Prediabetes phenotypes: can aetiology and risk profile guide lifestyle strategies for diabetes prevention?

Type 2 diabetes (T2D) continues to worsen globally alongside rise in obesity. Asymptomatic dysglycaemia, which precedes T2D, provides opportunities to identify those at risk and target prevention but prediabetes is highly variable. Not all with overweight develop dysglycaemia and not all with dysglycaemia are overweight. Important is the deposition of ectopic lipids in the pancreas, liver, and muscle. With no international definition, several prediabetes phenotypes exist, each based on one or more components of fasting glucose, postprandial glucose and/or HbA_1c.

We address variability in prediabetes phenotype and absence of a universal definition. With four main phenotypes based on the various glycemic definitions, it is likely they have different etiologies, risk profiles, timelines to T2D, and response to lifestyle intervention. Who do we treat, and when? Do we treat early or late? What is the optimum diet for T2D prevention? Do different phenotypes require different prevention approaches?

Personalized lifestyle, or phenotype-specific treatments, are likely to be more successful for T2D prevention than a 'one-size-fits-all' approach. Artificial intelligence (AI) methods, currently in their infancy, are expected to revolutionize personalized nutrition with integration of 'big data' better characterizing and predicting prediabetes phenotype, and phenotype-specific response to diet and lifestyle interventions.