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Non-alcoholic fatty liver disease (NAFLD) is a common diagnosis and is increasing in prevalence worldwide. NAFLD is usually asymptomatic at presentation; progression of the disease is unpredictable, leading to the development of a variety of techniques for screening, diagnosis and risk stratification. Clinical methods in current use include serum biomarker panels, hepatic ultrasound, magnetic resonance imaging, and liver biopsy. NAFLD is strongly associated with the metabolic syndrome, and the most common cause of death for people with the condition is cardiovascular disease. Whether NAFLD is an independent cardiovascular risk factor needs exploration. NAFLD has been associated with surrogate markers of cardiovascular disease such as carotid intima-media thickness, the presence of carotid plaque, brachial artery vasodilatory responsiveness and CT coronary artery calcification score. There is no effective medical treatment for NAFLD and evidence is lacking regarding the efficacy of interventions in mitigating cardiovascular risk. Health care professionals managing patients with NAFLD should tackle the issue with early identification of risk factors and aggressive modification. Current management strategies therefore comprise lifestyle change, with close attention to known cardiovascular risk factors.

Our objectives were to determine if there are quantitative associations between amounts and intensities of physical activities (PA) on NMR biomarkers and changes in skeletal muscle gene expressions in subjects with high risk for type 2 diabetes (T2D) performing a 3-month PA intervention. We found that PA was associated with beneficial biomarker changes in a factor containing several VLDL and HDL subclasses and lipids in principal component analysis (P =

C-reactive protein (CRP) and microalbuminuria reflect intimately related components of the atherosclerotic disease process. Epidemiological studies found only modest associations between CRP and microalbuminuria. Blood pressure, one of the components of the metabolic syndrome in the general population, is the main determinant of microalbuminuria in diabetes and hypertension. We questioned whether CRP modifies the relationship of blood pressure and other cardiovascular risk factors with microalbuminuria in a cross-sectional study in 8592 inhabitants from Groningen, The Netherlands. The crude data showed an increase in the prevalence of microalbuminuria with increasing CRP quartiles (4.8, 9.6, 14.5, and 18.6%, P P =0.03). In subjects with a MAP P =0.11). This trend was much steeper and significant in subjects with an MAP >90 mm Hg (prevalence: 6.7%, 13.6%, 20.4%, 25.1%; P P =0.0004). No significant interactions between other risk factors and CRP with respect to the risk of microalbuminuria were encountered. Thus, CRP modifies the relation between blood pressure and microalbuminuria.

C-reactive protein (CRP) and microalbuminuria (MA) have been identified as risk markers for cardiovascular disease (CVD). We questioned whether CRP and MA are similar markers of vascular disease in different regions of the vascular tree like the heart, kidneys and extremities or if they differ in their relationships with these vascular beds. Baseline levels of CRP and urinary albumin were measured in 6669 non-diabetic participants in the Prevention of Renal and Vascular ENdstage Disease (PREVEND) study, a Dutch cohort derived from the general population. We defined three domains of vascular disease; coronary heart disease (myocardial infarction or infarct pattern on the ECG), renal insufficiency (creatinine clearance

Aims/hypothesis Twin and family studies have shown the importance of genetic factors influencing fasting and 2 h glucose and insulin levels. However, the genetics of the physiological response to a glucose load has not been thoroughly investigated. Methods We studied 580 monozygotic and 1,937 dizygotic British female twins from the Twins UK Registry. The effects of genetic and environmental factors on fasting and 2 h glucose and insulin levels were estimated using univariate genetic modelling. Bivariate model fitting was used to investigate the glucose and insulin responses to a glucose load, i.e. an OGTT. Results The genetic effect on fasting and 2 h glucose and insulin levels ranged between 40% and 56% after adjustment for age and BMI. Exposure to a glucose load resulted in the emergence of novel genetic effects on 2 h glucose independent of the fasting level, accounting for about 55% of its heritability. For 2 h insulin, the effect of the same genes that already influenced fasting insulin was amplified by about 30%. Conclusions/interpretation Exposure to a glucose challenge uncovers new genetic variance for glucose and amplifies the effects of genes that already influence the fasting insulin level. Finding the genes acting on 2 h glucose independently of fasting glucose may offer new aetiological insight into the risk of cardiovascular events and death from all causes.