P1305 Prediction of extraintestinal manifestations in inflammatory bowel disease using clinical and genetic variables with machine learning
Authors: Pérez T , Bustamante M L , Reyes Pérez P , Medina Rivera A , Avendano C , Azocar L , Estela R , Aguilar N , Segovia Melero R , Silva V , De La Vega A , Arriagada E , Javier C , Hernandez E , Pavez-Ovalle C , Hernández-Rocha C , Miquel J F , Alvarez-Lobos M 
Published: January 2025

Background

Patients with inflammatory bowel diseases (IBD) may develop extraintestinal manifestations (EIM) that increase their morbidity. We investigated clinical and genetic factors associated with EIM, analyzing an IBD cohort between 2019-2024. We designed predictive models for EIM using machine learning techniques.

Methods

A total of 414 IBD patients were recruited (314 UC and 100 with CD). The presence of EIM was assessed, and clinical differences between the groups with and without EIM were analyzed using Chi-square tests and Mann-Whitney U tests. In a subset of 227 genotyped patients, genetic variants associated with EIM were identified, and a polygenic risk score (PRS) was calculated. Logistic regression (LR) and Random Forest (RF) predictive models were constructed. Furthermore, univariate/multivariate regression analyses were conducted to confirm associations with EIM.

Results

Clinical data from 414 patients were analysed, of which 29% (120) had EIM (Figure 1). Of these, 69% (83) had ulcerative colitis (UC). Meanwhile, 294 (71%) did not have EIM, of whom 231 (78.6%) had UC. Significant differences were observed between the groups with and without EIM: median age (45 vs. 52 years, p=0.01), BMI (26 vs. 27, p=0.006), and ESR (9 vs. 10, p=0.01). Categorical variables like family history of IBD (p=0.02) and anti-TNF use (p=0.01) were significant.

In genotyped group, 50 of 200 genetic variants were linked to EIM, with 2 significantly increasing EIM risk: rs44107871-TC (PVT1 gene), three-genotype model; OR = 1.89, CI = 1.06-3.41, p-value = 0.03 and rs9936833-C (LINC917, FENDR gene) recessive model OR 2.29, CI = 1.16-4.55, p-value = 0.02, dominant-C model OR 1.86, CI 1.01-3.49, p-value = 0.04, additive-CC model OR = 3.01, CI 1.36-6.80 (p=0.007). The PRS was not discriminative, with an AUC of 0.67 and an accuracy of 0.56. In contrast, the LR and RF models better differentiated groups with and without EIM (Figure 2).

Both in EIM univariate and multivariate analyses, significant associations were found with the variables rs9936833TT (univariate: OR=0.33, 95% CI=0.15-0.74, p=0.007; multivariate: OR=0.25, 95% CI=0.10-0.61, p=0.003), family history of IBD (univariate: OR=3.42, 95% CI=1.52-7.76, p=0.002; multivariate: OR=3.86, 95% CI=1.59-9.37, p=0.002), use of anti-TNF (univariate: OR=3.18, 95% CI=1.14-7.19, p=0.005; multivariate: OR=5.18, 95% CI=1.96-13.7, p=0.0009), age (univariate OR: 1.02, 95% CI 1.0-1.04, p=0.03, multivariate OR=1.03, 95% CI 1.00-1.06, p=0.01).

Conclusion

About third of IBD patients had EIM, as reported. Variants rs9936833 and rs4410871 were linked to higher EIM risk. While PRS had limits, LR and RF models predicted EIM well. Family history of IBD, rs9936833-CC, age, and anti-TNF use were significant risk factors.

References

Khrom M, Long M, Dube S, et al. Comprehensive Association Analyses of Extraintestinal Manifestations in Inflammatory Bowel Disease. Gastroenterology. 2024;167(2):315-332. doi:10.1053/j.gastro.2024.02.026

Gordon H, Burisch J, Ellul P, et al. ECCO Guidelines on Extraintestinal Manifestations in Inflammatory Bowel Disease. J Crohns Colitis. 2024;18(1):1-37. doi:10.1093/ecco-jcc/jjad108