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How Fast Will a Diabetes Patient Develop Insulin Dependency?

A woman in lab coat and gloves using a mass spectrometer with an overlaid illustration.
An image depicting a standing person working with a mass spectrometer. The image also has icons with TAGs (Triacylglycerols) and SMs (Sphingomyelins). Credit: Ronald Bonss.
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Type 2 diabetes (T2D) is a metabolic disease, primarily characterized by the beta cells’ lack of ability to produce insulin. Typically, patients use insulin to substitute for the loss of beta cell function. Unfortunately, a substantial number of patients develop insulin resistance as the disease progresses. An international team of scientists from the EU Innovative Medicines Initiative-2 Risk 138 Assessment and ProgreSsiOn of Diabetes (RHAPSODY) published their findings about insulin resistance development in Nature Communications.

A lack of insulin dependency progression biomarkers

It is important not only to treat T2D patients using different types of medication combined with dietary and lifestyle modifications, but also to predict insulin resistance development. This would require better diagnostics and treatment strategies to be developed, helping to manage the disease and leading to significant improvement of patient outcomes.

Biomarker analysis plays a crucial role in achieving these goals. By identifying specific biomarkers in blood plasma, healthcare professionals can gain insights into an individual's metabolic status. These biomarkers typically include glucose levels, insulin levels and glycated hemoglobin (HbA1c) among others.

However, only a few studies have analyzed the changes associated with the development of insulin resistance and diabetes progression as routinely used biomarkers do not allow for insulin resistance progression prediction. The current study addresses this gap.

Metabolic and lipid markers predict progression towards insulin requirement

The authors studied a plethora of biomarkers that showed promise in allowing the development of insulin resistance to be predicted.

2,973 individuals were included in this study. Males constituted 55% of the combined cohort and the age of participants ranged from 61 to 69 years, with a BMI of 30 to 32 kg/m2. The anamnesis of the patients included data about glycated hemoglobin, time from diagnosis to sampling, the presence of glucose-lowering medication and other parameters.

The researchers analyzed blood plasma samples and evaluated their metabolite, protein and - with the help of researchers at Lipotype Lipidomics who are coauthors in the study - lipid compositions. Subsequent modeling was performed based on the analytes and patients’ data to estimate the deterioration of glucose control.

The key findings of the paper were:

  • Several metabolic and lipid biomarkers were suggested to predict a faster progression towards insulin requirement
  •  Among the biomarkers, shotgun lipidomics identified eight different species of triglycerides and the sphingomyelin 42:2;2
  • Protein analysis allowed the team to identify the groups of proteins that were predictive of faster and slower progression rates
  • The authors performed several in vitro and in vivo animal experiments, mechanistically confirming their observations

Development of an insulin resistance prediction tool

By conducting a large multiomics study across three patients cohorts, the authors have explored various aspects of lipid, metabolite and protein biomarkers for diabetes progression toward insulin resistance. Importantly, identified biomarkers that can predict the progression of T2D come from different chemical classes. These findings have been replicated in independent diabetes progression cohorts or validated for incident and/or prevalent diabetes.

Specifically, 9 lipids, 3 small, charged molecules and 11 protein biomarkers that are associated with accelerated glycemic deterioration have been identified. These biomarkers can potentially serve as indicators of the progression of diabetes.

Additionally, biological data from pre-clinical models that offer insights into the possible mechanisms of action for NogoR and IL-18Ra have been provided, further enhancing the understanding of how these biomarkers may contribute to the progression of diabetes.

Interestingly, protein and lipid data suggest that the drivers of diabetes incidence and prevalence may be similar to those of diabetes progression. This finding implies that certain biomarkers and mechanisms may play roles not only in the development of diabetes but also in its progression.

This study identified molecular changes that are associated with the worsening of blood sugar control in individuals who have diabetes. By gaining a deeper understanding of the underlying biological mechanisms that contribute to this, it may become possible to develop targeted therapies that can prevent or slow down progression of the disease. This has the potential to revolutionize diabetes treatments and improve outcomes for individuals with diabetes.

Large multi-cohort studies do, however, come with challenges in evaluation and confirmation of the biomarkers identified. In this study, one sphingomyelin, SM 42:2;2, was the only biomarker associated with a lower risk of progressing toward insulin resistance, but interestingly, it was associated with an increased risk of future diabetes in the external validation data.

This could potentially be explained by the influence of metformin treatment on sphingomyelin levels, including SM 42:2;2, as shown in studies on metformin-treated animals and cell culture experiments. Causality analysis was conducted for the most strongly associated lipids, but generally, there were either no available instrumental variables or no evidence of causality was observed. However, the Mendelian randomization analysis of the lipid PE 18:0;0_18:2;0 supported a potential causal relationship with incident diabetes. Further analysis of the additional cohorts is required to investigate the predictive role of SM 42:2;2 in insulin resistance development.

On the path towards personalized diagnostics predictions

This study paves the way for further investigations and opens new avenues for developing targeted interventions to manage and prevent the worsening of diabetes. The findings provide insights into the molecular changes associated with the progression of diabetes, offering potential directions for future work. By building upon these discoveries, researchers can delve deeper into understanding the mechanisms underlying diabetes deterioration and explore novel strategies to manage and prevent the progression of the disease. Ultimately, this has the potential to lead to the development of more effective interventions that can significantly improve the lives of individuals living with diabetes.

Reference: Slieker RC, Donnelly L, Akalestou E, et al. Identification of biomarkers for glycaemic deterioration in type 2 diabetes. Nat Commun. 2023;14(2533). doi:10.1038/s41467-023-38148-7