Molecular prediction of disease risk and severity in a large Dutch Crohn's disease cohort.

BACKGROUND: Crohn's disease and ulcerative colitis have a complex genetic background. We assessed the risk for both the development and severity of the disease by combining information from genetic variants associated with inflammatory bowel disease (IBD).

METHODS: We studied 2804 patients (1684 with Crohn's disease and 1120 with ulcerative colitis) and 1350 controls from seven university hospitals. Details of the phenotype were available for 1600 patients with Crohn's disease and for 800 with ulcerative colitis. Genetic association for disease susceptibility was tested for the nucleotide-binding and oligomerisation domain 2 gene (NOD2), the IBD5 locus, the Drosophila discs large homologue 5 and autophagy-related 16-like 1 genes (DLG5 and ATG16L1) and the interleukin 23 receptor gene (IL23R). Interaction analysis was performed for Crohn's disease using the most associated single nucleotide polymorphism (SNP) for each locus. Odds ratios were calculated in an ordinal regression analysis with the number of risk alleles as an independent variable to analyse disease development and severity.

RESULTS: Association with Crohn's disease was confirmed for NOD2, IBD5, DLG5, ATG16L1 and IL23R. Patients with Crohn's disease carry more risk alleles than controls (p = 3.85 x 10(-22)). Individuals carrying an increasing number of risk alleles have an increasing risk for Crohn's disease, consistent with an independent effects multiplicative model (trend analysis p = 4.25 x 10(-23)). Patients with Crohn's disease with a more severe disease course, operations or an age of onset below 40 years have more risk alleles compared to non-stricturing, non-penetrating behaviour (p = 0.0008), no operations (p = 0.02) or age of onset above 40 years (p = 0.028).

CONCLUSION: Crohn's disease is a multigenic disorder. An increase in the number of risk alleles is associated with an increased risk for the development of Crohn's disease and with a more severe disease course. Combining information from the known common risk polymorphisms may enable clinicians to predict the course of Crohn's disease.