Abstract
Genomewide association studies have identified numerous chronic kidney disease-associated genetic variants, but often do not pinpoint causal genes. This limitation was addressed by combining Mouse Genome Informatics with human genomewide association studies of kidney function. Genes for which mouse models showed abnormal renal physiology, morphology, glomerular filtration rate (GFR), or urinary albumin-to-creatinine ratio were identified from Mouse Genome Informatics. The corresponding human orthologs were then evaluated for GFR-associated single-nucleotide polymorphisms in 133,814 individuals and urinary albumin-to-creatinine ratio-associated SNPs in 54,451 individuals in genome-wide association studies meta-analysis of the CKDGen Consortium. After multiple testing corrections, significant associations with estimated GFR in humans were identified for single-nucleotide polymorphisms in 2, 7, and 17 genes causing abnormal GFR, abnormal physiology, and abnormal morphology in mice, respectively. Genes identified for abnormal kidney morphology showed significant enrichment for estimated GFR-associated single-nucleotide polymorphisms. In total, 19 genes contained variants associated with estimated GFR or the urinary albumin-to-creatinine ratio of which 16 mapped into previously reported genomewide significant loci. CYP26A1 and BMP4 emerged as novel signals subsequently validated in a large, independent study. An additional gene, CYP24A1, was discovered after conditioning on a published nearby association signal. Thus, our novel approach to combine comprehensive mouse phenotype information with human genomewide association studies data resulted in the identification of candidate genes for kidney disease pathogenesis.