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Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation

Overview of attention for article published in PLoS Genetics, July 2015
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6 X users
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125 Mendeley
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3 CiteULike
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Article details
Title
Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation
Published in
PLoS Genetics, July 2015
DOI 10.1371/journal.pgen.1005230
Pubmed ID
Authors
Abstract

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

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The data shown below were collected from the profiles of 6 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 125 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 1 <1%
Ukraine 1 <1%
Netherlands 1 <1%
Luxembourg 1 <1%
France 1 <1%
Finland 1 <1%
Canada 1 <1%
Unknown 118 94%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 26 21%
Student > Ph. D. Student 16 13%
Student > Bachelor 11 9%
Professor 11 9%
Other 7 6%
Other 29 23%
Unknown 25 20%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 29 23%
Medicine and Dentistry 27 22%
Biochemistry, Genetics and Molecular Biology 21 17%
Nursing and Health Professions 4 3%
Social Sciences 4 3%
Other 10 8%
Unknown 30 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 28 April 2016.
All research outputs
#12,428,062
of 34,526,284 outputs
Outputs from PLoS Genetics
#6,200
of 9,882 outputs
Outputs of similar age
#115,464
of 302,976 outputs
Outputs of similar age from PLoS Genetics
#110
of 193 outputs
Altmetric has tracked 34,526,284 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,882 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.9. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
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 302,976 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 193 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.