One of the GEITP topics is to understand individual response to drugs and other environmental signals including toxicants. This “response” comprises the genetic architecture of each person or lab animal. To break it down further, this “response” includes genetics, epigenetics effects, environmental factors, endogenous influences, and our microbiome. Today’s topic is renal disease (which can be one of those endogenous influences): chronic kidney disease (CKD) is a major public health issue. Moreover, CDK can affect metabolism of drugs and environmental toxicants. Clinical trials in nephrology (study of the kidney) are still few and far between.
Genome-wide association studies (GWAS) and whole-exome sequencing (WES) of patients’ glomerular filtration rate — estimated from serum creatinine (eGFR; the main biomarker to quantify kidney function and to define CKD) — have identified nearly 100 eGFR-associated genetic loci in samples of Europeans, Asian, and multiple-ethnicity ancestry. However, just as with other multifactorial traits and complex diseases — identification of causal genes and molecular mechanisms (implicated by genetic associations) is challenging and has only been successful for a few kidney-function-associated loci. Advanced statistical fine-mapping approaches and newly emerging multi-tissue gene expression data provide new opportunities for prioritizing putative causal variants, effector genes, and target tissues from the results of large-scale GWAS meta-analyses.
Authors [see attached article] carried out a “trans-ancestry GWAS meta-analysis” in the CKD Genetics (CKDGen) Consortium (n = 765,348)
and replicated their findings in the Million Veteran Program (MVP; n = 280,722) — for a combined sample size of greater than 1 million
participants. The first aim of this study was to identify new globally important loci for kidney function (through maximizing statistical
power). Results from GWAS of the complementary kidney function marker blood urea nitrogen (BUN; n = 416,178) were used to prioritize the eGFR-associated loci on the basis of those most likely to be relevant for kidney function. A genetic risk score (GRS) for low eGFR was used to test relevance for clinically diagnosed CKD.The second aim was to characterize replicated eGFR-associated loci through complementary computational approaches, including various enrichment and network analyses, fine-mapping, and colocalization with gene expression in various tissues and protein levels.
Authors identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker, BUN (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A GRS for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Co-localization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide the most comprehensive priority list of molecular targets to date — for future CKD translational research.
DwN
Nat Genet June 2o19; 51: 957-972