Meta-analysis of Clinical Microbiome Studies in Urolithiasis Reveal Age, Stone Composition, and Study Location as the Predominant Factors in Urolithiasis-Associated Microbiome Composition.

To determine whether functionally relevant questions associated with the urinary or gut microbiome and urinary stone disease (USD) can be answered from metagenome-wide association studies (MWAS), we performed the most comprehensive meta-analysis of published clinical MWAS in USD to date, using publicly available data published prior to April 2021. Six relevant studies met inclusion criteria. For alpha-diversity, significant differences were noted between USD status, stone composition, sample type, study location, age, diet, and sex. For beta-diversity, significant differences were noted by USD status, stone composition, sample type, study location, antibiotic use (30 days and 12 months before sampling), sex, hypertension, water intake, body habitus, and age. and in the gut and urinary tract, respectively, were associated with healthy individuals, while was associated with USD in the urine and stones. Paradoxically, other strains were also strongly associated with USD in the gut microbiome. When data were analyzed together, USD status, stone composition, age group, and study location were the predominant factors associated with microbiome composition. Meta-analysis showed significant microbiome differences based on USD status, stone composition, age group or study location. However, analyses were limited by a lack of public data from published studies, metadata collected, and differing study protocols. Results highlight the need for field-specific standardization of experimental protocols in terms of sample collection procedures and the anatomical niches to assess, as well as in defining clinically relevant metadata and subphenotypes such as stone composition. Studies focused on the microbiome broadly support the hypothesis that the microbiome influences the onset of chronic diseases such as urinary stone disease. However, it is unclear what environmental factors shape the microbiome in ways that increase the risk for chronic disease. In addition, it is unclear how differences in study methodology can impact the results of clinical metagenome-wide association studies. In the current meta-analysis, we show that age, stone composition, and study location are the predominant factors that associate with the microbiome and USD status. Furthermore, we reveal differences in results based on specific analytical protocols, which impacts the interpretation of any microbiome study.