Diabesity - novel molecular targets for obesity and type 2 diabetes
 
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Dr Inês Barroso
The Wellcome Trust Sanger Institute
The Wellcome Trust Genome Campus
Hinxton
Cambridge
CB10 1SA
United Kingdom
Phone: +44 1223 495341
E-mail
Dr Inês Barroso
Workpackage 3 and 4 leader
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Research

Aim
The aim of the Metabolic Disease group is to understand the genetic aetiology of complex diseases such as type 2 diabetes, insulin resistance and obesity.  The knowledge of genetic predisposition is important to help those at high risk for these disorders develop healthier lifestyles and avoid risky behaviours (such as high fat diets).  It can also lead to the development of better drugs that work in each affected individual. In keeping with The Wellcome Trust Sanger Institute expertise in genomics and informatics we are taking advantage of existing high-throughput systems at the Sanger to explore the genetic predisposition to type 2 diabetes and obesity.

Approach
We are using a candidate gene approach in our genetic studies: using knowledge of the diseases, and of the pathways involved in glucose metabolism and feeding behaviour, we can make educated choices regarding which genes, if mutated, might predispose a person to type 2 diabetes and/or obesity.  Our strategy focuses on the genetic study of extreme phenotypes populations - extreme insulin resistance and extreme obesity (cohorts from Prof. Steve O'Rahilly) - coupled with population-based disease association studies (populations from Dr. Nick Wareham).  Extreme phenotypes may be genetically simpler than the more common complex diseases of obesity and type 2 diabetes.  By focussing initially on these extreme phenotypes, reducing background noise of non-genetic factors and enriching for those cases with a genetic susceptibility, we have had success in identifying the first example of a monogenic form of insulin-resistant diabetes due to mutations beyond the insulin receptor (Barroso, et al., 1999) and the first digenic disease of insulin action (Savage, et al., 2002).  Our data suggests that the PPP1R3A frameshift variant identified in the latter study is associated with an increased risk of type 2 diabetes (odds ratio 2.53, 95% confidence limits 1.06 - 6.70, p = 0.03) in the populations we studied.  We are currently following up this finding in additional population groups.

 

Diabesity: Novel molecular targets for obesity and type 2 diabetes
   
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