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1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function

Date Issued
2017-01-01
Author(s)
Gorski, Mathias
van der Most, Peter J.
Teumer, Alexander
Chu, Audrey Y.
Li, Man
Mijatovic, Vladan
Nolte, Ilja M.
Cocca, Massimiliano
Taliun, Daniel
Gomez, Felicia
Li, Yong
Tayo, Bamidele
Tin, Adrienne
Feitosa, Mary F.
Aspelund, Thor
Attia, John
Biffar, Reiner
Bochud, Murielle
Boerwinkle, Eric
Borecki, Ingrid
Bottinger, Erwin P.
Chen, Ming-Huei
Chouraki, Vincent
Ciullo, Marina
Coresh, Josef
Cornelis, Marilyn C.
Curhan, Gary C.
d'Adamo, Adamo Pio
Dehghan, Abbas
Dengler, Laura
Ding, Jingzhong
Eiriksdottir, Gudny
Endlich, Karlhans
Enroth, Stefan
Esko, Tõnu
Franco, Oscar H.
Gasparini, Paolo
Gieger, Christian
Girotto, Giorgia
Gottesman, Omri
Gudnason, Vilmundur
Gyllensten, Ulf
Hancock, Stephen J.
Harris, Tamara B.
Helmer, Catherine
Höllerer, Simon
Hofer, Edith
Hofman, Albert
Holliday, Elizabeth G.
Homuth, Georg
Hu, Frank B.
Huth, Cornelia
Hutri-Kähönen, Nina
Hwang, Shih-Jen
Imboden, Medea  
Johansson, Åsa
Kähönen, Mika
König, Wolfgang
Kramer, Holly
Krämer, Bernhard K.
Kumar, Ashish  
Kutalik, Zoltan
Lambert, Jean-Charles
Launer, Lenore J.
Lehtimäki, Terho
de Borst, Martin
Navis, Gerjan
Swertz, Morris
Liu, Yongmei
Lohman, Kurt
Loos, Ruth J. F.
Lu, Yingchang
Lyytikäinen, Leo-Pekka
McEvoy, Mark A.
Meisinger, Christa
Meitinger, Thomas
Metspalu, Andres
Metzger, Marie
Mihailov, Evelin
Mitchell, Paul
Nauck, Matthias
Oldehinkel, Albertine J.
Olden, Matthias
Wjh Penninx, Brenda
Pistis, Giorgio
Pramstaller, Peter P.
Probst-Hensch, Nicole  
Raitakari, Olli T.
Rettig, Rainer
Ridker, Paul M.
Rivadeneira, Fernando
Robino, Antonietta
Rosas, Sylvia E.
Ruderfer, Douglas
Ruggiero, Daniela
Saba, Yasaman
Sala, Cinzia
Schmidt, Helena
Schmidt, Reinhold
Scott, Rodney J.
Sedaghat, Sanaz
Smith, Albert V.
Sorice, Rossella
Stengel, Benedicte
Stracke, Sylvia
Strauch, Konstantin
Toniolo, Daniela
Uitterlinden, Andre G.
Ulivi, Sheila
Viikari, Jorma S.
Völker, Uwe
Vollenweider, Peter
Völzke, Henry
Vuckovic, Dragana
Waldenberger, Melanie
Jin Wang, Jie
Yang, Qiong
Chasman, Daniel I.
Tromp, Gerard
Snieder, Harold
Heid, Iris M.
Fox, Caroline S.
Köttgen, Anna
Pattaro, Cristian
Böger, Carsten A.
Fuchsberger, Christian
DOI
10.1038/srep45040
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 < 5 × 10(-8) previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples.
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