Login / Signup

Genome-Wide Association Studies of CKD and Related Traits.

Adrienne TinAnna Kottgen
Published in: Clinical journal of the American Society of Nephrology : CJASN (2020)
The past few years have seen major advances in genome-wide association studies (GWAS) of CKD and kidney function-related traits in several areas: increases in sample size from >100,000 to >1 million, enabling the discovery of >250 associated genetic loci that are highly reproducible; the inclusion of participants not only of European but also of non-European ancestries; and the use of advanced computational methods to integrate additional genomic and other unbiased, high-dimensional data to characterize the underlying genetic architecture and prioritize potentially causal genes and variants. Together with other large-scale biobank and genetic association studies of complex traits, these GWAS of kidney function-related traits have also provided novel insight into the relationship of kidney function to other diseases with respect to their genetic associations, genetic correlation, and directional relationships. A number of studies also included functional experiments using model organisms or cell lines to validate prioritized potentially causal genes and/or variants. In this review article, we will summarize these recent GWAS of CKD and kidney function-related traits, explain approaches for downstream characterization of associated genetic loci and the value of such computational follow-up analyses, and discuss related challenges along with potential solutions to ultimately enable improved treatment and prevention of kidney diseases through genetics.
Keyphrases
  • genome wide
  • copy number
  • dna methylation
  • genome wide association
  • chronic kidney disease
  • case control
  • risk assessment
  • big data
  • genome wide association study
  • deep learning