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Published on: July 5, 2022
Preventing type 2 diabetes mellitus: a call for personalized intervention
1Endocrinologist at the Sunnyside Medical Center in Clackamas, OR, and former Visiting Scientist at the Galil Center for Telemedicine, Medical Informatics and Personalized Medicine at RB Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.
Obesity increases the risk of prediabetes and type 2 diabetes (DM2). Identifying individuals most likely to progress from prediabetes to DM2 is crucial for targeted interventions and personalized medicine approaches.
Area of Science:
- Metabolic health
- Epidemiology
- Personalized medicine
Background:
- Rising global obesity rates, particularly in younger populations, correlate with increased incidence of metabolic disorders.
- Prediabetes affects a significant portion of the adult population, but its progression to type 2 diabetes (DM2) varies, with some individuals reverting to normal glucose levels.
- The uncertain prognosis of prediabetes complicates the identification of individuals who would most benefit from interventions aimed at reducing DM2 risk.
Purpose of the Study:
- To review factors influencing the development of type 2 diabetes (DM2).
- To summarize evidence from treatment trials on preventing DM2.
- To advocate for the development of tools for precise individual DM2 risk estimation using big data and personalized medicine.
Main Methods:
- Literature review of factors contributing to DM2 development.
- Analysis of treatment trial data demonstrating DM2 prevention strategies.
- Conceptual framework for applying big data and personalized medicine to risk assessment.
Main Results:
- A significant increase in prediabetes and type 2 diabetes (DM2) incidence and prevalence is observed globally, linked to rising obesity.
- A minority of individuals diagnosed with prediabetes progress to DM2, highlighting prognostic uncertainty.
- Existing interventions can reduce DM2 risk, but precise risk stratification is needed.
Conclusions:
- More precise tools are needed to estimate individual risk for type 2 diabetes (DM2) development.
- Personalized medicine and big data analytics offer promising approaches for improving risk prediction.
- Accurate risk assessment will enable more effective, targeted interventions for prediabetes management and DM2 prevention.
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