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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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Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk

TL;DR: In this article , the authors performed probabilistic transcriptome-wide association and locus-level colocalization analyses to integrate transcriptomics results for 49 tissues in 706 individuals from the GTEx project, metabolomics results from 1,391 plasma metabolites in 6,136 Finnish men from the METSIM study, and GWAS results for 2,861 disease traits in 260,405 Finnish individuals from FinnGen study.

Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits

Evangelos Evangelou, +279 more
TL;DR: In this paper, the authors report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry, identifying 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures.
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Linkage analysis of von Recklinghausen neurofibromatosis to DNA markers on chromosome 17

TL;DR: Strong evidence of linkage of NF1 to the centromeric marker D17Z1 is reported and a weaker suggestion of linkage to the ERBA1 oncogene is reported, both at a recombination fraction of zero.
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Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

Ying Wang, +125 more
- 01 Jan 2023 - 
TL;DR: In this article , the authors used data from Global Biobank Meta-analysis Initiative (GBMI) to explore methodological considerations and polygenic risk scores (PRSs) performance in 9 different biobanks for 14 disease endpoints.