BLOOD BIOMARKERS FOR APPENDICITIS AND DIAGNOSTICS METHODS USING

BIOMARKERS

CROSS-REFERENCE OF RELATED APPLICATION

[0001] This application claims priority to U.S. Provisional Application No. 62/067,414 filed

October 22, 2014, the entire contents of which are hereby incorporated by reference.

BACKGROUND

[0002] Technical Field

[0003] The field of the currently claimed embodiments of this invention relate to methods and kits for assessing and treating abdominal discomfort/pain (the terms abdominal pain and abdominal discomfort will be used interchangeably throughout) and appendicitis in a subject, and more particularly to assessing and treating abdominal discomfort and appendicitis in a subject using the analysis of biomarkers isolated from the subject

[0004] Discussion of Related Art

[0005] Abdominal pain is a major cause of hospital visits, accounting for about 10% of 62 million visits per year by adults who present at an emergency department (ED) for non-injury causes [1]. Acute appendicitis is one of the most common causes of abdominal pain and results in nearly 750,000 ED visits with approximately 250,000 appendectomies performed annually.

Globally, a small but significant portion of the operations are "negative appendectomies", resulting in the removal of a non-inflamed appendix due to misdiagnosis [2-4], reported as high as 17-28% outside the US and Western Europe [5,6].

[0006] Prior to the widespread availability of computed tomography (CT) scans, the accurate diagnosis of appendicitis could be challenging, and in places where CT is still not available, the Alvarado score of clinical characteristics is a widely used diagnostic tool [5,6]. Currently in the United States, CT scanning is the 'gold standard' for the diagnosis of appendicitis, with magnetic resonance imaging (MRI) being a reasonable alternative in pregnant women [7], and ultrasound sonography being an acceptable alternative for preliminary diagnostics to avoid radiation

[8]. While CT is the most sensitive and specific diagnostic tool for appendicitis [9,10], and used in almost 98% of patients undergoing appendectomy in the US [11], CT scanning carries a significant radiation exposure, and epidemiologic data suggest that radiation exposure can increase the risk of developing a future malignancy [12]. This issue is of particular concern in children because they are more sensitive to the hazards of radiation, they are among the most common patients to present to the ED with abdominal pain, and have the highest rate of misdiagnosis [10,13]. In an attempt to reduce the damaging effect of CT scans, several clinical trials are examining the diagnostic utility of lower doses of radiation, primarily in children [14-16].

[0007) In order to utilize CT scanning more appropriately, and to improve diagnosis in areas where CT scans are unavailable, blood biomarkers were identified that serve as a preliminary safe and rapid test to help identify patients with appendicitis. Genome-wide profiling of RNA transcripts in whole blood RNA of patients presenting at the ED for abdominal pain was conducted, resulting in confirmed appendicitis versus other abdominal abnormalities.

[0008] Some embodiments of the present invention include methods and kits for assessing and treating abdominal discomfort and appendicitis in a subject, and more particularly to assessing and treating abdominal discomfort and appendicitis in a subject using the analysis of biomarkers isolated from the subject.

SUMMARY

[0009] Embodiments of the invention include methods of diagnosing appendicitis in a subject, comprising obtaining a biological sample from said subject; detecting expression levels of at least three or more biomarkers in the biological sample selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor Illb (CD16b), MHC class Π DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha IB, Defensin alpha 3, 18S ribosomal RNA, CDC 14 A, 28S ribosomal RNA, 60S acidic ribosomal protein PI, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32; and comparing the expression levels of said at least three or more biomarkers to a control sample wherein an increase or decrease in the level of expression of said at least three or more biomarkers as compared to the control sample is indicative of appendicitis.

[0010] Embodiments of the invention include methods of treating appendicitis in a subject, comprising: obtaining a biological sample from said subject; detecting expression levels of at least three or more biomarkers in the biological sample selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor nib (CD16b), MHC class Π DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha IB, Defensin alpha 3, 18S ribosomal RNA, CDC 14 A, 28S ribosomal RNA, 60S acidic ribosomal protein PI, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC 100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32; comparing the expression levels of said at least three or more biomarkers to a control sample wherein an increase or decrease in the level of expression of said at least three or more biomarkers as compared to the control sample is indicative of appendicitis; and treating the subject for appendicitis.

[0011] Embodiments of the invention include kits for use in diagnosing appendicitis in a subject comprising: agents that specifically bind at least three or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor fi, Fc frag of IgG receptor Hlb (CD16b), MHC class Π DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha IB, Defensin alpha 3, 18S ribosomal RNA, CDC 14 A, 28S ribosomal RNA, 60S acidic ribosomal protein PI, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC 100134364, LOC391370, LOC646785, LOC644191 and C5orf32; a container for housing said agents; and instructions for use of the agents for determining expression levels of said at least three or more biomarkers and for comparing said expression levels to a control sample wherein an increase or decrease in the expression levels of said at least three or more biomarkers as compared to the control sample is indicative of and methods of using such kits for the diagnosis and/or treatment of appendicitis.

[0012] Embodiments of the invention include systems for evaluating biomarker levels, comprising a plurality of reagents which specifically bind for detection a plurality of biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor Illb (CD 16b), MHC class Π DR. beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha IB, Defensin alpha 3, 18S ribosomal RNA, CDC 14 A, 28S ribosomal RNA, 60S acidic ribosomal protein PI, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32; an assay instrument configured to (i) receive a biological sample, (ii) contact the plurality of reagents with the biological sample and (iii) generate and quantitatively display in human readable form one or more assay results indicative of binding of each biomarker which is assayed to a respective specific binding reagent in the plurality of reagents.

BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Further objectives and advantages will become apparent from a consideration of the description, drawings, and examples.

[0014] FIGURE 1 is a scatterplot of the expression patterns in 2 groups of patients. [0015] FIGURE 2 shows hierarchical clustering of 37 differentially expressed genes in appendicitis patients.

[0016] FIGURE 3 shows a graph displaying the Partial Least Squares Discriminant (PLSD)

Model for classification of appendicitis from RN A biomarkers.

[0017] FIGURE 4 is a graph showing results of defensins in appendicitis, hernia, and lower respiratory infection patients.

[0018] FIGURE 5 shows the behavior of selected transcripts in a validation cohort

[0019] FIGURE 6 shows a schematic of a model of appendicitis biomarker

pathophysiology.

[0020] FIGURE 7 shows a graph showing microarray and quantitative reverse-transcription polymerase chain reaction results for 3 genes differentially expressed in subjects with appendicitis.

[0021] FIGURE 8 shows a Receiving Operating Characteristic (ROC) curve with data from

3 gene transcripts.

DETAILED DESCRIPTION

[0022] In some embodiments, the invention relates to a method of diagnosing appendicitis in a subject, comprising obtaining a biological sample from said subject; detecting expression levels of at least three or more biomarkers in the biological sample selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor Illb (CD16b), MHC class II DR beta S, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha IB, Defensin alpha 3, 18S ribosomal RNA, CDC 14 A, 28S ribosomal RNA, 60S acidic ribosomal protein PI, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32; and comparing the expression levels of said at least three or more biomarkers to a control sample wherein an increase or decrease in the level of expression of said at least three or more biomarkers as compared to the control sample is indicative of appendicitis.

[0023] In some embodiments, the invention relates to the method above, wherein the biological sample is a blood or serum sample.

[0024] In some embodiments, the invention relates to the method above, wherein the at least three biological samples are selected from the list consisting of Interleukin 8 receptor B, Defensin alpha 1, Defensin alpha IB, Defensin alpha 3 and Alkaline phosphatase.

[0025] In some embodiments, the invention relates to a method of diagnosing appendicitis as above, and further comprising determining the ratio of expression between Alkaline phosphatase or Interleukin 8 receptor β and Defensin alpha 1 , Defensin alpha IB or Defensin alpha 3 and comparing said ratio to a control sample, wherein an increase in the ratio of expression is indicative of appendicitis.

[0026] In some embodiments, the invention relates to the method above, wherein the detecting expression levels of at least three or more biomarkers comprises measuring RNA levels of said at least three or more biomarkers.

[0027] In some embodiments, the invention relates to the method above, wherein measuring

RNA levels comprises using reverse transcriptase and polymerase chain reaction.

[0028] In some embodiments, the invention relates to the method above, wherein measuring

RNA levels comprises using microarray analysis.

[0029] In some embodiments, the invention relates to the method above, wherein measuring

RNA levels comprises using RNA sequencing.

[0030] In some embodiments, the invention relates to the method above, wherein comparing the expression levels of said at least three or more biomarkers comprises using a prediction model to determine if a pattern of expression of said at least three or more biomarkers is indicative of appendicitis.

[0031] In some embodiments, the invention relates to the method above by assigning a likelihood of a future outcome to a subject diagnosed with appendicitis.

[0032] In some embodiments, the invention relates to the method above, wherein the future outcome of the subject is mortality.

[0033] In some embodiments, the invention relates to the method above, wherein the subject is being evaluated for abdominal pain.

[0034] In some embodiments, the invention relates to a method of treating appendicitis in a subject, comprising: obtaining a biological sample from said subject; detecting expression levels of at least three or more biomarkers in the biological sample selected from the group consisting of Chemokine C-X-C receptor 1 , Interleukin 8 receptor β, Fc frag of IgG receptor nib (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha IB, Defensin alpha 3, 18S ribosomal RNA, CDC 14 A, 28S ribosomal RNA, 60S acidic ribosomal protein PI, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32; comparing the expression levels of said at least three or more biomarkers to a control sample wherein an increase or decrease in the level of expression of said at least three or more biomarkers as compared to the control sample is indicative of appendicitis; and treating the subject for appendicitis.

[0035] In some embodiments, the invention relates to the method of treating appendicitis above, wherein treating the subject for appendicitis comprises administering antibiotics to said subject, removing said subject's appendix or a combination thereof. [0036] In some embodiments, the invention relates to the method of treating appendicitis above, wherein the biological sample is a blood or serum sample.

[0037] In some embodiments, the invention relates to the method of treating appendicitis above, wherein the at least three biological samples are selected from the list consisting of

Interleukin 8 receptor β, Defensin alpha 1 , Defensin alpha IB, Defensin alpha 3 and Alkaline phosphatase.

[0038] In some embodiments, the invention relates to a method of treating appendicitis as above, and further comprises determining the ratio of expression between Alkaline phosphatase or Interleukin 8 receptor β and Defensin, alpha 1, Defensin, alpha IB or Defensin, alpha 3 and comparing said ratio to a control sample, wherein an increase in the ratio of expression is indicative of appendicitis.

[0039] In some embodiments, the invention relates to the method of treating appendicitis above, wherein detecting expression levels of at least three or more biomarkers comprises measuring RNA levels of said at least three or more biomarkers.

[0040] In some embodiments, the invention relates to the method of treating appendicitis above, wherein measuring RNA levels comprises using reverse transcriptase and polymerase chain reaction.

[0041] In some embodiments, the invention relates to the method of treating appendicitis above, wherein measuring RNA levels comprises using microarray analysis.

[0042] In some embodiments, the invention relates to the method of treating appendicitis above, wherein measuring RNA levels comprises using RNA sequencing.

[0043] In some embodiments, the invention relates to the method of treating appendicitis above, wherein comparing the expression levels of said at least three or more biomarkers comprises using a prediction model to determine if a pattern of expression of said at least three or more biomarkers is indicative of appendicitis. [0044] In some embodiments, the invention relates to the method of treating appendicitis above and further comprises performing a computed tomography scan on the subject prior to treating the subject for appendicitis.

[0045] In some embodiments, the invention relates to a kit for use in diagnosing

appendicitis in a subject comprising: agents that specifically bind at least three or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1 , Interleukin 8 receptor β, Fc frag of IgG receptor Illb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha IB, Defensin alpha 3, 18S ribosomal RNA, CDC 14 A, 28S ribosomal RNA, 60S acidic ribosomal protein PI, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394,

LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32; a container for housing said agents; and instructions for use of the agents for determining expression levels of said at least three or more biomarkers and for comparing said expression levels to a control sample wherein an increase or decrease in the expression levels of said at least three or more biomarkers as compared to the control sample is indicative of.

[0046] In some embodiments, the invention relates to the kit above, wherein the agents are polynucleotides that specifically bind to RNA transcripts of the at least three or more biomarkers.

[0047] In some embodiments, the invention relates to the kit above, wherein the

polynucleotides are labeled with a detectable marker.

[0048] In some embodiments, the invention relates to the kit above, wherein the agents are polynucleotides that amplify polynucleotides encoding the at least three or more biomarkers.

[0049] In some embodiments, the invention relates to the kit above, wherein the agents that specifically bind to at least three or more biomarkers bind to at least three or more biomarkers selected from the list consisting of Interleukin 8 receptor β, Defensin alpha 1, Defensin alpha IB, Defensin alpha 3 and Alkaline phosphatase. [0050] In some embodiments, the invention relates to the kit above, wherein the kit further comprises instructions for determining the ratio of expression between Alkaline phosphatase or Interleukin 8 receptor β and Defensin, alpha 1, Defensin, alpha IB or Defensin, alpha 3 and comparing said ratio to a control sample, wherein an increase in the ratio of expression is indicative of appendicitis.

[0051] In some embodiments, the invention relates to the kit above, wherein the kit further comprises reagents for reverse transcriptase and polymerase chain reaction.

[0052] In some embodiments, the invention relates to the kit above, wherein the kit further comprises reagents for microarray analysis.

[0053] In some embodiments, the invention relates to the kit above, wherein the kit further comprises reagents for RNA sequencing.

[0054] In some embodiments, the invention relates to the kit above, wherein the instructions included with the kit further comprise instructions for comparing the expression levels of said at least three or more biomarkers by using a prediction model to detennine if a pattern of expression of said at least three or more biomarkers is indicative of appendicitis.

[0055] In some embodiments, the invention relates to a method of diagnosing appendicitis in a subject comprising: obtaining a biological sample from said subject; and contacting the biological sample from said subject with the kit above.

[0056] In some embodiments, the invention relates to a method of treating appendicitis in a subject comprising: obtaining a biological sample from said subject; contacting the biological sample from said subject with the kit above; and treating the subject for appendicitis by

administering antibiotics to said subject, removing said subject's appendix or a combination thereof.

[0057] In some embodiments, the invention relates to a system for evaluating biomarker levels, comprising a plurality of reagents which specifically bind for detection a plurality of biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor fi, Fc frag of IgG receptor nib (CD16b) MHC class Π DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1 , Defensin alpha IB, Defensin alpha 3, 18S ribosomal RNA,

CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein PI, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2,

Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32; an assay instrument configured to (i) receive a biological sample, (ii) contact the plurality of reagents with the biological sample and (iii) generate and quantitatively display in human readable form one or more assay results indicative of binding of each biomarker which is assayed to a respective specific binding reagent in the plurality of reagents.

[0058] In some embodiments, the invention relates to the system above, wherein the reagents comprise a plurality of antibodies, at least one of which binds to each of the biomarkers which are assayed.

(0059] In some embodiments, the invention relates to the system above, wherein assay instrument comprises an assay device and an assay device reader, wherein the plurality of antibodies are immobilized at a plurality of predetermined locations within the assay device, wherein the assay device is configured to receive the biological sample such that the biological sample contacts the plurality of predetermined locations, and wherein the assay device reader interrogates the plurality of predetermined locations to generate the assay results.

[0060] Definitions

[0061] To facilitate an understanding of the present invention, a number of terms and phrases are defined below.

[0062] As used herein, the singular forms "a", "an", and "the" include plural forms unless the context clearly dictates otherwise. Thus, for example, reference to "a binding agent" includes reference to more than one binding agent.

[0063] The terms "diagnostic" and "diagnosis" refer to identifying the presence or nature of a pathologic condition and includes identifying patients who are at risk of developing a specific disease or disorder. Diagnostic methods differ in their sensitivity and specificity. The "sensitivity" of a diagnostic assay is the percentage of diseased individuals who test positive (percent of "true positives"). Diseased individuals not detected by the assay are "false negatives." Subjects who are not diseased and who test negative in the assay, are termed "true negatives." The "specificity" of a diagnostic assay is I minus the false positive rate, where the "false positive" rate is defined as the proportion of those without the disease who test positive. While a particular diagnostic method may not provide a definitive diagnosis of a condition, it suffices if the method provides a positive indication that aids in diagnosis.

[00641 The terms "detection", "detecting" and the like, may be used in the context of detecting biomarkers, or of detecting a disease or disorder (e.g., when positive assay results are obtained). In the latter context, "detecting" and "diagnosing" are considered synonymous.

[0065] The terms "subject", "patient" or "individual" generally refer to a human, although the methods of the invention are not limited to humans, and should be useful in other mammals (e.g., cats, dogs, etc.).

[0066] "Sample" is used herein in its broadest sense. Λ sample may comprise a bodily fluid including blood, serum, plasma, tears, aqueous and vitreous humor, spinal fluid, urine, and saliva; a soluble fraction of a cell or tissue preparation, or media in which cells were grown. Means of obtaining suitable biological samples are known to those of skill in the art

[0067] An "antibody" is an immunoglobulin molecule that recognizes and specifically binds to a target, such as a protein, polypeptide, peptide, carbohydrate, polynucleotide, lipid, etc., through at least one antigen recognition site within the variable region of the immunoglobulin molecule. As used herein, the term is used in the broadest sense and encompasses intact polyclonal antibodies, intact monoclonal antibodies, antibody fragments (such as Fab, Fab', F(ab')2, and Fv fragments), single chain Fv (scFv) mutants, multispecific antibodies such as bispecific antibodies generated from at least two intact antibodies, hybrid antibodies, fusion proteins comprising an antibody portion, and any other modified immunoglobulin molecule comprising an antigen recognition site so long as the antibodies exhibit the desired biological activity. An antibody may be of any the five major classes of immunoglobulins: IgA, IgD, IgE, IgG, and IgM, or subclasses (isotypes) thereof (e.g. IgGl, IgG2, IgG3, IgG4, IgAl and IgA2), based on the identity of their heavy-chain constant domains referred to as alpha, delta, epsilon, gamma, and mu, respectively. The different classes of immunoglobulins have different and well known subunit structures and three-dimensional configurations. Antibodies may be naked or conjugated to other molecules such as toxins, radioisotopes, etc.

[0068] The term "antibody fragments" refers to a portion of an intact antibody. Examples of antibody fragments include, but are not limited to, linear antibodies; single-chain antibody molecules; Fc or Fc' peptides, Fab and Fab fragments, and multispecific antibodies formed from antibody fragments.

[0069] "Hybrid antibodies" are immunoglobulin molecules in which pairs of heavy and light chains from antibodies with different antigenic determinant regions are assembled together so that two different epitopes or two different antigens may be recognized and bound by the resulting tetramer.

[0070] "Isolated" in regard to cells, refers to a cell that is removed from its natural environment and that is isolated or separated, and is at least about 30%, 50%, 75%, and 90% free from other cells with which it is naturally present, but which lack the marker based on which the cells were isolated.

[0071] For use in the diagnostic and therapeutic applications described herein, kits are also within the scope of the invention. Such kits can comprise a carrier, package or container that is compartmentalized to receive one or more containers such as vials, tubes, and the like, each of the containers) comprising one of the separate elements to be used in the method. For example, the containers) can comprise a probe that is or can be detectably labeled. The probe can be an antibody or polynucleotide specific for a biomarker of interest Alternatively, the kit can comprise a mass spectrometry (MS) probe. The kit can also include containers containing nucleotides) for amplification or silencing of a target nucleic acid sequence, and/or a container comprising a reporter means, such as a biotin-binding protein, e.g., avidin or streptavidin, bound to a detectable label, e.g., an enzymatic, florescent, or radioisotope label. The kit can include all or part of the amino acid sequence of the biomarker, or a nucleic acid molecule that encodes such amino acid sequences. [0072] The kit of the invention will typically comprise the container described above and one or more other containers comprising materials desirable from a commercial and user standpoint, including buffers, diluents, filters, needles, syringes, and package inserts with instructions for use. In addition, a label can be provided on the container to indicate that the composition is used for a specific therapeutic or non-therapeutic application, and can also indicate directions for either in vivo or in vitro use, such as those described above. Directions and or other information can also be included on an insert which is included with the kit.

[0073] Polynucleotides may be prepared using any of a variety of techniques known in the art. The polynucleotide sequences selected as probes (and bind to the biomarkers of interest) should be sufficiently long and sufficiently unambiguous that false positives are minimized. The polynucleotide is preferably labeled such that it can be detected upon hybridization to DNA and/or RNA in the assay being screened. Methods of labeling are well known in the art, and include the use of radiolabels, such as 32P-labeled ATP, biotinylation, fluorescent groups or enzyme labeling. Hybridization conditions, including moderate stringency and high stringency, are well known in the art

[0074] Polynucleotide variants may generally be prepared by any method known in the art, including chemical synthesis by, for example, solid phase phosphoramidite chemical synthesis. Modifications in a polynucleotide sequence may also be introduced using standard mutagenesis techniques, such as oligonucleotide-directed site-specific mutagenesis. Alternatively, RNA molecules may be generated by in vitro or in vivo. Certain portions may be used to prepare an encoded polypeptide.

[0075] Any polynucleotide may be further modified to increase stability in vivo and/or in vitro for improved activity and/or storage. Possible modifications include, but are not limited to, the addition of flanking sequences at the 5' and/or 3' ends; the use of phosphorothioate or 2' 0-methyl rather than phosphodiesterase linkages in the backbone; and/or the inclusion of nontraditional bases such as inosine, queosine and wybutosine, as well as acetyl- methyl-, thio- and other modified forms of adenine, cytidine, guanine, thymine and uridine. [0076] Polynucleotides and/or antibodies specific to biomarkers of interest can be conjugated to detectable markers to a second molecule. Suitable detectable markers include, but are not limited to, a radioisotope, a fluorescent compound, a biolurninescent compound,

chemiluminescent compound, a metal chelator or an enzyme. A second molecule for conjugation can be selected in accordance with the intended use. For example, for therapeutic use, the second molecule can be a toxin or therapeutic agent. Further, bi-specific antibodies specific for two or more biomarkers may be generated using methods generally known in the art. Homodimeric antibodies may also be generated by cross-linking techniques known in the art

EXAMPLES

[0077] The following examples help explain some concepts of the current invention.

However, the general concepts of the current invention are not limited to the particular examples.

[0078] Example 1: Acute Appendicitis: Transcript Profiling of Blood Identifies Promising

Biomarkers and Potential Underlying Processes

[0079] Materials and Methods

[0080] Subjects.

[0081] Ethics statement: The protocol of this observational study was approved by the

Institutional Review Board of The George Washington University, and all subjects gave informed consent. From a cohort of 270 patients presenting to the ED for various reasons, a subset of 40 subjects with a principal complaint of abdominal pain, and who met inclusion/exclusion criteria, were identified, and divided into a discovery set of 20 patients, and a validation set of 20 patients for transcript profiling of whole blood RNA by microarray.

[0082] Discovery Set: For the discovery set, we employed 20 subjects who presented to the

ED who were undergoing CT scanning. In order to meet criteria, the patient undergoing the CT scan must have had appendicitis suspected in the differential diagnosis. Appendicitis Patients'.

Patients with appendicitis were diagnosed by CT scanning (n-11), and had research blood samples drawn by venipuncture after anesthetic induction, but prior to skin incision for appendectomy. All cases of appendicitis were confirmed by intra-operative findings and pathology of the removed appendix. Control Patients: Patients included in the control arm (n=9) were patients who were found not to have appendicitis, by both CT scanning and clinical follow-up. This included patients with reported abdominal pain, later found to be caused by diverticulitis, or other gastrointestinal pathologies, but not clinically associated with appendicitis. Blood was drawn at study enrollment for these patients.

[0083] Validation Set: Control Patients. Because appendicitis can involve infection, we enrolled 5 patients with lower respiratory tract infections (LRI) in the ED as an 'infection' control. Also, as a control for surgical factors, we enrolled S patients undergoing elective ventral hernia or inguinal hernia repair (HER), and these were compared with 10 new patients with surgically confirmed appendicitis (APP). In all surgical patients, including appendicitis and hernia repairs, research blood samples were drawn by venipuncture after anesthetic induction, and prior to skin incision. Two patients, (1 HER, 1 APP) were excluded due to technical complications in RNA purification or micro array analysis.

[0084] Blood samples.

[0085] Blood was drawn in 3.2% sodium citrate tubes for frozen plasma samples, in Tempus

Blood RNA tubes (ABI) for genome-wide RNA profiling, and in BD Vacutainer K2 tubes for complete blood counts with differentials.

[0086] RNA purification for transcript profiling.

[0087] Tempus Blood RNA preservation tubes were stored at -80 ^* C and then thawed at 37'

C prior to processing according to manufacturer's methods. Total RNA was purified from whole blood using Tempus Blood RNA kit (ABI), followed by an aggressive DNAse treatment Briefly, the preserved whole blood was pelleted at 3000 x g for 30 minutes in a 4°C refrigerated centrifuge, redissolved in lysis buffer and nucleic acids were bound to a column. After washing, nucleic acids were eluted with RNAse/DNAse free water and quantified by with NanoDrop ND-1000

spectrophotometer. DNA was eliminated by aggressive DNAse treatment (TurboDNAse, Ambion) at 2 U/10 μg nucleic acids, followed by affinity removal of the DNAse. The remaining RNA was quantified and RNA integrity was evaluated by 260/280 ratio on ND-1000 and by capillary electrophoresis on a Bioanalyzer 2100 (Agilent). RIN scores >7 were considered acceptable for further sample processing and did not differ between groups.

[0088] Microarray Expression Profiling and Analysis.

[0089] Purified RNA (100 ng) was labeled with the Illumina cRNA synthesis kit and hybridized to Illumina Human HT-12v4 Expression BeadChip arrays

h\ttp:/www.illumina.com/products/humanht 12 expression beadchip kits v4.html) containing more man 47,000 probes derived from the NCBI RefSeq release 38

(http://www.ncbi.nlm.nih.gov/Tefseq/). The arrays were washed and then fluorescence was quantitated on an Illumina Hi Scan (http ://www. illurnina.com/systems/hiscan .html).

(0090] The fluorescence levels per bead were converted to transcript levels using IUumina

GeneStudio, which averaged typically 30 beads per transcript to produce a mean expression level for each of the 46K transcripts. Raw BeadChip fluorescence values were imported into GeneSpring GX12.S with normalization to the 75'percentile of expression, but without baseline transformation. The main effect of identifying differentially expressed genes (DEG) with respect to appendicitis versus controls was achieved by a combined filter for a p value <0.05 on t test without correction for multiple testing, and 2) fold change > 2.0. The DEG list was further analyzed for gene ontologies using DAVID [17]. Using the DEG list, a partial least squares discriminant (PLSD) prediction model was built in GeneSpring and internally validated with a Leave One Out Cross Validation (LOOCV) algorithm. The PLSD model was externally tested by applying the algorithm to a separate validation set of microarray samples not involved in building the model.

[0091] The PLSD model described here can be replicated by one of ordinary skill in the art by entering the PLSD loading weights for the genes disclosed in Tables 2 and 3 (below) into a suitable statistical package; in the instant invention, GeneSpring GX13 (Agilent) was used

(http://www.genomics.agilent.con/en/product.jsp?cid=AG-PT -130&tabld=AG-PR-

1061&_requestid=163669). Tables 5A and 5B below summarizes the loading weights for the genes of Table 2 and Table 3. [0092) Results

[0093] Clinical Parameters.

[0094] As shown in Table 1 , the clinical parameters between patients presenting with appendicitis versus other abdominal indications in the discovery set were generally similar. Age, gender, and body mass index (BMI) were comparable, although the appendicitis patients were principally of Caucasian race. Notably, white blood cell (WBC) counts were comparable, but appendicitis patients had 10% higher neutrophil count that was not statistically significant (77.18% vs 70%, NS). Appendicitis patients had significantly lower blood creatinine level (0.78 vs 1.54 mg/dJL, p=0.03 uncorrected). The two groups did not yield significantly different RNA quantities from blood, and the amplification of RNA for microarray labeling was similar.

[0095] Table 1 : Clinical Parameters of Discovery Set

* indicates p<0.05 (uncorrected probability)

% indicates the percent of patients exhibiting that trait, unless otherwise indicated

[0096] Identification of RNA biomarkers for appendicitis in whole blood.

[0097] A scatterplot of the expression patterns in the 2 groups (Figure 1) suggested that there was excellent linearity of quantitation over roughly 7 log2 orders of magnitude, with globins being the most highly and identically expressed transcripts between groups. By comparing the expression profiles of the two groups, and filtering for both a /-test probability <0.05 and a fold- change of >2.0, 37 transcripts were identified as significantly differentially expressed (Table 2, above). Hierarchical clustering of the 37 DEG was conducted to observe the pattern of covariance of the transcripts in these patients. A heatmap of the expression of these 37 transcripts across all 20 patients in the discovery set is shown in Figure 2.

[0098] Figure 1 shows a scatterplot of transcript levels in patients with appendicitis. In

Figure 1, whole blood RNA from patients with acute, surgically confirmed appendicitis (n=l 1) or abdominal pain (n=9) was profiled for the expression level of 45,966 transcripts on Illumina BeadChip Arrays (12v4). The expression level of each transcript was averaged within groups and plotted on a log2 scale to reveal transcripts which differ between more than 2-fold between groups (outside parallel lines).

[0099] Figure 2 shows hierarchical clustering of 37 differentially expressed genes in appendicitis patients. In Figure 6, transcripts which differed between groups by >2-fold with a t-test probability of <0.05 (uncorrected) were identified by combined filtering. Following a per-gene normalization, DEGs were subjected to hierarchical clustering to identify patterns of covariance among the transcripts. The upper block of transcripts from HLA-DRBS to CA4 are relatively higher in APP patients (red) compared to patients with other types of abdominal pain (yellow to blue). Conversely, transcripts from defensins (DEFA) and ribosomal transcripts, were relatively lower in APP than abdominal pain patients.

[00100] Table 2: Differentially expressed genes (DEO) sorted by functional grouping

[00101] Table 3 : A sixteen transcript set predictive of appendicitis

[00102] Certain aspects of this expression pattern increase the confidence that some of these changes are non-random: 1) multiple probe sets identifying the same transcript (DEFA1), 2) 'hits' on highly related transcripts such as DEFA1 and DEFA3, as well as CXCR1 (aka IL8 receptor a) and IL8 receptor β.

[00103] Table 4: DEG gene symbols and Oenbank IDs

[00104] Table 5A: PLSD loading weights for genes from Table 2:

[00105] Table 5B: PLSD loading weights for genes from Table 3 :

(00106] Functional analysis of DEG transcripts.

[00107] Of the well annotated transcripts, several had prior published relationships to infection, immunity, or inflammation, or stress/injury: notably, alkaline phosphatase

liver/bone/kidney isoform (ALPL), carbonic anhydrase IV (CA4), chemokine (C-X-C motif) receptor 1 (CXCR1), defensin al (DEFAl), defensin α3 (DEFA3), IgG Fc receptor lib

(FCGR3B/CD16B), interleukin 8 receptor β (EL8RB), ninjurin 1, (NINJ1), prokinectin 2 (PROK2), and superoxide dismutase 2 (SOD2). In addition to their logical connection to appendicitis, which often has an infectious etiology, certain aspects of this expression pattern increase the confidence that some of these changes are non-random: 1) multiple probe sets identifying the same transcript (DEFA1), 2) 'hits' on highly related transcripts, such as DEFA1 and DEFA3, as well as CXCR1 (aka IL8 receptor β) and IL8 receptor fi.

[00108] Defeasing. To understand the defensin pathway, the 5 a-defensin transcripts in the DEG list, which are all variant transcripts from the DEFA locus at 8p21.3, were averaged to create a 'defensin score', and then compared between groups (Table 1). Using a threshold determined by the mean of all 20 patients (1.87), 6 of 9 (67%) patients with other abdominal disorders showed elevated defensins, while only 1 of 11 (9%) of appendicitis patients had elevated defensin mRNA (see defensin cluster in Figure 2). Surprisingly, the defensin score was essentially uncorrelated with white blood cell count (WBC) (r = 0.07) and neutrophil % (r = 0.15).

[00109] Other immune/inflammatory pathways. Interestingly, 3 of the 37 DEG (LILRA3, CXCRML8RA, FCGR3A), which were higher in appendicitis patients compared to abdominal pain patients, are near or exact matches to transcripts discovered previously as down-regulated by exposure of isolated human neutrophils to R Coli [18]. However, across the 20 patients, they were not inversely correlated with defensin expression (LILRA=0.02, CXCR1=-0.02, FCGR3A=-0.33), suggesting they are regulated independently of infectious markers. Other transcripts were readily associated with tissue injury or inflammation, but not previously associated with pathogen infection. For instance, NINJ1 was identified as a transcript strongly upregulated after peripheral nerve injury [19]. PROK2 is elevated in colitis tissue [20], which, like appendicitis, is an inflammatory condition in the GI tract. Likewise, ALPL has a well-known role in modulating diverse inflammatory conditions not limited to infectious disease [21].

[00110] Ribosomal transcripts. While it is widely assumed that ribosomal RNAs (rRNA), such as 18S and 28S non-coding RNAs are 'invariant', or 'housekeeping' transcripts, there is considerable evidence that they are carefully regulated in cases such as granulocyte activation [22], and differ significantly in prostate cancer [23], and in hepatitis C infected livers [24]. hi fact, early studies with PHA-activated human lymphocytes demonstrated as much as 8-fold increases in rRNA levels within 20 hours [25,26]. Furthermore, if the observed changes were due to some type of loading or processing anomaly, then we would expect all of the ribosomal RNAs to be affected in the same direction, when in feet, 18S and 28S noncoding transcripts were increased in appendicitis, but most of the transcripts coding for ribosomal proteins were decreased, suggesting that this is a regulated process.

(00111} Minimally annotated transcripts. Of the 37 DEO, 11 transcripts were minimally annotated, i.e. 'predicted transcript', but further manual annotation using NCBI Gene revealed high likelihood assignments. Remarkably, 8 of the 11 transcripts were identified as ribosomal protein pseudogenes, which is quite unlikely to have occurred by chance. Two transcripts have been discontinued, and the eleventh was identified as CYSTM1 (C50RF32), which is a cysteine-rich transmembrane module-containing protein that 2-hybrid screens identified as an inhibitor of the glucagon- like peptide 1 receptor (GLP-1R) [27].

(00112] Prediction of appendicitis from DEG.

(00113] The PLSD model built on the 37 DEG list, was 100% accurate and specific within the discovery set, which is not surprising given the ability of PLSD models to accurately 'fit ^* data to outcomes. As shown in Figure 3, the first 3 latent factors in the PLSD model demonstrate tight clustering of the appendicitis patients (▲) distinct from patients presenting with other abdominal pain (■). Clearly, 7 of 9 abdominal patients can be discriminated by only the first latent factor (tO, X-axis). Two abdominal patients, one with a GI bleed and one with diverticulitis, are poorly discriminated by the tO latent factor shown in the X-axis, but are readily discriminated by one of the two other factors (Y or Z axis). To determine whether all 37 transcripts were necessary for prediction, 16 transcripts with a loading of X).2 in the PLSD model were used to rebuild a new PLSD prediction model (Table 3, above). This smaller model, which omitted the defensins, remained quite strong, predicting 100% of abdominal cases, 90.9% of appendicitis cases, for an overall accuracy of 95%.

[00114] Based on these data, a highly predictive model can be generated by observing expression level patterns utilizing as few as 3 RNA transcripts. Of course the more levels that are measured, the more sensitive and predictive the patterns become. Accordingly, the present invention can use the pattern generated from 3 or more RNA transcripts, 4 or more RNA transcripts,

5 or more RNA transcripts, 6 or more RNA transcripts, 7 or more RNA transcripts, 8 or more RNA transcripts, 9 or more RNA transcripts, 10 or more RNA transcripts, 12 or more RNA transcripts, 14 or more RNA transcripts, or 16 or more RNA transcripts. The only minimum is that the number and selection of transcripts define a pattern that distinguishes appendicitis from other causes of abdominal pain. In embodiments, the method is at least 75% accurate, for example at least 80% accurate, at least 90% accurate, or at least 95% accurate.

[001 IS] Figure 3 shows a graph displaying the Partial Least Squares Discriminant (PLSD) Model for classification of appendicitis from RNA biomarkers. In Figure 3, DEGs were analyzed by PLSD to compose a classification model for appendicitis based on RNA biomarkers in blood. The 3D plot shows the 20 patients in the discovery set as partitioned by the first 3 of 4 latent factors in the PLSD model. The■ represent abdominal pain patients (n=9), and A shows the cluster of appendicitis patients (n=l 1), as a function of the tO latent factor (X-axis), the tl factor (Y-axis), and the t2 factor (Z-axis). The majority of patients (7/9) are accurately classified by the tO component alone.

[00116] Validation of PLSD prediction model in unrelated samples.

[00117] To determine the robustness of the prediction model, a separate group of patients derived from the same overall cohort were similarly processed for whole blood RNA, and hybridized independently to Ulumina HT 12v4 Beadchip arrays. With only minimal normalization to correct for minor loading and hybridization differences, the PLSD prediction model was applied to the normalized values for the 37 transcripts in the model. The PLSD prediction model correctly identified 8 of 9 true appendicitis patients (88.9%) and predicted 3 of 4 patients (75%) with hernias as being 'abdominal pain'. Nearly 90% sensitivity in an unrelated cohort quantified on a different microarray run is encouraging toward the potential robustness of the model. Notably, the PLSD model includes no clinical variables, such as fever or white cell count

[00118] Behavior of the RNA biomarkers in non-appendicitis infections.

[00119] In 5 patients clinically diagnosed with LRI, which were not included in PLSD training, the model predicts 4 of 5 as appendicitis (80%), suggesting that the model may be sensitive to generalized infectious or inflammatory signals in blood. Using the 16 DEG model, only 60% were diagnosed as appendicitis. As shown in Figure 5, some transcripts, such as FCGR3 and NINJ1, were relatively selectively elevated in APP, but not LRI. Other transcripts, especially defensins, were much more sensitive to LRI than APP, showing 4-5 fold elevations in LRI versus HER, and 20-fold elevations in LRI vs APP. Most transcripts, as demonstrated by IL8RJJ, LILRA3, and ALPL, showed roughly similar changes in LRI and APP. Of the 37 transcripts, 10 are relatively selective for APP, 8 are selective for LRI, and 19 behave similarly in both APP and LRI.

[00120] Figure 5 shows graphs displaying the behavior of DEG biomarkers in a validation cohort In Figure S, the 37 DEG biomarker set was applied to transcript expression levels in unrelated patients presenting at the ER for either appendicitis (APP, green bars), lower respiratory infection (LRI, red bars), or hernias (HER, blue bars). Representative transcripts, such as Fc gamma receptor 3 (FCGR3) and ninjurin 1 (NDMJ1) are shown, in which the transcript behaves with relatively selective induction in APP, relative to HER or LRI. Conversely, transcripts in the defensin family (DEFA1, DEFA3), are significantly elevated in HER patients, relative to APP, but are strikingly induced in LRI patients. Most transcripts, such as alkaline phosphatase (ALPL) and the IL8 receptors (IL8RB, CXCR1), were induced in both APP and LRI patients.

[00121] DISCUSSION

[00122] Currently, there are no FDA-approved serum or urine biomarkers for abdominal pain or appendicitis. As noted earlier, abdominal pain is one of the most common complaints in the ED, and thus blood biomarkers represent an important unmet need in clinical medicine. In this discovery and validation study, we have identified a small set of RNA transcripts associated with appendicitis. Overall, a prediction model built on these markers was able to differentiate

appendicitis from other forms of intra-abdominal pathology, such as diverticulitis and hernias. Appendicitis is thought to be an inflammatory disease, similar to diverticulitis or colitis; however, there was differing activation of certain mRNA biomarkers between these conditions. Furthermore, the 37 DEG markers do not correlate with white blood cell count, per se, but a careful examination of the transcripts suggests that the RNA biomarkers may be measuring the activation state of immune cells, especially neutrophils.

[00123] The pattern of transcriptome changes in blood may help to refine our understanding of the etiology and progression of acute appendicitis as shown schematically in Figure 9. The classic explanation for appendicitis is that a fecalith or lymphoid hyperplasia block the outflow of the appendix, resulting in obstruction and ischemia [28]. Outflow obstruction may produce local changes that favor undesirable changes in the appendix microbiome. Several recent studies, including next-generation sequencing (NGS) of the 16S regions of the microbiome, have suggested that relatively selective changes in fiisobacteria species are associated with appendicitis [29-32]. Fusobacteria, a type of gram-negative bacteria, can induce toxicity in adjacent host cells, and colitis-like symptoms in mice, potentially by producing butyric acid (butyrate) [33]. RT-PCR analysis confirms that inflamed appendix tissue has elevated a-defensin and IL-8 mRNA levels [34]. Likewise, fiisobacterium mtcleatum biofUms stimulate IL-8 production in human oral epithelium cell lines [35] and fusobacterium necrophortm induces IL-8 production in cultured mesothelial cells [36].

[00124] Figure 6 shows a schematic of a model of appendicitis biomarker pathophysiology. It is believed that compacted fecal bodies, termed fecaliths, may occlude the outflow tract of the appendix, causing inflammatory conditions that are conducive to infection in the appendix.

Microbiome analysis of inflamed appendices typically indicates a predominance of biofilm-foiming bacteria, such as fiisobacteria. The biofilm protects the bacteria from antibiotics, and from direct immune attack, but soluble factors produced by the bacteria, such as LPS (endotoxins) and butyrate, or IL-8, can diffuse into adjacent lymphatic and circulatory beds to activate neutrophils. The primed neutrophils respond with elevated transcript levels of alkaline phosphatase (ALPL), interleukin-8 receptor beta (IL8RB) and related biomarkers of local infection. Background images of appendix and neutrophil courtesy ofBlausen.com staff, Wifaversity Journal of Medicine.

[00125] Thus, the absence of elevated a-defensin transcripts in the presence of elevated levels of mRNA for both IL-8 receptors suggests that circulating immune cells are primed by IL-8 produced in the inflamed appendix. However, it seems likely that the immune cells are not directly contacting the bacterial infection, which would elevate defensins, as demonstrated clearly in the LRI patients.

[00126] In addition to the IL-8 receptors, several other transcripts appear to be plausible biomarkers of localized inflammation. Notably, ALPL, along with IL8RB/CXCR2, was identified as an expression biomarker of asthma inflammatory subtypes [37]. In addition to these interesting innate immune markers, the results revealed unexpected changes in the ribosomal system. Humans utilize 4 ribosomal RNAs, which are non-coding (5S, 5.8S, 18S, 28S), and -80 ribosomal proteins to build multimeric translation complexes. Additionally, there are ~2000 ribosomal protein pseudogenes, which are thought to derive from inactivated duplications, but may be processed to varying degrees, and could have regulatory functions [38]. Transcripts for 18S and 28S, both originating from multiple 45S genes, were increased in the appendicitis blood RNA, which could be due to both increased transcription from active rDNA genes [39], as well engagement of previously inactive rDNA transcription units [26]. Conversely, most of the coding transcripts, such as RPLP1 and RPS26, were decreased in the blood of appendicitis patients. Because the specific pattern of ribosomal proteins defines the type of RNAs that are engaged and translated [40], it is possible that the translational machinery is being re-geared to adapt to a new demand. Unexpectedly, most of the poorly annotated transcripts mapped to ribosomal protein pseudogenes, suggesting that either the probesets are incorrectly detecting a change in coding ribosomal protein transcripts, or the pseudogenes are somehow regulated in conjunction with the reconfigured translational machinery. Conceptually, the pattern of chemokine, defensin, stress-related, and ribosomal processing changes is consistent with the immune system being 'primed' as the immune cells pass through an inflammatory field created by a localized biofilm infection.

[00127] Other investigators have sought to develop protein biomarkers for appendicitis in the blood, such as bilirubin [41], C-reactive protein (CRP) [42], and pro-calcitonin (PCT) [43].

However, recent comparisons of these biomarkers had difficulty improving on a purely clinical prediction model, such as the Alvarado score (ROC=0.74, vs CRP=0.61, PCT=0.69) [44].

Recently, a combination of WBC, CRP, and MRP8/14 (S100A8/S100A9) was shown to be 96% sensitive, but 43% specific for acute appendicitis [42]. Likewise, a multivariate model built on plasma protein levels of serum amyloid (SAA), myeloperoxidase (MPO), and MMP9 was less diagnostic than a largely clinical model (ROC = 0.71 vs 0.91 clinical model) [45].

[00128] While RNA-based diagnostic tests are currently on the market for breast cancer progression (MammaPrint, OncoType Dx), transplant rejection (AlloMap), and coronary artery disease (CorusCAD), this is the first report to assess blood RNA as a potential biomarker of appendicitis. Among the strengths of the present approach is that the test and validation sets included controls for surgical, inflammatory, and infectious factors. Further, the RNA profiling was broad and largely unbiased, and detected the same key pathways in the test and validation study.

[00129] Genome-wide RNA transcript profiling is thus demonstrated as being capable of identifying biomarkers of appendicitis. The detected biomarkers are consistent with prior published evidence that fusobacteria biofilms in the appendix may be an important putative mechanism in appendicitis.

[00130] By assaying the RNA levels by microarray analysis, alternative methods of assaying RNA levels can be applied in the steps of this invention. Examples of alternative methods including are real-time RT-PCR, real-time PCR, quantitative RT-PCR, qPCR, RT-PCR array, RNA

sequencing (RNA-Seq), northern blot, and serial analysis of gene expression (SAGE), measuring protein expression.

[00131] Patterns of RNA levels define biomarkers that identify appendicitis. Differential expression of RNA levels of a gene often coincide with differential expression levels of the resultant proteins translated from the RNA. For this reason, measuring the protein expression level patterns that correlate to the identified differentially expressed genes is an alternative method of diagnosing appendicitis. Protein expression levels can be measured from serum samples by a number of means including western blot, enzyme-linked immunosorbent assay (ELISA), mass spectrometry, and other means mat utilize antibody detection of proteins. Similar methods of testing as described for the RNA biomarkers can be used by replacing RNA measurement with protein measurement and determining suitable patterns. According to his embodiment, measuring the protein expression level patterns will diagnose appendicitis. In some embodiments, antibodies against specific proteins can be generated and used to measure protein expression levels.

[00132] References for Background and Example 1:

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34. Arlt A, Bharti R, lives I, Hasler R, Miettinen P, et al. (2013) Characteristic changes in microbial community composition and expression of innate immune genes in acute appendicitis. Innate Immun.

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41. D'Souza N, Karim D, Sunthareswaran R (2013) Bilirubin; a diagnostic marker for appendicitis. Int J Surg ll: 1114-1117.

42. Huckins DS, Simon HK, Copeland K, Spiro DM, Gogain J, et al. (2013) A novel biomarker panel to rule out acute appendicitis in pediatric patients with abdominal pain. Am J Emerg Med 31: 1368-1375.

43. Kaya B, Sana B, Eris C, Karabulut K, Bat O, et al. (2012) The diagnostic value of D-dimer, procalcitonin and CRP in acute appendicitis. Int J Med Sci 9: 909-915.

44. Wu JY, Chen HC, Lee SH, Chan RC, Lee CC, et al. (2012) Diagnostic role of procalcitonin in patients with suspected appendicitis. World J Surg 36: 1744-1749.

45. Andersson M, Ruber M, Ekerfelt C, Hallgren HB, Olaison G, et al. (2014) Can new inflammatory markers improve the diagnosis of acute appendicitis? World J Surg 38: 2777-2783. [00133] Example 2: Confirmation of microarray results

[00134] Quantitative Real Time Polymerase Chain Reaction (Q-RTPCR) was sued to confirm the microarray results from Example 1. Figure 7 shows Q-RTPCR results for 3 genes: ALPL, DEFA1/3 and IL8RB. As seen in Figure 7, results obtained from Q-RTPCR parallel the results obtained from the microarray assays.

[00135] Methods

[00136] 1) RN A purification:

[00137] 1.1) For validation studies, the RNA purified for microarray analysis was used. In new samples, or other embodiments, the sample of blood must be collected in an appropriate RNA stabilizer. In the present studies, Tempus tubes were used. Other stabilizers could be used, but it is possible that the specific transcripts levels of expression or their magnitude, could be different depending upon the RNA Blood tubes used and their RNA stabilizers. From the Tempus tubes, the manufacturer's instruction and reagents for column purification of RNA was used. However, technically, both DNA and RNA are purified.

[00138] 2) DNAse treatment:

[00139] 2.1) To remove the DNA, which will contuse the quantitation of RNA, the sample is treated with Turbo DNA-Free™ Kit (ThermoFisher Sci, Cat. No AMI 907). We used up to 5 ug total RNA/DNA treated with 2 units/uL of TurboDNAse for 30 min at 37°C. The inactivation of DNAse was performed using the "Inactivation Reagent" (IR) provided in the kit at 0.2 X volume of the total reaction, typically 20 uL of IR for 100 uL of DNase treatment. The IR contains an affinity capture reagent recognizing the TurboDNAse, thereby removing it from solution, and eluting relatively pure RNA. A variety of DNAse removal strategies are well known to anyone skilled in the art. In particular, it is common to heat-inactivate the DNAse. While probably acceptable, it has not been specifically tested, and we cannot exclude the possibility that this would be a source of variation (SOV). [00140] 2.2) The DNase treated RNA is further purified in Qiagen RNAeasy MiniElute kit (Qiagen, Cat No. 74204) on columns The RNA quantity is assessed by absorbance at 260 run (NanoDrop) and the quality is assessed by the ratio of absorbance at 260 run (RNA) to 280 nm (protein). A ratio (260/280) greater than 1.8 is desirable if measured in water, and greater than 2.0 if measured in water buffered with Tris/EDTA (TE).

[00141] 3) Complementary DNA (cDNA) Synthesis:

[00142] 3.1) The purified RNA was converted to cDNA using reverse transcriptase (RT) contained in the iScript cDNA Synthesis kit from Bio-Rad Laboratories (Cat. No. 170-8891). There are published reasons to believe that the type of RT enzyme could affect the efficiency of cDNA synthesis, and therefore, the measured levels of specific transcripts by qRT-PCR. In particular, the presence or absence of the RNAse H activity in the RT enzyme might be a relevant SOV. The iScript cDNA kit reverse transcriptase contains RNase H enzymes for degradation of RNA template in the amplification process.

[00143] 4) PCR Probe selection:

[00144] 4.1) Sense and antisense probes for PCR were selected using the cDNA sequences extracted from Genbank accession numbers disclosed in Table 1. The cDNA sequences were analyzed by Geneious software to identify primers with matching melting temperatures (Tm) of 60°C under standard RT-PCR conditions. The primers identified and used are shown in Table 1.

[00145] 4.2) In this example, 6 transcripts were targeted for qRT-PCR quantitation. Four of these transcripts (ALPL, DEFA1, DEFA3, IL8RB) were selected from the 16g and 37g lists of DEGs that are diagnostic of appendicitis. Two other transcripts, ACTB and SpiB, were used as transcripts which should not vary according to appendicitis status, and thus are considered 'invariant' for this example.

[00146] 4.3) For each transcript-specific reaction, additional samples are prepared in which the pooled control cDNA (Con) is used at higher, and lower quantities, typically in 10-fold steps, to create a standard dose-response curve for each primer pair. This curve confirms mat the qPCR is able to detect higher and lower transcript levels, and is used to convert the Ct to a relative abundance measure as described below.

[00147] 5) qRT-PCR conditions:

[00148] 5.1) A standard amount of cDNA (0.20-0.25 ng) from the patient samples, or a pooled control sample (Con), was combined with a fixed amount of the transcript-specific primer pairs (1.25 uM) and a master mix SSOAdvanced™ Universal SYBR® Green Supermix (Bio-Rad, Cat. No.: 172-5274) containing a mix of antibody-mediated hot-start Sso7d fusion polymerase, dNTPs, MgC12, enhancers, stabilizers, a blend of passive reference dyes (including ROX and fluorescein) and SYBR Green fluorescent dye, which reports the level of PCR amplimer that is present after each amplification cycle. There are numerous acceptable ways to quantitate PCR amplimer levels, including, but not limited to, SYBR Green, EVA green, and fluorescently-labeled internal probes commonly referred to TaqMan probes. Another envisioned embodiment of the invention would be to quantitate the transcript levels using droplet digital PCR (ddPCR, BioRad) or hybrid-based transcript counting methods, such as Nanostring.

[00149] In this example, we employed the BioRad SSOAdvanced kit reagents. Each transcript-specific primer pair and sample, cDNA was analyzed in a separate well of a 384- well plate in duplicate for each primer pair. Thus, for a given patient sample, 12 qPCR reactions were performed (6 primer pairs, each in duplicate). The mixture containing probes, cDNA sample, and PCR reagents, including fluorescent dye, in a final volume of 14 ul, were loaded using the automatic liquid handler (Eppendorf, epMotion® 5770) subjected to thermocycling as described below.

[00150] 5.2) The mixture of these reagents was incubated in a BioRad CFX384™ Real-Time System with CI 000™ thermocycler using a temperature program of: 2 min at 98 ^Q C, followed by 45 amplification cycles of 5 sec at 98°C, and 10 sec @ 60°C, finalized with 10 sec @ 75°C and 4 sec @ 95°C dissociation stage. After each cycle, the level of fluorescence of the SYBR Green dye bound to dsDNA amplimers was quantified by stimulation with appropriate filters for excitation and emission. The reaction was cycled 40 times and then held at 4°C after the last cycle. [00151] 6) Data analysis:

[00152] 6.1) The real-time quantitative PCR instruments measure fluorescence generated by the amplimer/dye complex after each cycle of amplification. Because the amounts of primers and free nucleic acids are limiting, these reaction reach a saturated maximum of fluorescence typically prior to 40 cycles of amplification. The number of cycles observed to reach naif-maximal fluorescent intensity is said to be a Cycle Threshold (Ct) of Cycle Quantity (Cq) which is inversely correlated to the amount of transcript cDNA in the reaction. Thus, the higher the level of target cDNA present, the fewer cycles will be needed to reach a given Ct. In practice, there are numerous acceptable methods to stipulate the Ct based on the fluorescence curve, and as long as the Ct is applied uniformly to the samples in each transcript-specific reaction, including the Con samples, then the results should be informative for the present purposes.

[00153] 6.2) The Ct values for each reaction are converted to a relative abundance (RA) of the transcript by interpolation to the standard curve for each primer pair. That RA level per duplicate PCR tube is then averaged for the 2 duplicates, and then adjusted by the abundance of the 'invariant' transcript levels. A very large number of invariant transcripts would be acceptable, and some that are commonly used by those skilled in the art include: glyceraldehyde 3 -phosphate dehydrogenase (GAPDH), B-actin (ACTB), hypozanthine phosphoribosyltransferase 1 (HPRT), and 18S ribosomal RNA. In the present invention, it was empirically determined that ACTB provided efficient normalization, but the invention is not constrained by the method of normalization.

[00154] 6.3) The RA levels of the 4 diagnostic transcripts were combined in the following way to predict the outcome of appendicitis:

[00155] 6.3.1) To account for arbitrary nature of RA value, it was normalized to a percentile of the mean value in the entire run of 36 samples, yielding a %RA value, where 1.00 would be equal to the mean value of mat transcript target.

[00156] 6.3.2) Using the %RA value, the diagnostic goal is to determine whether the ALPL and IL8RB levels are increased disproportionately to the DEFA1 levels. In principle, DEFA3 levels could be used, or a combination of DEFA1 and DEFA3 levels, but for simplicity DEFA1 levels were found to be adequate. Thus, the ratio of %RA of ALPL (%ALPL) to %RA of DEFA1 (%DEFA1), and the ratio of %RA of IL8RB (%IL8RB) to %DEFA1 were computed to yield %ALPL/%DEFA1 and %IL8RB/%DEFA1. Those two values were averaged to compute the App Score. In this series of 36 patient samples, the App Score had a range of 0.04-44.7.

[00157] Thus, to summarize,

[00158] App Score = [(%ALPL/%DEFA1) + (%lL8RB/%DEFAl)]/2

[00159] Another construction is App Score = [(%ALPL + %IL8RB)/2]/%DEFAl

[00160] 6.3.3) On both logical grounds, and empirical observation, if the App Score is >1 then the normalized ALPL and IL8RB levels are higher than DEFA1 levels and this is taken as diagnostic of an increased likelihood of appendicitis. In actual practice, there would be numerous mathematical and technical means to arrive at a similar assessment of the relative levels of these predictive transcripts identified in the 16g or 37g lists.

[00161] 6.3.4) To test the diagnostic ability of the App Score, it was converted to a scale of 1-10 which is a common metric range used in the Receiver-Operator Characteristic (ROC) statistic. The conversion from App Score to App Level (1-10) was achieved with the following conversion table:

[00162] Table 6: Conversion Table for converting App Score to App Level

[00163] As discussed above, a predictive test was built taking the data from Figure 10. A very simple way to predict Appendicitis (Appy) using only 3 gene transcripts (IL8RB, DEFA1, ALPL) and one control transcript (Actin) was developed. Figure 8 shows a graph of the ROC curve with sensitivity and specificity. In practice, the test gives a score from 1 to 10, where 5-6 is about a 50% risk of Appy, and a score above 7 indicates likely Appy.

[00164] The true presence or absence of appendicitis was known from clinical analysis and was scored as a binary variable where 0=absent, l=appendicitis. Five of the 36 patients were excluded from analysis because they had a clinical diagnoses of lower respiratory infection, which is unrelated to the present invention. An App Score >1, which is an App Level of 6 or greater, was used as a threshold for predicted appendicitis. The predicted outcome (App Level) and the true outcome were used to compute a 'confusion table' and an ROC curve by the method of John Eng: (JROCFIT: Johns Hopkins University, Baltimore, MD Version 1.0.2, March 2004. URL:

http:/www.rad.jhmi.edu/jeg/janvarad/roc/JRCFITi.html).

[00165] The results are shown in Figure 8, and indicate that overall the accuracy was 80.6%, with 94.4% sensitivity in detecting clinically diagnosed appendicitis.

[00166] The embodiments illustrated and discussed in this specification are intended only to teach those skilled in the art how to make and use the invention. In describing embodiments of the invention, specific terminology is employed for the sake of clarity. However, the invention is not intended to be limited to the specific terminology so selected. The above-described embodiments of the invention may be modified or varied, without departing from the invention, as appreciated by those skilled in the art in light of the above teachings. It is therefore to be understood that, within the scope of the claims and their equivalents, the invention may be practiced otherwise than as specifically described.