A new study by Edith Cowan University (ECU) introduces a blood test with the potential to predict the risk of type 2 diabetes more effectively.
Until now, the primary marker used in predicting diabetes risk has been high-sensitivity C-reactive protein (CRP), which indicates inflammation in the body.
However, this new research suggests that assessing a combination of biomarkers, including CRP and the monocyte to high-density lipoprotein ratio (MHR), could significantly enhance the accuracy of diabetes risk prediction.
The study, led by ECU researcher Dan Wu, analyzed the relationship between systemic inflammation—measured by both CRP and MHR—and the onset of type 2 diabetes.
Tracking over 40,800 individuals without diabetes at the start, the research spanned nearly a decade, during which more than 4,800 participants developed the condition.
Wu discovered a notable link between elevated levels of MHR and CRP and the increased incidence of diabetes, especially when these markers rose together.
This association, Wu found, varied with age and sex, and was also influenced by other health conditions like hypertension, high cholesterol, or prediabetes.
Adding MHR and CRP levels to existing clinical risk models substantially improved the prediction capabilities for diabetes, indicating that this combined assessment could be a game-changer in early diabetes detection.
Interestingly, the study revealed that women are at a higher risk of developing type 2 diabetes from increases in CRP and MHR, a disparity possibly explained by differences in sex hormones.
This finding underscores the role of chronic inflammation in the development of early-onset diabetes, a condition on the rise, particularly in developing countries.
Wu emphasizes the significance of this age-specific link between inflammation and diabetes, suggesting it could pave the way for early identification and personalized interventions for young adults at risk.
Wu also points out the critical nature of addressing diabetes promptly due to its progressive nature and the severe health complications it can lead to.
While some risk factors like age and genetics cannot be changed, lifestyle modifications can significantly impact other risk factors related to inflammation.
Diet, sleep patterns, stress levels, and metabolic conditions are all influential, highlighting the importance of monitoring and managing these aspects for diabetes prevention.
The practicality of using cumulative MHR and CRP levels in clinical settings—due to their cost-effectiveness and widespread availability—makes this method an appealing option for predicting diabetes risk.
This advancement in predicting diabetes risk holds promise for improving early detection and intervention strategies, potentially reducing the global burden of this chronic disease.
The findings are detailed in the Journal of Translational Medicine, offering a new perspective on combating diabetes through innovative and accessible diagnostic tools.
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The research findings can be found in the Journal of Translational Medicine.
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