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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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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, +258 more
- 12 Sep 2017 - 
TL;DR: This multiancestry study recommends investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G 6PD deficiency is common, and investigates the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance.
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Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity

Antigone S. Dimas, +64 more
- 01 Jun 2014 - 
TL;DR: By assembling extensive data on continuous glycemic traits, this work has exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.
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Genetic Counseling for Families With Inherited Susceptibility to Breast and Ovarian Cancer

TL;DR: This work has identified several families that show linkage between breast and/or ovarian cancer and genetic markers that flank BRCA1 and developed a protocol to address the many issues that arise in the delivery of these services.
Journal Article

Genetic linkage of Beckwith-Wiedemann syndrome to 11p15.

TL;DR: Genetic linkage analysis on two BWS kindreds suggests that BWS defines a tumor-predisposition gene on 11p15.5, which is related to the Wilms tumor gene on11p13 or, alternatively, to growth factor genes on 11 p15.
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Improved Inference of Relationship for Pairs of Individuals

TL;DR: This work modifications a likelihood-based method to infer the most likely relationship of a pair of putative sibs to consider all possible pairs of individuals in the sample, to test for additional relationships, to allow explicitly for genotyping error, and to include X-linked data.