Genome-wide association studies (GWAS) are often used to study complex disorders such as chronic kidney disease (CKD), which represents a substantial global health burden. “Larger sample sizes, better statistical methods and new publicly available omics data sets enabled us to detect novel lower frequency variants associated with CKD, and to map causal genes,” report Anna Köttgen, Cristian Pattaro and colleagues.
In a trans-ancestry meta-analysis of data from >700,000 individuals, the researchers first identified genome-wide significant loci associated with creatinine-based estimated glomerular filtration rate (eGFR). “These loci explain nearly 20% of eGFR genetic heritability, which doubles previous estimates,” remarks Pattaro. Another GWAS cohort of nearly 300,000 individuals enabled the replication of 264 single-nucleotide polymorphisms (SNPs), of which 147 were significantly associated with blood urea nitrogen (BUN) and prioritized for analysis as they were more likely to be directly linked to renal function, not just creatinine metabolism. In fact, a genetic risk score based on these 147 SNPs was associated with higher odds ratios of renal disease in a cohort of nearly 0.5 million individuals. “These results support the clinical and epidemiological relevance of our findings,” remarks Köttgen.
The researchers also performed colocalization analyses of transcripts mapped to eGFR-associated loci with gene expression data from 46 tissues, including micro-dissected renal tubules and glomeruli. “This is an unbiased way to highlight the most likely causal genes and tissues,” explains Pattaro. “Fine-mapping analysis also allowed us to narrow down GWAS association signals to single causal variants or genes, and we identified missense variants in 11 genes.”
“We created a large list of candidate genes for translational research and all our results are publicly available,” notes Köttgen. “This is perhaps one of the most important features of this kind of large-scale effort: the generation and sharing of a resource that can be used for many additional projects.”
Wuttke, M. et al. A catalog of genetic loci associated with kidney function from analyses of a million individuals. Nat. Genet. 51, 957–972 (2019)
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Wang, M. A million genotypes to find CKD-linked loci. Nat Rev Nephrol 15, 458 (2019). https://doi.org/10.1038/s41581-019-0170-3