Urolithiasis and osteoporosis are two prevalent conditions with potentially overlapping pathophysiological mechanisms. While urolithiasis is characterized by the formation of urinary stones, osteoporosis involves reduced bone density and an increased risk of fractures. Previous studies suggest a possible clinical and genetic association between these conditions. This study aims to analyze their epidemiological distribution, genetic predispositions, and potential risk factors using a large-scale genomic dataset.

A cohort of 54,823 individuals was initially selected from the TPMI database (version: tpmi037). Urolithiasis was identified using ICD-10 diagnostic codes (N20.0, N20.1, N20.2, N20.9, N22) and corresponding procedure codes (50023B, 76016B, 77026B, 77027B, 77028B). Osteoporosis was diagnosed based on ICD-10 codes (M80–M82) and osteoporotic fractures at various sites. Stringent sample quality control measures were applied, including sex verification, duplicate sample removal, call rate checks, homozygosity checks, and ancestry divergence filtering, resulting in a final dataset of 54,146 samples. A genome-wide association study (GWAS) was conducted to identify genetic variants associated with these conditions, with multiple testing corrections applied via Bonferroni (p<1.13e-07) and False Discovery Rate (FDR) methods.

The age distribution analysis indicated that males had a higher prevalence of urolithiasis than females, except in the 20–30 age group. Conversely, osteoporosis was more common in females across all age groups. A total of 151 significant SNPs related to urolithiasis and osteoporosis were identified. Further Mendelian randomization (MR) analysis was performed to assess causality, using instrumental variables that met the significance threshold of p<0.05. Additionally, key clinical variables, such as serum calcium, creatinine levels, and glomerular filtration rate, were analyzed for their potential roles in disease manifestation.

This study provides insights into the epidemiological and genetic correlations between urolithiasis and osteoporosis. The findings suggest a potential shared genetic basis and metabolic pathways underlying both conditions. Future research should focus on refining the case-control definitions based on clinical covariates and incorporating additional biomarkers to improve disease risk prediction.