About this trial
The goal of this observational study is to establish a multicenter prospective clinical and biospecimen platform for biomarker discovery and validation in inflammatory bowel disease, including Crohn's disease and ulcerative colitis.
Researchers want to learn whether candidate biomarkers or combined biomarker models can help assess intestinal inflammation, monitor response to routine clinical treatment, predict treatment outcomes, and identify participants who may be at higher risk of disease progression.
The study may enroll participants with inflammatory bowel disease, unaffected first-degree relatives of participants with inflammatory bowel disease, unrelated healthy controls, and non-IBD disease controls when appropriate. Clinical information and biological samples, including blood, stool, and intestinal tissue, may be collected. Biomarkers measured in blood, stool, intestinal tissue, genetic data, immune profiles, microbiome data, and other multi-omics data may be evaluated.
The main questions this study aims to answer are:
Can candidate biomarkers or combined biomarker models identify endoscopic disease activity when compared with endoscopic assessment?
Can these biomarkers monitor or predict clinical response, clinical remission, endoscopic response, endoscopic remission, imaging response, or biomarker response during routine clinical care?
Can these biomarkers help predict treatment failure, disease progression, hospitalization, surgery, treatment escalation, or complex Crohn's disease phenotypes?
Participants will not be assigned to any treatment by the study. All treatments and clinical management decisions will be chosen by treating physicians as part of routine medical care.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Age 14 years or older.
Able to provide written informed consent; for minors, consent from a legal guardian and assent from the participant will be obtained according to local ethics requirements.
Willing to provide clinical information and/or biospecimens, which may include blood, stool, intestinal tissue, or other available biological samples.
Able to participate in study-related data and sample collection according to the study protocol.
Disqualifiers
Refusal or inability to provide informed consent or required assent when applicable.
Active severe infection or chronic infectious disease that may substantially affect biomarker interpretation, including active tuberculosis, active hepatitis B or C, HIV infection, or other clinically significant active infection.
Pregnancy or lactation at the time of enrollment.
Severe mental illness, cognitive impairment, or other condition that prevents cooperation with study procedures.
Trial population
This multicenter prospective observational cohort will enroll approximately 6,000 participants aged 14 years or older. The study population may include participants with inflammatory bowel disease, including Crohn's disease, ulcerative colitis, or IBD-unclassified; unaffected first-degree relatives of participants with inflammatory bowel disease; unrelated healthy controls; and non-IBD disease controls. Clinical information, treatment exposure data, follow-up outcomes, and biospecimens may be collected to support biomarker discovery, validation, multi-omics research, treatment monitoring, and risk stratification. Participants with severe active infection, pregnancy or lactation, severe mental illness, or major confounding systemic inflammatory or autoimmune diseases may be excluded.
Trial design
Cohort
Prospective
Treatments tested in this trial
Not listed
Trial groups
Trial outcomes
Primary outcomes
Diagnostic Performance of Candidate Biomarkers or Combined Biomarker Models for Endoscopic Disease Activity
Diagnostic performance of pre-specified and newly identified candidate biomarkers or combined biomarker models for identifying endoscopic disease activity in inflammatory bowel disease. Endoscopic assessments will serve as the primary reference standard. 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 will include AUC, sensitivity, specificity, positive predictive value, negative predictive value, and biomarker cut-off values. Cut-off values will be explored in discovery datasets and evaluated in internal and external validation cohorts.
Predictive Performance of Candidate Biomarkers or Combined Biomarker Models for Treatment Response
Predictive performance of baseline candidate biomarkers, longitudinal biomarker changes, or combined biomarker models for response to routine clinical treatment will be evaluated. Treatment response outcomes may include clinical response, clinical remission, endoscopic response, endoscopic remission, inflammatory marker response, imaging response, treatment escalation, treatment failure, hospitalization, surgery, or relapse when available. Treatments are not assigned by the study and are recorded only as routine-care clinical exposures.
Secondary outcomes
Diagnostic Performance of Candidate Biomarkers or Combined Biomarker Models for Histologic Disease Activity and Remission
Diagnostic performance of candidate biomarkers or combined biomarker models for histologic disease activity and histologic remission will be evaluated when tissue samples or pathology results are available. For ulcerative colitis, histologic activity may be assessed using Nancy Histological Index, Geboes score, Robarts Histopathology Index, or local pathology assessment when available. For Crohn's disease, active histologic inflammation may be assessed using standardized or study-defined pathology criteria when available. Performance measures may include AUC, sensitivity, specificity, predictive values, and biomarker cut-off values.
Concordance and Predictive Performance of Candidate Biomarkers or Combined Models for Clinical Remission Rate
Concordance and predictive performance of candidate biomarkers or combined biomarker models for clinical remission rate will be evaluated. Clinical remission rate is the proportion of participants achieving disease-specific clinical remission at follow-up. For Crohn's disease, remission will be defined uniformly as CDAI \<150. HBI will not define this registered endpoint and may be used only for supportive analyses. For ulcerative colitis, remission will be defined as partial Mayo score \<=2 with no individual subscore \>1 and rectal bleeding subscore =0. Analyses will compare biomarker levels and changes with remission status and remission rate.
Concordance and Predictive Performance of Candidate Biomarkers or Combined Models for Clinical Response Rate
Concordance and predictive performance of candidate biomarkers or combined biomarker models for clinical response rate will be evaluated. Clinical response rate is the proportion of participants achieving disease-specific clinical response at follow-up. For Crohn's disease, response will be defined uniformly as a CDAI decrease of at least 100 points from treatment baseline. HBI will not define this registered endpoint and may be used only for supportive analyses. For ulcerative colitis, response will be defined as a partial Mayo score decrease of at least 2 points and at least 30% from baseline, with rectal bleeding subscore decrease of at least 1 point or absolute rectal bleeding subscore of 0 or 1.
Concordance Between Candidate Biomarkers or Combined Models and Fecal Calprotectin for Intestinal Inflammatory Activity
Concordance between candidate biomarkers or combined biomarker models and fecal calprotectin (FC) as an established stool-based comparator biomarker for intestinal inflammatory activity will be evaluated. FC will be measured in micrograms/g and analyzed as a continuous variable and by categories: \<150, 150-250, and \>250 micrograms/g when applicable. Analyses will assess cross-sectional concordance and longitudinal trend consistency between biomarker changes and FC changes. FC response may be defined as at least 50% decrease from baseline among participants with elevated baseline FC, and FC normalization as \<150 micrograms/g. FC will not serve as the primary reference standard.
Other outcomes
Discovery of Multi-Omics-Derived Candidate Biomarkers
Identification of candidate biomarkers from genetic, immune, microbiome, transcriptomic, proteomic, metabolomic, single-cell, tissue-based, spatial, or other multi-omics analyses. Candidate biomarkers may be selected from discovery datasets and subsequently evaluated in internal or external validation cohorts for disease activity assessment, treatment monitoring, treatment prediction, risk stratification, or disease progression.
Association of Genetic and Pharmacogenetic Markers With Treatment Outcomes
Exploratory associations between genetic or pharmacogenetic markers and treatment outcomes will be evaluated when data are available. Candidate markers may include TNFSF15 genotype, selected HLA variants, or other variants identified from genomic or pharmacogenetic analyses. Outcomes may include treatment response, treatment failure, immunogenicity-related outcomes, disease progression, perianal disease, stricturing or penetrating disease, hospitalization, surgery, or treatment escalation.
Family-Based Differences in Biomarker Profiles
Differences in biomarker, genetic, immune, microbiome, and multi-omics profiles will be compared among participants with inflammatory bowel disease, unaffected first-degree relatives, unrelated healthy controls, and non-IBD disease controls. Analyses may support assessment of genetic susceptibility, shared environmental exposure, microbiome background, immune activation, and disease-associated biomarker patterns.
Biomarker Profiles Associated With Complex Crohn's Disease Phenotypes
Exploratory evaluation of biomarker profiles associated with complex Crohn's disease phenotypes. Phenotypes may include perianal fistula, stricturing disease, penetrating disease, abscess, inflammatory mass, prior or future surgery, treatment escalation, or treatment failure. Analyses may identify candidate biomarkers or biomarker models associated with complex disease behavior and poor outcomes.
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