Prediction of Extraintestinal Manifestations in Inflammatory Bowel Disease Using Clinical and Genetic Variables with Machine Learning in a Latin IBD Group

Pérez-Jeldres, Tamara; Reyes-Pérez, Paula; Gonzalez-Hormazabal, Patricio; Avendano, Cristóbal; Segovia Melero, Roberto; Azocar, Lorena; Silva, Veronica; De La Vega, Andres; Arriagada, Elizabeth; Hernandez, Elisa; Aguilar, Nataly; Pavez-Ovalle, Carolina; Hernández-Rocha, Cristian; Candia, Roberto; Miquel, Juan Francisco; Alvarez-Lobos, Manuel; Valdes, Ivania; Medina-Rivera, Alejandra; Bustamante, Maria Leonor

doi:10.3390/ijms26125741

Open AccessArticle

Prediction of Extraintestinal Manifestations in Inflammatory Bowel Disease Using Clinical and Genetic Variables with Machine Learning in a Latin IBD Group^†

by

Tamara Pérez-Jeldres

^1,2,*,

Paula Reyes-Pérez

³,

Patricio Gonzalez-Hormazabal

⁴,

Cristóbal Avendano

⁵,

Roberto Segovia Melero

¹,

Lorena Azocar

¹,

Veronica Silva

²,

Andres De La Vega

²,

Elizabeth Arriagada

²,

Elisa Hernandez

¹,

Nataly Aguilar

¹,

Carolina Pavez-Ovalle

¹,

Cristian Hernández-Rocha

¹,

Roberto Candia

¹

,

Juan Francisco Miquel

¹,

Manuel Alvarez-Lobos

¹,

Ivania Valdes

⁶

,

Alejandra Medina-Rivera

³ and

Maria Leonor Bustamante

^4,*

¹

Departmento de Gastroenterología, Pontificia University Católica de Chile, Santiago 8330024, Chile

²

Departmento de Gastroenterología, Hospital san Borja Arriaran, Santiago 8360160, Chile

³

Laboratorio Internacional de Investigación Sobre el Genoma Humano, University Nacional Autónoma de Mexico, Mexico 76230, Mexico

⁴

Programa de Genética Humana, Facultad de Medicina, Instituto de Ciencias Biomédicas (ICBM), Santiago 8380453, Chile

⁵

Departmento de Ciencias de la Computación, Pontificia University Católica de Chile, Santiago 7820436, Chile

⁶

Departmento de Enfermedades Respiratorias, Escuela de Medicina, Pontificia University Católica de Chile, Santiago 8330024, Chile

^*

Authors to whom correspondence should be addressed.

^†

This paper is an extended version of our paper published in Pérez, T.; Bustamante, M.L.; Pérez, P.R.; Rivera, A.M.; Avendano, C.; Azocar, L.; Estela, R.; Aguilar, N.; Melero, R.S.; Silva, V.; et al. Prediction of extraintestinal manifestations in inflammatory bowel disease using clinical and genetic variables with machine learning. In Proceedings of the European Crohn’s and Colitis Organization Congress, Berlin, Germany, 21–24 February 2025.

Int. J. Mol. Sci. 2025, 26(12), 5741; https://doi.org/10.3390/ijms26125741

Submission received: 21 April 2025 / Revised: 5 June 2025 / Accepted: 10 June 2025 / Published: 15 June 2025

(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Autoimmune Diseases—2nd Edition)

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Abstract

Extraintestinal manifestations (EIMs) significantly increase morbidity in inflammatory bowel disease (IBD) patients. In this study, we examined clinical and genetic factors associated with EIMs in 414 Latin IBD patients, utilizing machine learning for predictive modeling. In our IBD group (314 ulcerative colitis (UC) and 100 Crohn’s disease (CD) patients), EIM presence was assessed. Clinical differences between patients with and without EIMs were analyzed using Chi-square and Mann–Whitney U tests. Based on the genetic data of 232 patients, we identified variants linked to EIMs, and the polygenic risk score (PRS) was calculated. A machine learning approach based on logistic regression (LR), random forest (RF), and gradient boosting (GB) models was employed for predicting EIMs. EIMs were present in 29% (120/414) of patients. EIM patients were older (52 vs. 45 years, p = 0.01) and were more likely to have a family history of IBD (p = 0.02) or use anti-TNF therapy (p = 0.01). EIMs were more common in patients with CD than in those with UC without reaching statistical significance (p = 0.06). Four genetic variants were associated with EIM risk (rs9936833, rs4410871, rs3132680, and rs3823417). While the PRS showed limited predictive power (AUC = 0.69), the LR, GB, and RF models demonstrated good predictive capabilities. Approximately one-third of IBD patients experienced EIMs. Significant risk factors included genetic variants, family history, age, and anti-TNF therapy, with predictive models effectively identifying EIM risk.

Keywords: inflammatory bowel disease; extraintestinal manifestation; genetic variants

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MDPI and ACS Style

Pérez-Jeldres, T.; Reyes-Pérez, P.; Gonzalez-Hormazabal, P.; Avendano, C.; Segovia Melero, R.; Azocar, L.; Silva, V.; De La Vega, A.; Arriagada, E.; Hernandez, E.; et al. Prediction of Extraintestinal Manifestations in Inflammatory Bowel Disease Using Clinical and Genetic Variables with Machine Learning in a Latin IBD Group. Int. J. Mol. Sci. 2025, 26, 5741. https://doi.org/10.3390/ijms26125741

AMA Style

Pérez-Jeldres T, Reyes-Pérez P, Gonzalez-Hormazabal P, Avendano C, Segovia Melero R, Azocar L, Silva V, De La Vega A, Arriagada E, Hernandez E, et al. Prediction of Extraintestinal Manifestations in Inflammatory Bowel Disease Using Clinical and Genetic Variables with Machine Learning in a Latin IBD Group. International Journal of Molecular Sciences. 2025; 26(12):5741. https://doi.org/10.3390/ijms26125741

Chicago/Turabian Style

Pérez-Jeldres, Tamara, Paula Reyes-Pérez, Patricio Gonzalez-Hormazabal, Cristóbal Avendano, Roberto Segovia Melero, Lorena Azocar, Veronica Silva, Andres De La Vega, Elizabeth Arriagada, Elisa Hernandez, and et al. 2025. "Prediction of Extraintestinal Manifestations in Inflammatory Bowel Disease Using Clinical and Genetic Variables with Machine Learning in a Latin IBD Group" International Journal of Molecular Sciences 26, no. 12: 5741. https://doi.org/10.3390/ijms26125741

APA Style

Pérez-Jeldres, T., Reyes-Pérez, P., Gonzalez-Hormazabal, P., Avendano, C., Segovia Melero, R., Azocar, L., Silva, V., De La Vega, A., Arriagada, E., Hernandez, E., Aguilar, N., Pavez-Ovalle, C., Hernández-Rocha, C., Candia, R., Miquel, J. F., Alvarez-Lobos, M., Valdes, I., Medina-Rivera, A., & Bustamante, M. L. (2025). Prediction of Extraintestinal Manifestations in Inflammatory Bowel Disease Using Clinical and Genetic Variables with Machine Learning in a Latin IBD Group. International Journal of Molecular Sciences, 26(12), 5741. https://doi.org/10.3390/ijms26125741

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Prediction of Extraintestinal Manifestations in Inflammatory Bowel Disease Using Clinical and Genetic Variables with Machine Learning in a Latin IBD Group^†

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Prediction of Extraintestinal Manifestations in Inflammatory Bowel Disease Using Clinical and Genetic Variables with Machine Learning in a Latin IBD Group †

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Prediction of Extraintestinal Manifestations in Inflammatory Bowel Disease Using Clinical and Genetic Variables with Machine Learning in a Latin IBD Group^†