Innovative biomarkers of insulin resistance and lipid metabolism predicting diabetes:studies in the general population and renal transplant recipients

This dissertation explores various biomarkers associated with type 2 diabetes (T2D) in different subgroups of individuals with metabolic syndrome and obesity, as well as their potential role in risk prediction and the development of post-transplantation diabetes (PTDM) in kidney transplant patients.For T2D, C-peptide and proinsulin are considered potential biomarkers that provide insight into beta-cell function and the early physiological changes preceding the disease. Additionally, lipid biomarkers measured using nuclear magnetic resonance (NMR) are associated with beta-cell function and the risk of T2D. The study highlights the potential of these biomarkers for early T2D prediction.While previous studies have examined biomarkers in the general population, the research emphasizes the importance of evaluating biomarkers in different subgroups with distinct characteristics, such as kidney transplant recipients (KTRs), who are at an increased risk of PTDM. The study demonstrates that certain biomarkers, such as insulin resistance indices and HDL particle characteristics, have predictive value for PTDM in KTRs.Furthermore, the research underscores the potential of combined biomarkers over individual biomarkers for T2D prediction. It highlights the value of simple methods, such as insulin-free formulas, in identifying kidney transplant patients at an elevated risk of PTDM.The results suggest that new biomarkers of insulin resistance and lipid metabolism may be valuable for predicting T2D and PTDM, emphasizing the importance of tailoring biomarker research to specific patient groups

Innovative biomarkers of insulin resistance and lipid metabolism predicting diabetes:studies in the general population and renal transplant recipients

This dissertation explores various biomarkers associated with type 2 diabetes (T2D) in different subgroups of individuals with metabolic syndrome and obesity, as well as their potential role in risk prediction and the development of post-transplantation diabetes (PTDM) in kidney transplant patients.For T2D, C-peptide and proinsulin are considered potential biomarkers that provide insight into beta-cell function and the early physiological changes preceding the disease. Additionally, lipid biomarkers measured using nuclear magnetic resonance (NMR) are associated with beta-cell function and the risk of T2D. The study highlights the potential of these biomarkers for early T2D prediction.While previous studies have examined biomarkers in the general population, the research emphasizes the importance of evaluating biomarkers in different subgroups with distinct characteristics, such as kidney transplant recipients (KTRs), who are at an increased risk of PTDM. The study demonstrates that certain biomarkers, such as insulin resistance indices and HDL particle characteristics, have predictive value for PTDM in KTRs.Furthermore, the research underscores the potential of combined biomarkers over individual biomarkers for T2D prediction. It highlights the value of simple methods, such as insulin-free formulas, in identifying kidney transplant patients at an elevated risk of PTDM.The results suggest that new biomarkers of insulin resistance and lipid metabolism may be valuable for predicting T2D and PTDM, emphasizing the importance of tailoring biomarker research to specific patient groups

Remnant lipoprotein cholesterol is associated with incident new onset diabetes after transplantation (NODAT) in renal transplant recipients:results of the TransplantLines Biobank and cohort Studies

BACKGROUND: New onset diabetes after transplantation (NODAT) is a frequent and serious complication of renal transplantation resulting in worse graft and patient outcomes. The pathophysiology of NODAT is incompletely understood, and no prospective biomarkers have been established to predict NODAT risk in renal transplant recipients (RTR). The present work aimed to determine whether remnant lipoprotein (RLP) cholesterol could serve as such a biomarker that would also provide a novel target for therapeutic intervention. METHODS: This longitudinal cohort study included 480 RTR free of diabetes at baseline. 53 patients (11%) were diagnosed with NODAT during a median [interquartile range, IQR] follow-up of 5.2 [4.1–5.8] years. RLP cholesterol was calculated by subtracting HDL and LDL cholesterol from total cholesterol values (all directly measured). RESULTS: Baseline remnant cholesterol values were significantly higher in RTR who subsequently developed NODAT (0.9 [0.5–1.2] mmol/L vs. 0.6 [0.4–0.9] mmol/L, p = 0.001). Kaplan-Meier analysis showed that higher RLP cholesterol values were associated with an increased risk of incident NODAT (log rank test, p < 0.001). Cox regression demonstrated a significant longitudinal association between baseline RLP cholesterol levels and NODAT (HR, 2.27 [1.64–3.14] per 1 SD increase, p < 0.001) that remained after adjusting for plasma glucose and HbA1c (p = 0.002), HDL and LDL cholesterol (p = 0.008) and use of immunosuppressive medication (p < 0.001), among others. Adding baseline remnant cholesterol to the Framingham Diabetes Risk Score significantly improved NODAT prediction (change in C-statistic, p = 0.01). CONCLUSIONS: This study demonstrates that baseline RLP cholesterol levels strongly associate with incident NODAT independent of several other recognized risk factors

HDL Particle Subspecies and Their Association With Incident Type 2 Diabetes:The PREVEND Study

Context: 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 7 HDL subspecies. Objective: We aimed to investigate the association of HDL particle subspecies with incident T2D in the general population. 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: A total of 265 individuals developed T2D (median follow-up of 7.3 years). In Cox regression models, HDL size and H4P (hazard ratio [HR] per 1 SD increase 0.83 [95% CI, 0.690.99] and 0.85 [95% CI, 0.75-0.95], respectively) were inversely associated with incident T2D, after adjustment for relevant covariates. In contrast, levels of H2P were positively associated with incidentT2D (HR 1.15 [95% CI, 1.01-1.32]). In secondary analyses, associations with large HDL particles and H6P were modified by body mass index (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 nonobese subjects

Triglyceride-rich lipoprotein and LDL particle subfractions and their association with incident type 2 diabetes:the PREVEND study

Abstract 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

High-density lipoprotein particles and their relationship to posttransplantation diabetes mellitus in renal transplant recipients

High concentrations of high-density lipoprotein (HDL) cholesterol are likely associated with a lower risk of posttransplantation diabetes mellitus (PTDM). However, HDL particles vary in size and density with yet unestablished associations with PTDM risk. The aim of our study was to determine the association between different HDL particles and development of PTDM in renal transplant recipients (RTRs). We included 351 stable outpatient adult RTRs without diabetes at baseline evaluation. HDL particle characteristics and size were measured by nuclear magnetic resonance (NMR) spectroscopy. During 5.2 (IQR, 4.1‒5.8) years of follow-up, 39 (11%) RTRs developed PTDM. In multivariable Cox regression analysis, levels of HDL cholesterol (hazard ratio [HR] 0.61, 95% confidence interval [CI] 0.40–0.94 per 1SD increase; p = 0.024) and of large HDL particles (HR 0.68, 95% CI 0.50–0.93 per log 1SD increase; p = 0.017), as well as larger HDL size (HR 0.58, 95% CI 0.36–0.93 per 1SD increase; p = 0.025) were inversely associated with PTDM development, independently of relevant covariates including, age, sex, body mass index, medication use, transplantation-specific parameters, blood pressure, triglycerides, and glucose. In conclusion, higher concentrations of HDL cholesterol and of large HDL particles and greater HDL size were associated with a lower risk of PTDM development in RTRs, independently of established risk factors for PTDM development

Fasting Proinsulin Independently Predicts Incident Type 2 Diabetes in the General Population

Fasting proinsulin levels may serve as a marker of beta-cell dysfunction and predict type 2 diabetes (T2D) development. Kidneys have been found to be a major site for the degradation of proinsulin. We aimed to evaluate the predictive value of proinsulin for the risk of incident T2D added to a base model of clinical predictors and examined potential effect modification by variables related to kidney function. Proinsulin was measured in plasma with U-PLEX platform using ELISA immunoassay. We included 5001 participants without T2D at baseline and during a median follow up of 7.2 years; 271 participants developed T2D. Higher levels of proinsulin were associated with increased risk of T2D independent of glucose, insulin, C-peptide, and other clinical factors (hazard ratio (HR): 1.28; per 1 SD increase 95% confidence interval (CI): 1.08-1.52). Harrell's C-index for the Framingham offspring risk score was improved with the addition of proinsulin (p = 0.019). Furthermore, we found effect modification by hypertension (p = 0.019), eGFR (p = 0.020) and urinary albumin excretion (p = 0.034), consistent with an association only present in participants with hypertension or kidney dysfunction. Higher fasting proinsulin level is an independent predictor of incident T2D in the general population, particularly in participants with hypertension or kidney dysfunction

Plasma C-Peptide and Risk of Developing Type 2 Diabetes in the General Population

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

Androgens and Development of Posttransplantation Diabetes Mellitus in Male Kidney Transplant Recipients:A Post Hoc Analysis of a Prospective Study

OBJECTIVE: Posttransplantation diabetes mellitus (PTDM) effects up to 30% of all kidney transplant recipients (KTR). Recent studies in mice found that sufficient androgen levels are necessary for β-cell health and adequate insulin secretion. This raises the question whether a similar relationship might be present in KTR. Hence, we hypothesized that dihydrotestosterone and testosterone are associated with the development of PTDM in male KTR. RESEARCH DESIGN AND METHODS: We conducted a post hoc analyses of a prospective single-center cohort study including adult male KTR with a functioning graft ≥1 year posttransplantation. Androgen levels were assessed by liquid chromatography-tandem mass spectrometry. Development of PTDM was defined according to the American Diabetes Association's criteria. RESULTS: We included 243 male KTR (aged 51 ± 14 years), with a median dihydrotestosterone 0.9 (0.7-1.3) nmol/L and testosterone of 12.1 (9.4-15.8) nmol/L. During 5.3 (3.7-5.8) years of follow-up, 28 KTR (11.5%) developed PTDM. A clear association was observed, as 15 (19%), 10 (12%), and 3 (4%) male KTR developed PTDM in the respective tertiles of dihydrotestosterone (P = 0.008). In Cox regression analyses, both dihydrotestosterone and testosterone as continuous variables were inversely associated with the risk to development PTDM, independent of glucose and HbA1c (hazard ratio [HR] 0.31 [95%CI 0.16-0.59], P < 0.001; and HR 0.32 [95%CI 0.15-0.68], P = 0.003, respectively). CONCLUSIONS: Our results suggest that low androgen levels are a novel potential modifiable risk factor for the development of PTDM in male KTR