FLUCTUATIONS IN AMYLOID BETA AS A BIOMARKER FOR

ALZHEIMER'S DISEASE

GOVERNMENTAL RIGHTS

[0001] The present invention was made, at least in part, with funding from the National Institutes of Health, NIH grant 5K08AG02709102. Accordingly, the United States Government may have certain rights in this invention.

FIELD OF THE INVENTION

[0002] The present invention generally relates to Alzheimer's disease. In particular, the present invention provides biomarkers for Alzheimer's disease and methods of using the biomarkers to diagnose, monitor treatment, and/or identify individuals at risk for Alzheimer's disease.

BACKGROUND OF THE INVENTION

[0003] Alzheimer's disease (AD) is the most common cause of dementia and is an increasing public health problem. It is currently estimated to afflict 5 million people in the United States, with an expected increase to 13 million by the year 2050 (Hebert et al., 2003, Arch Neurol 60(8):1119-1122). AD leads to loss of memory, cognitive function, and ultimately independence. AD takes a heavy personal and financial toll on the patient and the family. Because of the severity and increasing prevalence of the disease in the population, it is urgent that better treatments be developed.

[0004] The neuropathologic and neurochemical hallmarks of AD include synaptic loss and selective neuronal death, a decrease in specific neurotransmitters, and the presence of abnormal proteinaceous deposits in neurons (neurofibrillary tangles) and in the extracellular space (cerebrovascular, diffuse, and neuritic plaques). The main constituent of plaques is amyloid-beta (Aβ), a 38-43 amino acid peptide cleaved from the amyloid precursor protein (APP) (Golde et al., 2000, Biochim Biophys Acta 1502(1 ):172-87; Selkoe, 2001 , Physiol. Rev. 81 :741 -766). Throughout life, soluble

Aβ is secreted mostly by neurons, but also by other cell types. Multiple lines of evidence suggest that Aβ accumulation and change of conformation to forms with a high β-sheet structure (e.g., amyloid oligomers) is central in AD pathogenesis (Holtzman, 2002, Neurobiol Aging 23(6):1085-8).

[0005] Investigators at the Washington University School of Medicine developed a Clinical Dementia Rating (CDR) scale in which an individual's cognition is rated as normal (CDR 0), or demented with severities of very mild, mild, moderate or severe (CDR 0.5, 1 , 2, or 3, respectively) (See Morris, 1993, Neurology, 43:2412, hereby incorporated by reference). Individuals diagnosed with possible/probable dementia of the Alzheimer's type (DAT) are usually CDR 1 or greater. One challenge has been to diagnose individuals at earlier stages, when clinical symptoms are less severe. During these early stages (CDR 0.5, often lasting 2-5 years or longer), many individuals meet clinical criteria for mild cognitive impairment (MCI) (Peterson et al., 1999; Arch. Neurol, 56:303). Data suggest an early and insidious pathogenesis of AD, the clinical manifestations of which become apparent only after substantial neuronal cell death and synapse loss has taken place. These findings have profound implications for AD therapeutic and diagnostic strategies.

[0006] Currently, there are some medications that modify Alzheimer's symptoms, however, there are no disease modifying treatments. Disease modifying treatments will likely be most effective when given before the onset of permanent brain damage. However, by the time clinical diagnosis of AD is made, extensive neuronal loss has already occurred (Price et al., 2001 , Arch Neurol 58(9):1395-402). Therefore, a way to identify those at risk of developing AD will be most helpful in preventing or delaying clinical AD onset. Consequently, there is a need in the art to identify biomarkers of the pathophysiologic changes that occur in AD.

SUMMARY OF THE INVENTION

[0007] Among the various aspects of the present invention is the provision of a biomarker for Alzheimer's disease. The biomarker comprises either (a) the

attenuation of amyloid-beta fluctuation over time in a subject, or (b) the attenuation of correlation between amyloid-beta species over time in the subject.

[0008] Another aspect of the invention encompasses a method for diagnosing Alzheimer's disease in a subject. The method comprises either (a) determining the fluctuation of amyloid-beta over time in the subject, wherein an attenuated fluctuation indicates the diagnosis of Alzheimer's disease, or (b) determining the correlation between amyloid-beta species over time in the subject, wherein an attenuated correlation indicates the diagnosis of Alzheimer's disease.

[0009] A further aspect of the invention provides a method for determining whether a subject is at risk for Alzheimer's disease. The method comprising either (a) determining the fluctuation of amyloid-beta over time in the subject, wherein an attenuated fluctuation indicates the subject is at risk for Alzheimer's disease, or (b) determining the correlation between amyloid-beta species over time in the subject, wherein an attenuated correlation indicates the subject is at risk for Alzheimer's disease.

[0010] Other aspect and features of the invention are described in more detail below.

DESCRIPTION OF THE FIGURES

[0011 ] Figure 1 depicts a series of graphs illustrating that human CSF Aβ levels fluctuate over hours. (A-C) The levels of human CSF Aβi _-X (triangle), Aβ ₄₀ (square), and Aβ ₄₂ (circle) over 36 hours are shown in three typical individual participants (A, B age 20 to 45, C age 46 to 80). Aβ levels had significant fluctuations, changing >50% within 6 hours, and >100% over 12 hours. (D-F) Mean levels of Aβi _-X (D), Aβi _-40 (E), and Aβi _-42 (F) averaged across all participants at each sample time are shown as a percent of the average Aβ level. Aβ levels demonstrate troughs at 0 and 25 hours with peaks at 14 and 23 hours.

[0012] Figure 2 depicts a series of graphs showing that CSF Aβ ₄₀ , Aβ ₄₂ , and Aβi _-X are correlated over time and mean levels vary by time of day. The CSF Aβi _-X versus Aβ ₄₀ and Aβ ₄₂ , and Aβ ₄₀ versus Aβ ₄₂ are shown for three participants (A, B, and

C). Aβ ₄₀ and Aβ ₄₂ are correlated with Aβi _-X , and Aβ ₄₂ is correlated with Aβ ₄₀ . Linear regression of each indicates a strong correlation between each pair of human Aβ species assessed in CSF (p < 0.0001 ).

[0013] Figure 3 depicts a graph showing that the loss of correlation in the fluctuation of Aβ is predictive of those affected or at risk for AD versus normal controls.

[0014] Figure 4 depicts two graphs showing the fluctuations of Aβ in DAT participants (CDR >0) (B) and cognitively normal controls (A).

DETAILED DESCRIPTION OF THE INVENTION

[0015] The present invention provides novel AD biomarkers present in the bodily fluid or tissue of a subject. These biomarkers correlate with CDR score, and therefore may allow a more accurate diagnosis or prognosis of AD in subjects that are at risk for AD, that show no clinical signs of AD, or that show minor clinical signs of AD. Furthermore, the biomarkers may allow the monitoring of AD, such that a comparison of biomarker levels allows an evaluation of disease progression in subjects that have been diagnosed with AD, or that do not yet show any clinical signs of AD. Moreover, the AD biomarkers of the invention may be used in concert with known AD biomarkers such that a more accurate diagnosis or prognosis of AD may be made.

/. Biomarkers For Alzheimer's Disease

[0016] One aspect of the invention encompasses biomarkers for AD. One biomarker for AD comprises an attenuation of the fluctuation of Aβ over time in a subject. Another biomarker for AD comprises an attenuation of the correlation between Aβ species over time in a subject.

[0017] As used herein, Aβ refers to the level of Aβ in two or more samples from a subject. Aβ, unless otherwise indicated, may refer to Aβ polypeptides (e.g., Aβi. x), Aβ ₄₂ (Aβi _-42 ), Aβ ₄₀ (Aβi-40), or any combination thereof. In one embodiment, Aβ refers to Aβ ₄₂ . Methods of measuring the level of Aβ in a sample are known in the art. Generally speaking, one skilled in the art will consider the source and quantity of the sample when selecting a method of measuring the level of Aβ in a sample. For

instance, an ELISA may be used to measure the level of Aβ in a sample. For more details, see the methods for Example 1.

[0018] Aβ may be measured in cerebral spinal fluid (CSF) samples, tissue samples, blood samples, microdialysis samples, or other samples that comprise Aβ and reflect physiological fluctuations in Aβ levels. In one embodiment, Aβ may be measured in CSF samples. Methods for collecting CSF samples are known in the art. For more details, see the methods for Example 1 below. In another embodiment, Aβ may be measured in blood samples. In still another embodiment, Aβ may be measured in blood plasma samples. Methods for collecting blood samples are known in the art. In yet another embodiment, Aβ may be measured in tissue samples. Methods for collecting tissue samples, including brain tissue samples, are well known in the art. In still another embodiment, Aβ may be measured in microdialysis samples. Methods for collecting microdialysis samples are well known in the art.

[0019] The amount of sample collected, depends in part, on the type of sample being collected. Generally speaking, the amount collected will be enough to measure Aβ by the method selected.

[0020] A sample may be collected and tested from any animal known to suffer from Alzheimer's disease, including humans, or used as a disease model for Alzheimer's disease. In one embodiment, the subject may be a rodent. Examples of rodents include mice, rats, and guinea pigs. In another embodiment, the subject may be a primate. Examples of primates include monkeys, apes, and humans. In an exemplary embodiment, the subject may be a human. In some embodiments, the subject may have no clinical signs of AD. In other embodiments, the subject may have a CDR score of greater than 0. In further embodiments, the subject may have mild clinical signs of AD, for instance, corresponding to a CDR score of 0.5 or higher. In yet other embodiments, the subject may be at risk for AD. For instance, in a non-limiting example, the subject may have a CDR score of 0 but have amyloid plaques in the brain. In still other embodiments, the subject may have been diagnosed with AD.

(a) attenuation of the fluctuation of Aβ

[0021] Fluctuation in Aβ refers to changes, variations, variability, or dynamics in the level of Aβ over time in a subject (or the ratio of Aβ over time in a subject). The changes may be reflected in increased levels or ratios, decreased levels or ratios, or changed patterns of fluctuation (e.g., sinusoidal vs. non-sinusoidal).

[0022] Generally speaking, the level of Aβ fluctuates over time in a subject that is not afflicted with AD. Stated another way, the level of Aβ fluctuates over time in a subject with a clinical dementia rating (CDR) of 0 that lacks amyloid plaques in the brain. Consequently, in some embodiments, attenuation of the fluctuation of Aβ over time comprises a biomarker for diagnosing AD in a subject or for predicting whether a subject will develop AD. For instance, in one embodiment, attenuation of the fluctuation of Aβ over time may comprise a biomarker for AD in subjects who have neuropathologic AD but have not yet manifested clinical signs of AD.

[0023] One method to quantify the fluctuation of Aβ in a subject is to determine the level of Aβ in two or more samples from the subject over a given time period. Another method to quantify the fluctuation of Aβ in the subject is to calculate the standard deviation of Aβ levels in two or more samples from the subject over a given time period. Methods of calculating standard deviations are known in the art. In some embodiments, the level of Aβ and/or the standard deviation may be calculated from 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, or more samples from the subject. The time interval between two consecutive samples may range from minutes to hours to days to months. In certain embodiments, the time interval between two consecutive samples may be at least about 0.5, 1 , 2, 5, 10, 20, 30, 60, 120, 240, or more minutes. In other embodiments, the time interval between two consecutive samples may be at least about 3, 5, 10, 15, 20, 25, 30, or more hours. In still other embodiments, the time interval between two consecutive samples may be at least about 1 , 2, 5, 10, 15, 20, 30, 60, 120, or more days.

[0024] Typically, for a subject with a CDR >0, the fluctuation is attenuated compared to the fluctuation in a subject with a CDR of 0 who lacks amyloid plaques in the brain. In some embodiments, the fluctuation is attenuated for a subject afflicted with

AD. In other embodiments, the fluctuation is attenuated for a subject who is at risk for developing AD (i.e., who is developing amyloid plaques in the brain but is still clinically normal, with a CDR of 0). In certain embodiments, the fluctuation may be attenuated in a subject who is likely to develop AD but has not yet shown clinical symptoms of the disease.

[0025] In the present context, attenuation means that the fluctuation is at least about 10% less than that seen in a subject with a CDR of 0 who lacks amyloid plaques in the brain. In some embodiments, the fluctuation may be at least about 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% less than that seen in a subject with a CDR of 0 who lacks amyloid plaques in the brain.

(b) attenuation of the correlation between Aβ ₄₂ and other Aβ species

[0026] Generally speaking, the levels of Aβ ₄₂ correlate positively with other

Aβ species in a subject who is not afflicted with AD. As used herein, Aβ species refers to an Aβ polypeptide, or, in some embodiments, the total of all or some Aβ polypeptides. For instance, if the total level of Aβ increases in a subject, the level of Aβ ₄₂ also increases. Consequently, in some embodiments, the attenuation of the correlation between Aβ ₄₂ and total Aβ or Aβ ₄₀ over time comprises a biomarker for AD in a subject. In other embodiments, the attenuation of correlation is a biomarker for a subject who is at risk for developing AD. In certain embodiments, the attenuation of correlation is a biomarker for a subject who is likely to develop AD but has not yet shown clinical symptoms of the disease (e.g., a subject who is developing amyloid plaques in the brain, but is still clinically normal, with a CDR of 0). In still other embodiments, the attenuation of correlation is a biomarker for a subject that has a CDR >0.

[0027] Typically, there is a positive linear correlation between the level of

Aβ ₄₂ and the level of other Aβ species, such as total Aβ or Aβ ₄₀ over time in a subject. This correlation may be measured using methods known in the art, as illustrated in Example 1. Typically, the correlation between Aβ species is calculated from two or more samples from the subject over a time period. The time interval between two

consecutive samples may range from minutes to hours to days to months. In certain embodiments, the time interval between two consecutive samples may be at least about 0.5, 1 , 2, 5, 10, 20, 30, 60, 120, 240, or more minutes. In other embodiments, the time interval between two consecutive samples may be at least about 3, 5, 10, 15, 20, 25, 30, or more hours. In still other embodiments, the time interval between two consecutive samples may be at least about 1 , 2, 5, 10, 15, 20, 30, 60, or more days.

[0028] As detailed above, attenuation means that the correlation is at least about 10% less than that seen in a subject with a CDR of 0 who lacks amyloid plaques in the brain. In some embodiments, the correlation may be at least about 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% less than that seen in a subject with a CDR of 0 who lacks amyloid plaques in the brain.

(c) combinations of biomarkers

[0029] Each of the biomarkers identified above may be used in concert with another biomarker for purposes including but not limited to diagnosis of AD, prognosis of AD, determining risk of AD, and monitoring treatment of AD. For instance, two or more, three or more, four or more, five or more, or six or more AD biomarkers may be used in concert. As explained above, there are several known biomarkers for AD. In one embodiment, at least one biomarker of the invention and one or more biomarkers from the group comprising ACT, ATIII, ZAG, CNDP1 , and tau may be used in concert. In yet another embodiment, at least one biomarker of the invention and two or more biomarkers from the group comprising ACT, ATIII, ZAG, CNDP1 , and tau may be used in concert. In still another embodiment, at least one biomarker of the invention and three or more biomarkers from the group comprising ACT, ATIII, ZAG, CNDP1 , and tau may be used in concert. In yet still another embodiment, at lest one biomarker of the invention and ACT, ATIII, ZAG, CNDP1 , and tau may be used in concert as biomarkers for AD.

//. Methods For Using The Biomarker Of The Invention

[0030] Another aspect of the invention encompasses methods for using the biomarkers of the invention.

[0031] In one embodiment, one of the biomarkers detailed in section I above may be used in a method for diagnosing AD in a subject. The method may comprise determining the fluctuation of Aβ over time in the subject, wherein an attenuated fluctuation indicates a diagnosis of AD. Alternatively, the method may comprise determining the correlation of Aβ species over time in a subject, wherein an attenuated correlation indicates a diagnosis of AD. Determining the fluctuation or correlation over time comprises measuring Aβ in at least two samples from the subject.

[0032] In another embodiment, one of the biomarkers detailed in section I above may be used in a method for determining whether a subject is at risk of developing AD. In particular, the biomarkers may be used for assessing whether a subject is likely to develop AD but has not yet shown clinical symptoms of the disease. The method may comprise determining the fluctuation of Aβ over time in the subject, wherein an attenuated fluctuation indicates the subject is at risk of developing AD. Alternatively, the method may comprise determining the correlation of Aβ species over time in the subject, wherein an attenuated correlation indicates the subject is at risk of developing AD. Determining the fluctuation or correlation over time comprises measuring Aβ in at least two samples from the subject.

[0033] In still another embodiment, one of the biomarkers detailed in section I above may be used for monitoring AD. The method may comprise determining the fluctuation of Aβ or determining the correlation of Aβ species in the subject over time after the diagnosis of AD. The comparison of the biomarker at two or more time points may give an indication of disease progression. For example, no further attenuation of the fluctuation or correlation indicates that the disease has not progressed or worsened. Additionally, the comparison may serve to measure the rate of disease progression.

[0034] In a further embodiment, a biomarker detailed in section I above may be used for monitoring treatment of a subject having AD. The method may

comprise determining the fluctuation of Aβ or determining the correlation of Aβ species in the subject before and after the administration of the treatment. A reduced attenuation of fluctuation or correlation after treatment indicates a positive response to the treatment. Alternatively, if the fluctuation or correlation does not change or is increased after treatment, then the subject's response to the treatment is neutral or negative. Therefore, the comparison may serve to measure the effectiveness of a chosen therapeutic treatment.

[0035] Typically, the therapeutic treatment for AD will comprise administration of a therapeutic agent. Non-limiting examples of suitable AD therapeutic agents include gamma-secretase inhibitors, beta-secretase inhibitors, alpha-secretase activators, RAGE inhibitors, small molecule inhibitors of Aβ production, small molecule inhibitors of Aβ polymerization, platinum-based inhibitors of Aβ production, platinum- based inhibitors of polymerization, agents that interfere with metal-protein interactions, proteins (such as, e.g., low-density lipoprotein receptor-related protein (LRP) or soluble LRP) that bind soluble Aβ, and antibodies that clear soluble Aβ and/or break down deposited Aβ. Other suitable AD therapeutic agents include cholesterylester transfer protein (CETP) inhibitors, metalloprotease inhibitors, cholinesterase inhibitors, NMDA receptor antagonists, hormones, neuroprotective agents, and cell death inhibitors. The therapeutic agent will be administered to the subject in accord with known methods. Typically, the therapeutic agent will be administered orally, but other routes of administration such as parenteral or topical may also be used. The amount of therapeutic agent that is administered to the subject can and will vary depending upon the type of agent, the subject, and the particular mode of administration.

[0036] For each of the above embodiments, suitable subjects include those detailed in section I above. In exemplary embodiments, the subject is human.

[0037] The following examples are included to demonstrate preferred embodiments of the invention. It should be appreciated by those of skill in the art that the techniques disclosed in the examples that follow represent techniques discovered by the inventors to function well in the practice of the invention. Those of skill in the art should, however, in light of the present disclosure, appreciate that many changes can

be made in the specific embodiments that are disclosed and still obtain a like or similar result without departing from the spirit and scope of the invention, therefore all matter set forth or shown in the accompanying drawings is to be interpreted as illustrative and not in a limiting sense.

EXAMPLES

[0038] The following example illustrates various iterations of the invention.

Example 1 : Fluctuations of CSF Amyloid-β Levels

[0039] There are strong genetic, biochemical, and animal model data that support the importance of amyloid-β (Aβ) in AD. Due to Aβ deposition as insoluble aggregates in plaques, Aβ levels are increased by 100-fold or more in the brains of individuals with AD vs. controls. Thus, understanding Aβ metabolism both prior to and after Aβ deposition is likely to lead to insight in AD pathogenesis. Accordingly, the following example was designed to investigate the stability and time course of human CSF Aβ levels over hours.

[0040] Participants. All human studies were approved by the Washington

University Human Studies Committee and the GCRC Advisory Committee. Informed consent was obtained from all participants. All participants were screened to be in good general health and without neurologic disease. Participants older than 65 were non- demented controls, enrolled in the Washington University ADRC, and had a Clinical Dementia Rating of 0 (no dementia). Nine men and six women (23 to 78 years old) participated. The lumbar catheter was placed by trained physicians between 7:30 AM and 9 AM, and sample collection started between 8 AM and 9:30 AM in all participants. CSF samples were collected in polypropylene tubes hourly throughout the study. The participants were encouraged to stay in bed. The participants had meals at 9 AM, 1 PM, and 7 PM. Participants were allowed free choice of when to sleep, read, watch television, or talk throughout the study.

[0041] CSF analysis. Six milliliters of CSF was obtained each hour for 12,

24, or 36 hours. CSF aliquots were frozen at -80 ⁰ C immediately after collection in 1 ml_

polypropylene tubes. One milliliter of CSF from each collection hour was thawed and Aβ _1-X , Aβ _1-40 (Aβ ₄₀ ), and Aβ _1-42 (Aβ ₄₂ ) levels were measured by ELISA as described by Cirrito et al. (2003, J Neurosci 23:8844-8853). Briefly, 3D6 (anti-Aβi _-5 , requiring position 1 ) (Vanderstichele et al., 2005, Clin Chem 51 :1650-1660) was used as the detection antibody, and m266 (anti-mid-domain Aβ for Aβi _-X ), 2G3 (for anti-Aβ ₄₀ ), and 21 F12 (for anti-Aβ ₄₂ ) antibodies were used as capture antibodies. Each sample was assessed in duplicate. All samples from each subject were measured together on the same ELISA plate to avoid interplate variation. To measure the effect of ELISA assay variability, separate ELISA plates for Aβi _-X , Aβi _-40 , and Aβi _-42 were run with a single CSF sample for the entire plate. The means of the intrasample coefficient of variation for duplicates were 4.9% for Aβi _-X , 10.4% for Aβ ₄₀ , and 5.9% for Aβ ₄₂ .

[0042] Statistical analysis. All analyses were performed using Graph-Pad

Prism version 4.03 for Windows, GraphPad Software, San Diego, CA, www.graphpad.com. The minimum, maximum, mean, SD, and coefficient of variation were calculated for each participant's hourly values for Aβ i _-x , Aβ i _-40 , and Aβ i _-42 . Correlation analysis between Aβ species was performed using a two-tailed Pearson correlation of each hourly measurement. For averaging across participants, Aβ levels in pg/mL were normalized for each participant by calculating the percent change from the mean of all values for each participant. The normalized values were averaged across all participants to produce an average normalized curve.

[0043] Results. Aβ levels in human CSF had significant variability over 12 hours (n = 1 ), 24 hours (n = 3), and 36 hours (n = 11 ) of sampling (Figure 1 , A through C, and Table 1 ). In most participants, the levels for Aβi _-X , Aβ ₄₀ , and Aβ ₄₂ varied by 50% or more over several hours and the maximum Aβ levels were greater than 200% the minimum values over the entire study. There were no significant differences in average Aβ _1-X , Aβ _1-40 , or Aβ _1-42 minimums, maximums, or means between the younger (20 to 45 years) and older (46 to 80 years) groups in this group of participants.

Atty. Docket No. 47563-130679 Via EFS Web

Table t Human CSF Aβ Levels

Participant

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Age

20-45 20-45 20-45 20-45 20-45 20-45 20-45 20-45 20-45 20-45 46-80 46-80 46-80 46-80 46-80

(decade)

Minimum 12,860 11 ,637 12,173 5,740 13,062 30,332 20,663 10,189 13,475 8,069 8,916 13,117 10,256 10,054 21,320

Maximum 30,506 28,744 26,990 18,000 37,229 52,263 35,815 33,384 37.903 24,681 19,338 36,676 25,126 21,743 32,235

Mean 21,013 18,460 19,079 14,462 27,247 35,702 30,456 23,897 26,910 17,389 12,992 18,460 15,977 16,591 26,607

Minimum 3,980 4,477 5,683 2,593 4,950 11,238 4,817 3,648 5,898 2,261 4,219 3,949 4,394 6,489 8,294

Maximum 13,121 16,074 14,356 6,656 18,699 19,924 17,176 14,903 17,491 12,434 11,617 12,378 11,396 17,253 16,173

Mean 8,179 8,259 9,194 4,671 12,284 16,147 11,802 10,008 13,363 8,290 6,685 6,505 8,296 11,375 12,983

Minimum 660.7 313.8 597.4 384.7 972 699.6 1 ,077 922.1 773.3 175.8 237 528.5 595.4 206 581.5

Maximum 1 ,561 1 ,634 1,664 1,269 3,090 1,507 2 ,034 2,459 1,842 1,250 995.5 1,549 1,849 685.4 1,317

Mean 1 ,032 781.4 1,119 900.1 1,925 1,091 1 ,620 1,619 1,241 849.5 529.7 1,135 1,107 456.4 901.5

^* Participants were studied over 12 (n = 1), 24 (n = 3), or 36 (n = 11) hours. Levels of Aβ are presented in pg/ml.

[0044] Aβ ₄₀ and Aβ ₄₂ were correlated (p<0.05) to Aβ _1-X in all samples

(Figure 2) except in the samples of three older participants (n = 3, average age 67 years). For significant correlations, the average correlation was r = 0.77 for Aβi _-40 and r = 0.68 for Aβi _-42 compared to Aβi _-X . Aβi _-42 was correlated to Aβi _-40 in all participants except in two older participants (n = 2, average age 65.5 years). For significant correlations, the average correlation of Aβ ₄₀ to Aβ ₄₂ was r = 0.67.

[0045] There was a significant correlation of Aβi _-X to Aβ ₄₀ and Aβ ₄₂ , as well as Aβ ₄₀ to Aβ ₄₂ . The Aβ species 40 and 42 were tightly correlated to each other in hourly measurements, and this likely indicates similar processes in the production and clearance of each from human CSF. The relationship may be altered in the presence of Aβ deposition in plaques, leading to a decreased level of Aβ ₄₂ and a decreased ratio of Aβ ₄₂ to Aβ ₄₀ reported in studies (Sunderland et al., 2003, JAMA 289:2094-2103). In addition, in several older participants, there was not a significant correlation of Aβ ₄₂ to Aβ ₄₀ or to Aβi _-X . This may reflect a disturbance in clearance of Aβ ₄₂ relative to Aβ ₄₀ and may be a precursor or an indicator of AD pathology.

[0046] The absolute levels of Aβi _-42 over 36 hours was higher in cognitively normal (CDR 0) participants compared with cognitively impaired DAT (CDR >0) (Figure 3). Similar results have been reported in single time point CSF studies (Galasko et al., 1998, Arch Neurol 55(7):937-45). However, the increased Aβi _-42 was not observed in all CDR 0 participants. One participant had low levels (< 250 pg/ml), while two other participants had several time points of lower Aβ _1-42 . In CDR > 0 participants, four of five had low Aβi _-42 , while one participant had > 500 pg/ml. This is consistent with the predicted diagnostic accuracy of the clinical evaluation. About 20- 30% of CDR 0 participants between the ages of 70-75 have Alzheimer disease pathology and 10-20% of CDR >0 participants misdiagnosed as DAT do not have Alzheimer pathology. Therefore, Aβi _-42 may be extremely highly correlated to Alzheimer pathology, as suggested by recent studies of Aβi _-42 and PET PIB, which is an Aβ plaque imaging technique (Fagan et al., 2006, Annals of Neurology 59(3):512-519).

[0047] Also of note, the variability of Aβi _-42 in cognitively normal participants (CDR 0) appears higher than in participants with DAT (CDR >0) (Figure 4). Table 2 below summarizes the differences in variability between AD and controls. The Aβ fluctuations are a biologic change in levels and not an artifact (e.g., a floor effect) of the assay, which has a sensitivity of 10 pg/ml (Bateman et al., 2007, Neurology 68(9):666-669). These fluctuations were demonstrated in young healthy controls and age matched older controls, but appear to be significantly decreased in participants with DAT.

Table 2. Comparison of Aβ ₄₂ Variability.

[0048] The interparticipant hourly average of Aβ levels suggests a sinusoidal pattern over the time period measured (Figure 1 , D through F). Aβ levels increased from 0 to 14 hours, with peaks at 14 and 23 hours and troughs at 0 and 25 hours in the levels of Aβi _-X , Aβ ₄₀ , and Aβ ₄₂ . This may be time of day or activity dependent. There is recent evidence from cellular and animal studies that Aβ release is dependent on synaptic activity (Cirrito et al., 2005, Neuron 48:913; Kamenetz et al., 2003, Neuron, 37:925-937) and this may account for much of the observed variability in CSF levels. In recent animal studies using microdialysis in APP transgenic mice, a similar dynamic variability over hours in Aβ levels in brain interstitial fluid was observed, similar to that observed here in human CSF.