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Bengt Sennblad

Researcher at Science for Life Laboratory

Publications -  82
Citations -  12462

Bengt Sennblad is an academic researcher from Science for Life Laboratory. The author has contributed to research in topics: Genome-wide association study & Type 2 diabetes. The author has an hindex of 40, co-authored 79 publications receiving 10488 citations. Previous affiliations of Bengt Sennblad include Stockholm University & Karolinska University Hospital.

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Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes

Andrew P. Morris, +232 more
- 01 Sep 2012 - 
TL;DR: This article conducted a meta-analysis of genetic variants on the Metabochip, including 34,840 cases and 114,981 controls, overwhelmingly of European descent, and identified ten previously unreported T2D susceptibility loci, including two showing sex-differentiated association.
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Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

Anubha Mahajan, +395 more
- 01 Mar 2014 - 
TL;DR: In this paper, the authors aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry.
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The interleukin-6 receptor as a target for prevention of coronary heart disease: a mendelian randomisation analysis.

Daniel I. Swerdlow, +115 more
- 31 Mar 2012 - 
TL;DR: IL6R blockade could provide a novel therapeutic approach to prevention of coronary heart disease that warrants testing in suitably powered randomised trials and could help to validate and prioritise novel drug targets or to repurpose existing agents and targets for new therapeutic uses.
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A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance.

Alisa K. Manning, +243 more
- 01 Jun 2012 - 
TL;DR: Six previously unknown loci associated with fasting insulin at P < 5 × 10−8 in combined discovery and follow-up analyses of 52 studies comprising up to 96,496 non-diabetic individuals are presented.
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Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

Robert A. Scott, +216 more
- 01 Sep 2012 - 
TL;DR: Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations and further functional analysis of these newly discovered loci will further improve the understanding of glycemic control.