Novel Proteome Targets Marking Insulin Resistance in Metabolic Syndrome.

CONTEXT/OBJECTIVE: In order to better understand which metabolic differences are related to insulin resistance in metabolic syndrome (MetSyn), we used hyperinsulinemic-euglycemic (HE) clamps in individuals with MetSyn and related peripheral insulin resistance to circulating biomarkers. DESIGN/METHODS: In this cross-sectional study, HE-clamps were performed in treatment-naive men (n = 97) with MetSyn. Subjects were defined as insulin-resistant based on the rate of disappearance (Rd). Machine learning models and conventional statistics were used to identify biomarkers of insulin resistance. Findings were replicated in a cohort with n = 282 obese men and women with (n = 156) and without (n = 126) MetSyn. In addition to this, the relation between biomarkers and adipose tissue was assessed by nuclear magnetic resonance imaging. RESULTS: Peripheral insulin resistance is marked by changes in proteins related to inflammatory processes such as IL-1 and TNF-receptor and superfamily members. These proteins can distinguish between insulin-resistant and insulin-sensitive individuals (AUC = 0.72 ± 0.10) with MetSyn. These proteins were also associated with IFG, liver fat (rho 0.36, p = 1.79 × 10-9) and visceral adipose tissue (rho = 0.35, p = 6.80 × 10-9). Interestingly, these proteins had the strongest association in the MetSyn subgroup compared to individuals without MetSyn. CONCLUSIONS: MetSyn associated with insulin resistance is characterized by protein changes related to body fat content, insulin signaling and pro-inflammatory processes. These findings provide novel targets for intervention studies and should be the focus of future in vitro and in vivo studies.

Metabolite Profile of Treatment-Naive Metabolic Syndrome Subjects in Relation to Cardiovascular Disease Risk.

Metabolic syndrome (MetSyn) is an important risk factor for type 2 diabetes and cardiovascular diseases (CVD). This study aimed to find distinct plasma metabolite profiles between insulin-resistant and non-insulin resistant subjects with MetSyn and evaluate if MetSyn metabolite profiles are related to CVD risk and lipid fluxes. In a cross-sectional study, untargeted metabolomics of treatment-naive males with MetSyn (n = 132) were analyzed together with clinical parameters. In a subset of MetSyn participants, CVD risk was calculated using the Framingham score (n = 111), and lipolysis (n = 39) was measured by a two-step hyperinsulinemic euglycemic clamp using [1,1,2,3,3-2H5] glycerol to calculate lipolysis suppression rates. Peripheral insulin resistance was related to fatty acid metabolism and glycerolphosphorylcholine. Interestingly, although insulin resistance is considered to be a risk factor for CVD, we observed that there was little correspondence between metabolites associated with insulin resistance and metabolites associated with CVD risk. The latter mainly belonged to the androgenic steroid, fatty acid, phosphatidylethanolamine, and phophatidylcholine pathways. These data provide new insights into metabolic changes in mild MetSyn pathophysiology and MetSyn CVD risk related to lipid metabolism. Prospective studies may focus on the pathophysiological role of the here-identified biomarkers.

Donor Fecal Microbiota Transplantation Alters Gut Microbiota and Metabolites in Obese Individuals With Steatohepatitis.

The intestinal microbiota has been linked to the development and prevalence of steatohepatitis in humans. Interestingly, steatohepatitis is significantly lower in individuals taking a plant-based, low-animal-protein diet, which is thought to be mediated by gut microbiota. However, data on causality between these observations in humans is scarce. In this regard, fecal microbiota transplantation (FMT) using healthy donors is safe and is capable of changing microbial composition in human disease. We therefore performed a double-blind randomized controlled proof-of-principle study in which individuals with hepatic steatosis on ultrasound were randomized to two study arms: lean vegan donor (allogenic n = 10) or own (autologous n = 11) FMT. Both were performed three times at 8-week intervals. A liver biopsy was performed at baseline and after 24 weeks in every subject to determine histopathology (Nonalcoholic Steatohepatitis Clinical Research Network) classification and changes in hepatic gene expression based on RNA sequencing. Secondary outcome parameters were changes in intestinal microbiota composition and fasting plasma metabolomics. We observed a trend toward improved necro-inflammatory histology, and found significant changes in expression of hepatic genes involved in inflammation and lipid metabolism following allogenic FMT. Intestinal microbial community structure changed following allogenic FMT, which was associated with changes in plasma metabolites as well as markers of . Conclusion: Allogenic FMT using lean vegan donors in individuals with hepatic steatosis shows an effect on intestinal microbiota composition, which is associated with beneficial changes in plasma metabolites and markers of steatohepatitis.

Plasma Metabolites Related to Peripheral and Hepatic Insulin Sensitivity Are Not Directly Linked to Gut Microbiota Composition.

Plasma metabolites affect a range of metabolic functions in humans, including insulin sensitivity (IS). A subset of these plasma metabolites is modified by the gut microbiota. To identify potential microbial-metabolite pathways involved in IS, we investigated the link between plasma metabolites, gut microbiota composition, and IS, using the gold-standard for peripheral and hepatic IS measurement in a group of participants with metabolic syndrome (MetSyn). In a cross-sectional study with 115 MetSyn participants, fasting plasma samples were collected for untargeted metabolomics analysis and fecal samples for 16S rRNA gene amplicon sequencing. A two-step hyperinsulinemic euglycemic clamp was performed to assess peripheral and hepatic IS. Collected data were integrated and potential interdependence between metabolites, gut microbiota, and IS was analyzed using machine learning prediction models. Plasma metabolites explained 13.2% and 16.7% of variance in peripheral and hepatic IS, respectively. Fecal microbiota composition explained 4.2% of variance in peripheral IS and was not related to hepatic IS. Although metabolites could partially explain the variances in IS, the top metabolites related to peripheral and hepatic IS did not significantly correlate with gut microbiota composition (both on taxonomical level and alpha-diversity). However, all plasma metabolites could explain 18.5% of the variance in microbial alpha-diversity (Shannon); the top 20 metabolites could even explain 44.5% of gut microbial alpha-diversity. In conclusion, plasma metabolites could partially explain the variance in peripheral and hepatic IS; however, these metabolites were not directly linked to the gut microbiota composition, underscoring the intricate relation between plasma metabolites, the gut microbiota, and IS in MetSyn.

The effect of dapagliflozin on apolipoprotein B and glucose fluxes in patients with type 2 diabetes and well-controlled plasma LDL cholesterol.

AIM: To dissect the effects of the sodium-glucose linked transporter 2 inhibitor dapagliflozin on lipid metabolism and assess whether these effects could potentially offset cardiovascular benefit with this drug-class. MATERIALS AND METHODS: We assessed the effect of dapagliflozin on lipid metabolism in 11 adults with uncomplicated type 2 diabetes. After 4 weeks of statin wash-out and 4 weeks of rosuvastatin 10 mg treatment, participants were treated with dapagliflozin 10 mg once-daily for 5 weeks. Before and after dapagliflozin, plasma lipids were measured and very low-density lipoprotein (VLDL)-1 and VLDL-2 apolipoprotein (Apo)B fluxes were assessed using (5.5.5-2 H3 )-leucine tracer infusion. In addition, hepatic and peripheral insulin sensitivity as well as insulin-mediated inhibition of peripheral lipolysis were measured during a two-step hyperinsulinemic-euglycaemic clamp using (6,6-2 H2 )-glucose and (1,1,2,3,3-2 H5 )-glycerol tracers. RESULTS: Rosuvastatin decreased all plasma lipids significantly: total cholesterol from 4.5 (3.2-6.2) to 3.1 (2.5-3.8) mmol/L, LDL cholesterol from 2.6 (1.7-3.4) to 1.5 (1.1-2.2) mmol/L, HDL cholesterol from 1.34 (0.80-2.02) to 1.19 (0.74-1.89) mmol/L and triglycerides from 0.92 (0.31-3.91) to 0.79 (0.32-2.10) mmol/L. The addition of dapaglifozin to rosuvastatin did not raise either LDL cholesterol or total cholesterol, and only increased HDL cholesterol by 0.08 (-0.03-0.13) mmol/L (P = 0.03). In line with this, dapagliflozin did not affect VLDL-1 or VLDL-2 ApoB fluxes. Fasting endogenous glucose production tended to increase by 0.9 (-3.4-3.1) µmol kg-1 min-1 (P = 0.06), but no effect on hepatic and peripheral insulin sensitivity or on peripheral lipolysis was observed. CONCLUSIONS: Dapagliflozin has no effect on plasma LDL-cholesterol levels or VLDL-apoB fluxes in the context of optimal lipid-lowering treatment, which will thus not limit cardiovascular benefit when lipids are adequately controlled.

Insights into the role of the microbiome in obesity and type 2 diabetes.

The worldwide prevalence of obesity and type 2 diabetes mellitus (T2DM) continues to rise at an alarming pace. Recently the potential role of the gut microbiome in these metabolic disorders has been identified. Obesity is associated with changes in the composition of the intestinal microbiota, and the obese microbiome seems to be more efficient in harvesting energy from the diet. Lean male donor fecal microbiota transplantation (FMT) in males with metabolic syndrome resulted in a significant improvement in insulin sensitivity in conjunction with an increased intestinal microbial diversity, including a distinct increase in butyrate-producing bacterial strains. Such differences in gut microbiota composition might function as early diagnostic markers for the development of T2DM in high-risk patients. Products of intestinal microbes such as butyrate may induce beneficial metabolic effects through enhancement of mitochondrial activity, prevention of metabolic endotoxemia, and activation of intestinal gluconeogenesis via different routes of gene expression and hormone regulation. Future research should focus on whether bacterial products (like butyrate) have the same effects as the intestinal bacteria that produce it, in order to ultimately pave the way for more successful interventions for obesity and T2DM. The rapid development of the currently available techniques, including use of fecal transplantations, has already shown promising results, so there is hope for novel therapies based on the microbiota in the future.

Therapeutic potential of fecal microbiota transplantation.

There has been growing interest in the use of fecal microbiota for the treatment of patients with chronic gastrointestinal infections and inflammatory bowel diseases. Lately, there has also been interest in its therapeutic potential for cardiometabolic, autoimmune, and other extraintestinal conditions that were not previously considered to be associated with the intestinal microbiota. Although it is not clear if changes in the microbiota cause these conditions, we review the most current and best methods for performing fecal microbiota transplantation and summarize clinical observations that have implicated the intestinal microbiota in various diseases. We also discuss case reports of fecal microbiota transplantations for different disorders, including Clostridium difficile infection, irritable bowel syndrome, inflammatory bowel diseases, insulin resistance, multiple sclerosis, and idiopathic thrombocytopenic purpura. There has been increasing focus on the interaction between the intestinal microbiome, obesity, and cardiometabolic diseases, and we explore these relationships and the potential roles of different microbial strains. We might someday be able to mine for intestinal bacterial strains that can be used in the diagnosis or treatment of these diseases.