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Meta-Analysis of Genome-Wide Association Studies in African Americans Provides Insights into the Genetic Architecture of Type 2 Diabetes

Overview of attention for article published in PLoS Genetics, August 2014
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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14 X users

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195 Dimensions

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Title
Meta-Analysis of Genome-Wide Association Studies in African Americans Provides Insights into the Genetic Architecture of Type 2 Diabetes
Published in
PLoS Genetics, August 2014
DOI 10.1371/journal.pgen.1004517
Pubmed ID
Authors

Maggie C. Y. Ng, Daniel Shriner, Brian H. Chen, Jiang Li, Wei-Min Chen, Xiuqing Guo, Jiankang Liu, Suzette J. Bielinski, Lisa R. Yanek, Michael A. Nalls, Mary E. Comeau, Laura J. Rasmussen-Torvik, Richard A. Jensen, Daniel S. Evans, Yan V. Sun, Ping An, Sanjay R. Patel, Yingchang Lu, Jirong Long, Loren L. Armstrong, Lynne Wagenknecht, Lingyao Yang, Beverly M. Snively, Nicholette D. Palmer, Poorva Mudgal, Carl D. Langefeld, Keith L. Keene, Barry I. Freedman, Josyf C. Mychaleckyj, Uma Nayak, Leslie J. Raffel, Mark O. Goodarzi, Y-D Ida Chen, Herman A. Taylor, Adolfo Correa, Mario Sims, David Couper, James S. Pankow, Eric Boerwinkle, Adebowale Adeyemo, Ayo Doumatey, Guanjie Chen, Rasika A. Mathias, Dhananjay Vaidya, Andrew B. Singleton, Alan B. Zonderman, Robert P. Igo, John R. Sedor, Edmond K. Kabagambe, David S. Siscovick, Barbara McKnight, Kenneth Rice, Yongmei Liu, Wen-Chi Hsueh, Wei Zhao, Lawrence F. Bielak, Aldi Kraja, Michael A. Province, Erwin P. Bottinger, Omri Gottesman, Qiuyin Cai, Wei Zheng, William J. Blot, William L. Lowe, Jennifer A. Pacheco, Dana C. Crawford, Elin Grundberg, Stephen S. Rich, M. Geoffrey Hayes, Xiao-Ou Shu, Ruth J. F. Loos, Ingrid B. Borecki, Patricia A. Peyser, Steven R. Cummings, Bruce M. Psaty, Myriam Fornage, Sudha K. Iyengar, Michele K. Evans, Diane M. Becker, W. H. Linda Kao, James G. Wilson, Jerome I. Rotter, Michèle M. Sale, Simin Liu, Charles N. Rotimi, Donald W. Bowden

Abstract

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94)<P<5 × 10(-8), odds ratio (OR)  = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2 × 10(-23) < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 306 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
Mexico 1 <1%
Netherlands 1 <1%
France 1 <1%
Unknown 301 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 56 18%
Student > Ph. D. Student 53 17%
Student > Master 27 9%
Student > Bachelor 21 7%
Professor 17 6%
Other 64 21%
Unknown 68 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 74 24%
Agricultural and Biological Sciences 51 17%
Medicine and Dentistry 48 16%
Computer Science 7 2%
Nursing and Health Professions 7 2%
Other 44 14%
Unknown 75 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 22 August 2014.
All research outputs
#5,439,769
of 25,728,855 outputs
Outputs from PLoS Genetics
#3,928
of 8,996 outputs
Outputs of similar age
#49,811
of 242,286 outputs
Outputs of similar age from PLoS Genetics
#65
of 182 outputs
Altmetric has tracked 25,728,855 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,996 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.8. This one has gotten more attention than average, scoring higher than 55% 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 242,286 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 182 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 62% of its contemporaries.