OBJECTIVEInsulin clearance is decreased in type 2 diabetes mellitus (T2DM) for unknown reasons. Subjects with metabolic syndrome are hyperinsulinemic and have an increased risk of T2DM. We aimed to investigate the relationship between hepatic insulin clearance (HIC) and different components of metabolic syndrome and tested the hypothesis that HIC may predict the risk of metabolic syndrome.RESEARCH DESIGN AND METHODSIndividuals without diabetes from the Metabolic Syndrome Berlin Brandenburg (MeSyBePo) study (800 subjects with the baseline examination and 189 subjects from the MeSyBePo recall study) underwent an oral glucose tolerance test (OGTT) with assessment of insulin secretion (insulin secretion rate [ISR]) and insulin sensitivity. Two indices of HIC were calculated.RESULTSBoth HIC indices showed lower values in subjects with metabolic syndrome (P < 0.001) at baseline. HIC indices correlate inversely with waist circumference, diastolic blood pressure, fasting glucose, triglycerides, and OGTT-derived insulin secretion index. During a mean follow-up of 5.1 ± 0.9 years, 47 individuals developed metabolic syndrome and 33 subjects progressed to impaired glucose metabolism. Both indices of HIC showed a trend of an association with increased risk of metabolic syndrome (HICC-peptide odds ratio 1.13 [95% CI 0.97–1.31], P = 0.12, and HICISR 1.38 [0.88–2.17], P = 0.16) and impaired glucose metabolism (HICC-peptide 1.12 [0.92–1.36], P = 0.26, and HICISR 1.31 [0.74–2.33] P = 0.36), although point estimates reached no statistical significance.CONCLUSIONSHIC was associated with different components of metabolic syndrome and markers of insulin secretion and insulin sensitivity. Decreased HIC may represent a novel pathophysiological mechanism of the metabolic syndrome, which may be used additionally for early identification of high-risk subjects.

Aims/hypothesis Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes. Methods We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data ( n = 340) and epidemiological case–control studies of prevalent ( n = 4925) and incident ( n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders. Results There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p < 9.2 × 10 −7 ). These associations were significantly stronger compared with the individual metabolite components. One of the ratios, valine to phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2), in addition showed a directionally consistent positive association with OGTT-derived measures of insulin secretion and resistance ( p ≤ 5.4 × 10 −3 ) and prevalent type 2 diabetes (OR Val_PC ae C32:2 2.64 [β 0.97 ± 0.09], p = 1.0 × 10 −27 ). Furthermore, Val_PC ae C32:2 predicted incident diabetes independent of established risk factors in two epidemiological cohort studies (HR Val_PC ae C32:2 1.57 [β 0.45 ± 0.06]; p = 1.3 × 10 −15 ), leading to modest improvements in the receiver operating characteristics when added to a model containing a set of established risk factors in both cohorts (increases from 0.780 to 0.801 and from 0.862 to 0.865 respectively, when added to the model containing traditional risk factors + glucose). Conclusions/interpretation In this study we have shown that the Val_PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors. Electronic supplementary material The online version of this article (10.1007/s00125-017-443...

There was no evidence of associations between alcohol use and the odds of developing either UC or CD.

The advancing age of the participants of the European Prospective Investigation into Cancer and Nutrition (EPIC)—Potsdam study was the incentive to investigate frailty as a major parameter of ageing. The aim of this study was to develop a multidimensional tool to measure frailty in an ageing, free-living study population. The “accumulation of deficits approach” was used to develop a frailty index (FI) to characterize a sub-sample (N = 815) of the EPIC-Potsdam (EPIC-P) study population regarding the aging phenomenon. The EPIC-P frailty index (EPIC-P-FI) included 32 variables from the following domains: health, physical ability, psychosocial and physiological aspects. P–values were calculated for the linear trend between sociodemographic and life style variables and the EPIC-P-FI was calculated using regression analysis adjusted for age. The relationship between the EPIC-P-FI and age was investigated using fractional polynomials. Some characteristics such as age, education, time spent watching TV, cycling and a biomarker of inflammation (C-reactive protein) were associated with frailty in men and women. Interestingly, living alone, having no partner and smoking status were only associated with frailty in men, and alcohol use and physical fitness (VO2max) only in women. The generated, multidimensional FI, adapted to the EPIC-P study, showed that this cohort is a valuable source for further exploration of factors that promote healthy ageing.

Reduction of the glycemic load by acarbose decreased fasting levels of proinsulin but had no effect on adiponectin and whole-body insulin sensitivity as well as biomarkers reflecting inflammation. The preventive effects of acarbose on type 2 diabetes mellitus and cardiovascular risk need further investigation and cannot be explained by changes of insulin resistance and inflammatory biomarkers.