Diabetes risk assessments remain largely confined to clinical research. Widespread screening strategies are impeded by the need for specialized clinical expertise, expensive medical tests, and significant time investment. Typically, assessments combine glucose and insulin levels from an oral glucose tolerance test, triglycerides, HDL, BMI, and measurements reflecting fat distribution in the body and liver.
Now, researchers in Germany, have discovered an epigenetic marker for prediabetes that can be measured in blood. In a paper published in Biomarker Research, scientists propose a single blood draw for DNA methylation profiling to distinguish between high- and low-risk individuals.
To find out how this new approach might impact diabetes outcomes in the future, we spoke with lead researcher Meriem Ouni, from the German Center for Diabetes Research (DZD).
What are the main benefits and challenges of diabetes risk assessment?
Identifying individuals at elevated risk for diabetes has significant practical implications. Early disease diagnosis and intervention can prevent or delay Type 2 diabetes (T2D) onset and potentially lessen the clinical and economic burden.
However, the current approach necessitates numerous expensive clinical tests and measurements, and crucially relies on patient cooperation. Not all participants are willing to spend extended periods in the clinic to complete these evaluations; for example, an oral glucose tolerance test (OGTT) typically takes at least one and a half hours.
How does your epigenetic marker approach help to assign patients to prediabetes risk clusters?
Our strategy utilizes a machine learning workflow that incorporates DNA methylation data to clearly distinguish between individuals at low and high risk. Knowing the participants’ age and their blood DNA methylation profiles from 1557 methylation sites is sufficient for this risk stratification.
These blood-based epigenetic classifiers offer strong prognostic potential for identifying individuals at high risk of diabetes and its complications, providing a more accessible and cost-effective alternative to complex clinical assessments.
What are the advantages of this approach compared with glucose tolerance testing and insulin-based phenotyping?
The OGTT relies on glucose and insulin measurements. It necessitates multiple blood draws, at least three times over a ninety-minute period, requiring patient cooperation, time, and resources.
In contrast, the epigenetic marker approach determines DNA methylation levels at 1557 sites – which can accurately classify individuals into risk groups – and requires only a single blood draw. This approach could extend risk stratification to broader populations and represents a promising step toward developing noninvasive tests to identify individuals at high risk of diabetes and its complications.
As this technology’s costs are expected to decrease significantly in the near future, methylation markers offer a more cost-effective and time-saving way to assess the risk of T2D and its complications, compared with the standard of care.
Does the test primarily detect early disease biology that is already underway, or could it still identify risk before measurable metabolic decline?
Yes, we believe that these markers are predicting later onset of metabolic deterioration, such as elevated blood glucose levels, as well as T2D complications.
As these epigenetic markers are located in genes linked to distinct biological pathways reflecting each cluster’s metabolic profile, they likely contribute to the molecular heterogeneity of prediabetes. This positions the blood epigenome as a valuable proxy for predicting future diabetes complications.
Our findings are strengthened by the fact that several DNA methylation sites known to be involved in T2D nephropathy were also included within our set of 1557 methylation markers.
As such, these epigenetic markers have a high potential to detect future complications and this will be further confirmed in our future research.
What work is needed to translate the epigenetic test for clinical use?
We aim to develop risk stratification tests based on epigenetic markers. We will first refine and reduce the number of markers to ensure feasibility and practicality in clinical settings. Next, we will design a customized array-based chip optimized for easy detection of prediabetes risk clusters with cost-effective measurement.
We will simplify the usage of the customized array to make it accessible for all laboratories. The data output from the customized array is then processed with our bioinformatic workflow, which will be implemented as an application software.
We also plan to test multiplex RT-qPCR, which is more practical for larger scale testing and does not require strong standardization efforts.
What evidence would be most convincing that risk stratification changes T2D outcomes?
Prevention of T2D and its complications are the most convincing evidence, but we also showed that earlier intervention improves the metabolic health of the high-risk clusters. For example, it has been shown that individuals with high insulin resistance and high fatty liver (cluster 5) benefit the most from bariatric surgery. Indeed, providing early and better interventions adjusted to subphenotypes will reduce the economic and clinical burden of the progression of T2D.
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