A multidisciplinary approach to validate the role of ATM in glycaemic response to metformin in type 2 diabetes

Lead Research Organisation: University of Dundee
Department Name: Biomedical Research Centre

Abstract

Metformin is used by over 100 million people world wide primarily to treat diabetes, but more recently the potential benefits of this drug in cancer prevention or treatment are being realized. Despite its use for over 50 years the mechanism of action of metformin has not been fully determined. An innovative study on the genetics of response to metformin has revealed that an area of the genome that includes the ?cancer associated? gene ATM is involved in how metformin lowers blood sugar in people with diabetes.
We propose key follow on studies to confirm that it is the ATM gene that is responsible for this ?genetic signal?. We will use the considerable collaborative resources within the Diabetes Research Centre in Dundee, and the genetics expertise both within Dundee and the Wellcome Trust Centre for Human Genetics in Oxford, to address this key step, using studies in humans, mice and cells. The genetic studies will be used to look for genetic variants (or changes in the DNA) that are associated with large changes in metformin response as these may be usefully clinically to predict who will respond to metformin treatment and who won?t. In the mouse studies, we will look at normal mice and mice that lack one (of two) copies of the Atm gene. We will feed them with a high fat and high carbohydrate diet, which will result in some of them developing diabetes, and we will then treat those with diabetes with metformin to see if the genetic difference alters metformin response. Then in studies of cells (either standard laboratory ?cell-lines? or cells from human blood donors) we will study the mechanism whereby ATM variation alters metformin response.
The likely key outcome of this study is that we will have validated that the gene ATM is a key gene involved in metformin response and gained insight into the mechanism. This has implications for the treatment of diabetic patients with metformin, especially as 1% of the population has one faulty copy of the ATM gene; and may have implications for the rare group of patients who have the neurological/cancer syndrome ?ataxia-telangiectasia?. In addition, this will be an important result for both cancer biologists, biologists interested in metabolism, and the pharmaceutical industry as this unexpected mechanism for metformin may reveal novel pathways for drug development.

Technical Summary

Metformin is the most commonly used drug to treat diabetes, and more recently has been shown to reduce risk of cancer, yet its mechanism of action at the cell and whole body level remains uncertain. Using a top down genome wide approach we have shown that a locus that contains the cancer gene ATM is associated with glucose response to Metformin in type 2 diabetes. Preliminary functional data, and other recent published data strongly support ATM as the likely causal gene at this locus.

The aim of this proposal is to undertake a multidisciplinary approach to validate the role of ATM in glycaemic response to metformin, and to gain insight into the mechanism whereby ATM alters metformin response. Utilising the broad translational expertise in the Diabetes Research Centre, at the University of Dundee, we propose the following approaches to follow up on the GWA result.

Firstly, we will sequence across the locus in patients with extreme metformin response to identify rare variants of large effect and clinical utility, and identify the causal transcript.

Secondly we will study mice heterozygous null for ATM who develop diabetes on a high CHO/high fat diet, and assess the effect of metformin on glucose homeostasis compared to wildtype mice. This approach mirrors that used to establish the role of LKB1 in metformin action.

Thirdly we will employ a number of molecular biological approaches to investigate how ATM alters metformin activation of AMPK, and the role of ATM in other key signalling pathways. We will also investigate, ex-vivo, the role of the human variants on metformin action in human PBMCs selected by genotype.

Finally, we will follow up on a bioinformatic analysis suggesting a role for the metformin associated SNP in alteration of polyadenylation of ATM. We will use PBMCs from individuals with different genotypes at the identified locus, to assess ATM transcript size and stability.

We believe that all four approaches are required to validate the role of ATM in metformin action, and to investigate the molecular biological mechanism. This study will provide considerable insight into the novel role for ATM in glucose homeostasis in the exciting and rapidly developing cross-speciality field of metabolism and cancer. These studies are needed prior to recruit-by-ATM-genotype clinical trials of metformin response, and intensive mouse metabolic phenotyping.

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