Imputation-powered whole-exome analysis identifies genes associated with kidney function and disease in the UK Biobank.
Nat Commun
; 14(1): 1287, 2023 03 09.
Article
em En
| MEDLINE
| ID: mdl-36890159
ABSTRACT
Genome-wide association studies have discovered hundreds of associations between common genotypes and kidney function but cannot comprehensively investigate rare coding variants. Here, we apply a genotype imputation approach to whole exome sequencing data from the UK Biobank to increase sample size from 166,891 to 408,511. We detect 158 rare variants and 105 genes significantly associated with one or more of five kidney function traits, including genes not previously linked to kidney disease in humans. The imputation-powered findings derive support from clinical record-based kidney disease information, such as for a previously unreported splice allele in PKD2, and from functional studies of a previously unreported frameshift allele in CLDN10. This cost-efficient approach boosts statistical power to detect and characterize both known and novel disease susceptibility variants and genes, can be generalized to larger future studies, and generates a comprehensive resource ( https//ckdgen-ukbb.gm.eurac.edu/ ) to direct experimental and clinical studies of kidney disease.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Estudo de Associação Genômica Ampla
/
Exoma
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
País/Região como assunto:
Europa
Idioma:
En
Revista:
Nat Commun
Ano de publicação:
2023
Tipo de documento:
Article