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

Recruiting

• Conditions: Diarrhea Infantile

• Registration Number: NCT06356545
• Lead Sponsor: Children's Hospital of Fudan University

Brief Summary

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.

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 Timeline

• Study First Submitted: 2024-03-21
• Study First Submitted QC: 2024-04-07
• Study First Posted: 2024-04-10
• Study Start: 2024-04-15
• Status Verified: 2024-07
• Last Update Submitted: 2024-07-03
• Last Update Posted: 2024-07-05
• Primary Completion: 2026-04
• Study Completion: 2026-10

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 60

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 & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Clinical phenotype of congenital diarrhea and enteropathy in China	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.

Secondary Outcome Measures

Name	Time	Method
Cinical risk prediction model for congenital diarrhea and enteropathy built by artificial intelligence and machine learning	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
Biomarkers of congenital diarrhea and enteropathy with diagnostic value through microbiome, metabolome and proteome features	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.

Trial Locations

Locations (1)

Yanqiu Wang; 🇨🇳 Shanghai, Shanghai, China