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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dc.catalogadordfo
dc.contributor.authorPérez Jeldres, Tamara de Lourdes
dc.contributor.authorReyes Pérez, Paula
dc.contributor.authorGonzález Hormazábal, Patricio
dc.contributor.authorAvendaño Soriano, Cristóbal Raimundo
dc.contributor.authorSegovia Melero, Roberto
dc.contributor.authorAzócar, Lorena
dc.contributor.authorVerónica Silva
dc.contributor.authorAndrés de la Vega
dc.contributor.authorArriagada, Elizabeth
dc.contributor.authorHernández, Elisa
dc.contributor.authorAguilar, Nataly
dc.contributor.authorPavez Ovalle, Carolina Denisse
dc.contributor.authorHernández Rocha, Cristián Antonio
dc.contributor.authorCandia Balboa, Roberto Andrés
dc.contributor.authorMiquel Poblete, Juan Francisco
dc.contributor.authorÁlvarez Lobos, Manuel Marcelo
dc.contributor.authorValdés, Ivania
dc.contributor.authorMedina Rivera, Alejandra
dc.contributor.authorBustamante, María Leonor
dc.date.accessioned2025-06-26T19:32:23Z
dc.date.available2025-06-26T19:32:23Z
dc.date.issued2025
dc.description.abstractExtraintestinal 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.
dc.fechaingreso.objetodigital2025-06-26
dc.fuente.origenORCID
dc.identifier.doi10.3390/ijms26125741
dc.identifier.issn1422-0067
dc.identifier.urihttps://doi.org/10.3390/ijms26125741
dc.identifier.urihttps://www.mdpi.com/1422-0067/26/12/5741
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/104769
dc.information.autorucEscuela de Medicina; Perez Jeldres Tamara De Lourdes; S/I; 1024946
dc.information.autorucEscuela de Medicina; Pavez Ovalle Carolina Denisse; S/I; 190170
dc.information.autorucEscuela de Medicina; Hernandez Rocha Cristian Antonio; 0000-0001-9018-4242; 175117
dc.information.autorucEscuela de Medicina; Candia Balboa Roberto Andres; 0000-0003-1856-7737; 16705
dc.information.autorucEscuela de Medicina; Miquel Poblete Juan Francisco; 0000-0002-0526-4377; 72216
dc.information.autorucEscuela de Medicina; Alvarez Lobos Manuel Marcelo; S/I; 6131
dc.information.autorucEscuela de Ingeniería; Avendaño Soriano Cristobal Raimundo; S/I; 178742
dc.issue.numero12
dc.language.isoen
dc.nota.accesocontenido completo
dc.revistaInternational Journal of Molecular Sciences
dc.rightsacceso abierto
dc.rights.licenseAtribución/Reconocimiento 4.0 Internacional
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/deed.es
dc.subjectInflammatory bowel disease
dc.subjectExtraintestinal manifestation
dc.subjectGenetic variants
dc.subject.ddc610
dc.subject.deweyMedicina y saludes_ES
dc.subject.ods03 Good health and well-being
dc.subject.odspa03 Salud y bienestar
dc.titlePrediction of Extraintestinal Manifestations in Inflammatory Bowel Disease Using Clinical and Genetic Variables with Machine Learning in a Latin IBD Group
dc.typeartículo
dc.volumen26
sipa.codpersvinculados1024946
sipa.codpersvinculados190170
sipa.codpersvinculados175117
sipa.codpersvinculados16705
sipa.codpersvinculados72216
sipa.codpersvinculados6131
sipa.codpersvinculados178742
sipa.trazabilidadORCID;2025-06-23
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