Method for determining the risk of crohn's disease-related complications
View Patent ↗The methods and systems of the present invention are useful in the diagnosis of inflammatory bowel disease (IBD) and in the prognosis of IBD progression and disease complications. With the present invention, it is possible to predict outcome of disease and patients who will have a particular risk of disease complications and/or progression to surgery.
1. A method for determining the risk that an individual diagnosed with Crohn's disease (CD) develops a stricturing or penetrating disease presentation, said method comprising:
(a) detecting in a sample obtained from said individual the presence, absence, or level of a combination of serological markers by immunoassay and the genotype of a combination of genetic markers,
wherein said serological markers comprise anti- Saccharomyces cerevisiae immunoglobulin A (ASCA-IgA), anti- Saccharomyces cerevisiae immunoglobulin G (ASCA-IgG), an anti-outer membrane protein C (anti-OmpC) antibody, an anti-CBir-1 antibody, an anti-I2 antibody, and a perinuclear anti-neutrophil cytoplasmic antibody (pANCA), and
wherein said genetic markers comprise SNP8 (R702W), SNP12 (G908R), and SNP13 (3020InsC) in the NOD2 gene;
(b) applying a quartile analysis to each of said serological markers to obtain a quartile sum score (QSS) for said individual by:
(b1) converting the level of each of said serological markers ASCA-IgA, ASCA-IgG, anti-OmpC antibody, anti-CBir-1 antibody, and anti-I2 antibody into a quartile score for each of said serological markers;
(b2) converting the presence of said serological marker pANCA into a quartile score of 1 and the absence of said serological marker pANCA into a quartile score of 4; and
(b3) summing said quartile scores for each of said serological markers from steps (b1) and (b2) to obtain the QSS;
(c) deriving a logistic regression model by applying logistic regression analysis to a set of parameters determined in a retrospective cohort of patients with a stricturing or penetrating disease presentation, the set of parameters comprising (1) the quartile sum scores obtained from the presence, absence, or level of said serological markers in the retrospective cohort, (2) the presence or absence of a SNP13 (3020InsC) genotype in the NOD2 gene in the retrospective cohort, and (3) the duration of CD in the retrospective cohort wherein said logistic regression model provides a cumulative probability of developing said stricturing or penetrating disease presentation over time;
(d) comparing said QSS and the genotype of said genetic markers for said individual to said logistic regression model; and
(e) determining the risk that said individual develops said stricturing or penetrating disease presentation based on said comparison in step (d),
wherein said individual has a risk of developing said stricturing or penetrating disease presentation at a rate of about 60% or more by the first year after diagnosis of CD when said QSS ranges from 6-24 and said SNP13 (3020InsC) genotype in the NOD2 gene is present.
2. The method of claim 1 , wherein said serological markers further comprise an anti-neutrophil antibody, an anti- Saccharomyces cerevisiae antibody, an antimicrobial antibody, an acute phase protein, an apolipoprotein, a defensin, a growth factor, a cytokine, a cadherin, and a combination thereof.
3. The method of claim 2 , wherein said anti-neutrophil antibody comprises an anti-neutrophil cytoplasmic antibody (ANCA).
4. The method of claim 2 , wherein said antimicrobial antibody comprises an anti-flagellin antibody.
5. The method of claim 1 , wherein the presence, absence, or level of each of said serological markers is detected with an enzyme immunoassay (EIA) or immunohistochemical assay.
6. The method of claim 1 , wherein said genetic markers further comprise at least one of the genes set forth in Tables 1A-1E.
7. The method of claim 1 , wherein the genotype of said genetic markers is detected by genotyping for the presence or absence of said single nucleotide polymorphism (SNP).
8. The method of claim 1 , wherein said sample is selected from the group consisting of serum, plasma, whole blood, and stool.
9. The method of claim 1 , wherein said logistic regression model comprises a look-up table or graph.
10. The method of claim 1 , further comprising recommending a course of therapy for said individual based upon the risk that said individual develops said stricturing or penetrating disease presentation.
11. The method of claim 5 , wherein said enzyme immunoassay (EIA) is an enzyme-linked immunosorbent assay (ELISA).