Scientists find 10 gene regions associated with type 2 diabetes

by Sarita Sheth on August 14, 2012

More than 60 DNA 'hotspots' have now been identified

Scientists are coming closer to understanding the biology of type 2 diabetes after discovering a further 10 gene regions associated with the disease.

The discovery by a team lead by Professor Mark McCarthy of the Wellcome Trust Centre for Human Genetics at Oxford University means that more than 60 DNA ‘hotspots’ have now been identified.

It means that they are nearer finding out what the genetic differences are between individuals that affect the risk of developing type 2 diabetes which is the most common form of the disease and is linked to obesity and lifestyle.

‘The 10 gene regions we have shown to be associated with Type 2 diabetes are taking us nearer a biological understanding of the disease,’ said Professor McCarthy.

‘It is hard to come up with new drugs for diabetes without first having an understanding of which biological processes in the body to target. This work is taking us closer to that goal,’ he explained.

DNA from almost 35,000 people with Type 2 diabetes and 115,000 healthy individuals was analysed by the scientists who were able to identify 10 new gene regions where DNA changes could be reliably linked to risk of the disease.

Two of these were separately associated with greater diabetes risk in men and women. The research is published in the journal Nature Genetics.

‘By looking at all 60 or so gene regions together we can look for signatures of the type of genes that influence the risk of Type 2 diabetes. We see genes involved in controlling the process of cell growth, division and ageing, particularly those that are active in the pancreas where insulin is produced,’ said the professor.

‘We see genes involved in pathways through which the body’s fat cells can influence biological processes elsewhere in the body. And we see a set of transcription factor genes, genes that help control what other genes are active,’ he added.

Professor McCarthy is currently leading another international study that has mapped the entire genetic codes of 2,800 people with and without diabetes and its first results will be available next year.

The results come hot on the heels of another international study which found that type 2 diabetes in leaner people is more genetically driven. A research team led by the Peninsula College of Medicine and Dentistry (PCMD) at the University of Exeter also identified a new genetic factor associated only with lean diabetes sufferers.

Using genetic data from genome wide association studies, the research team tested genetic markers across the genome in approximately 5,000 lean patients with type 2 diabetes, 13,000 obese patients with the disease and 75,000 healthy controls.

The team found differences in genetic enrichment between lean and obese cases, which support the hypothesis that lean diabetes sufferers had a greater genetic predisposition to the disease. This is in contrast to obese patients with type 2 diabetes, where factors other than type 2 diabetes genes are more likely to be responsible.

‘Whenever a new disease gene is found, there is always the potential for it to be used as a drug target for new therapies or as a biomarker, but more work is needed to see whether or not this new gene has that potential,’ said Dr. John Perry, one of the lead authors of the study.

‘This is the first time that a type 2 diabetes gene has been found to act in this way. We do not know why it should be associated in one sub-group of patients and not another. It could point to the fact that type 2 diabetes may not be one disease, but may represent a number of subgroups. Again, more work is required to prove this hypothesis,’ he added.


The opinions expressed in this article do not necessarily reflect the views of the DiabetesForum.com Community and should not be interpreted as medical advice. Please see your doctor before making any changes to your diabetes management plan.

{ 0 comments… add one now }

Leave a Comment

Previous post:

Next post: