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Markus Perola

Researcher at National Institute for Health and Welfare

Publications -  622
Citations -  90776

Markus Perola is an academic researcher from National Institute for Health and Welfare. The author has contributed to research in topics: Population & Genome-wide association study. The author has an hindex of 46, co-authored 573 publications receiving 78670 citations. Previous affiliations of Markus Perola include Estonian Biocentre & University of Helsinki.

Papers
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Biological, clinical and population relevance of 95 loci for blood lipids

Tanya M. Teslovich, +218 more
- 05 Aug 2010 - 
TL;DR: The results identify several novel loci associated with plasma lipids that are also associated with CAD and provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

Genetic studies of body mass index yield new insights for obesity biology

Adam E. Locke, +481 more
TL;DR: This paper conducted a genome-wide association study and meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals.
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Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index

Elizabeth K. Speliotes, +413 more
- 01 Nov 2010 - 
TL;DR: Genetic loci associated with body mass index map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor, which may provide new insights into human body weight regulation.
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Discovery and refinement of loci associated with lipid levels

Cristen J. Willer, +319 more
- 06 Oct 2013 - 
TL;DR: It is found that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index.
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New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk

Josée Dupuis, +339 more
- 01 Feb 2010 - 
TL;DR: It is demonstrated that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.