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Michael Boehnke

Researcher at University of Michigan

Publications -  540
Citations -  155551

Michael Boehnke is an academic researcher from University of Michigan. The author has contributed to research in topics: Genome-wide association study & Type 2 diabetes. The author has an hindex of 152, co-authored 511 publications receiving 136681 citations. Previous affiliations of Michael Boehnke include SUNY Downstate Medical Center & Norwegian University of Science and Technology.

Papers
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Journal ArticleDOI

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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A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance.

Alisa K. Manning, +243 more
- 01 Jun 2012 - 
TL;DR: Six previously unknown loci associated with fasting insulin at P < 5 × 10−8 in combined discovery and follow-up analyses of 52 studies comprising up to 96,496 non-diabetic individuals are presented.
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Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.

Daniel Taliun, +205 more
- 10 Feb 2021 - 
TL;DR: The Trans-Omics for Precision Medicine (TOPMed) project as discussed by the authors aims to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases.

Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution

Iris M. Heid, +299 more
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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.