Colesevelam enhances the beneficial effects of brown fat activation on hyperlipidaemia and atherosclerosis development

Aims

Brown fat activation accelerates the uptake of cholesterol-enriched remnants by the liver and thereby lowers plasma cholesterol, consequently protecting against atherosclerosis development. Hepatic cholesterol is then converted into bile acids (BAs) that are secreted into the intestine and largely maintained within the enterohepatic circulation. We now aimed to evaluate the effects of prolonged brown fat activation combined with inhibition of intestinal BA reabsorption on plasma cholesterol metabolism and atherosclerosis development.

Methods and results

APOE*3-Leiden.CETP mice with humanized lipoprotein metabolism were treated for 9 weeks with the selective β3-adrenergic receptor (AR) agonist CL316,243 to substantially activate brown fat. Prolonged β3-AR agonism reduced faecal BA excretion (−31%), while markedly increasing plasma levels of total BAs (+258%), cholic acid-derived BAs (+295%), and chenodeoxycholic acid-derived BAs (+217%), and decreasing the expression of hepatic genes involved in BA production. In subsequent experiments, mice were additionally treated with the BA sequestrant Colesevelam to inhibit BA reabsorption. Concomitant intestinal BA sequestration increased faecal BA excretion, normalized plasma BA levels, and reduced hepatic cholesterol. Moreover, concomitant BA sequestration further reduced plasma total cholesterol (−49%) and non-high-density lipoprotein cholesterol (−56%), tended to further attenuate atherosclerotic lesion area (−54%). Concomitant BA sequestration further increased the proportion of lesion-free valves (+34%) and decreased the relative macrophage area within the lesion (−26%), thereby further increasing the plaque stability index (+44%).

Conclusion

BA sequestration prevents the marked accumulation of plasma BAs as induced by prolonged brown fat activation, thereby further improving cholesterol metabolism and reducing atherosclerosis development. These data suggest that combining brown fat activation with BA sequestration is a promising new therapeutic strategy to reduce hyperlipidaemia and cardiovascular diseases.

Effect of Fecal Microbiota Transplantation Combined With Mediterranean Diet on Insulin Sensitivity in Subjects With Metabolic Syndrome

Background

Recent studies demonstrate that a Mediterranean diet has beneficial metabolic effects in metabolic syndrome subjects. Since we have shown that fecal microbiota transplantation (FMT) from lean donors exerts beneficial effects on insulin sensitivity, in the present trial, we investigated the potential synergistic effects on insulin sensitivity of combining a Mediterranean diet with donor FMT in subjects with metabolic syndrome.

Design

Twenty-four male subjects with metabolic syndrome were put on a Mediterranean diet and after a 2-week run-in phase, the subjects were randomized to either lean donor (n = 12) or autologous (n = 12) FMT. Changes in the gut microbiota composition and bacterial strain engraftment after the 2-week dietary regimens and 6 weeks post-FMT were the primary endpoints. The secondary objectives were changes in glucose fluxes (both hepatic and peripheral insulin sensitivity), postprandial plasma incretin (GLP-1) levels, subcutaneous adipose tissue inflammation, and plasma metabolites.

Results

Consumption of the Mediterranean diet resulted in a reduction in body weight, HOMA-IR, and lipid levels. However, no large synergistic effects of combining the diet with lean donor FMT were seen on the gut microbiota diversity after 6 weeks. Although we did observe changes in specific bacterial species and plasma metabolites, no significant beneficial effects on glucose fluxes, postprandial incretins, or subcutaneous adipose tissue inflammation were detected.

Conclusions

In this small pilot randomized controlled trial, no synergistic beneficial metabolic effects of combining a Mediterranean diet with lean donor FMT on glucose metabolism were achieved. However, we observed engraftment of specific bacterial species. Future trials are warranted to test the combination of other microbial interventions and diets in metabolic syndrome.

Psychological functioning and well-being before and after bariatric surgery; what is the benefit of being self-compassionate?

Objective

To investigate whether patients’ psychological well‐being (depression, quality of life, body image satisfaction) and functioning (self‐efficacy for eating and exercising behaviours and food cravings) improve 12 months after bariatric surgery and whether self‐compassion is associated with better psychological outcomes and lower weight after bariatric surgery.

Design

Longitudinal, prospective observational study.

Methods

Bariatric patients (n = 126, 77.8% female, 46.4 ± 10.8 years) completed the Self‐compassion Scale, Center for Epidemiology Studies Depression Scale, Impact of Weight on Quality‐of‐Life questionnaire, Body Image Scale, Weight Efficacy Lifestyle Questionnaire, Spinal Cord Injury Exercise Self‐Efficacy Scale, and G‐Food Craving Questionnaire pre‐operatively and 12 months post‐operatively. A medical professional measured patients’ weight during each assessment. Data were analysed using repeated measures t‐tests and multivariate regression analyses with Benjamini–Hochberg correction for multiple testing.

Results

Patients’ BMI, depression, and food cravings decreased significantly after surgery while quality of life, body image satisfaction, and self‐efficacy to exercise improved. Higher self‐compassion was associated with lower post‐operative depression, greater quality of life, higher body image satisfaction, and better self‐efficacy for eating behaviours (p‐values <.05) but not with post‐operative BMI, self‐efficacy to exercise, or food cravings.

Conclusions

Even though pre‐operative self‐compassion was not directly associated with a lower 12‐month post‐operative BMI, it had a positive relationship with patients’ post‐operative well‐being and self‐efficacy for controlling eating behaviour. In turn, this could help patients to manage their health long after bariatric surgery. Further work regarding the role of self‐compassion on long‐term health outcomes would be worthwhile.

Fecal Microbiota Transplantation from Overweight or Obese Donors in Cachectic Patients with Advanced Gastroesophageal Cancer: A Randomized, Double-blind, Placebo-Controlled, Phase II Study

PURPOSE

Cachexia is a multifactorial syndrome, associated with poor survival in patients with cancer, and is influenced by the gut microbiota. We investigated the effects of fecal microbiota transplantation (FMT) on cachexia and treatment response in patients with advanced gastroesophageal cancer.

EXPERIMENTAL DESIGN

In a double-blind randomized placebo-controlled trial performed in the Amsterdam University Medical Center, we assigned 24 cachectic patients with metastatic HER2-negative gastroesophageal cancer to either allogenic FMT (healthy obese donor) or autologous FMT, prior to palliative chemotherapy (capecitabine and oxaliplatin). Primary objective was to assess the effect of allogenic FMT on satiety. Secondary outcomes were other features of cachexia, along with disease control rate (DCR), overall survival (OS), progression-free survival (PFS), and toxicity. Finally, exploratory analyses were performed on the effect of FMT on gut microbiota composition (metagenomic sequencing) and metabolites (untargeted metabolomics).

RESULTS

Allogenic FMT did not improve any of the cachexia outcomes. Patients in the allogenic group (n = 12) had a higher DCR at 12 weeks (P = 0.035) compared with the autologous group (n = 12), longer median OS of 365 versus 227 days [HR = 0.38; 95% confidence interval (CI), 0.14-1.05; P = 0.057] and PFS of 204 versus 93 days (HR = 0.50; 95% CI, 0.21-1.20; P = 0.092). Patients in the allogenic group showed a significant shift in fecal microbiota composition after FMT (P = 0.010) indicating proper engraftment of the donor microbiota.

CONCLUSIONS

FMT from a healthy obese donor prior to first-line chemotherapy did not affect cachexia, but may have improved response and survival in patients with metastatic gastroesophageal cancer. These results provide a rational for larger FMT trials.

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.

A hierarchical dynamic model used for investigating feed efficiency and its relationship with hepatic gene expression in APOE*3-Leiden.CETP mice

BACKGROUND

Feed efficiency (FE) is an important trait for livestock and humans. While the livestock industry focuses on increasing FE, in the current obesogenic society it is more of interest to decrease FE. Hence, understanding mechanisms involved in the regulation of FE and particularly how it can be decreased would help tremendously in counteracting the obesity pandemic. However, it is difficult to accurately measure or calculate FE in humans. In this study, we aimed to address this challenge by developing a hierarchical dynamic model based on humanized mouse data.

METHODS

We analyzed existing experimental data derived from 105 APOE*3-Leiden.CETP (E3L.CETP) mice fed a high-fat high-cholesterol (HFHC) diet for 1 (N = 20), 2 (N = 19), 3 (N = 20), and 6 (N = 46) month. We developed an ordinary differential equation (ODE) based model to estimate the FE based on the longitudinal data of body weight and food intake. Since the liver plays an important role in maintaining metabolic homeostasis, we evaluated associations between FE and hepatic gene expression levels. Depending on the feeding duration, we observed different relationships between FE and hepatic gene expression levels.

RESULTS

After 1-month feeding of HFHC diet, we observed that FE was associated with vitamin A metabolism, arachidonic acid metabolism, and the PPAR signaling pathway. After 3- and 6-month feeding of HFHC diet, we observed that FE was associated most strongly with expression levels of Spink1 and H19, genes involved in cell proliferation and glucose metabolism, respectively.

CONCLUSIONS

In conclusion, our analysis suggests that various biological processes such as vitamin A metabolism, hepatic response to inflammation, and cell proliferation associate with FE at different stages of diet-induced obesity.

Metabolic Modeling Combined With Machine Learning Integrates Longitudinal Data and Identifies the Origin of LXR-Induced Hepatic Steatosis

Temporal multi-omics data can provide information about the dynamics of disease development and therapeutic response. However, statistical analysis of high-dimensional time-series data is challenging. Here we develop a novel approach to model temporal metabolomic and transcriptomic data by combining machine learning with metabolic models. ADAPT (Analysis of Dynamic Adaptations in Parameter Trajectories) performs metabolic trajectory modeling by introducing time-dependent parameters in differential equation models of metabolic systems. ADAPT translates structural uncertainty in the model, such as missing information about regulation, into a parameter estimation problem that is solved by iterative learning. We have now extended ADAPT to include both metabolic and transcriptomic time-series data by introducing a regularization function in the learning algorithm. The ADAPT learning algorithm was (re)formulated as a multi-objective optimization problem in which the estimation of trajectories of metabolic parameters is constrained by the metabolite data and refined by gene expression data. ADAPT was applied to a model of hepatic lipid and plasma lipoprotein metabolism to predict metabolic adaptations that are induced upon pharmacological treatment of mice by a Liver X receptor (LXR) agonist. We investigated the excessive accumulation of triglycerides (TG) in the liver resulting in the development of hepatic steatosis. ADAPT predicted that hepatic TG accumulation after LXR activation originates for 80% from an increased influx of free fatty acids. The model also correctly estimated that TG was stored in the cytosol rather than transferred to nascent very-low density lipoproteins. Through model-based integration of temporal metabolic and gene expression data we discovered that increased free fatty acid influx instead of de novo lipogenesis is the main driver of LXR-induced hepatic steatosis. This study illustrates how ADAPT provides estimates for biomedically important parameters that cannot be measured directly, explaining (side-)effects of pharmacological treatment with LXR agonists.

A systems biology approach to understand gut microbiota and host metabolism in morbid obesity: design of the BARIA Longitudinal Cohort Study

INTRODUCTION

Prevalence of obesity and associated diseases, including type 2 diabetes mellitus, dyslipidaemia and non-alcoholic fatty liver disease (NAFLD), are increasing. Underlying mechanisms, especially in humans, are unclear. Bariatric surgery provides the unique opportunity to obtain biopsies and portal vein blood-samples.

METHODS

The BARIA Study aims to assess how microbiota and their metabolites affect transcription in key tissues and clinical outcome in obese subjects and how baseline anthropometric and metabolic characteristics determine weight loss and glucose homeostasis after bariatric surgery. We phenotype patients undergoing bariatric surgery (predominantly laparoscopic Roux-en-Y gastric bypass), before weight loss, with biometrics, dietary and psychological questionnaires, mixed meal test (MMT) and collect fecal-samples and intra-operative biopsies from liver, adipose tissues and jejunum. We aim to include 1500 patients. A subset (approximately 25%) will undergo intra-operative portal vein blood-sampling. Fecal-samples are analyzed with shotgun metagenomics and targeted metabolomics, fasted and postprandial plasma-samples are subjected to metabolomics, and RNA is extracted from the tissues for RNAseq-analyses. Data will be integrated using state-of-the-art neuronal networks and metabolic modeling. Patient follow-up will be ten years.

RESULTS

Preoperative MMT of 170 patients were analysed and clear differences were observed in glucose homeostasis between individuals. Repeated MMT in 10 patients showed satisfactory intra-individual reproducibility, with differences in plasma glucose, insulin and triglycerides within 20% of the mean difference.

CONCLUSION

The BARIA study can add more understanding in how gut-microbiota affect metabolism, especially with regard to obesity, glucose metabolism and NAFLD. Identification of key factors may provide diagnostic and therapeutic leads to control the obesity-associated disease epidemic.

Protein Phosphatase 1 Regulatory Subunit 3B Genotype at rs4240624 Has a Major Effect on Gallbladder Bile Composition

The protein phosphatase 1 regulatory subunit 3B (PPP1R3B) gene is a target of farnesoid X receptor (FXR), which is a major regulator of bile acid metabolism. Both PPP1R3B and FXR have been suggested to take part in glycogen metabolism, which may explain the association of PPP1R3B gene variants with altered hepatic computed tomography attenuation. We analyzed the effect of PPP1R3B rs4240624 variant on bile acid composition in individuals with obesity. The study cohort consisted of 242 individuals from the Kuopio Obesity Surgery Study (73 men, 169 women, age 47.6 ± 9.0 years, body mass index 43.2 ± 5.4 kg/m²) with PPP1R3B genotype and liver RNA sequencing (RNA-seq) data available. Fasting plasma and gallbladder bile samples were collected from 50 individuals. Bile acids in plasma did not differ based on the PPP1R3B rs4240624 genotype. However, the concentration of total bile acids (109 ± 55 vs. 35 ± 19 mM; P = 1.0 × 10^-5) and all individual bile acids (also 7α-hydroxy-4-cholesten-3-one [C4]) measured from bile were significantly lower in those with the AG genotype compared to those with the AA genotype. In addition, total cholesterol (P = 0.011) and phospholipid (P = 0.001) levels were lower in individuals with the AG genotype, but cholesterol saturation index did not differ, indicating that the decrease in cholesterol and phospholipid levels was secondary to the change in bile acids. Liver RNA-seq data demonstrated that expression of PPP1R3B, tankyrase (TNKS), Homo sapiens chromosome 8 clone RP11-10A14.5 (AC022784.1 [LOC157273]), Homo sapiens chromosome 8 clone RP11-375N15.1 (AC021242.1), and Homo sapiens chromosome 8, clone RP11-10A14 (AC022784.6) associated with the PPP1R3B genotype. In addition, genes enriched in transmembrane transport and phospholipid binding pathways were associated with the genotype. Conclusion: The rs4240624 variant in PPP1R3B has a major effect on the composition of gallbladder bile. Other transcripts in the same loci may be important mediators of the variant effect.

Model-based data analysis of individual human postprandial plasma bile acid responses indicates a major role for the gallbladder and intestine

BACKGROUND

Bile acids are multifaceted metabolic compounds that signal to cholesterol, glucose, and lipid homeostasis via receptors like the Farnesoid X Receptor (FXR) and transmembrane Takeda G protein-coupled receptor 5 (TGR5). The postprandial increase in plasma bile acid concentrations is therefore a potential metabolic signal. However, this postprandial response has a high interindividual variability. Such variability may affect bile acid receptor activation.

METHODS

In this study, we analyzed the inter- and intraindividual variability of fasting and postprandial bile acid concentrations during three identical meals on separate days in eight healthy lean male subjects using a statistical and mathematical approach.

MAIN FINDINGS

The postprandial bile acid responses exhibited large interindividual and intraindividual variability. The individual mathematical models, which represent the enterohepatic circulation of bile acids in each subject, suggest that interindividual variability results from quantitative and qualitative differences of distal active uptake, colon transit, and microbial bile acid transformation. Conversely, intraindividual variations in gallbladder kinetics can explain intraindividual differences in the postprandial responses.

CONCLUSIONS

We conclude that there is considerable inter- and intraindividual variation in postprandial plasma bile acid levels. The presented personalized approach is a promising tool to identify unique characteristics of underlying physiological processes and can be applied to investigate bile acid metabolism in pathophysiological conditions.

Altered bile acid kinetics contribute to postprandial hypoglycaemia after Roux-en-Y gastric bypass surgery

BACKGROUND/OBJECTIVES

Bile acids (BA) act as detergents in intestinal fat absorption and as modulators of metabolic processes via activation of receptors such as FXR and TGR5. Elevated plasma BA as well as increased intestinal BA signalling to promote GLP-1 release have been implicated in beneficial health effects of Roux-en-Y gastric bypass surgery (RYGB). Whether BA also contribute to the postprandial hypoglycaemia that is frequently observed post-RYGB is unknown.

METHODS

Plasma BA, fibroblast growth factor 19 (FGF19), 7α-hydroxy-4-cholesten-3-one (C4), GLP-1, insulin and glucose levels were determined during 3.5 h mixed-meal tolerance tests (MMTT) in subjects after RYGB, either with (RYGB, n = 11) or without a functioning gallbladder due to cholecystectomy (RYGB-CC, n = 11). Basal values were compared to those of age, BMI and sex-matched obese controls without RYGB (n = 22).

RESULTS

Fasting BA as well as FGF19 levels were elevated in RYGB and RYGB-CC subjects compared to non-bariatric controls, without significant differences between RYGB and RYGB-CC. Postprandial hypoglycaemia was observed in 8/11 RYGB-CC and only in 3/11 RYGB. Subjects who developed hypoglycaemia showed higher postprandial BA levels coinciding with augmented GLP-1 and insulin responses during the MMTT. The nadir of plasma glucose concentrations after meals showed a negative relationship with postprandial BA peaks. Plasma C4 was lower during MMTT in subjects experiencing hypoglycaemia, indicating lower hepatic BA synthesis. Computer simulations revealed that altered intestinal transit underlies the occurrence of exaggerated postprandial BA responses in hypoglycaemic subjects.

CONCLUSION

Altered BA kinetics upon ingestion of a meal, as frequently observed in RYGB-CC subjects, appear to contribute to postprandial hypoglycaemia by stimulating intestinal GLP-1 release.

Infusion of donor feces affects the gut-brain axis in humans with metabolic syndrome

OBJECTIVE

Increasing evidence indicates that intestinal microbiota play a role in diverse metabolic processes via intestinal butyrate production. Human bariatric surgery data suggest that the gut-brain axis is also involved in this process, but the underlying mechanisms remain unknown.

METHODS

We compared the effect of fecal microbiota transfer (FMT) from post-Roux-en-Y gastric bypass (RYGB) donors vs oral butyrate supplementation on (123I-FP-CIT-determined) brain dopamine transporter (DAT) and serotonin transporter (SERT) binding as well as stable isotope-determined insulin sensitivity at baseline and after 4 weeks in 24 male and female treatment-naïve metabolic syndrome subjects. Plasma metabolites and fecal microbiota were also determined at these time points.

RESULTS

We observed an increase in brain DAT after donor FMT compared to oral butyrate that reduced this binding. However, no effect on body weight and insulin sensitivity was demonstrated after post-RYGB donor feces transfer in humans with metabolic syndrome. Increases in fecal levels of Bacteroides uniformis were significantly associated with an increase in DAT, whereas increases in Prevotella spp. showed an inverse association. Changes in the plasma metabolites glycine, betaine, methionine, and lysine (associated with the S-adenosylmethionine cycle) were also associated with altered striatal DAT expression.

CONCLUSIONS

Although more and larger studies are needed, our data suggest a potential gut microbiota-driven modulation of brain dopamine and serotonin transporters in human subjects with obese metabolic syndrome. These data also suggest the presence of a gut-brain axis in humans that can be modulated.

NTR REGISTRATION

4488.

Distinct differences in gut microbial composition and functional potential from lean to morbidly obese subjects

INTRODUCTION

The gut microbiome may contribute to the development of obesity. So far, the extent of microbiome variation in people with obesity has not been determined in large cohorts and for a wide range of body mass index (BMI). Here, we aimed to investigate whether the faecal microbial metagenome can explain the variance in several clinical phenotypes associated with morbid obesity.

METHODS

Caucasian subjects were recruited at our hospital. Blood pressure and anthropometric measurements were taken. Dietary intake was determined using questionnaires. Shotgun metagenomic sequencing was performed on faecal samples from 177 subjects.

RESULTS

Subjects without obesity (n = 82, BMI 24.7 ± 2.9 kg m^-2 ) and subjects with obesity (n = 95, BMI 38.6 ± 5.1 kg m^-2 ) could be clearly distinguished based on microbial composition and microbial metabolic pathways. A total number of 52 bacterial species differed significantly in people with and without obesity. Independent of dietary intake, we found that microbial pathways involved in biosynthesis of amino acids were enriched in subjects with obesity, whereas pathways involved in the degradation of amino acids were depleted. Machine learning models showed that more than half of the variance in body fat composition followed by BMI could be explained by the gut microbiome, composition and microbial metabolic pathways, compared with 6% of variation explained in triglycerides and 9% in HDL.

CONCLUSION

Based on the faecal microbiota composition, we were able to separate subjects with and without obesity. In addition, we found strong associations between gut microbial amino acid metabolism and specific microbial species in relation to clinical features of obesity.

Improved cardiovascular risk prediction using targeted plasma proteomics in primary prevention

AIMS

In the era of personalized medicine, it is of utmost importance to be able to identify subjects at the highest cardiovascular (CV) risk. To date, single biomarkers have failed to markedly improve the estimation of CV risk. Using novel technology, simultaneous assessment of large numbers of biomarkers may hold promise to improve prediction. In the present study, we compared a protein-based risk model with a model using traditional risk factors in predicting CV events in the primary prevention setting of the European Prospective Investigation (EPIC)-Norfolk study, followed by validation in the Progressione della Lesione Intimale Carotidea (PLIC) cohort.

METHODS AND RESULTS

Using the proximity extension assay, 368 proteins were measured in a nested case-control sample of 822 individuals from the EPIC-Norfolk prospective cohort study and 702 individuals from the PLIC cohort. Using tree-based ensemble and boosting methods, we constructed a protein-based prediction model, an optimized clinical risk model, and a model combining both. In the derivation cohort (EPIC-Norfolk), we defined a panel of 50 proteins, which outperformed the clinical risk model in the prediction of myocardial infarction [area under the curve (AUC) 0.754 vs. 0.730; P < 0.001] during a median follow-up of 20 years. The clinically more relevant prediction of events occurring within 3 years showed an AUC of 0.732 using the clinical risk model and an AUC of 0.803 for the protein model (P < 0.001). The predictive value of the protein panel was confirmed to be superior to the clinical risk model in the validation cohort (AUC 0.705 vs. 0.609; P < 0.001).

CONCLUSION

In a primary prevention setting, a proteome-based model outperforms a model comprising clinical risk factors in predicting the risk of CV events. Validation in a large prospective primary prevention cohort is required to address the value for future clinical implementation in CV prevention.

Differential DNA methylation in familial hypercholesterolemia

Background

Familial hypercholesterolemia (FH) is a monogenic disorder characterized by elevated low-density lipoprotein cholesterol (LDL-C). A FH causing genetic variant in LDLR, APOB, or PCSK9 is not identified in 12–60% of clinical FH patients (FH mutation-negative patients). We aimed to assess whether altered DNA methylation might be associated with FH in this latter group

Methods

In this study we included 78 FH mutation-negative patients and 58 FH mutation-positive patients with a pathogenic LDLR variant. All patients were male, not using lipid lowering therapies and had LDL-C levels >6 mmol/L and triglyceride levels <3•5 mmol/L. DNA methylation was measured with the Infinium Methylation EPIC 850 K beadchip assay. Multiple linear regression analyses were used to explore DNA methylation differences between the two groups in genes related to lipid metabolism. A gradient boosting machine learning model was applied to investigate accumulated genome-wide differences between the two groups.

Findings

Candidate gene analysis revealed one significantly hypomethylated CpG site in CPT1A (cg00574958) in FH mutation-negative patients, while no differences in methylation in other lipid genes were observed. The machine learning model did distinguish the two groups with a mean Area Under the Curve (AUC)±SD of 0•80±0•17 and provided two CpG sites (cg26426080 and cg11478607) in genes with a possible link to lipid metabolism (PRDM16 and GSTT1).

Interpretation

FH mutation-negative patients are characterized by accumulated genome wide DNA methylation differences, but not by major DNA methylation alterations in known lipid genes compared to FH mutation-positive patients.

Funding

ZonMW grant (VIDI no. 016.156.445)

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.

Genetic and Microbial Associations to Plasma and Fecal Bile Acids in Obesity Relate to Plasma Lipids and Liver Fat Content

Bile acids (BAs) are implicated in the etiology of obesity-related conditions such as non-alcoholic fatty liver disease. Differently structured BA species display variable signaling activities via farnesoid X receptor (FXR) and Takeda G protein-coupled BA receptor 1 (TGR5). This study profiles plasma and fecal BAs and plasma 7α-hydroxy-4-cholesten-3-one (C4) in 297 persons with obesity, identifies underlying genetic and microbial determinants, and establishes BA correlations with liver fat and plasma lipid parameters. We identify 27 genetic associations (p < 5 × 10^-8) and 439 microbial correlations (FDR < 0.05) for 50 BA entities. Additionally, we report 111 correlations between BA and 88 lipid parameters (FDR < 0.05), mainly for C4 reflecting hepatic BA synthesis. Inter-individual variability in the plasma BA profile does not reflect hepatic BA synthetic pathways, but rather transport and metabolism within the enterohepatic circulation. Our study reveals genetic and microbial determinants of BAs in obesity and their relationship to disease-relevant lipid parameters that are important for the design of personalized therapies targeting BA-signaling pathways.

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

Correlation of plasma metabolites with glucose and lipid fluxes in human insulin resistance

OBJECTIVE

Insulin resistance develops prior to the onset of overt type 2 diabetes, making its early detection vital. Direct accurate evaluation is currently only possible with complex examinations like the stable isotope-based hyperinsulinemic euglycemic clamp (HIEC). Metabolomic profiling enables the detection of thousands of plasma metabolites, providing a tool to identify novel biomarkers in human obesity.

DESIGN

Liquid chromatography mass spectrometry-based untargeted plasma metabolomics was applied in 60 participants with obesity with a large range of peripheral insulin sensitivity as determined via a two-step HIEC with stable isotopes [6,6-2H2]glucose and [1,1,2,3,3-2H5]glycerol. This additionally enabled measuring insulin-regulated lipolysis, which combined with metabolomics, to the knowledge of this research group, has not been reported on before.

RESULTS

Several plasma metabolites were identified that significantly correlated with glucose and lipid fluxes, led by plasma (gamma-glutamyl)citrulline, followed by betaine, beta-cryptoxanthin, fructosyllysine, octanylcarnitine, sphingomyelin (d18:0/18:0, d19:0/17:0) and thyroxine. Subsequent machine learning analysis showed that a panel of these metabolites derived from a number of metabolic pathways may be used to predict insulin resistance, dominated by non-essential amino acid citrulline and its metabolite gamma-glutamylcitrulline.

CONCLUSION

This approach revealed a number of plasma metabolites that correlated reasonably well with glycemic and lipolytic flux parameters, measured using gold standard techniques. These metabolites may be used to predict the rate of glucose disposal in humans with obesity to a similar extend as HOMA, thus providing potential novel biomarkers for insulin resistance.

Metabolic effects of PCSK9 inhibition with Evolocumab in subjects with elevated Lp(a)

Background

Epidemiological studies substantiated that subjects with elevated lipoprotein(a) [Lp(a)] have a markedly increased cardiovascular risk. Inhibition of proprotein convertase subtilisin/kexin type 9 (PCSK9) lowers both LDL cholesterol (LDL-C) as well as Lp(a), albeit modestly. Effects of PCSK9 inhibition on circulating metabolites such as lipoprotein subclasses, amino acids and fatty acids remain to be characterized.

Methods

We performed nuclear magnetic resonance (NMR) metabolomics on plasma samples derived from 30 individuals with elevated Lp(a) (> 150 mg/dL). The 30 participants were randomly assigned into two groups, placebo (N = 14) and evolocumab (N = 16). We assessed the effect of 16 weeks of evolocumab 420 mg Q4W treatment on circulating metabolites by running lognormal regression analyses, and compared this to placebo. Subsequently, we assessed the interrelationship between Lp(a) and 14 lipoprotein subclasses in response to treatment with evolocumab, by running multilevel multivariate regression analyses.

Results

On average, evolocumab treatment for 16 weeks resulted in a 17% (95% credible interval: 8 to 26%, P < 0.001) reduction of circulating Lp(a), coupled with substantial reduction of VLDL, IDL and LDL particles as well as their lipid contents. Interestingly, increasing concentrations of baseline Lp(a) were associated with larger reduction in triglyceride-rich VLDL particles after evolocumab treatment.

Conclusions

Inhibition of PCSK9 with evolocumab markedly reduced VLDL particle concentrations in addition to lowering LDL-C. The extent of reduction in VLDL particles depended on the baseline level of Lp(a). Our findings suggest a marked effect of evolocumab on VLDL metabolism in subjects with elevated Lp(a).

Trial registration

Clinical trial registration information is registered at ClinicalTrials.gov on April 14, 2016 with the registration number NCT02729025.

Treatment with Anaerobutyricum soehngenii: a pilot study of safety and dose-response effects on glucose metabolism in human subjects with metabolic syndrome

Dysbiosis of the intestinal microbiota has been implicated in insulin resistance, although evidence regarding causality in humans is scarce. We performed a phase I/II dose-finding and safety study on the effect of oral intake of the anaerobic butyrogenic strain Anaerobutyricum soehngenii on glucose metabolism in 24 subjects with metabolic syndrome. We found that treatment with A. soehngenii was safe and observed a significant correlation between the measured fecal abundance of administered A. soehngenii and improvement in peripheral insulin sensitivity after 4 weeks of treatment. This was accompanied by an altered microbiota composition and a change in bile acid metabolism. Finally, we show that metabolic response upon administration of A. soehngenii (defined as improved insulin sensitivity 4 weeks after A. soehngenii intake) is dependent on microbiota composition at baseline. These data in humans are promising, but additional studies are needed to reproduce our findings and to investigate long-term effects, as well as other modes of delivery.