Urolithiasis, a common urological disorder affecting about 10% of the global population, is known for its high recurrence rate, yet its genetic mechanisms remain poorly understood. This study aimed to fill this gap by identifying potential pathogenic genes associated with urolithiasis using a multi-omics Mendelian randomization approach. We conducted a comprehensive analysis that integrated genome-wide association studies (GWAS), expression quantitative trait loci (eQTL), methylation quantitative trait loci (mQTL), and protein quantitative trait loci (pQTL) data. Summary Data-Based Mendelian Randomization (SMR) and Bayesian colocalization analyses were employed to investigate causal relationships between gene expression and urolithiasis, while external validation and multivariable MR controlled for confounding factors. Seven genes were identified as significantly associated with urolithiasis, with LMAN2, NUCKS1, and L3MBTL3 highlighted as key contributors. LMAN2 was positively associated with urolithiasis risk (SMR b = 0.842, FDR < 0.05), with evidence that increased LMAN2 expression elevates stone formation likelihood, supported by findings from DNA methylation and protein level analyses. Conversely, NUCKS1 and L3MBTL3 exhibited protective effects, with NUCKS1 expression negatively associated with urolithiasis and supported by methylation at the cg12081870 site. Bayesian colocalization analysis showed strong shared genetic bases for NUCKS1 and L3MBTL3 with urolithiasis, with further multivariable MR confirming these associations were independent of BMI, smoking, alcohol consumption, and serum calcium levels. Genetic correlation analysis revealed significant positive genetic correlations between LMAN2 and urolithiasis (rg = 1.12, P = 8.11e-11), while NUCKS1 (rg = - 0.60, P = 3.10e-03) and L3MBTL3 (rg = - 0.38, P = 1.20e-03) showed strong negative correlations. These findings provide critical insights into the genetic basis of urolithiasis, identifying LMAN2, NUCKS1, and L3MBTL3 as potential biomarkers and therapeutic targets, offering a pathway toward personalized treatment strategies.

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http://dx.doi.org/10.1007/s00240-024-01675-zDOI Listing

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