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dc.contributor.authorWuttke, Matthias
dc.contributor.authorKöttgen, Anna
dc.contributor.authorPattaro, Cristian
dc.contributor.authorO'Connell, Jeffrey R.
dc.contributor.authorRyan, Kathleen A.
dc.contributor.authorParsa, Afshin
dc.date.accessioned2019-06-19T14:26:28Z
dc.date.available2019-06-19T14:26:28Z
dc.date.issued2019-05-31
dc.identifier.urihttp://hdl.handle.net/10713/9566
dc.descriptionThis research has been conducted using the UK Biobank resource under application number 20272. Any methods, additional references, Nature Research reporting summaries, source data, statements of code and data availability and associated accession codes are available at https://doi.org/10.1038/ s41588-019-0407-x.en_US
dc.description.abstractChronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we 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 blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization 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 a comprehensive priority list of molecular targets for translational research. © 2019, The Author(s), under exclusive licence to Springer Nature America, Inc.en_US
dc.description.sponsorshipThis study is supported by a consulting contract between Data Tecnica International and the National Institute on Aging (NIA), National Institutes of Health (NIH) and consults for Illumina, the Michael J. Fox Foundation and University of California Healthcare.en_US
dc.description.urihttps://doi.org/10.1038/s41588-019-0407-xen_US
dc.language.isoen_USen_US
dc.publisherNature Publishing Groupen_US
dc.relation.ispartofNature Geneticsen_US
dc.subject.meshRenal Insufficiency, Chronicen_US
dc.subject.meshGenetic Locien_US
dc.titleA catalog of genetic loci associated with kidney function from analyses of a million individuals(Article)en_US
dc.typeArticleen_US
dc.identifier.doi10.1038/s41588-019-0407-x


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