Projects per year
Abstract
To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting insulin, a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in fasting plasma insulin (FI) levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-hour insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio=1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.
Original language | English |
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Pages (from-to) | 2019-2032 |
Number of pages | 14 |
Journal | Diabetes |
Volume | 66 |
Issue number | 7 |
Early online date | 24 Mar 2017 |
DOIs | |
Publication status | Published - Jul 2017 |
Keywords
- Journal article
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- 1 Finished
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The Scottish eHealth Informatics Research Centre (E-HIRCs) (Joint with Universities of Aberdeen, Glasgow, Edinburgh, Strathclyde, St Andrews & Leicester and ISD)
Colhoun, H. (Investigator), Donnan, P. (Investigator), Guthrie, B. (Investigator), Jefferson, E. (Investigator), MacDonald, T. (Investigator), McCowan, C. (Investigator), Morris, A. (Investigator), Pearson, E. (Investigator), Sullivan, F. (Investigator) & Swedlow, J. (Investigator)
1/03/13 → 31/12/18
Project: Research