| Title |
1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function
|
|---|---|
| Published in |
Scientific Reports, April 2017
|
| DOI | 10.1038/srep45040 |
| Pubmed ID | |
| Authors |
Mathias Gorski, Peter J. van der Most, Alexander Teumer, Audrey Y. Chu, Man Li, Vladan Mijatovic, Ilja M. Nolte, Massimiliano Cocca, Daniel Taliun, Felicia Gomez, Yong Li, Bamidele Tayo, Adrienne Tin, Mary F. Feitosa, Thor Aspelund, John Attia, Reiner Biffar, Murielle Bochud, Eric Boerwinkle, Ingrid Borecki, Erwin P. Bottinger, Ming-Huei Chen, Vincent Chouraki, Marina Ciullo, Josef Coresh, Marilyn C. Cornelis, Gary C. Curhan, Adamo Pio d’Adamo, Abbas Dehghan, Laura Dengler, Jingzhong Ding, Gudny Eiriksdottir, Karlhans Endlich, Stefan Enroth, Tõnu Esko, Oscar H. Franco, Paolo Gasparini, Christian Gieger, Giorgia Girotto, Omri Gottesman, Vilmundur Gudnason, Ulf Gyllensten, Stephen J. Hancock, Tamara B. Harris, Catherine Helmer, Simon Höllerer, Edith Hofer, Albert Hofman, Elizabeth G. Holliday, Georg Homuth, Frank B. Hu, Cornelia Huth, Nina Hutri-Kähönen, Shih-Jen Hwang, Medea Imboden, Åsa Johansson, Mika Kähönen, Wolfgang König, Holly Kramer, Bernhard K. Krämer, Ashish Kumar, Zoltan Kutalik, Jean-Charles Lambert, Lenore J. Launer, Terho Lehtimäki, Martin H. de Borst, Gerjan Navis, Morris Swertz, Yongmei Liu, Kurt Lohman, Ruth J. F. Loos, Yingchang Lu, Leo-Pekka Lyytikäinen, Mark A. McEvoy, Christa Meisinger, Thomas Meitinger, Andres Metspalu, Marie Metzger, Evelin Mihailov, Paul Mitchell, Matthias Nauck, Albertine J. Oldehinkel, Matthias Olden, Brenda WJH Penninx, Giorgio Pistis, Peter P. Pramstaller, Nicole Probst-Hensch, Olli T. Raitakari, Rainer Rettig, Paul M. Ridker, Fernando Rivadeneira, Antonietta Robino, Sylvia E. Rosas, Douglas Ruderfer, Daniela Ruggiero, Yasaman Saba, Cinzia Sala, Helena Schmidt, Reinhold Schmidt, Rodney J. Scott, Sanaz Sedaghat, Albert V. Smith, Rossella Sorice, Benedicte Stengel, Sylvia Stracke, Konstantin Strauch, Daniela Toniolo, Andre G. Uitterlinden, Sheila Ulivi, Jorma S. Viikari, Uwe Völker, Peter Vollenweider, Henry Völzke, Dragana Vuckovic, Melanie Waldenberger, Jie Jin Wang, Qiong Yang, Daniel I. Chasman, Gerard Tromp, Harold Snieder, Iris M. Heid, Caroline S. Fox, Anna Köttgen, Cristian Pattaro, Carsten A. Böger, Christian Fuchsberger |
| 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. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 30% |
| United Kingdom | 2 | 20% |
| Germany | 1 | 10% |
| Italy | 1 | 10% |
| Unknown | 3 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 60% |
| Scientists | 4 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 155 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 1% |
| Sweden | 1 | <1% |
| Unknown | 152 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 34 | 22% |
| Student > Ph. D. Student | 26 | 17% |
| Student > Master | 15 | 10% |
| Student > Bachelor | 13 | 8% |
| Professor > Associate Professor | 10 | 6% |
| Other | 27 | 17% |
| Unknown | 30 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 50 | 32% |
| Medicine and Dentistry | 26 | 17% |
| Agricultural and Biological Sciences | 15 | 10% |
| Mathematics | 4 | 3% |
| Nursing and Health Professions | 2 | 1% |
| Other | 13 | 8% |
| Unknown | 45 | 29% |
Attention Score in Context
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