Circulating long non-coding RNAs as predictors of type 2 diabetes mellitus development: results from the CORDIOPREV study

Abstract

Background: Type 2 diabetes mellitus (T2DM) is a growing global health challenge. Conventional diagnostic tools have limited sensitivity and specificity for early-stage disease. In this context, long non-coding RNAs (lncRNAs) have emerged as promising biomarkers for T2DM risk. However, studies exploring their predictive value remain limited. This study aimed to evaluate the potential of circulating lncRNAs in T2DM development and to assess their interaction with dietary interventions. Methods: The study included 462 non-diabetic participants from the CORDIOPREV study, followed for 5 years under Mediterranean or low-fat diet interventions. Expression levels of 22 circulating lncRNAs were quantified by qPCR. A series of statistical and machine learning methods were applied. Results: Random forest analysis identified four lncRNAs (XIST, LINC01116, CASC2, LINC01370) as predictive of T2DM incidence. The combination of these lncRNAs with clinical variables significantly improved prediction performance (AUC = 0.730) compared to models with Hb1Ac (p = 0.015) or clinical variables alone (p < 0.001). Regarding the constructed lncRNA score from the previous model, a lower lncRNA score was associated with a reduced risk of developing T2DM (HR 0.37 (0.24–0.59), p < 0.001), and showed an inverse correlation with the disposition index among individuals following a Mediterranean diet (r = − 0.18, p = 0.009). Conclusion: Circulating lncRNAs, particularly integrated into an epigenetic score, represent promising predictive biomarkers for T2DM development. The interaction with dietary intervention—especially the Mediterranean diet—supports their potential use in guiding personalized dietary strategies for T2DM prevention in high-risk populations.