Metabolic-renal disease genetic architecture revealed by genomic structural equation modeling.

Physiologic mechanisms underlying metabolic and renal diseases interact and are highly comorbid, yet their genetic associations and underlying mechanisms have not been systematically elucidated. Using genome-wide association study (GWAS) summary statistics from UK Biobank, FinnGen, and CKDGen, we integrated and analyzed gout, serum urate, chronic kidney disease, kidney stones, and metabolic syndrome. Using genomic structural equation modeling (GSEM), we created the first genetic linkage map for 'gout-urate-kidney-metabolism' (GUKM) to explore shared genetic architecture. Post-GWAS analyses for GUKM-GSEM GWAS, including functional annotation, enrichment, fine-mapping, causal inference, and gsMap, identified key genetic loci, pathways, tissues/cell types, and potential drug targets. We identified 164 lead SNPs, including rs1260326 (chr2) and rs73607783 (chr8), with GSEA showing significant enrichment of GUKM-GSEM GWAS in cholesterol metabolism and lipid pathways (adjP < 0.05). Tissue and cell enrichment highlighted the liver, renal cortex, pancreas, proximal tubular epithelial cells, and hepatocytes (P < 0.05). Mendelian randomization indicated a potential causal role of GCKR (FDR < 0.05), which gsMap showed to be highly expressed in hepatocytes and liver tissue. The present study revealed the common genetic basis of metabolic and renal diseases and emphasized that lipid metabolism may be a key intermediary pathway connecting the 'metabolic-renal axis'. The liver, renal cortex, and pancreas were the primary enriched tissues, and GCKR was identified as a core gene and potential drug target. Overall, this study provides an important reference for the genetic mechanisms, key mechanisms, and intervention targets of related diseases.