Methods for improving inflammatory bowel disease diagnosis

Abstract

The present invention provides methods and systems to predict and diagnose inflammatory bowel disease (IBD) and subtypes such as ulcerative colitis (UC) and Crohn's disease (CD) by detecting the presence, absence, level, and/or genotype of one or more sero-genetic-inflammation markers. Advantageously, with the present invention, it is possible to provide a diagnosis of IBD versus non-IBD, to rule out IBD that is inconclusive for CD and UC, and to differentiate between CD and UC with increased accuracy.

1 . A method for diagnosing inflammatory bowel disease (IBD) and/or a clinical subtype thereof in an individual, said method comprising:
 (a) analyzing a sample obtained from said individual to determine the presence, level or genotype of one or more markers selected from the group consisting of a serological marker, a genetic marker, an inflammation marker, and a combination thereof in said sample to obtain a marker profile;   (b) applying a first random forest statistical analysis to said marker profile to obtain a decision whether said marker profile is an IBD sample or a nonIBD sample;   (c) optionally applying a decision tree or set of rules to said sample designated as an IBD sample to determine if said IBD sample is categorized as an inconclusive sample; and   (d) optionally applying a second random forest statistical analysis to said IBD sample to determine a clinical subtype of IBD.   
     
     
         2 . The method of  claim 1 , wherein said inflammation marker is selected from the group consisting of an acute phase protein, an apolipoprotein, a growth factor, a cellular adhesion molecule, and a combination thereof. 
     
     
         3 . The method of  claim 1 , wherein said serological marker is selected from the group consisting of an anti-neutrophil antibody, an anti- Saccharomyces cerevisiae  antibody, an antimicrobial antibody, and a combination thereof. 
     
     
         4 . The method of  claim 1 , wherein said genetic marker is selected from the group consisting of ATG16L1, ECM1, NKX2-3, STAT3, and a combination thereof. 
     
     
         5 . The method of  claim 3 , wherein said anti-neutrophil antibody is selected from the group consisting of an anti-neutrophil cytoplasmic antibody (ANCA), perinuclear anti-neutrophil cytoplasmic antibody (pANCA), pANCA2 and a combination thereof. 
     
     
         6 . The method of  claim 3 , wherein said anti- Saccharomyces cerevisiae  antibody is selected from the group consisting of anti- Saccharomyces cerevisiae  immunoglobulin A (ASCA-IgA), anti- Saccharomyces cerevisiae  immunoglobulin G (ASCA-IgG), and a combination thereof. 
     
     
         7 . The method of  claim 3 , wherein said antimicrobial antibody is selected from the group consisting of an anti-outer membrane protein C (anti-OmpC) antibody, an anti-flagellin antibody, an anti-I2 antibody, and a combination thereof. 
     
     
         8 . The method of  claim 2 , wherein said acute phase protein is C-reactive protein (CRP). 
     
     
         9 . The method of  claim 2 , wherein said apolipoprotein is serum amyloid A protein (SAA). 
     
     
         10 . The method of  claim 2 , wherein said growth factor is vascular endothelial growth factor (VEGF). 
     
     
         11 . The method of  claim 2 , wherein said cellular adhesion molecule is selected from the group consisting of inter-cellular adhesion molecule 1 (ICAM-1), vascular cellular adhesion molecule 1 (VCAM-1), and a combination thereof. 
     
     
         12 . The method of  claim 1 , wherein said serological marker is selected from the group consisting of pANCA, pANCA2, ANCA, CRP, SAA, VEGF, ICAM-1, VCAM-1, and a combination thereof. 
     
     
         13 . The method of  claim 1 , wherein said serological marker is selected from the group consisting of ASCA-IgA, ASCA-IgG, anti-OmpC antibody, anti-CBir-1 antibody, anti-Fla2 antibody, anti-FlaX antibody, and a combination thereof. 
     
     
         14 . The method of  claim 1 , wherein the presence or level of said serological marker or inflammation marker is detected with a hybridization assay, amplification-based assay, immunoassay, or immunohistochemical assay. 
     
     
         15 . The method of  claim 1 , wherein said genetic marker is at least one of the genes set forth in Tables A-E. 
     
     
         16 . The method of  claim 1 , wherein the genotype of said genetic marker is detected by genotyping for the presence or absence of a single nucleotide polymorphism (SNP) in said genetic marker. 
     
     
         17 . The method of  claim 16 , wherein said SNP is at least one of the SNPs set forth in Tables B-E. 
     
     
         18 . The method of  claim 16 , wherein said genetic marker is selected from the group consisting of ATG16L1, STAT3, NKX2-3, ECM1, and a combination thereof. 
     
     
         19 . The method of  claim 1 , wherein said marker profile is determined by detecting the presence, level or genotype of at least two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, or eighteen markers. 
     
     
         20 . The method of  claim 1 , wherein the markers for the first random forest algorithm are selected from the group consisting of ANCA, ASCA-A, ASCA-G, pANCA, pANCA2, anti-FlaX antibody, SAA, anti-Fla2 antibody, ICAM, anti-OmpC antibody, anti-CBir1 antibody, VCAM, CRP, NKX2-3, ATG16L1, STAT3, ECM1, VEGF and a combination thereof. 
     
     
         21 - 78 . (canceled)