Title | 1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function. |
Publication Type | Journal Article |
Year of Publication | 2017 |
Authors | Gorski M, van der Most PJ, Teumer A, et al. |
Secondary Authors | Fuchsberger C |
Journal | Sci Rep |
Volume | 7 |
Pagination | 45040 |
Date Published | 2017 04 28 |
ISSN | 2045-2322 |
Keywords | Computational Biology, Gene Frequency, Genetic Loci, Genome, Human, Genome-Wide Association Study, Genotyping Techniques, Humans, Kidney, Polymorphism, Single Nucleotide |
Abstract | HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value |
DOI | 10.1038/srep45040 |
Alternate Journal | Sci Rep |
PubMed ID | 28452372 |
PubMed Central ID | PMC5408227 |
Grant List | R21 DK112087 / DK / NIDDK NIH HHS / United States S10 OD018522 / OD / NIH HHS / United States UM1 CA182913 / CA / NCI NIH HHS / United States |