Inflammatory Bowel Disease Whitepaper

Inflammatory Bowel Disease Whitepaper
Orchid's team of genetic experts has developed a genetic risk score (GRS) for inflammatory bowel disease.
Written by  Orchid Team
Orchid has developed advanced genetic risk scores (GRS) for a variety of diseases. Here we present our data on our GRS of inflammatory bowel disease.

Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a term for two conditions (Crohn’s disease and ulcerative colitis) that are characterized by chronic inflammation of the gastrointestinal tract [1]. Both forms of IBD are caused by systemic immune dysfunction, where the body’s immune system attacks the GI tract rather than foreign viruses or bacteria. There is a substantial genetic component to IBD; having a first degree relative with the disease is the highest risk factor, and those with two affected parents have a 30% risk of developing the disease, compared to a population prevalence of 1.3% [2]. The heritability of IBD is approximately 70%, based on a literature review of several twin studies drawn from a number of European twin registries, including those of Denmark, Sweden, and Britain [2].

Genetic risk score (GRS) 

A genetic risk score quantifies the degree to which an individual’s genetics increases their likelihood of developing a specific disease. The GRS for IBD includes 1,097,724  variants and was developed based on the variants identified in a study that analyzed genomes of 34,652 individuals of European ancestry. The study included 12,882 cases (individuals with IBD) and 21,770 healthy controls [3]. The risk score model adjusted weights for linkage disequilibrium using the PRScs software.

Table 1: Discovery cohort statistics. Variants in GRS and sample number used in the IBD GWAS.

Clinical Impact and Prevalence 

IBD affects over 3 million Americans, or roughly 1.3% of the US population [4]. It is usually diagnosed between 15 and 35, with 29 being the average age of diagnosis [5]. Typical symptoms of IBD include persistent diarrhea, abdominal pain, rectal bleeding, weight loss, and fatigue [1],[6].  While IBD is an immune disorder with no known cure, several medications may be used to treat the symptoms of IBD: aminosalicylates, corticosteroids (such as prednisone), and immunomodulators can be prescribed by a gastroenterologist [7]. People with IBD may have higher rates of colorectal cancer, though current treatments may reduce that risk somewhat [8].

Performant inflammatory bowel disease risk stratification   

Validated using a large cohort of adults with known inflammatory bowel disease status 

Individuals in the 99th percentile of genetic risk have a 5.8 percent absolute risk of inflammatory bowel disease, compared to the average of 1.46 percent.

Figure 1: Risk gradient for inflammatory bowel disease. Each blue dot represents a percentile of Genetic Risk Score, with its percent prevalence in UK Biobank self-reported White British in the y-axis. The black line represents the predicted prevalence from a logistic regression derived from the data.


Validation in UK Biobank. In the UK Biobank, cases were identified using self-reported IBD, relevant ICD-10 diagnosis and death codes. See the phenotype supplement for full details. In the validation set, prevalence of the disease increased with GRS.

People at the tail end of GRS distribution were at an elevated risk (had higher odds) for developing the disease in comparison to the baseline rate. For each GRS threshold, we also computed the odds ratio. Baseline rate is the prevalence of the disease in the entire reference population. 

Identification of adults at 4-5 times the baseline risk of inflammatory bowel disease 

Adults in the 99th percentile of genetic risk have a 5.80% risk of developing inflammatory bowel disease. The odds ratio for adults in the 99th percentile of genetic risk was 4.16. 

Table 2: Disease prevalence and odd ratios in elevated genetic risk subgroups for white British individuals.

Comparison to Published Benchmarks

Orchid’s model achieves comparable stratification performance with an AUC of 0.654 compared to the benchmark at 0.618. 

We compared the performance of our model as validated on the UK Biobank with the performance of the best model in Khera et al. To make a comparison of models, we restricted our validation sample to those in Phase II of the UK Biobank release, as in Khera et. al. In the first column, we give the results for our predictor with the phenotype as described above. In the second, we report the metrics for the best-performing predictor in Khera et. al using the same phenotype as ours.

Table 3: Accuracy metric comparison. Our model compared to reference.

1 Khera et al [3]

2 Odds ratio per std. of GRS, controlling for age and PCs is 1.73 and 1.61 for Orchid’s and Khera’s model, respectively.


1. What is inflammatory bowel disease (IBD)? 11 May 2020 [cited 4 Jan 2022]. Available:

2. Gordon H, Moller FT, Andersen V, Harbord M. Heritability in Inflammatory Bowel Disease: From the First Twin Study to Genome-Wide Association Studies. Inflamm Bowel Dis. 2015;21: 1428.

3. Khera AV, Chaffin M, Aragam KG, Haas ME, Roselli C, Choi SH, et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat Genet. 2018;50: 1219–1224.

4. CDC. IBD Data and Statistics. 10 Nov 2021 [cited 4 Jan 2022]. Available:

5. Shivashankar R, Tremaine WJ, Harmsen WS, Loftus EV Jr. Incidence and Prevalence of Crohn’s Disease and Ulcerative Colitis in Olmsted County, Minnesota From 1970 Through 2010. Clin Gastroenterol Hepatol. 2017;15: 857–863.

6. Crohn’s & Colitis Foundation of America. IBD Factbook. [cited 4 Jan 2022]. Available:

7. Matsuoka K, Kobayashi T, Ueno F, Matsui T, Hirai F, Inoue N, et al. Evidence-based clinical practice guidelines for inflammatory bowel disease. J Gastroenterol. 2018;53: 305–353.

8. Stidham RW, Higgins PDR. Colorectal Cancer in Inflammatory Bowel Disease. Clin Colon Rectal Surg. 2018;31: 168–178.

Appendix: Disease case identification and number of cases in UK Biobank

*Type 1 diabetes was defined as a combination the following inclusion and exclusion criteria:

  • Self-diagnosed diabetes (any type)
  • No self-diagnosed Type 2 diabetes
  • Age of diabetes onset between 0 and 20 years
  • Started insulin within one year of diagnosis of diabetes
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