Prediabetes: diagnostic aspects, clinical features, and emerging therapeutic opportunities, with a focus on Vitamin D.

BACKGROUND

Prediabetes is a highly prevalent and heterogeneous condition associated with an increased risk of type 2 diabetes mellitus (T2DM), cardiovascular disease, and other cardiometabolic complications. Growing evidence suggests a potential role of vitamin D in glucose metabolism and diabetes prevention.

OBJECTIVE

To provide a clinically oriented interpretation of the available evidence on epidemiology, pathophysiology, clinical implications, and management of prediabetes, with a specific focus on the rationale and evidence supporting vitamin D supplementation in individuals at increased metabolic risk.

METHODS

A multidisciplinary panel of Italian experts in endocrinology, diabetology, and metabolic diseases reviewed current guidelines, epidemiological studies, randomized clinical trials, meta-analyses, and recent consensus statements addressing prediabetes and vitamin D.

RESULTS

Prediabetes is a dynamic and potentially reversible condition characterized by heterogeneous trajectories of progression, persistence, or regression. Lifestyle intervention remains the cornerstone of prevention. Vitamin D deficiency is common among individuals with prediabetes and may contribute to insulin resistance, β-cell dysfunction, inflammation, and endothelial dysfunction. Clinical trials and meta-analyses suggest that vitamin D supplementation may reduce the risk of progression to T2DM and increase the likelihood of regression to normoglycemia, particularly in individuals with vitamin D deficiency or high metabolic risk, although treatment effects remain heterogeneous.

CONCLUSIONS

Given the growing clinical and public health burden of prediabetes, early identification and personalized preventive strategies are needed. Current evidence supports consideration of vitamin D supplementation as a complementary intervention in selected high-risk individuals with documented deficiency, while further studies are required to better define optimal treatment targets and patient selection criteria.