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

Overview of attention for article published in Scientific Reports, April 2017
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  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

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159 Mendeley
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Article details
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.

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X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 159 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 1%
Sweden 1 <1%
Unknown 156 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 34 21%
Student > Ph. D. Student 26 16%
Student > Master 16 10%
Student > Bachelor 13 8%
Professor > Associate Professor 10 6%
Other 26 16%
Unknown 34 21%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 51 32%
Medicine and Dentistry 26 16%
Agricultural and Biological Sciences 14 9%
Mathematics 4 3%
Computer Science 3 2%
Other 13 8%
Unknown 48 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 January 2018.
All research outputs
#8,694,935
of 27,789,879 outputs
Outputs from Scientific Reports
#58,047
of 152,714 outputs
Outputs of similar age
#117,119
of 331,547 outputs
Outputs of similar age from Scientific Reports
#1,578
of 4,108 outputs
Altmetric has tracked 27,789,879 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 152,714 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.9. This one has gotten more attention than average, scoring higher than 61% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 331,547 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 4,108 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.