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

Gorski, M.; van der Most, P.J.; Teumer, A.; Chu, A.Y.; Li, M.; Mijatovic, V.; Nolte, I.M.; Cocca, M.; Taliun, D.; Gomez, F.; Li, Y.; Tayo, B.; Tin, A.; Feitosa, M.F.; Aspelund, T.; Attia, J.; Biffar, R.; Bochud, M.; Boerwinkle, E.; Borecki, I.; Bottinger, E.P.; Chen, M.H.; Chouraki, V.; Ciullo, M.; Coresh, J.; Cornelis, M.C.; Curhan, G.C.; d'Adamo, A.P.; Dehghan, A.; Dengler, L.; Ding, J.; Eiriksdottir, G.; Endlich, K.; Enroth, S.; Esko, T.; Franco, O.H.; Gasparini, P.; Gieger, C.; Girotto, G.; Gottesman, O.; Gudnason, V.; Gyllensten, U.; Hancock, S.J.; Harris, T.B.; Helmer, C.; Höllerer, S.; Hofer, E.; Hofman, A.; Holliday, E.G.; Homuth, G.; Hu, F.B.; Huth, C.; Hutri-Kähönen, N.; Hwang, S.J.; Imboden, M.; Johansson, Å.; Kähönen, M.; König, W.; Kramer, H.; Krämer, B.K.; Kumar, A.; Kutalik, Z.; Lambert, J.C.; Launer, L.J.; Lehtimäki, T.; de Borst, M.; Navis, G.; Swertz, M.; Liu, Y.; Lohman, K.; Loos, RJF; Lu, Y.; Lyytikäinen, L.P.; McEvoy, M.A.; Meisinger, C.; Meitinger, T.; Metspalu, A.; Metzger, M.; Mihailov, E.; Mitchell, P.; Nauck, M.; Oldehinkel, A.J.; Olden, M.; Wjh Penninx, B.; Pistis, G.; Pramstaller, P.P.; Probst-Hensch, N.; Raitakari, O.T.; Rettig, R.; Ridker, P.M.; Rivadeneira, F.; Robino, A.; Rosas, S.E.; Ruderfer, D.; Ruggiero, D.; Saba, Y.; Sala, C.; Schmidt, H.; Schmidt, R.; Scott, R.J.; Sedaghat, S.; Smith, A.V.; Sorice, R.; Stengel, B.; Stracke, S.; Strauch, K.; Toniolo, D.; Uitterlinden, A.G.; Ulivi, S.; Viikari, J.S.; Völker, U.; Vollenweider, P.; Völzke, H.; Vuckovic, D.; Waldenberger, M.; Jin Wang, J.; Yang, Q.; Chasman, D.I.; Tromp, G.; Snieder, H.; Heid, I.M.; Fox, C.S.; Köttgen, A.; Pattaro, C.; Böger, C.A.; Fuchsberger, C.

doi:10.1038/srep45040

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

Details

Download: BIB_DA35C65A8356.pdf (780.25 [Ko])
State: Public
Version: Final published version

Serval ID

serval:BIB_DA35C65A8356

Type

Article: article from journal or magazin.

Collection

Publications

Institution

UNIL/CHUV

Title

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

Journal

Scientific reports

Author(s)

Gorski M., van der Most P.J., Teumer A., Chu A.Y., Li M., Mijatovic V., Nolte I.M., Cocca M., Taliun D., Gomez F., Li Y., Tayo B., Tin A., Feitosa M.F., Aspelund T., Attia J., Biffar R., Bochud M., Boerwinkle E., Borecki I., Bottinger E.P., Chen M.H., Chouraki V., Ciullo M., Coresh J., Cornelis M.C., Curhan G.C., d'Adamo A.P., Dehghan A., Dengler L., Ding J., Eiriksdottir G., Endlich K., Enroth S., Esko T., Franco O.H., Gasparini P., Gieger C., Girotto G., Gottesman O., Gudnason V., Gyllensten U., Hancock S.J., Harris T.B., Helmer C., Höllerer S., Hofer E., Hofman A., Holliday E.G., Homuth G., Hu F.B., Huth C., Hutri-Kähönen N., Hwang S.J., Imboden M., Johansson Å., Kähönen M., König W., Kramer H., Krämer B.K., Kumar A., Kutalik Z., Lambert J.C., Launer L.J., Lehtimäki T., de Borst M., Navis G., Swertz M., Liu Y., Lohman K., Loos RJF, Lu Y., Lyytikäinen L.P., McEvoy M.A., Meisinger C., Meitinger T., Metspalu A., Metzger M., Mihailov E., Mitchell P., Nauck M., Oldehinkel A.J., Olden M., Wjh Penninx B., Pistis G., Pramstaller P.P., Probst-Hensch N., Raitakari O.T., Rettig R., Ridker P.M., Rivadeneira F., Robino A., Rosas S.E., Ruderfer D., Ruggiero D., Saba Y., Sala C., Schmidt H., Schmidt R., Scott R.J., Sedaghat S., Smith A.V., Sorice R., Stengel B., Stracke S., Strauch K., Toniolo D., Uitterlinden A.G., Ulivi S., Viikari J.S., Völker U., Vollenweider P., Völzke H., Vuckovic D., Waldenberger M., Jin Wang J., Yang Q., Chasman D.I., Tromp G., Snieder H., Heid I.M., Fox C.S., Köttgen A., Pattaro C., Böger C.A., Fuchsberger C.

ISSN

2045-2322 (Electronic)

ISSN-L

2045-2322

Publication state

Published

Issued date

28/04/2017

Peer-reviewed

Oui

Volume

Pages

45040

Language

english

Notes

Publication types: Journal Article
Publication Status: epublish

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.

URN

urn:nbn:ch:serval-BIB_DA35C65A83562

OAI-PMH

oai:serval.unil.ch:BIB_DA35C65A8356

DOI

10.1038/srep45040

Pubmed

28452372

Web of science

000400432700001

Open Access

Yes