Researchers in the UK have discovered a new way to assess the risk of developing type 2 diabetes years before any symptoms appear. By analyzing changes found in the DNA of a person’s blood, scientists can now provide a more accurate prediction of the likelihood of developing this condition. This breakthrough has the potential to improve early detection and enable the implementation of preventive measures, ultimately reducing the economic and health burdens associated with type 2 diabetes.
So, how does this method work? Researchers at the University of Edinburgh (UoE) examined a process called DNA methylation, which involves the addition of a small molecule called a methyl group to DNA. By studying these alterations, they were able to determine how they interacted with other known risk factors for type 2 diabetes, such as age, sex, body mass index (BMI), and family history of the disease.
DNA methylation serves as a valuable biomarker in disease research, particularly in the field of epigenetics. Epigenetic modifications, including DNA methylation, influence gene expression while preserving the DNA sequence. Emerging evidence highlights the association between abnormal DNA methylation patterns and the development and progression of diabetes.
For instance, studies have demonstrated that changes in mitochondrial DNA methylation are linked to insulin resistance in individuals with prediabetes. Additionally, alterations in DNA methylation within the pancreas have been identified as an early indicator of type 2 diabetes. These findings underscore the potential of DNA methylation as a diagnostic tool for identifying individuals at risk of developing diabetes at an early stage.
In the current study, the researchers assessed the validity of their findings by conducting a hypothetical screening of 10,000 individuals. Over a 10-year span, approximately one-third of the participants were expected to develop type 2 diabetes. By comparing their model, which incorporated DNA methylation data (DNAm), with a model of only traditional risk factors, they discovered that the DNAm model correctly identified an additional 449 individuals who were at risk of developing type 2 diabetes.
The data for the study came from 14,613 volunteers who participated in the Generation Scotland cohort. This extensive study aims to investigate the causes of various diseases, understand healthcare priorities, and shape future medical treatments and health policies. To ensure the reliability of their findings across different populations, the scientists also replicated their analyses using data from 1,451 individuals in a German study.
Type 2 diabetes is a serious condition characterized by the body’s inability to properly utilize or produce enough insulin, resulting in elevated blood sugar levels. It is the most common form of diabetes and is often associated with lifestyle factors such as obesity, physical inactivity, and poor diet. If left uncontrolled, type 2 diabetes can lead to serious health problems, including heart disease, kidney damage, nerve damage, and vision problems.
Yipeng Cheng, a PhD student at UoE’s Centre for Genomic and Experimental Medicine, expressed optimism about the study’s results, stating, “It is promising that our findings were observed in the Scottish and German studies with both showing an improvement in prediction above and beyond commonly used risk factors. Delaying onset is important as diabetes is a risk factor for other common diseases, including dementias.”
Professor Riccardo Marioni, the study’s lead researcher from UoE, suggested that similar approaches could be used for other common diseases to create broad health predictions from a single blood or saliva sample. He expressed gratitude to the study volunteers, emphasizing that their participation enables the identification of signals that could help delay or reduce the onset of diseases as people age.
This groundbreaking research offers hope for the development of a test to identify individuals at higher risk for type 2 diabetes. This would enable early intervention and preventive measures. By gaining a deeper understanding of the risk factors associated with chronic diseases like type 2 diabetes, we can strive towards healthier, longer, and more fulfilling lives.
Source: Y. Cheng et al. Development and validation of DNA methylation scores in two European cohorts augment 10-year risk prediction of type 2 diabetes. Nature Aging, April 6, 2023.
Reference: New test could help identify type 2 diabetes risk. The University of Edinburgh. April 6, 2023.
