Background and aims High-density lipoproteins (HDL) may be protective against type 2 diabetes (T2D) development, but HDL particles vary in size and function which could lead to differential associations with incident T2D. A newly developed nuclear magnetic resonance (NMR)-derived algorithm provides concentrations for seven HDL subspecies. We aimed to investigate the association of HDL particle subspecies with incident T2D in the general population. Materials and methods Among 4828 subjects of the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study without T2D at baseline. HDL subspecies with increasing size from H1P to H7P were measured by NMR (LP4 algorithm of the Vantera NMR platform). Results 265 individuals developed T2D (median follow-up of 7.3 years). In Cox regression models, HDL size and H4P [HR per 1 SD increase 0.83 (95% CI, 0.69-0.99) and 0.85 (95% CI, 0.75-0.95), respectively] were inversely associated with incident T2D, after adjustment for relevant covariates. Oppositely, levels of H2P were positively associated with incident T2D (HR 1.15 (95% CI, 1.01-1.32)). In secondary analyses, associations with large HDL particles and H6P were modified by BMI in such a way that they were particularly associated with a lower risk of incident T2D, in subjects with BMI < 30 kg/m 2. Conclusion Greater HDL size and lower levels of H4P were associated with a lower risk, whereas higher levels of H2P were associated with a higher risk of developing T2D. In addition, large HDL particles and H6P were inversely associated with T2D in non-obese subjects.

Background Triglyceride-rich lipoproteins particles (TRLP) and low density lipoprotein particles (LDLP) vary in size. Their association with β-cell function is not well described. We determined associations of TRLP and LDLP subfractions with β-cell function, estimated as HOMA-β, and evaluated their associations with incident T2D in the general population. Methods We included 4818 subjects of the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study without T2D at baseline. TRLP and LDLP subfraction concentrations and their average sizes were measured using the LP4 algorithm of the Vantera nuclear magnetic resonance platform. HOMA-IR was used as measure of insulin resistance. HOMA-β was used as a proxy of β-cell function. Results In subjects without T2D at baseline, very large TRLP, and LDL size were inversely associated with HOMA-β, whereas large TRLP were positively associated with HOMA-β when taking account of HOMA-IR. During a median follow-up of 7.3 years, 263 participants developed T2D. In multivariable-adjusted Cox regression models, higher concentrations of total, very large, large, and very small TRLP (reflecting remnants lipoproteins) and greater TRL size were associated with an increased T2D risk after adjustment for relevant covariates, including age, sex, BMI, HDL-C, HOMA-β, and HOMA-IR. On the contrary, higher concentrations of large LDLP and greater LDL size were associated with a lower risk of developing T2D. Conclusions Specific TRL and LDL particle characteristics are associated with β-cell function taking account of HOMA-IR. Moreover, TRL and LDL particle characteristics are differently associated with incident T2D, even when taking account of HOMA-β and HOMA-IR.

C-peptide measurement may represent a better index of pancreatic β-cell function compared to insulin. While insulin is mainly cleared by liver, C-peptide is mainly metabolized by kidneys. The aim of our study was to evaluate the association between baseline plasma C-peptide level and the development of type 2 diabetes independent of glucose and insulin levels and to examine potential effect-modification by variables related to kidney function. We included 5176 subjects of the Prevention of Renal and Vascular End-Stage Disease study without type 2 diabetes at baseline. C-peptide was measured in plasma with an electrochemiluminescent immunoassay. Cox proportional hazards regression was used to evaluate the association between C-peptide level and type 2 diabetes development. Median C-peptide was 722 (566–935) pmol/L. During a median follow-up of 7.2 (6.0–7.7) years, 289 individuals developed type 2 diabetes. In multivariable-adjusted Cox regression models, we observed a significant positive association of C-peptide with the risk of type 2 diabetes independent of glucose and insulin levels (hazard ratio (HR): 2.35; 95% confidence interval (CI): 1.49–3.70). Moreover, we found significant effect modification by hypertension and albuminuria (p < 0.001 and p = 0.001 for interaction, respectively), with a stronger association in normotensive and normo-albuminuric subjects and absence of an association in subjects with hypertension or albuminuria. In this population-based cohort, elevated C-peptide levels are associated with an increased risk of type 2 diabetes independent of glucose, insulin levels, and clinical risk factors. Elevated C-peptide level was not independently associated with an increased risk of type 2 diabetes in individuals with hypertension or albuminuria.