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

Gorski, Mathias and van der Most, Peter J. and Teumer, Alexander and Chu, Audrey Y. and Li, Man and Mijatovic, Vladan and Nolte, Ilja M. and Cocca, Massimiliano and Taliun, Daniel and Gomez, Felicia and Li, Yong and Tayo, Bamidele and Tin, Adrienne and Feitosa, Mary F. and Aspelund, Thor and Attia, John and Biffar, Reiner and Bochud, Murielle and Boerwinkle, Eric and Borecki, Ingrid and Bottinger, Erwin P. and Chen, Ming-Huei and Chouraki, Vincent and Ciullo, Marina and Coresh, Josef and Cornelis, Marilyn C. and Curhan, Gary C. and d'Adamo, Adamo Pio and Dehghan, Abbas and Dengler, Laura and Ding, Jingzhong and Eiriksdottir, Gudny and Endlich, Karlhans and Enroth, Stefan and Esko, Tõnu and Franco, Oscar H. and Gasparini, Paolo and Gieger, Christian and Girotto, Giorgia and Gottesman, Omri and Gudnason, Vilmundur and Gyllensten, Ulf and Hancock, Stephen J. and Harris, Tamara B. and Helmer, Catherine and Höllerer, Simon and Hofer, Edith and Hofman, Albert and Holliday, Elizabeth G. and Homuth, Georg and Hu, Frank B. and Huth, Cornelia and Hutri-Kähönen, Nina and Hwang, Shih-Jen and Imboden, Medea and Johansson, Åsa and Kähönen, Mika and König, Wolfgang and Kramer, Holly and Krämer, Bernhard K. and Kumar, Ashish and Kutalik, Zoltan and Lambert, Jean-Charles and Launer, Lenore J. and Lehtimäki, Terho and de Borst, Martin and Navis, Gerjan and Swertz, Morris and Liu, Yongmei and Lohman, Kurt and Loos, Ruth J. F. and Lu, Yingchang and Lyytikäinen, Leo-Pekka and McEvoy, Mark A. and Meisinger, Christa and Meitinger, Thomas and Metspalu, Andres and Metzger, Marie and Mihailov, Evelin and Mitchell, Paul and Nauck, Matthias and Oldehinkel, Albertine J. and Olden, Matthias and Wjh Penninx, Brenda and Pistis, Giorgio and Pramstaller, Peter P. and Probst-Hensch, Nicole and Raitakari, Olli T. and Rettig, Rainer and Ridker, Paul M. and Rivadeneira, Fernando and Robino, Antonietta and Rosas, Sylvia E. and Ruderfer, Douglas and Ruggiero, Daniela and Saba, Yasaman and Sala, Cinzia and Schmidt, Helena and Schmidt, Reinhold and Scott, Rodney J. and Sedaghat, Sanaz and Smith, Albert V. and Sorice, Rossella and Stengel, Benedicte and Stracke, Sylvia and Strauch, Konstantin and Toniolo, Daniela and Uitterlinden, Andre G. and Ulivi, Sheila and Viikari, Jorma S. and Völker, Uwe and Vollenweider, Peter and Völzke, Henry and Vuckovic, Dragana and Waldenberger, Melanie and Jin Wang, Jie and Yang, Qiong and Chasman, Daniel I. and Tromp, Gerard and Snieder, Harold and Heid, Iris M. and Fox, Caroline S. and Köttgen, Anna and Pattaro, Cristian and Böger, Carsten A. and Fuchsberger, Christian. (2017) 1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function. Scientific reports, 7. p. 45040.

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Official URL: http://edoc.unibas.ch/55317/

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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.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Chronic Disease Epidemiology > Genetic Epidemiology of Non-Communicable Diseases (Probst-Hensch)
03 Faculty of Medicine > Departement Public Health > Sozial- und Präventivmedizin > Genetic Epidemiology of Non-Communicable Diseases (Probst-Hensch)
UniBasel Contributors:Imboden, Medea and Kumar, Ashish and Probst Hensch, Nicole
Item Type:Article, refereed
ISSN:0169-5487
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:06 Jun 2017 12:26
Deposited On:06 Jun 2017 12:26

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