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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.

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New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

Yingchang Lu, +311 more
TL;DR: The loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.
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Detailed Physiologic Characterization Reveals Diverse Mechanisms for Novel Genetic Loci Regulating Glucose and Insulin Metabolism in Humans

Erik Ingelsson, +69 more
- 01 May 2010 - 
TL;DR: The authors investigated associations of loci identified by the Meta-Analyses of Glucose and Insulin related traits Consortium (MAGIC) with circulating proinsulin, measures of insulin secretion and sensitivity from oral glucose tolerance tests (OGTTs), euglycemic clamps, insulin suppression tests, or frequently sampled intravenous glucose tolerance test in nondiabetic humans (n = 29,084).
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Genome-wide linkage analysis of families with obsessive-compulsive disorder ascertained through pediatric probands.

TL;DR: The results provide suggestive evidence for linkage on 9p and identify regions requiring further study with much larger samples, to identify chromosomal regions likely to contain susceptibility alleles for early-onset obsessive-compulsive disorder.
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General Framework for Meta-analysis of Rare Variants in Sequencing Association Studies

TL;DR: The proposed meta-analysis methods for commonly used gene- or region-based rare variants tests, such as burden tests and variance component tests, are applicable to meta- analysis of multiple ancestry groups and are essentially as powerful as joint analysis by directly pooling individual level genotype data.

Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis

Eleanor Wheeler, +214 more
TL;DR: In this article, the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance was investigated.