Kidney CalculiNCT07043374
Impact of Humid-Heat on Gut-Tryptophan-Stone Pathway
An observational study of Kidney Calculi and Ureteral Calculi, run by Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Kidney Calculi, Ureteral Calculi
- How many people
- 270 participants
- Where
- No sites listed yet
- Study dates
- 1 Sep 2026to 31 Dec 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Case group: Patients diagnosed with kidney stones Control group: Healthy volunteers without kidney stones
Who may be able to join
- 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.
- Age>=18 years;
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- 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.
Who cannot join
- 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;
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- 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.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: A Mechanistic Study on How Humid and Hot Environment Promotes Urinary Tract Stone Formation Through Influencing Gut Microbiota and Tryptophan Metabolism
Investigating the differences in gut microbiota composition and tryptophan metabolite levels between kidney stone patients and healthy individuals, with special focus on:
- Comparing the gut microbiota composition between kidney stone patients and healthy controls, with emphasis on analyzing the relative abundance of Lactobacillus salivarius
- Comparing the differences in tryptophan metabolite levels such as indole-3-carboxylic acid (ICA) and kynurenine (Kyn) in serum between the two groups
- Exploring the correlation between gut microbiota composition and tryptophan metabolite levels
- Analyzing the influence of different environmental conditions (seasons, temperature and humidity) on gut microbiota and metabolite levels
Read the detailed description
- 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.
- Conditions
- Kidney Calculi, Ureteral Calculi
- Medical subject headings
- Kidney Calculi, Ureteral Calculi
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Kidney Stone Group | Patients diagnosed with kidney stones via imaging examinations (ultrasound, CT, or urography) were recruited from both outpatient clinics and inpatient departments of the Urology Department at our hospital. | |
| Healthy Control Group | 1. Recruit healthy volunteers confirmed by imaging examinations to be free of kidney stones from our hospital's Physical Examination Center. 2. Recruit patients with no history of kidney diseases from other departments of our hospital (e.g., Department of Orthopedics, Department of General Surgery). 3. Recruit healthy volunteers through community outreach, confirmed by ultrasound examination to be free of kidney stones. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Gut microbiota differences
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)
Measured: 3 months postoperatively
Serum indole-3-carboxylic acid (ICA) concentration and Serum kynurenine (Kyn) concentration
Comparison of serum ICA (indole-3-carboxylic acid) and Kyn (kynurenine) levels between the case and control groups.
Unit of Measure: ng/mL.
Measured: 3 months postoperatively
Secondary outcomes (8)
Kynurenine to indole-3-carboxylic acid ratio (Kyn/ICA)
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).
Measured: 3 months postoperatively
Spearman correlation coefficient between Lactobacillus salivarius abundance and serum ICA concentration
Unit of Measure: Correlation coefficient (ρ-value, unitless). Method: Spearman rank correlation analysis.
Measured: 3 months postoperatively
Gut microbiota α-diversity
Unit of Measure: Diversity index (e.g., Shannon index, unitless). Method: 16S rRNA gene sequencing; multivariate linear regression
Measured: 3 months postoperatively
Gut microbiota β-diversity
Unit of Measure: Dissimilarity index (e.g., Bray-Curtis, unitless). Method: 16S rRNA gene sequencing; PERMANOVA.
Measured: 3 months postoperatively
Relative abundance of Lactobacillus salivarius
Unit of Measure: Relative abundance (unitless proportion). Method: 16S rRNA gene sequencing; multivariate linear regression.
Measured: 3 months postoperatively
Kidney stone recurrence status
Unit of Measure: Binary outcome (Recurrence: Yes/No). Method: Ultrasound/CT detection (≥2mm stones); logistic regression.
Measured: 3 months postoperatively
Mean ambient temperature
Unit of Measure: °C. Method: Portable environmental recorder.
Measured: 3 months postoperatively
Mean ambient relative humidity
Unit of Measure: %. Method: Portable environmental recorder.
Measured: 3 months postoperatively
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Jun 2025
- Study start1 Sep 2026 (estimated)
- Primary completion20 Nov 2026 (estimated)
- Study completion31 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Kidney CalculiStudies of the same condition, open and under way.
- More trials run by Shanghai General Hospital, Shanghai Jiao Tong University School of MedicineThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 270 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yi Shao, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
- Investigators
- Shao Yi, Principal investigator, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07043374
- Sponsor's protocol ID
- IIT2025-059
- Status last verified
- Jan 2026
- First submitted
- 21 May 2025
- Last updated
- 21 Jan 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 21 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Mechanistic Study on How Humid and Hot Environment Promotes Urinary Tract Stone Formation Through Influencing Gut Microbiota and Tryptophan Metabolism
- ClinicalTrials.gov ID
- NCT07043374
- Acronym / sponsor ID
- IIT2025-059
- Conditions
- Kidney Calculi, Ureteral Calculi
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 270 participants (estimated)
- Lead sponsor
- Shanghai General Hospital, Shanghai Jiao Tong University School of MedicineUniversity, hospital or other
- Study start
- 1 Sep 2026 (estimated)
- Primary completion
- 20 Nov 2026 (estimated)
- Study completion
- 31 Dec 2027 (estimated)
- First posted
- 29 Jun 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Investigating the differences in gut microbiota composition and tryptophan metabolite levels between kidney stone patients and healthy individuals, with special focus on:
- Comparing the gut microbiota composition between kidney stone patients and healthy controls, with emphasis on analyzing the relative abundance of Lactobacillus salivarius
- Comparing the differences in tryptophan metabolite levels such as indole-3-carboxylic acid (ICA) and kynurenine (Kyn) in serum between the two groups
- Exploring the correlation between gut microbiota composition and tryptophan metabolite levels
- Analyzing the influence of different environmental conditions (seasons, temperature and humidity) on gut microbiota and metabolite levels
Detailed description
- 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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Kidney Stone Group | – | –Patients diagnosed with kidney stones via imaging examinations (ultrasound, CT, or urography) were recruited from both outpatient clinics and inpatient departments of the Urology Department at our hospital. |
| Healthy Control Group | – | –1. Recruit healthy volunteers confirmed by imaging examinations to be free of kidney stones from our hospital's Physical Examination Center. 2. Recruit patients with no history of kidney diseases from other departments of our hospital (e.g., Department of Orthopedics, Department of General Surgery). 3. Recruit healthy volunteers through community outreach, confirmed by ultrasound examination to be free of kidney stones. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Case group: Patients diagnosed with kidney stones Control group: Healthy volunteers without kidney stones
Key inclusion criteria (11 listed)
Key exclusion criteria (10 listed)
- 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;
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
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)
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.
8 secondary outcomes
Kynurenine to indole-3-carboxylic acid ratio (Kyn/ICA)
Time frame: 3 months postoperatively
Spearman correlation coefficient between Lactobacillus salivarius abundance and serum ICA concentration
Time frame: 3 months postoperatively
Gut microbiota α-diversity
Time frame: 3 months postoperatively
Gut microbiota β-diversity
Time frame: 3 months postoperatively
Relative abundance of Lactobacillus salivarius
Time frame: 3 months postoperatively
Kidney stone recurrence status
Time frame: 3 months postoperatively
Mean ambient temperature
Time frame: 3 months postoperatively
Mean ambient relative humidity
Time frame: 3 months postoperatively
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Jan 2026.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Shao Yi principal investigator
Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
Questions about this trial
What is this clinical trial studying?
An observational study of Kidney Calculi and Ureteral Calculi, run by Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 11 inclusion and 10 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 21 Jan 2026. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Zhu Ruixuan (+86 13780820139, luluzhu2023@qq.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Gut microbiota differences (time frame: 3 months postoperatively). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Jan 2026.