 and 2001 through the glaucoma and general clinics at the Leicester Royal Infirmary, UK ² . POAG was defined as an IOP of ≥ 22mmHg with evidence of glaucomatous optic neuropathy and a corresponding visual field loss. At the time of ascertainment, 413 patients were over 40 years of age, and the average age was 72 years (range 27-96 years). Ethical approval for the study was obtained from the Leicestershire Health Authority Research Ethics Committee and all subjects provided written informed consent to participate. As controls we used samples from Scotland and England. The Scottish control samples are from Aberdeen and are comprised of 230 population controls and 220 samples from schizophrenia patients. Population controls were volunteers recruited through general practices in Scotland. All participants are self-identified as born in the British Isles (95% in Scotland). The English control samples are from London and are comprised of 98 population controls and 122 samples from schizophrenia patients. All subjects were unrelated individuals of European descent from London.

Southampton POAG cases were collected as previously described ³ . This included 78 cases with normal tension glaucoma and 370 high tension glaucoma cases. Normal tension glaucoma was defined as the average maximum IOP averaged over both eyes of 21 mmHg or less. Four cases had data for only one eye, in this case the data for that eye is used instead of an average, and 19 cases had no IOP data. The Southampton controls were selected from a previously collected control cohort ⁴ . These control patients were diagnosed as not having glaucoma on the basis of not reporting a history of either glaucoma or ocular hypertension. In addition they had no history of previous glaucoma surgery and were not receiving any glaucoma medication. Finally they had no examination findings suggestive of glaucoma such as a cupped disc and had not had a previous abnormal visual field test.

Subjects from Sweden

Glaucoma patients were recruited through the out-patient clinic at the Department of

Opthalmology, University Hospital, Uppsala, and the Department of Ophthalmology, Tierps Hospital, Tierp, located close to Uppsala. After obtaining informed consent, samples of peripheral blood were collected from 200 unrelated patients diagnosed with POAG and 200 unrelated patients with exfoliative glaucoma. Diagnostic criteria included increased IOP and glaucomatous damage to the optic nerve head and/or glaucomatous damage to the visual field. Diagnoses were obtained from the patients' medical records. The grading of the optic nerve head damage, therefore, had been performed by the patients' treating and examining physician.

Correspondingly, many different perimetric methods for visual field testing were used, and the grading of the fields was based on the examining physicians' evaluation. At the two clinics involved in this study, dilation of the pupils and gonioscopy are standard procedures for the diagnosis of glaucoma. The presence of exfoliative material on, e.g. the iris or lens was needed for the diagnosis of exfoliation glaucoma. None of the patients in the POAG and the exfoliation glaucoma groups were related. An additional 200 samples were collected from control individuals matched for age, sex, and geographic and ethnic origin, in whom glaucoma had been excluded using IOP measurements and ophthalmoscopy of the optic disc. The study was approved by the local Research Ethics Committee and performed according to the Declaration of Helsinki. Subjects from Australia

The Australian POAG sample consists of participants recruited through three separate studies, from the Australian states of Tasmania, South Australia and New South Wales. All patients reported being of Northern European descent. Written informed consent was obtained from each participant.

The Tasmanian cohort was recruited through the Glaucoma Inheritance Study in Tasmania (GIST) ⁵ . This cohort was ascertained over the previous decade and approximately 2,000 unselected Tasmanian POAG cases, representing close to full population ascertainment of diagnosed glaucoma cases, have been reviewed. GIST case subjects were unselected in terms of known family history, and unrelated subjects were used in this study. 147 people were specifically recruited, from local Tasmanian aged care facilities or through an adjuvant genetic study, to act as control subjects. The GIST was approved by the relevant ethics committees of the following institutions: The University of Tasmania (Hobart), the Royal Hobart Hospital (Hobart, Tasmania), and the Royal Victorian Eye and Ear Hospital (Melbourne, Victoria), and was conducted in accordance with the revised Declaration of Helsinki.

The South Australian cohort, which represents the first spoke of the Australian and New Zealand Registry of Advanced Glaucoma (ANZRAG; www.anzrag.com), was recruited through the cooperation of local ophthalmologists, the Royal Society for the Blind, and Glaucoma Australia ⁶ . Control subjects were ascertained through local media advertisement and from independent- living retirement villages. Ethical approval was obtained from the relevant joint committee of Flinders University and Flinders Medical Centre.

Unrelated control subjects were also selected through the Blue Mountains Eye Study (BMES). The BMES is a population-based cohort study investigating the aetiology of common ocular diseases among suburban residents aged 49 years or older, living in the Blue Mountains region, west of Sydney, New South Wales, Australia. Subjects were recruited during one of four surveys between 1992 and 2004. A total of 493 control subjects were utilised. In addition 130 POAG cases identified during this population-based survey were also genotyped ⁷ . Approval for this study was obtained from the Human Research Ethics committee of the Westmead Millennium Institute at the University of Sydney. Disease definition: Case subjects had concordant findings of typical glaucomatous visual field defects on the Humphrey 24-2 (for GIST and ANZRAG) or 30-2 (for BMES) visual field (Carl Zeiss Pty. Ltd., Sydney, Australia) test together with corresponding neuroretinal rim thinning, including an enlarged cup-disc ratio (≥ 0.7) or cup-disc ratio asymmetry (≥0.2) between the two eyes. IOP was not considered in the diagnostic criteria. Visual fields were deemed to be reliable if there were less than 33% false-negative and false-positive errors. Clinical exclusion criteria included: i) pigmentary glaucoma, ii) angle closure or mixed mechanism glaucoma; iii) secondary glaucoma due to aphakia, rubella, rubeosis or inflammation; iv) congenital or infantile glaucoma, juvenile glaucoma with age of onset less than 20 years; or v) glaucoma in the presence of a known syndrome. Subjects were excluded from this study if they had previously been identified as having a disease-causing mutation in myocilin gene (accounting for 3-4% of POAG in our combined data sets) ⁸ .

All control subjects were required to have no known family history of POAG, as well as a normal IOP, optic disc and visual field. Additionally those control subjects in the SA and GIST cohort were age and gender matched to the cases. The population-based BMES control cohort comprised the eldest subgroup of people meeting control inclusion criteria.

The Australian Twin Eye Study ⁹ comprises participants examined as part of the Twins Eye Study in Tasmania (TEST) or the Brisbane Adolescent Twins Study (BATS). Ethical approval was obtained from the Royal Victorian Eye and Ear Hospital, the University of Tasmania, the

Australian Twin Registry and the Queensland Institute of Medical Research. Participants underwent a comprehensive ophthalmic examination as outlined previously ⁹ . IOP and central corneal thickness was measured using a calibrated TONO-PEN XL (Reichert, Inc. New York, USA) and a Tomey SP 2000 (Tomey Corp., Nagoya, Japan) pachymeter with topical benoxinate. Following instillation of one drop of tropicamide 1%, cycloplegic refraction was measured using a Humphrey-598 automatic refractor (Carl Zeiss Meditec, Inc., Miami, Florida, USA). Exclusion criteria from analysis included the presence of visually significant pterygium (n = 19), previous cataract or refractive surgery (π = 10) and significant corneal scaring (n = 1). The mean IOP, central corneal thickness and spherical equivalent of both eyes was used for analysis. Genomic DNA was obtained by either buccal swab or venous blood collection.

DNA was extracted from peripheral blood or saliva samples. Participants were typed on the Illumina Human HapθlOW Quad array (Illumina Inc., San Diego, USA). Most participants recruited as part of the BATS were genotyped as part of a larger project contracted to deCODE Genetics (Reykjavik, Iceland). A small number of BATS individuals (50) and the participants of the TEST were genotyped at the Center for Inherited Disease Research (CIDR; The Johns

Hopkins University, Baltimore, USA). The exclusion criteria for SNPs were minor allele frequency < 1%, Hardy-Weinberg equilibrium (HWE) p< 10-6, or SNP call rate≤95% and Illumina

Beadstudio Gencall Score <0.7.

Subjects from Hong Kong and Shantou All subjects in the Hong Kong study population were of southern Han Chinese ancestry residing in Hong Kong. The cases consisted of 176 individuals with POAG recruited from the Eye Clinic at the Prince of Wales Hospital and 1,027 controls. Ninety-two of the control individuals were also recruited from the Eye Clinic at the Prince of Wales Hospital. This study was approved by the Clinical Research Ethics Committee of the Chinese University of Hong Kong. Additional 935 control subjects of southern Han Chinese ancestry residing in Hong Kong were also recruited at the Prince of Wales Hospital in Hong Kong from the general population participating in a community-based cardiovascular risk screening program as well as hospital staff. In addition, subjects were recruited from a cardiovascular risk screening program for adolescents. Informed consent was obtained for each participating subject.

All subjects in the Shantou study population were of Han Chinese ancestry residing in the Shantou area for generations. The cases consisted of 123 individuals with POAG recruited from the Joint Shantou International Eye Center of Shantou University and Chinese University of Hong Kong, and Joint Shantou International Eye Center of Shantou University and Chinese University of Hong Kong, Shantou, China, and 332 controls.

The POAG patients met all the following criteria: exclusion of secondary causes (e.g., trauma, uveitis, steroid-induced glaucoma, or exfoliation glaucoma), Shaffer grade III or IV open iridocorneal angle on gonioscopy, characteristic optic disc damage or typical visual field loss by Humphrey automated perimeter with the Glaucoma Hemifield test. IOP was determined by applanation tonometry. All the POAG patients were late-onset HTG, with age of diagnosis higher than 50 years and highest IOP without treatment greater than 22 mmHg. The controls included 92 individuals, aged between 60 to 99 years and recruited from people who attended the same clinic for conditions of senile cataract, floaters, refractive errors, or itchy eyes. They were excluded from glaucoma using the same criteria of diagnosis as the POAG patients after going through the same procedure of ophthalmic examination.

Illumina Genome-Wide Genotyping

All Icelandic case and control samples were assayed with the Illumina HumanHap300 or HumanHapCNV370 bead chips (Illumina, SanDiego, CA, USA), containing 317,503 and 370,404 SNPs derived from phase I of the International HapMap project. Only SNPs present on both chips were included in the analysis and SNPs were excluded if they had (a) yield lower than 95% in cases or controls, (b) minor allele frequency less than 1% in the population, or (c) showed significant deviation from Hardy-Weinberg equilibrium in the controls (P < 0.001). Any samples with a call rate below 98% were excluded from the analysis. The final analysis included 303,117 SNPs. Single SNP Genotyping

Single SNP genotyping for the POAG replication sample sets from Sweden, UK and Australia, was carried out at deCODE genetics in Reykjavik, Iceland, applying the same platform to all populations studied. All single SNP genotyping was carried out using the Centaurus (Nanogen) platform ¹⁰ . The quality of each Centaurus SNP assay was evaluated by genotyping each assay on the CEU samples and comparing the results with the HapMap data. All assays had mismatch rate <0.5%. Additionally, all markers were re-genotyped on more than 10% of samples typed with the Illumina platform resulting in an observed mismatch in less than 0.5% of samples.

Association Analysis

For association analysis we utilized a standard likelihood ratio statistic, implemented in the NEMO software ¹¹ to calculate two-sided P values and odds ratios (ORs) for each individual allele, assuming a multiplicative model for risk, i.e. that the risk of the two alleles a person carries multiplies ¹² . Allelic frequencies, rather than carrier frequencies are presented for the markers and P values are given after adjustment for the relatedness of the subjects. When estimating genotype specific OR, genotype frequencies in the population were estimated assuming Hardy- Weinberg equilibrium.

In general, allele and haplotype frequencies are estimated by maximum likelihood and tests of differences between cases and controls are performed using a generalized likelihood ratio test ¹³ . This method is particularly useful in situations where there are some missing genotypes for the marker of interest and genotypes of another marker, which is in strong LD with the marker of interest, are used to provide some partial information. This was used in the association tests presented in Tables 5, 7 and 8 to ensure that the comparison of the highly correlated markers was done using the same number of individuals. To handle uncertainties with phase and missing genotypes, maximum likelihood estimates, likelihood ratios and P values are computed directly for the observed data, and hence the loss of information due to uncertainty in phase and missing genotypes is automatically captured by the likelihood ratios. Results from multiple case-control groups were combined using a Mantel-Haenszel model ¹³ in which the groups were allowed to have different population frequencies for alleles, haplotypes and genotypes but were assumed to have common relative risks.

We used multiple regression to test the correlation between variations in IOP, CCT and spherical equivalent refraction error (SEq), calculated as the average over both eyes, and the number of copies of rs4236601[A] an individual carries. The effect of age of exam and sex of the individual was taken into account by including those variables as explanatory variables in the regression analysis. The spherical equivalent refraction error was calculated as SEq = spherical error + cylinder error / 2 and myopia was defined when SEq was -3 diopters or higher.

Correction for Relatedness of the Subjects and Genomic Control Some of the individuals in both the Icelandic patient and control groups are related to each other, causing the χ ² -square test statistic to have a mean >1 and median >0.455. We estimated the inflation factor for the genome-wide association by calculating the average of the 303,117 cχ ² -square statistics, which was a method of genomic control ¹⁴ to adjust for both relatedness and potential population stratification. The inflation factor was estimated as 1.182 and the results presented from the genome-wide association and in Table 4, 5, 7 and 8 are based on adjusting the χ ² -square statistics by dividing each of them by 1.182.

Sequencing of CAVl and CAV 2

We resequenced the exons of the CAVl and CAV2 genes and the sequence flanking the exons in 280 Icelandic cases and 358 Icelandic controls. Sequencing assays (ranging in amplimer size from 371 to 624 bp) were designed for each of the exons using NCBI assembly build 36 and the Winseq program (developed at deCODE genetics based on the Primer3 software) ¹⁶ . The 5μl PCR amplification reactions were set up on the Zymark SciClone ALH 300 robotic workstation in a 384 well PCR plate and amplified on a MJR Tetrad (Trademark of MJ. Research, Inc., Watertown, MA). Ampure (Agencourt) 384 PCR filters were used to remove unincorporated PCR primers and mononucleotides from the PCR reaction. The 5μl cycle sequencing dye terminator reaction was set up on a Zymark SciClone ALH 300 robotic workstation in a 384 well PCR plate and amplified on a MJR Tetrad (Trademark of MJ. Research, Inc., Watertown, MA). Dye terminator removal was set up on a Zymark SciClone ALH 300 robotic workstation using CleanSEQ (Agencourt) 384 PCR filters. Electrophoresis was performed on Applied Biosystems 3700 DNA Analyzers (Perkin- Elmer, Foster City, CA). deCODE genetics SequenceMiner (Trademark of deCODE genetics Inc., Iceland) sequence assembly software was used to manually analyse and edit the generated sequence.

Accession numbers: CAVl and CAV2 exons for sequencing were based on the Genbank Accession IDs NM_001753 (http://www.ncbi.nlm.nih.gov/nuccore/15451855) and NM_001233

(http://www.ncbi.nlm.nih.gov/nuccore/38176290) respectively. The positions of the amino acids within the caveolin-1 and caveolin-2 proteins were based on Genpept Accession IDs NP_001744 (http://www.ncbi.nlm.nih.gov/protein/15451856) and NP_001224

(http://www.ncbi.nlm.nih.gov/ protein/4557413), respectively.

Two variants identified in the sequencing and that show strong association in the Icelandic cohort, rsl052990 located in the 3' UTR of CAV2 and rs8940 a non-synonomous coding change in one of the exons of CAV2, were genotyped in the three cohorts from Australia, GIST, ANZRAG and BMES, and in the cohort from Sweden and tested for association with POAG. In the four cohorts combined rsl052990[G] had an OR = 1.20 (P = 0.0055) and rs8940[G] had OR = 1.16 (P = 0.076). However, after adjusting for the effect of rs436601 neither variant showed significant association with POAG (P _adJ = 0.94 and 0.28) for rsl052990[G] and rs8940[G], respectively. The same was true when the results for the four cohorts were combined with the results from the Icelandic discovery cohort, moreover, in all cohorts combined rs4236601 remained significant after adjusting for either rsl052990 (P _adj2 = 0.0010) or rs8940 (P _adj2 = 7.6χlO ^"6 ) suggesting that neither variant can explain the observed association with rs4326601.

References:

1. Jonassoπ, F., et al. Prevalence of open-angle glaucoma in Iceland : Reykjavik Eye Study. Eye

(Lond) 17, 747-753 (2003).

2. Aldred, M. A., et al. Low prevalence of MYOC mutations in UK primary open-angle glaucoma patients limits the utility of genetic testing. Hum Genet 115, 428-431 (2004).

3. Ennis, S., et al. Prevalence of myocilin gene mutations in a novel UK cohort of POAG patients.

Eye (Lond) 24, 328-333 (2010).

4. Ennis, S., et al. Association between the SERPINGl gene and age-related macular

degeneration : a two-stage case-control study. Lancet 372, 1828-1834 (2008).

5. Green, CM., et al. How significant is a family history of glaucoma? Experience from the

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19. Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 39, 906-913 (2007). EXAMPLE 4

An association analysis was performed for markers identified in the 1000 genomes project as correlated markers with rs4236601. This was done by imputation of genotypes for Icelandic glaucoma cases based on the 1000 genomes data.

Results of the association analysis is shown in Table 9. As expected, almost all of the markers do show significant association with glaucoma. The strength of the observed association in general is correlated with the strength of the LD between the particular marker and rs4236601.