Patients Diabetes (Type 2)
Why Lifestyle Changes Won’t Work For Everyone With Type 2 Diabetes
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Experts from the University of Stirling in the U.K. have made a breakthrough in understanding how people respond to lifestyle changes for preventing type 2 diabetes.
The team discovered a new genomic signature in people whose type 2 diabetes status improves following a treatment intervention. According to a press release, the discovery is significantly the first reliable signature for insulin sensitivity in human muscle.
Scientists believe that the findings, published in Nucleic Acids Research, will inform future research by helping to understand why not all people are able to eliminate the risk of the condition by changing their lifestyle.
“Our hypothesis was that with sufficient numbers of well-characterized subjects and our new analysis methods, we could reveal a robust signature for what is known as ‘insulin resistance’ — an important precursor for developing type 2 diabetes,” explains Dr. Iain J Gallagher.
“Importantly, because we could also examine how the activation status of each insulin resistance; gene responded to treatment, we have also discovered a potential explanation for why not all people eliminate their type 2 diabetes risk by following a lifestyle and exercise training program.”
For their research, the team analyzed more than 1,000 human muscle samples and five distinct treatment regimes.
In doing so, they demonstrated that 16 genes are consistently “switched” on or off in muscle tissue, but only in those people whose type 2 diabetes risk factors improved. In such cases, the gene changes increased the individuals’ insulin sensitivity — a measure of how effectively the hormone insulin is working.
Activation of the signature is impaired in people with poor insulin sensitivity and is dysregulated to a greater extent following various types of standard lifestyle treatment.
The signature includes more than 300 measures of gene activity, representing both protein-coding and long non-coding genes. It was extensively modeled to take into account body weight and age, as well as exercise capacity.
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