scispace - formally typeset
M

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
More filters
Journal ArticleDOI

Quantifying and correcting for the winner's curse in genetic association studies.

TL;DR: It is shown that overestimation of the genetic effect by the uncorrected estimator decreases as the power of the association study increases and that the ascertainment‐corrected method reduces absolute bias and mean square error unless power to detect association is high.
Journal ArticleDOI

Association of 18 confirmed susceptibility loci for type 2 diabetes with indices of insulin release, proinsulin conversion, and insulin sensitivity in 5,327 nondiabetic Finnish men.

TL;DR: Eight type 2 diabetes–related loci were significantly or nominally associated with impaired early-phase insulin release and effects of SLC30A8, HHEX, CDKAL1, and TCF7L2 on insulin release could be partially explained by impaired proinsulin conversion.
Journal ArticleDOI

Variations in the G6PC2/ABCB11 genomic region are associated with fasting glucose levels.

TL;DR: The results in combination with data reported in the literature suggest that G6PC2, a glucose-6-phosphatase almost exclusively expressed in pancreatic islet cells, may underlie variation in fasting glucose, though it is possible that ABCB11, which is expressed primarily in liver, may also contribute to such variation.
Journal ArticleDOI

Statistical methods for polyploid radiation hybrid mapping.

TL;DR: A model of fragment generation and retention for data involving two or more copies of the chromosome of interest per clone is presented and statistical criteria such as minimum obligate breaks, maximum likelihood ratios, and Bayesian posterior probabilities can be used to decide locus order.

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

Yingchang Lu, +311 more
TL;DR: In this paper, the authors conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals to increase the understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk.