Association Between Fecal Microbiota Composition, Metabolite Concentrations, and Indoxyl Sulfate Levels
2 other identifiers
observational
58
1 country
1
Brief Summary
Gut dysbiosis is frequently characterized by decreased microbial diversity and alterations in the abundance of certain microbial species. In individuals with chronic kidney disease (CKD), dysbiosis and metabolic imbalances are prevalent, contributing to the buildup of gut-derived retention solutes and metabolites in the bloodstream. Research has consistently shown that CKD patients exhibit lower levels of beneficial gut bacteria. However, the specific functional changes in gut microbiota and their interactions with levels of uremic toxins in hemodialysis (HD) patients remain incompletely understood. This study seeks to explore the association of fecal metagenomics and targeted metabolomics in a cohort of 60 patients with different levels of to characterize the complex interplay between the gut microbiome and fecal and serum metabolites.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P25-P50 for all trials
Started Apr 2025
Shorter than P25 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
March 10, 2025
CompletedFirst Posted
Study publicly available on registry
March 14, 2025
CompletedStudy Start
First participant enrolled
April 1, 2025
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2025
CompletedMay 13, 2026
May 1, 2026
9 months
March 10, 2025
May 11, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Fecal microbiota profile
Alpha diversity, Beta diversity and functional composition of metagenomes is predicted from 16S rRNA data using the PICRUSt software with Python scripts
1 years
Secondary Outcomes (5)
Measurement of serum uremic toxins
1 years
Evaluation of short-chain fatty acids(SCFAs) and branched-chain SCFAs
1 years
Measurement of serum uremic toxins
1 years
Measurement of serum uremic toxins
1 years
Measurement of serum uremic toxins
1 years
Study Arms (1)
Hemodialysis Patients
This study seeks to explore the association of fecal metagenomics and targeted metabolomics in a cohort of 60 patients with different levels of to characterize the complex interplay between the gut microbiome and fecal and serum metabolites.
Eligibility Criteria
hemodialysis patients
You may qualify if:
- age 18-80 years and
- diagnosed with CKD stage V
- currently receiving hemodialysis treatment\>3 months
You may not qualify if:
- pregnant or nursing women
- patients with kidney transplant
- severe infections
- severe cardiac diseases
- liver diseases
- malignancy
- autoimmune disorders
- severe malnutrition
- consumed any type of pre-or probiotics
- had antibiotic therapy within 1 month
- diagnosed irritable bowel syndrome
- Crohn's disease
- ulcerative colitis
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Tungs' Taichung Metroharbour Hospital
Taichung, Wuqi District, 435, Taiwan
Related Publications (29)
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PMID: 17898101BACKGROUND
Biospecimen
serum and stool
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Paik Seong Lim, PhD
Tungs' Taichung Metroharbour Hospital
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- CROSS SECTIONAL
- Target Duration
- 1 Year
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
March 10, 2025
First Posted
March 14, 2025
Study Start
April 1, 2025
Primary Completion
December 31, 2025
Study Completion
December 31, 2025
Last Updated
May 13, 2026
Record last verified: 2026-05
Data Sharing
- IPD Sharing
- Will share
all collected IPD, all IPD that underlie results in a publication