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Ying Wu

Researcher at University of North Carolina at Chapel Hill

Publications -  104
Citations -  16215

Ying Wu is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Genome-wide association study & Type 2 diabetes. The author has an hindex of 46, co-authored 101 publications receiving 13796 citations. Previous affiliations of Ying Wu include Delft University of Technology & Huawei.

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Journal ArticleDOI

Discovery and refinement of loci associated with lipid levels

Cristen J. Willer, +319 more
- 06 Oct 2013 - 
TL;DR: It is found that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index.
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Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk

Georg Ehret, +391 more
- 06 Oct 2011 - 
TL;DR: A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function, and these findings suggest potential novel therapeutic pathways for cardiovascular disease prevention.
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Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

Anubha Mahajan, +395 more
- 01 Mar 2014 - 
TL;DR: In this paper, the authors aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry.
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Common variants associated with plasma triglycerides and risk for coronary artery disease

Ron Do, +266 more
- 01 Nov 2013 - 
TL;DR: It is suggested that triglyceride-rich lipoproteins causally influence risk for CAD, and the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk.
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Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

Robert A. Scott, +216 more
- 01 Sep 2012 - 
TL;DR: Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations and further functional analysis of these newly discovered loci will further improve the understanding of glycemic control.