IBD-BIOPDescubrimiento de Biomarcadores y Perfilado Multi-ómico para la Evaluación de la Actividad de la Enfermedad y el Monitoreo del Tratamiento en la Enfermedad Inflamatoria Intestinal

This is a multicenter prospective observational cohort study designed to establish a clinical data and biospecimen-based platform for biomarker discovery, validation, and multi-omics research in inflammatory bowel disease. The study will enroll participants with inflammatory bowel disease, including Crohn's disease, ulcerative colitis, or IBD-unclassified when applicable, as well as unaffected first-degree relatives, unrelated healthy controls, and non-IBD disease controls when appropriate. The study is not designed to assign or test any study-directed treatment. All medical treatments, including biologic therapies, targeted small-molecule therapies, nutritional therapy, endoscopy, imaging, surgery, and other clinical management decisions, will be determined by treating physicians according to routine clinical practice. The study will observe participants during routine care and collect standardized clinical data, biospecimens, endoscopic findings, histologic findings, laboratory results, imaging findings, treatment exposure information, and follow-up outcomes. The overall purpose of this study is to evaluate whether candidate biomarkers or combined biomarker models can be used to assess disease activity, identify endoscopic and histologic inflammation, monitor response to routine clinical treatment, predict treatment outcomes, and support risk stratification for disease progression. Endoscopic assessment will serve as the primary reference standard for evaluating biomarker performance for objective intestinal inflammation. The study is intended to function as an open biomarker discovery and validation platform. It will evaluate both pre-specified biomarkers and additional candidate biomarkers identified through genetic, pharmacogenetic, immune, microbiome, transcriptomic, proteomic, metabolomic, single-cell, tissue-based, spatial, or other multi-omics analyses. Pre-specified biomarker domains may include blood-based biomarkers, stool-based biomarkers, tissue-based biomarkers, genetic markers, immune-related markers, microbiome-derived markers, and multi-omics-derived candidate biomarkers. Examples may include leucine-rich alpha-2 glycoprotein, fecal calprotectin, C-reactive protein, oncostatin M, TL1A/TNFSF15-related markers, TNFSF15 genotype, selected HLA or other pharmacogenetic markers when available, and additional biomarkers selected from exploratory omics analyses. The primary analysis will evaluate the diagnostic performance of candidate biomarkers or combined biomarker models for endoscopic disease activity. Reference measures may include SES-CD, standardized small-bowel endoscopic assessments, capsule endoscopy scores, Mayo endoscopic score, UCEIS, or other accepted endoscopic assessments when applicable. Performance measures may include area under the receiver operating characteristic curve, sensitivity, specificity, predictive values, and biomarker cut-off values. Cut-off values may be explored in discovery datasets and evaluated in internal and external validation cohorts. A second core analysis will evaluate whether baseline biomarker profiles, longitudinal biomarker changes, or combined biomarker models can monitor or predict treatment response during routine clinical care. Treatment response outcomes may include clinical response, clinical remission, endoscopic response, endoscopic remission, imaging-defined response or remission, fecal calprotectin response, C-reactive protein response, treatment escalation, treatment failure, hospitalization, surgery, or relapse when available. Secondary analyses will evaluate biomarker performance against specific clinical and objective outcomes. These may include histologic disease activity and histologic remission; clinical remission rate and clinical response rate using disease-specific clinical definitions; concordance with fecal calprotectin as an established stool-based comparator biomarker; concordance with C-reactive protein as an established blood-based comparator biomarker; cross-sectional imaging-defined radiologic response and remission using MRE or CTE when available; intestinal ultrasound-defined response and remission or transmural healing; and disease progression or poor outcomes. The study will also include family-based and exploratory analyses. The inclusion of unaffected first-degree relatives is intended to support analyses of genetic susceptibility, shared environmental exposure, immune profiles, microbiome features, and other biomarkers related to inflammatory bowel disease. Exploratory analyses may assess genetic or pharmacogenetic markers, multi-omics-derived biomarkers, and biomarker profiles associated with complex Crohn's disease phenotypes, including perianal fistula, stricturing disease, penetrating disease, surgery, treatment escalation, or treatment failure. Previously collected biospecimens and clinical data from prior ethics-approved prospective studies may be included as discovery datasets when permitted by the original consent, ethics approval, and the current platform protocol. Later enrolled participants from the same research network may be used as an internal validation cohort. Participants from collaborating centers or external datasets may be used as an external validation cohort when available. This discovery and validation framework is intended to improve reproducibility, reduce overfitting, and evaluate the generalizability of candidate biomarkers and biomarker-based prediction models. Statistical analyses may include descriptive statistics, group comparisons, correlation analyses, regression models, survival analyses, mixed-effects models for longitudinal data, receiver operating characteristic analyses, threshold exploration, model calibration, model discrimination, reclassification analyses, decision curve analyses, and internal or external validation. The long-term goal is to provide a standardized clinical and biospecimen platform to support objective disease monitoring, treatment prediction, risk stratification, and future precision medicine research in inflammatory bowel disease.