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Investigating the differences in gut microbiota composition and tryptophan metabolite levels between kidney stone patients and healthy individuals, with special focus on:
Full description
1. Objectives
To investigate differences in gut microbiota composition and tryptophan metabolite levels between kidney stone patients and healthy individuals, specifically focusing on:
2. Trial Design This prospective case-control study compares gut microbiota composition and serum metabolite levels between kidney stone patients (case group) and stone-free healthy volunteers (control group), while exploring associations with environmental factors.
3. Participants Case Group: Patients diagnosed with kidney stones. Control Group: Healthy volunteers without kidney stones.
4. Group Allocation Case Group: Kidney stone patients. Control Group: Stone-free healthy volunteers. Participants are assigned based on clinical status (no randomization).
Stratified analyses will consider:
Environmental exposure (temperature/humidity data). Seasonal factors (summer vs. non-summer). Gut microbiota composition (L. salivarius abundance via 16S rRNA sequencing). Serum metabolite levels (ICA, Kyn).
5. Endpoints
Primary Endpoints:
Gut microbiota differences (α/β diversity, L. salivarius abundance). Serum ICA and Kyn level differences.
Secondary Endpoints:
Tryptophan pathway metabolite changes (Trp, IAA, Kyn/Trp ratio, ICA/Trp ratio). Microbiota-metabolite correlations. Environmental impact analysis.
6. Observational Parameters
Primary Parameters:
Gut microbiota structure (α/β diversity, L. salivarius abundance). Serum ICA/Kyn concentrations (ng/ml).
Secondary Parameters:
Tryptophan pathway metabolites (Trp, IAA, ratios). Environmental factors (temperature, humidity, season). Demographics (gender, age, BMI). Stone history (type, frequency, seasonality). Comorbidities (hypertension, diabetes, intestinal diseases).
7. Randomization Not applicable (case-control design). Participants are assigned based on clinical diagnosis.
8. Blinding No blinding during enrollment. Laboratory personnel are blinded to group allocation during 16S rRNA sequencing and metabolomic analyses. Samples are coded, and statisticians design analysis plans before data unblinding.
9. Sample Size Calculation
Accounting for 10% attrition and multiple analyses, final recruitment targets:
200 cases and 100 controls (expected completions: 180 cases, 90 controls).
10. Statistical Analysis Descriptive Statistics: Mean±SD for continuous variables; frequencies for categorical variables.
Group Comparisons: t-test/Mann-Whitney U (continuous); χ²/Fisher's exact test (categorical).
Correlations: Spearman/partial correlation analysis. Multivariate Analysis: Linear/logistic regression adjusting for confounders. Microbiome Analysis: QIIME2 (α/β diversity, LEfSe, ANCOM). Metabolomics: MetaboAnalyst (pathway enrichment). Software: R 4.3.0; P<0.05 deemed significant.
11. Follow-up Plan
Screening Period (-7 days):
Informed consent. Demographics, medical history, physical exam, vital signs (blood pressure, pulse, temperature, respiration).
Case group: Collect routine renal function tests, electrolytes, and imaging data.
Sample Collection Phase:
Case Group:
Fecal sample (5g) for 16S rRNA sequencing. Venous blood (10ml) for LC-MS metabolomics. Residual surgical stones (if available).
Control Group:
Fecal sample (5g) and venous blood (10ml). All samples collected in a single visit. Follow-up via phone for health status confirmation.
Enrollment
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Inclusion criteria
Inclusion criteria for patients with kidney stones
Inclusion criteria for the healthy control group
Exclusion criteria
270 participants in 2 patient groups
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Central trial contact
Zhu Ruixuan
Data sourced from clinicaltrials.gov
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