Cross-Species Comparison between Mouse Kidney Multi-Omics and Human Genome-Wide Association Studies Highlights Molecular Features Associated with Oxalate Nephropathy

Background: – Urolithiasis, a recurrent and increasingly prevalent disease worldwide, has a complex pathophysiology that hinders a comprehensive understanding.Methods: – We performed a cross-species integrative analysis combining multi-omics profiling of kidneys from a hyperoxaluric mouse model and summary statistics from a large-scale human genome-wide association study (GWAS).Results: – In the multi-omics analysis of kidneys from a hyperoxaluric mouse model using RNA-seq, whole-cell proteomics, and phosphoproteomics, we identified 1, 173 genes, 342 proteins, and 516 phosphorylated peptides that were differentially expressed compared with control mice. We utilized publicly available large-scale meta-GWAS summary statistics of urolithiasis from BioBank Japan, UK Biobank, and FinnGen (n = 198, 769) and prioritized genes using gene enrichment analysis. Through cross-species integration of mouse and human omics, we identified 46 molecules potentially relevant to urolithiasis, hereafter referred to as cross-species urolithiasis-related molecules. We examined the expression and genetic associations of these 46 molecules in human urolithiasis. Among these, CRYAB and SHROOM3 showed differential expression in human renal papilla tissues with and without stones. Colocalization analysis between urolithiasis GWAS and expression quantitative trait loci (eQTL) data of human renal tubules and glomeruli suggested shared signals at the GLUD1, UMOD, SLC34A1, TCEA3, and H1-0 regions. Mendelian randomization analysis using the same renal eQTL datasets further supported these findings, with GLUD1, UMOD, TCEA3, and H1-0 showing statistically significant associations, suggesting a strong genetic link with urolithiasis.Conclusions: – The study's findings highlight a set of cross-species urolithiasis-related molecules, supported by both expression and genetic evidence, offering insights for future functional validation and mechanistic investigations.