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NCT Number: NCT07043374

Impact of Humid-Heat on Gut-Tryptophan-Stone Pathway

Investigating the differences in gut microbiota composition and tryptophan metabolite levels between kidney stone patients and healthy individuals, with special focus on:

1. Comparing the gut microbiota composition between kidney stone patients and healthy controls, with emphasis on analyzing the relative abundance of Lactobacillus salivarius 2. Comparing the differences in tryptophan metabolite levels such as indole-3-carboxylic acid (ICA) and kynurenine (Kyn) in serum between the two groups 3. Exploring the correlation between gut microbiota composition and tryptophan metabolite levels 4. Analyzing the influence of different environmental conditions (seasons, temperature and humidity) on gut microbiota and metabolite levels

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Key information

About this study

  • Objectives

To investigate differences in gut microbiota composition and tryptophan metabolite levels between kidney stone patients and healthy individuals, specifically focusing on:

  • Comparing gut microbiota composition between stone patients and healthy controls, with emphasis on the relative abundance of Lactobacillus salivarius.
  • Comparing serum levels of tryptophan metabolites-indole-3-carboxylic acid (ICA) and kynurenine (Kyn)-between groups.
  • Exploring correlations between gut microbiota composition and tryptophan metabolite levels.
  • Analyzing the impact of environmental conditions (season, temperature/humidity) on gut microbiota and metabolite levels.
  • 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.
  • Participants Case Group: Patients diagnosed with kidney stones. Control Group: Healthy volunteers without kidney stones.
  • 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).

  • 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.

  • 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).

  • Randomization Not applicable (case-control design). Participants are assigned based on clinical diagnosis.
  • 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.
  • Sample Size Calculation

Accounting for 10% attrition and multiple analyses, final recruitment targets:

200 cases and 100 controls (expected completions: 180 cases, 90 controls).

  • 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.

  • 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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Inclusion criteria for patients with kidney stones
  • Age>=18 years;
  • Diagnosed with kidney stones by ultrasound, CT or urography;
  • Willing to provide stool samples and serum samples for study;
  • No history of antimicrobial use in the past 3 months;
  • Signed and dated informed consent indicating that the patient or his/her legal representative is fully informed of the study-related information and agrees to participate.
  • Inclusion criteria for the healthy control group
  • Age>=18 years;
  • No history of kidney stones and family history;
  • Imaging examination (such as abdominal ultrasound) showed no kidney stones;
  • Willing to provide stool samples and serum samples for research;
  • No history of antibiotic use in the past 3 months;
  • Signed and dated informed consent indicating that the volunteer is fully informed about the study-related information and agrees to participate.

Exclusion criteria

  • Use of antimicrobials or probiotics within the past 3 months;
  • Presence of active urinary tract infection;
  • Presence of other serious systemic diseases, such as hepatic or renal insufficiency, cardiac or pulmonary diseases, malignant tumors, and immunodeficiency states;
  • Congenital urinary tract abnormalities;
  • Previous history of kidney transplantation or urinary diversion surgery;
  • Pregnant or lactating women;
  • Presence of chronic intestinal diseases, such as inflammatory bowel disease, irritable bowel syndrome, etc.;
  • Inability to provide samples or complete follow-up according to the research protocol;
  • Participation in other clinical studies within the past 3 months;
  • Other conditions deemed unsuitable for participation in this study by the researcher.

Treatment and study plan

Primary outcomes

  1. Gut microbiota differences

    Time frame: 3 months postoperatively

    Comparison of gut microbiota composition between the case and control groups, particularly the relative abundance of Lactobacillus salivarius.

    Unit of Measure: Relative abundance (unitless proportion)

  2. Serum indole-3-carboxylic acid (ICA) concentration and Serum kynurenine (Kyn) concentration

    Time frame: 3 months postoperatively

    Comparison of serum ICA (indole-3-carboxylic acid) and Kyn (kynurenine) levels between the case and control groups.

    Unit of Measure: ng/mL.

Secondary outcomes

  1. Kynurenine to indole-3-carboxylic acid ratio (Kyn/ICA)

    Time frame: 3 months postoperatively

    Evaluation of differences in tryptophan metabolism-related metabolites across groups, with a focus on changes in the Kyn/ICA ratio.

    Unit of Measure: Ratio (unitless).

  2. Spearman correlation coefficient between Lactobacillus salivarius abundance and serum ICA concentration

    Time frame: 3 months postoperatively

    Unit of Measure: Correlation coefficient (ρ-value, unitless). Method: Spearman rank correlation analysis.

  3. Gut microbiota α-diversity

    Time frame: 3 months postoperatively

    Unit of Measure: Diversity index (e.g., Shannon index, unitless). Method: 16S rRNA gene sequencing; multivariate linear regression

  4. Gut microbiota β-diversity

    Time frame: 3 months postoperatively

    Unit of Measure: Dissimilarity index (e.g., Bray-Curtis, unitless). Method: 16S rRNA gene sequencing; PERMANOVA.

  5. Relative abundance of Lactobacillus salivarius

    Time frame: 3 months postoperatively

    Unit of Measure: Relative abundance (unitless proportion). Method: 16S rRNA gene sequencing; multivariate linear regression.

  6. Kidney stone recurrence status

    Time frame: 3 months postoperatively

    Unit of Measure: Binary outcome (Recurrence: Yes/No). Method: Ultrasound/CT detection (≥2mm stones); logistic regression.

  7. Mean ambient temperature

    Time frame: 3 months postoperatively

    Unit of Measure: °C. Method: Portable environmental recorder.

  8. Mean ambient relative humidity

    Time frame: 3 months postoperatively

    Unit of Measure: %. Method: Portable environmental recorder.

Study contacts

Contact information is provided by the study sponsor or research team.

Zhu Ruixuan

CONTACT

[email protected]

+86 13780820139

Sponsors and collaborators

Lead sponsor

Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Other

Registry information

Official study title

A Mechanistic Study on How Humid and Hot Environment Promotes Urinary Tract Stone Formation Through Influencing Gut Microbiota and Tryptophan Metabolism

Important dates

Study start
2026
Primary completion
2026
Study completion
2027
First posted
Jun 29, 2025
Registry last updated
Jan 21, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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