The discovery of a biomarker in the blood that indicates how well the brain responds to insulin could be used as a screening tool for type 2 diabetes risk, researchers say.
When the brain does not respond properly to insulin, it is known as insulin resistance. This can lead to weight gain, diabetes, and Alzheimer’s disease.
A team from the German Center for Diabetes Research has found that small chemical changes (epigenetic changes) to genetic material in the blood shows the brain’s response to insulin.
The findings could pave the way for the use of a simple blood test to detect insulin resistance in the brain for early, targeted intervention for those found to be more at risk of type 2 diabetes.
The study’s first author Professor Dr Stephanie Kullmann said: “Insulin is not only involved in metabolism but also plays a key role in the brain with regard to cognitive functions, appetite regulation, and energy homeostasis.”
Researchers used a machine learning method – a branch of AI – to analyse patterns in DNA methylation (small chemical changes in DNA) in the blood.
They analysed people without type 2 diabetes who had similar peripheral insulin sensitivity values but differed in their brain’s response to insulin.
They found 540 so-called CpG sites with methylation patterns that allowed the team to differentiate between people with and without insulin resistance in the brain.
Last author Meriem Ouni said: “It is noteworthy that many of these methylation sites were associated with an elevated risk of type 2 diabetes. This suggests a mutual influence between insulin resistance in the brain and metabolic disease.
“Our findings suggest that the epigenetic profile in the blood can reflect key processes in the brain.”
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It is well known that people with insulin resistance in the brain do not respond as well to lifestyle interventions. They also store more visceral fat and are more prone to cravings – all factors for developing type 2 diabetes.
The discovery of a new biomarker in the blood could be used as a screening instrument to detect risk patients early on and provide them with targeted treatment, including more intensified lifestyle changes.
Ouni added: “If we know who is insulin resistant in the brain, we can make interventions much more targeted and effective.”
Read more in Science Translational Medicine.
