Elevated serum urate levels cause gout and correlate with cardiometabolic diseases via poorly understood mechanisms. We performed a trans-ancestry genome-wide association study of serum urate in 457,690 individuals, identifying 183 loci (147 previously unknown) that improve the prediction of gout in an independent cohort of 334,880 individuals. Serum urate showed significant genetic correlations with many cardiometabolic traits, with genetic causality analyses supporting a substantial role for pleiotropy. Enrichment analysis, fine-mapping of urate-associated loci and colocalization with gene expression in 47 tissues implicated the kidney and liver as the main target organs and prioritized potentially causal genes and variants, including the transcriptional master regulators in the liver and kidney, HNF1A and HNF4A. Experimental validation showed that HNF4A transactivated the promoter of ABCG2, encoding a major urate transporter, in kidney cells, and that HNF4Ap.Thr139Ile is a functional variant. Transcriptional coregulation within and across organs may be a general mechanism underlying the observed pleiotropy between urate and cardiometabolic traits.
GWAS of kidney function related traits and kidney disease
Chronic kidney disease (CKD) is a major health issue associated with cardiovascular outcomes. To expand the knowledge of its biological basis, large-scale meta-analyses of genome-wide association studies (GWAS) of renal function have already been conducted, but much unexplained heritability remains. The aim of the proposed research is to carry out GWAS of kidney function related traits and kidney disease, and to characterize known genetic risk loci in a large sample size for context-specific effects. We aim to analyze the UKBB data by itself and meta-analyze it with data from other cohorts and the CKDGen Consortium. CKD is a major health issue affecting >10% of adults in many countries worldwide. By finding genetic susceptibility loci we will increase our knowledge of biological and functional pathways underlying impaired kidney function. This knowledge will eventually support the improvement of the prevention, diagnosis and treatment of kidney diseases. We will check genetic markers across the whole human genome for association with kidney function measures estimated based on serum creatinine and urinary albumin-to-creatinine ratio, kidney disease, and decline of renal function over time. By revealing associated genetic loci and genes, we will obtain insight into the biological functions that may cause kidney diseases. This knowledge will eventually help to improve the prevention of the disease, and the design and development of drugs for the condition. Full cohort with available genetic data (imputed Axiom Genotyping Array data)
|Lead investigator:||Dr Alexander Teumer|
|Lead institution:||University of Greifswald|