BackgroundLimited evidence is available about the association between serum uric acid and sub-stages of the spectrum from normoglycaemia to type 2 diabetes mellitus. We aimed to investigate the association between serum uric acid and risk of prediabetes and type 2 diabetes mellitus.MethodsEligible participants of the Rotterdam Study (n = 8,367) were classified into mutually exclusive subgroups of normoglycaemia (n = 7,030) and prediabetes (n = 1,337) at baseline. These subgroups were followed up for incident prediabetes (n = 1,071) and incident type 2 diabetes mellitus (n = 407), respectively. We used Cox proportional hazard models to determine hazard ratios (HRs) for incident prediabetes among individuals with normoglycaemia and incident type 2 diabetes mellitus among individuals with prediabetes.ResultsThe mean duration of follow-up was 7.5 years for incident prediabetes and 7.2 years for incident type 2 diabetes mellitus. A standard deviation increment in serum uric acid was significantly associated with incident prediabetes among individuals with normoglycaemia (HR 1.10, 95% confidence interval (CI) 1.01; 1.18), but not with incident type 2 diabetes mellitus among individuals with prediabetes (HR 1.07, 95% CI 0.94; 1.21). Exclusion of individuals who used diuretics or individuals with hypertension did not change our results. Serum uric acid was significantly associated with incident prediabetes among normoglycaemic women (HR 1.13, 95% CI 1.02; 1.25) but not among normoglycaemic men (HR 1.08, 95% CI 0.96; 1.21). In contrast, serum uric acid was significantly associated with incident type 2 diabetes mellitus among prediabetic men (HR 1.23, 95% CI 1.01; 1.48) but not among prediabetic women (HR 1.00, 95% CI 0.84; 1.19).ConclusionsOur findings agree with the notion that serum uric acid is more closely related to early-phase mechanisms in the development of type 2 diabetes mellitus than late-phase mechanisms.

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Serum apoCIII levels as well as apoCIII-to-apoA1 ratio are associated with incident T2D. They are associated independent of known risk factors and stronger than HDL-C levels.

The immune response involved in each phase of type 2 diabetes (T2D) development might be different. We aimed to identify novel inflammatory markers that predict progression from normoglycemia to pre-diabetes, incident T2D and insulin therapy. We used plasma levels of 26 inflammatory markers in 971 subjects from the Rotterdam Study. Among them 17 are novel and 9 previously studied. Cox regression models were built to perform survival analysis. Main Outcome Measures: During a follow-up of up to 14.7 years (between April 1, 1997, and Jan 1, 2012) 139 cases of pre-diabetes, 110 cases of T2D and 26 cases of insulin initiation were identified. In age and sex adjusted Cox models, IL13 (HR = 0.78), EN-RAGE (1.30), CFH (1.24), IL18 (1.22) and CRP (1.32) were associated with incident pre-diabetes. IL13 (0.62), IL17 (0.75), EN-RAGE (1.25), complement 3 (1.44), IL18 (1.35), TNFRII (1.27), IL1ra (1.24) and CRP (1.64) were associated with incident T2D. In multivariate models, IL13 (0.77), EN-RAGE (1.23) and CRP (1.26) remained associated with pre-diabetes. IL13 (0.67), IL17 (0.76) and CRP (1.32) remained associated with T2D. IL13 (0.55) was the only marker associated with initiation of insulin therapy in diabetics. Various inflammatory markers are associated with progression from normoglycemia to pre-diabetes (IL13, EN-RAGE, CRP), T2D (IL13, IL17, CRP) or insulin therapy start (IL13). Among them, EN-RAGE is a novel inflammatory marker for pre-diabetes, IL17 for incident T2D and IL13 for pre-diabetes, incident T2D and insulin therapy start.Electronic supplementary materialThe online version of this article (doi:10.1007/s10654-017-0236-0) contains supplementary material, which is available to authorized users.

Aims/hypothesis Both visceral and truncal fat have been associated with metabolic disturbances. We aimed to investigate the associations of several novel metabolic indices, combining anthropometric and lipid measures, and dual-energy x-ray absorptiometry (DXA) measurements of body fat, with incident type 2 diabetes among women and men from the large population-based Rotterdam Study. Methods Cox proportional hazards models were used to investigate associations of visceral adiposity index (VAI), lipid accumulation product (LAP), the product of triacylglycerol and glucose (TyG), their formula components and DXA measures with incident type 2 diabetes. Associations were adjusted for traditional diabetes risk factors. Results Among 5576 women and 3988 men free of diabetes, 511 women and 388 men developed type 2 diabetes during a median follow-up of 6.5 years. In adjusted models, the three metabolic indices VAI (per 1 SD naturally log-transformed HR; 95%

Context There is a need for novel biomarkers and better understanding of the pathophysiology of diabetic kidney disease. Objective To investigate associations between plasma metabolites and kidney function in people with type 2 diabetes (T2D). Design 3089 samples from individuals with T2D, collected between 1999 and 2015, from 5 independent Dutch cohort studies were included. Up to 7 years follow-up was available in 1100 individuals from 2 of the cohorts. Main outcome measures Plasma metabolites (n = 149) were measured by nuclear magnetic resonance spectroscopy. Associations between metabolites and estimated glomerular filtration rate (eGFR), urinary albumin-to-creatinine ratio (UACR), and eGFR slopes were investigated in each study followed by random effect meta-analysis. Adjustments included traditional cardiovascular risk factors and correction for multiple testing. Results In total, 125 metabolites were significantly associated (PFDR = 1.5×10–32 − 0.046; β = −11.98-2.17) with eGFR. Inverse associations with eGFR were demonstrated for branched-chain and aromatic amino acids (AAAs), glycoprotein acetyls, triglycerides (TGs), lipids in very low-density lipoproteins (VLDL) subclasses, and fatty acids (PFDR < 0.03). We observed positive associations with cholesterol and phospholipids in high-density lipoproteins (HDL) and apolipoprotein A1 (PFDR < 0.05). Albeit some metabolites were associated with UACR levels (P < 0.05), significance was lost after correction for multiple testing. Tyrosine and HDL-related metabolites were positively associated with eGFR slopes before adjustment for multiple testing (PTyr = 0.003; PHDLrelated < 0.05), but not after. Conclusions This study identified metabolites associated with impaired kidney function in T2D, implying involvement of lipid and amino acid metabolism in the pathogenesis. Whether these processes precede or are consequences of renal impairment needs further investigation.

Blood metabolomic measures were associated with present and future glycemic control and might thus provide relevant cues to identify those at increased risk of treatment failure.

Aims/hypothesis Previous literature documents controversial results for the impact of dehydroepiandrosterone (DHEA) in glucose metabolism. We aimed to assess the associations between serum levels of DHEA and its main derivatives DHEA sulphate (DHEAS) and androstenedione, as well as the ratio of DHEAS to DHEA, and risk of type 2 diabetes. Methods We used data on serum levels of DHEA, DHEAS and androstenedione from 5189 middle-aged and elderly men and women from the prospective population-based Rotterdam Study. Type 2 diabetes was defined as a fasting blood glucose ≥7.0 mmol/l or a non-fasting blood glucose ≥11.1 mmol/l. Results During a median follow-up of 10.9 years, 643 patients with incident type 2 diabetes were identified. After adjusting for age, sex, cohort, fasting status, fasting glucose and insulin, and BMI, both serum DHEA levels (per 1 unit natural logtransformed, HR 0.76, 95% CI 0.67, 0.87) and serum DHEAS levels (per 1 unit natural log-transformed, HR 0.82, 95% CI 0.73, 0.92) were inversely associated with risk of type 2 diabetes in the total population. Further adjustment for alcohol, smoking, physical activity, prevalent cardiovascular disease, serum total cholesterol, use of lipid-lowering medications, systolic BP, treatment for hypertension, C-reactive protein, oestradiol and testosterone did not substantially affect the association between DHEA and incident type 2 diabetes (per 1 unit natural log-transformed, HR 0.80, 95% CI 0.65, 0.99), but abolished the association between DHEAS and type 2 diabetes. Androstenedione was not associated with risk of type 2 diabetes, nor was DHEAS to DHEA ratio. Conclusions/interpretation DHEA serum levels might be an independent marker of type 2 diabetes.