Phenotype and Multi-omics Analysis of Children With Congenital Diarrhea and Enteropathy in China

September 3, 2025 updated by: Children's Hospital of Fudan University

A Case-control Study of Phenotype and Multi-omics Analysis of Children With Congenital Diarrhea and Enteropathy in China

This study will establish a clinical cohort of children with congenital diarrhea and enteropathy (CODE), mine biomarkers of CODE through multi-omics technology and construct a clinical risk prediction model.

Study Overview

Status

Recruiting

Conditions

Detailed Description

This study will establish a clinical cohort and a clinical phenotype database of children with congenital diarrhea and enteropathy (CODE), The investigator will mine biomarkers of CODE through multi-omics technology. This study is designed to construct a clinical risk prediction model by combining artificial intelligence technology.

Study Type

Observational

Enrollment (Estimated)

60

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

    • Shanghai Municipality
      • Shanghai, Shanghai Municipality, China, 201102
        • Recruiting
        • Yanqiu Wang
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

Patients with chronic diarrhea lasting greater than 2 months or greater than 1 month in patients younger than 2 months of age

Description

Inclusion Criteria:

  • Patients with chronic diarrhea lasting greater than 2 months or greater than 1 month in patients younger than 2 months of age
  • Patients with consent from parents or legal guardians

Exclusion Criteria:

  • Chronic diarrhea caused by specific infections, i.e. CMV, Clostridioides difficile
  • Chronic diarrhea with necrotizing enterocolitis, short bowel syndrome
  • Functional diarrhea
  • Patients with poor compliance

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Control
Healthy children
Case
Congenital diarrhea and enteropathy (CODE) patients

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Clinical phenotype of congenital diarrhea and enteropathy in China
Time Frame: Within approximately 2 years of enrollment
Describe the clinical phenotype(Birth status, family history, clinical features of diarrhea, laboratory examination, endoscopic and histological evaluation results, growth and development indicators, previous treatment and effect were collected) of congenital diarrhea and enteropathy in China,We will use our own mobile application or to collect the relevant data, which will be filled in by the parents of the child.
Within approximately 2 years of enrollment

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Biomarkers of congenital diarrhea and enteropathy with diagnostic value through microbiome, metabolome and proteome features
Time Frame: Within approximately 2 years of enrollment
Plasma and stool were collected from patients and healthy control children for multi-omics screening to identify biomarkers, of which differential expression were mined through proteome(olink), microbiome(metagenomic sequencing) and metabolome( untargeted metabolomics),relevant statistical analyses were performed using non-parametric tests, such as the Wilcoxon signed-rank test.
Within approximately 2 years of enrollment
Cinical risk prediction model for congenital diarrhea and enteropathy built by artificial intelligence and machine learning
Time Frame: Within approximately 30 months of enrollment
Using artificial intelligence and machine learning to construct predictive models for congenital diarrhea and enteropathy by combining children's clinical phenotypes and multi-omics results,such as the random forest model
Within approximately 30 months of enrollment

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

April 15, 2024

Primary Completion (Estimated)

April 1, 2026

Study Completion (Estimated)

October 1, 2026

Study Registration Dates

First Submitted

March 21, 2024

First Submitted That Met QC Criteria

April 7, 2024

First Posted (Actual)

April 10, 2024

Study Record Updates

Last Update Posted (Estimated)

September 10, 2025

Last Update Submitted That Met QC Criteria

September 3, 2025

Last Verified

September 1, 2025

More Information

Terms related to this study

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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