The goal of this observational study is to investigate the systemic pathogenesis and identify potential diagnostic biomarkers in patients with ureteral stricture and healthy volunteers. The main questions it aims to answer are: What are the systemic differences in the gut microbiome, urine microbiome, and metabolomic profiles (fecal, urinary, and serum) between patients with ureteral stricture and healthy controls? What are the correlations between these microbial/metabolic alterations and clinical phenotypes, such as stricture severity, inflammatory levels, and renal function? Researchers will compare the biological panoramic profiles of patients with ureteral stricture to those of healthy controls to see if specific "microbiome-metabolite-disease" regulatory networks drive the development of the condition. Participants will: Provide stool samples for gut microbiome (16S/Metagenomics) and metabolomic analysis. Provide urine samples for urine microbiome and metabolomic analysis. Provide blood (serum) samples for systemic metabolomic profiling. Undergo clinical assessments, including medical history collection, imaging (e.g., CT/IVP), and laboratory tests (e.g., renal function, inflammatory markers) to evaluate disease severity.
Background and Scientific Rationale Ureteral stricture is a major urological challenge that leads to urinary tract obstruction and progressive renal impairment. While its etiology is diverse-ranging from iatrogenic injury to congenital anomalies-the underlying molecular mechanisms, particularly in inflammatory and idiopathic cases, remain poorly understood. Current surgical interventions carry a risk of recurrence, underscoring the urgent need to identify systemic biomarkers and novel therapeutic targets. The Gut-Kidney Axis and Urinary Microbiome Recent advances have highlighted the "gut-kidney axis," where the gut microbiota and its metabolites modulate distant organ pathology through immune regulation and metabolic signaling. Furthermore, the discovery of a unique urinary microbiome has challenged the traditional view of urinary sterility, suggesting that local dysbiosis may contribute to urological diseases. Metabolites, serving as the functional intermediaries between the microbiome and the host phenotype, provide a critical bridge to understanding these complex interactions. Integrated Multi-omics Strategy This study adopts an innovative integrated multi-omics approach to characterize the biological landscape of ureteral stricture across three compartments: the intestine, the urinary tract, and the systemic circulation. By combining high-throughput sequencing of gut and urine microbiomes with mass spectrometry-based metabolomic profiling (fecal, urinary, and serum), we aim to: Map Systemic Dysbiosis: Identify specific microbial taxa and metabolic signatures that distinguish patients with ureteral stricture from healthy individuals. Elucidate Regulatory Networks: Construct "microbiome-metabolite-disease" networks to explore how microbial alterations correlate with clinical phenotypes, such as fibrosis markers, inflammatory levels, and renal function indicators. Identify Functional Pathways: Utilize functional enrichment analysis to pinpoint metabolic pathways (e.g., those related to inflammation or tissue fibrosis) that are modulated by the microbiota. Clinical Significance The ultimate goal of this research is to provide a systemic biological perspective on the pathogenesis of ureteral stricture. By integrating cross-platform data, we expect to identify high-sensitivity non-invasive biomarkers for early diagnosis and provide a theoretical foundation for future microecology-targeted interventions.
Study Type
OBSERVATIONAL
Enrollment
120
Department of Urology, The First Affiliated Hospital of Chongqing Medical University
Chongqing, China
Differences in Gut and Urinary Microbiome Composition
Comparison of microbial diversity and taxonomic composition between ureteral stricture patients and healthy controls. Metrics include Alpha-diversity (e.g., Shannon Index), Beta-diversity (e.g., PCoA based on Bray-Curtis distance), and relative abundance of specific microbial taxa from Phylum to Genus levels using 16S rRNA or metagenomic sequencing.
Time frame: Baseline (at the time of sample collection, within 1 week of enrollment)
Differential Metabolomic Profiles in Fecal, Urinary, and Serum Samples
Identification of significantly different metabolites between the two groups. Parameters include the concentration and relative intensity of metabolites identified via LC-MS/MS or GC-MS. Significant metabolites will be screened based on Variable Importance in Projection (VIP) \> 1.0 and p-value \< 0.05 from multivariate and univariate statistical analyses.
Time frame: Baseline (at the time of sample collection, within 1 week of enrollment)
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