[New aspects of nonalcoholic steatohepatitis]

During the past 10 years nonalcoholic fatty liver disease (NAFLD) has moved more and more into the focus of attention of clinical research. The term NAFLD comprises the simple nonalcoholic steatosis or fatty liver (NAFL) and nonalcoholic steatohepatitis (NASH). As the incidence of NAFLD has dramatically increased, it is expected that during the coming years NASH in particular will become the main reason for liver transplantation in industrialized countries. In addition, it has become evident that scirrhotic liver fibrosis can develop directly from NAFL without going through the stage of NASH. Finally, there is accumulating evidence that both NAFL and NASH are strongly associated with an increased risk of type 2 diabetes and cardiovascular diseases and on the other hand that NAFL and NASH are complications of diabetes. This article addresses the current knowledge about the prevalence, diagnosis, risk prediction and treatment of NAFLD.

The protective effect of human renal sinus fat on glomerular cells is reversed by the hepatokine fetuin-A

Renal sinus fat (RSF) is a perivascular fat compartment located around renal arteries. In this in vitro and in vivo study we hypothesized that the hepatokine fetuin-A may impair renal function in non alcoholic fatty liver disease (NAFLD) by altering inflammatory signalling in RSF. To study effects of the crosstalk between fetuin-A, RSF and kidney, human renal sinus fat cells (RSFC) were isolated and cocultured with human endothelial cells (EC) or podocytes (PO). RSFC caused downregulation of proinflammatory and upregulation of regenerative factors in cocultured EC and PO, indicating a protective influence of RFSC. However, fetuin-A inverted these benign effects of RSFC from an anti- to a proinflammatory status. RSF was quantified by magnetic resonance imaging and liver fat content by ¹H-MR spectroscopy in 449 individuals at risk for type 2 diabetes. Impaired renal function was determined via urinary albumin/creatinine-ratio (uACR). RSF did not correlate with uACR in subjects without NAFLD (n = 212, p = 0.94), but correlated positively in subjects with NAFLD (n = 105, p = 0.0005). Estimated glomerular filtration rate (eGRF) was inversely correlated with RSF, suggesting lower eGFR for subjects with higher RSF (r = 0.24, p < 0.0001). In conclusion, our data suggest that in the presence of NAFLD elevated fetuin-A levels may impair renal function by RSF-induced proinflammatory signalling in glomerular cells.

Age-dependent association of serum prolactin with glycaemia and insulin sensitivity in humans

The dopamine agonist bromocriptine has been approved for the treatment of type 2 diabetes in the United States. Bromocriptine inhibits prolactin secretion, and patients with hyperprolactinaemia display impaired insulin sensitivity. We therefore hypothesized that low prolactin levels are associated with lower glycaemia and higher insulin sensitivity in healthy subjects. Prolactin levels were determined from fasting serum in participants without diabetes from the cross-sectional Tübingen family study for type 2 diabetes (m/f = 562/1,121, age = 40 ± 13 years, BMI = 30 ± 9 kg/m(2)). A 75 g oral glucose tolerance test was performed, and the area under the glucose curve (AUC(0-120)Glucose) and insulin sensitivity index were calculated. A subgroup (n = 494) underwent hyperinsulinaemic-euglycaemic clamp tests. Prolactin associated positively with insulin sensitivity (p = 0.001, adjusted for gender, age, and BMI). Age strongly interacted (p < 0.0001) with the effect of prolactin on insulin sensitivity, inverting the positive relationship to a negative one in younger participants. Glycated haemoglobin (HbA1c) and AUC(0-120)Glucose correlated negatively with prolactin, and an interaction with age was found as well. Higher prolactin levels are associated with improved insulin sensitivity and lower glucose in individuals without diabetes. This relationship turns to its opposite in younger persons. As prolactin is a proxy for the dopaminergic tone in the central nervous system, these associations may indicate an age-dependent influence of the brain on peripheral insulin sensitivity.

Impairment of GLP1-induced insulin secretion: role of genetic background, insulin resistance and hyperglycaemia

One major risk factor of type 2 diabetes is the impairment of glucose-induced insulin secretion which is mediated by the individual genetic background and environmental factors. In addition to impairment of glucose-induced insulin secretion, impaired glucagon-like peptide (GLP)1-induced insulin secretion has been identified to be present in subjects with diabetes and impaired glucose tolerance, but little is known about its fundamental mechanisms. The state of GLP1 resistance is probably an important mechanism explaining the reduced incretin effect observed in type 2 diabetes. In this review, we address methods that can be used for the measurement of insulin secretion in response to GLP1 in humans, and studies showing that specific diabetes risk genes are associated with resistance of the secretory function of the β-cell in response to GLP1 administration. Furthermore, we discuss other factors that are associated with impaired GLP1-induced insulin secretion, for example, insulin resistance. Finally, we provide evidence that hyperglycaemia per se, the genetic background and their interaction result in the development of GLP1 resistance of the β-cell. We speculate that the response or the non-response to therapy with GLP1 analogues and/or dipeptidyl peptidase-4 (DPP-IV) inhibitors is critically dependent on GLP1 resistance.

Impairment of GLP1-induced insulin secretion: role of genetic background, insulin resistance and hyperglycaemia

One major risk factor of type 2 diabetes is the impairment of glucose-induced insulin secretion which is mediated by the individual genetic background and environmental factors. In addition to impairment of glucose-induced insulin secretion, impaired glucagon-like peptide (GLP)1-induced insulin secretion has been identified to be present in subjects with diabetes and impaired glucose tolerance, but little is known about its fundamental mechanisms. The state of GLP1 resistance is probably an important mechanism explaining the reduced incretin effect observed in type 2 diabetes. In this review, we address methods that can be used for the measurement of insulin secretion in response to GLP1 in humans, and studies showing that specific diabetes risk genes are associated with resistance of the secretory function of the β-cell in response to GLP1 administration. Furthermore, we discuss other factors that are associated with impaired GLP1-induced insulin secretion, for example, insulin resistance. Finally, we provide evidence that hyperglycaemia per se, the genetic background and their interaction result in the development of GLP1 resistance of the β-cell. We speculate that the response or the non-response to therapy with GLP1 analogues and/or dipeptidyl peptidase-4 (DPP-IV) inhibitors is critically dependent on GLP1 resistance.

Insulin resistant phenotype of polycystic ovary syndrome does not seem to be caused by variation in FTO

Genetic variation in the FTO gene is associated with increased body weight and reduced insulin sensitivity. We investigated whether genetic variation in FTO is associated with polycystic ovary syndrome (PCOS), a condition also characterized by insulin resistance. Furthermore, we tested whether insulin resistance is specifically associated with genetic variation in FTO in women with PCOS. Sixty-two nondiabetic patients with PCOS defined by the Rotterdam criteria were compared to BMI and age-matched women. Each PCOS case was matched to 2 controls. All participants underwent an oral glucose tolerance test and were genotyped for the single nucleotide polymorphism rs8050136 in the FTO gene. There was no difference in the frequency of FTO genotypes between the PCOS and the non-PCOS groups. In non-PCOS participants, genetic variation in FTO is associated with insulin sensitivity (p=0.03). This association remained significant after adjustment for age and/or BMI (p<= 0.03). In subjects with PCOS, however, FTO did not associate with insulin sensitivity (p=0.67). Genetic variation in FTO does not have an impact on insulin sensitivity in women with PCOS and is therefore not involved in the pathogenesis of the insulin resistant phenotype seen in patients with PCOS.

Body adiposity index, body fat content and incidence of type 2 diabetes

AIMS/HYPOTHESIS

The aim of this study was to compare estimates of body fat content, i.e. body adiposity index (BAI), BMI and waist and hip circumferences, with respect to their ability to predict the percentage of body fat (PBF; confirmed by magnetic resonance tomography) and incident type 2 diabetes.

METHODS

Associations between anthropometric measurements and PBF were evaluated in the Tübingen Lifestyle Intervention Program (TULIP; 138 men, 222 women), and between these measurements and incident type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study (9,729 men, 15,438 women) and the Cooperative Health Research in the Region of Augsburg (KORA) study (5,573 men, 5,628 women), using correlation and multivariate Cox regression analyses.

RESULTS

BMI more strongly correlated with PBF (men: r = 0.81, women: r = 0.84) than BAI (r = 0.68 and 0.81, respectively), while waist circumference among men (r = 0.84) and hip circumference among women (r = 0.88) showed the strongest correlations. BAI overestimated PBF among men (mean difference -3.0%), and this error was dependent on the value of PBF. BAI was more weakly associated with diabetes risk (RRs for 1 SD, EPIC-Potsdam men: 1.62 [95% CI 1.52, 1.72], women: 1.67 [95% CI 1.55, 1.80]; KORA men: 1.62 [95% CI 1.48, 1.78], women: 1.82 [95% CI 1.65, 2.02]) compared with BMI (RRs, EPIC-Potsdam men: 1.95 [95% CI 1.83, 2.09], women 1.88 [95% CI 1.76, 2.02], KORA men 1.75 [95% CI 1.62, 1.89], women 2.00 [95% CI 1.81, 2.22]), while waist circumference showed the strongest associations (RRs: 2.17 [95% CI 2.01, 2.35], 2.33 [95% CI 2.15, 2.53], 1.81 [95% CI 1.66, 1.96] and 2.29 [95% CI 2.05, 2.57] for EPIC-Potsdam men and women and KORA men and women, respectively).

CONCLUSIONS/INTERPRETATION

Waist circumference in men and hip circumference in women are better predictors of PBF than BAI and BMI. BAI was not as strong a predictor of diabetes as BMI, while waist circumference was the strongest predictor.