Disentangle beneficial effects of strain engraftment after fecal microbiota transplantation in subjects with MetSyn.

Fecal Microbiota Transplantation (FMT) has emerged as a potential modality for mitigating microbiome-associated diseases. Despite this potential, the precise causal pathways by which specific gut microbiota strains induce remission remain inadequately elucidated. In this study, we aimed to discern the impact of engraftment of donor-infused strains on alterations in plasma metabolites, subsequently contributing to the amelioration of clinical parameters involved in subjects with metabolic syndrome (MetSyn) receiving an FMT. We observed that a higher fraction of donor strains engrafted in the recipient is correlated to a reduction in diastolic blood pressure and found specific strain associations through canonical correlation analysis. Integrating the metabolomics profile shows that engraftment of Collinsella aerofaciens and Fusocatenibacter saccharovorans was related to a reduction in 2-oxoarginine in plasma, which was subsequently correlated to a reduction in diastolic blood pressure. In conclusion, we applied a novel framework to elucidate on the complex and heterogenous FMT intervention, establishing a connection between engrafted microbiota and clinical outcome parameters. Our findings underscore the potential therapeutic efficacy of FMT in ameliorating MetSyn, demonstrating a potential contribution of microbial strain engraftment to the improvement of MetSyn via modulation of circulating metabolites.

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.

Ethnic variations in metabolic syndrome components and their associations with the gut microbiota: the HELIUS study.

BACKGROUND: The occurrence of metabolic syndrome (MetS) and the gut microbiota composition are known to differ across ethnicities yet how these three factors are interwoven is unknown. Also, it is unknown what the relative contribution of the gut microbiota composition is to each MetS component and whether this differs between ethnicities. We therefore determined the occurrence of MetS and its components in the multi-ethnic HELIUS cohort and tested the overall and ethnic-specific associations with the gut microbiota composition. METHODS: We included 16,209 treatment naïve participants of the HELIUS study, which were of Dutch, African Surinamese, South-Asian Surinamese, Ghanaian, Turkish, and Moroccan descent to analyze MetS and its components across ethnicities. In a subset (n = 3443), the gut microbiota composition (16S) was associated with MetS outcomes using linear and logistic regression models. RESULTS: A differential, often sex-dependent, prevalence of MetS components and their combinations were observed across ethnicities. Increased blood pressure was commonly seen especially in Ghanaians, while South-Asian Surinamese and Turkish had higher MetS rates in general and were characterized by worse lipid-related measures. Regarding the gut microbiota, when ethnic-independent associations were assumed, a higher α-diversity, higher abundance of several ASVs (mostly for waist and triglyceride-related outcomes) and a trophic network of ASVs of Ruminococcaceae, Christensenellaceae, and Methanobrevibacter (RCM) bacteria were associated with better MetS outcomes. Statistically significant ethnic-specific associations were however noticed for α-diversity and the RCM trophic network. Associations were significant in the Dutch but not always in all other ethnicities. In Ghanaians, a higher α-diversity and RCM network abundance showed an aberrant positive association with high blood pressure measures compared to the other ethnicities. Even though adjustment for socioeconomic status-, lifestyle-, and diet-related variables often attenuated the effect size and/or the statistical significance of the ethnic-specific associations, an overall similar pattern across outcomes and ethnicities remained. CONCLUSIONS: The occurrence of MetS characteristics among ethnicities is heterogeneous. Both ethnic-independent and ethnic-specific associations were identified between the gut microbiota and MetS outcomes. Across multiple ethnicities, a one-size-fits-all approach may thus be reconsidered in regard to both the definition and/or treatment of MetS and its relation to the gut microbiota.

Networks of gut bacteria relate to cardiovascular disease in a multi-ethnic population: the HELIUS study.

AIMS: Gut microbiota have been linked to blood lipid levels and cardiovascular diseases (CVDs). The composition and abundance of gut microbiota trophic networks differ between ethnicities. We aim to evaluate the relationship between gut microbiotal trophic networks and CVD phenotypes. METHODS AND RESULTS: We included cross-sectional data from 3860 individuals without CVD history from 6 ethnicities living in the Amsterdam region participating in the prospective Healthy Life in Urban Setting (HELIUS) study. Genetic variants were genotyped, faecal gut microbiota were profiled, and blood and anthropometric parameters were measured. A machine learning approach was used to assess the relationship between CVD risk (Framingham score) and gut microbiota stratified by ethnicity. Potential causal relationships between gut microbiota composition and CVD were inferred by performing two-sample Mendelian randomization with hard CVD events from the Pan-UK Biobank and microbiome genome-wide association studies summary data from a subset of the HELIUS cohort (n = 4117). Microbial taxa identified to be associated with CVD by machine learning and Mendelian randomization were often ethnic-specific, but some concordance across ethnicities was found. The microbes Akkermansia muciniphila and Ruminococcaceae UCG-002 were protective against ischaemic heart disease in African-Surinamese and Moroccans, respectively. We identified a strong inverse association between blood lipids, CVD risk, and the combined abundance of the correlated microbes Christensenellaceae-Methanobrevibacter-Ruminococcaceae (CMR). The CMR cluster was also identified in two independent cohorts and the association with triglycerides was replicated. CONCLUSION: Certain gut microbes can have a potentially causal relationship with CVD events, with possible ethnic-specific effects. We identified a trophic network centred around Christensenellaceae, Methanobrevibacter, and various Ruminococcaceae, frequently lacking in South-Asian Surinamese, to be protective against CVD risk and associated with low triglyceride levels.

Multiomics Analysis Provides Novel Pathways Related to Progression of Heart Failure.

BACKGROUND: Despite major advances in pharmacological treatment for patients with heart failure, residual mortality remains high. This suggests that important pathways are not yet targeted by current heart failure therapies. OBJECTIVES: We sought integration of genetic, transcriptomic, and proteomic data in a large cohort of patients with heart failure to detect major pathways related to progression of heart failure leading to death. METHODS: We used machine learning methodology based on stacked generalization framework and gradient boosting algorithms, using 54 clinical phenotypes, 403 circulating plasma proteins, 36,046 transcript expression levels in whole blood, and 6 million genomic markers to model all-cause mortality in 2,516 patients with heart failure from the BIOSTAT-CHF (Systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure) study. Results were validated in an independent cohort of 1,738 patients. RESULTS: The mean age of the patients was 70 years (Q1-Q3: 61-78 years), 27% were female, median N-terminal pro-B-type natriuretic peptide was 4,275 ng/L (Q1-Q3: 2,360-8,486 ng/L), and 7% had heart failure with preserved ejection fraction. During a median follow-up of 21 months, 657 (26%) of patients died. The 4 major pathways with a significant association to all-cause mortality were: 1) the PI3K/Akt pathway; 2) the MAPK pathway; 3) the Ras signaling pathway; and 4) epidermal growth factor receptor tyrosine kinase inhibitor resistance. Results were validated in an independent cohort of 1,738 patients. CONCLUSIONS: A systems biology approach integrating genomic, transcriptomic, and proteomic data identified 4 major pathways related to mortality. These pathways are related to decreased activation of the cardioprotective ERBB2 receptor, which can be modified by neuregulin.

Peripheral blood DNA methylation signatures and response to tofacitinib in moderate-to-severe ulcerative colitis.

INTRODUCTION: Predictive biomarkers for treatment efficacy of ulcerative colitis (UC) treatments are lacking. Here, we performed a longitudinal study investigating the association and potential predictive power of genome-wide peripheral blood (PB) DNA methylation signatures and response to tofacitinib treatment in UC. METHODS: We recruited moderate-to-severe UC patients starting tofacitinib treatment and measured PB DNA methylation profiles at baseline (T1), after 8 weeks (T2), and in a subset (n=8), after a median of 20 weeks (T3) using the Illumina Infinium HumanMethylation EPIC BeadChip. After 8 weeks, we categorized responders (R) from non-responders (NR) based on a centrally read endoscopic response (decrease in endoscopic mayo score ≥1 or UCEIS ≥2) combined with corticosteroid-free clinical- and/or biochemical response. T1 PB samples were used for biomarker identification, while T2 and publicly available intra-class correlation (ICC) data were used for stability analyses. RNA-sequencing was performed to understand the downstream effects of the predictor CpG loci. RESULTS: In total, 16 R and 15 NR patients with a median disease duration of 7 (4-12) years and overall comparable patient characteristics at baseline were analyzed. We identified a panel of 53 differentially methylated positions (DMPs) associated with response to tofacitinib (AUROC 0.74). Most DMPs (77%) demonstrated both short- and long-term hyper stability (ICC ≥0.90), irrespective of inflammatory status. Gene expression analysis showed lower FGFR2 (pBH=0.011) and LRPAP1 (pBH=0.020), and higher OR2L13 (pBH=0.016) expression at T1 in R compared to NR. CONCLUSION: Our observations demonstrate the utility of genome-wide PB DNA methylation signatures to predict response to tofacitinib.

Faecal Microbiota transplantation affects liver DNA methylation in Non-alcoholic fatty liver disease: a multi-omics approach.

Individuals with nonalcoholic fatty liver disease (NAFLD) have an altered gut microbiota composition. Moreover, hepatic DNA methylation may be altered in the state of NAFLD. Using a fecal microbiota transplantation (FMT) intervention, we aimed to investigate whether a change in gut microbiota composition relates to altered liver DNA methylation in NAFLD. Moreover, we assessed whether plasma metabolite profiles altered by FMT relate to changes in liver DNA methylation. Twenty-one individuals with NAFLD underwent three 8-weekly vegan allogenic donor (n = 10) or autologous (n = 11) FMTs. We obtained hepatic DNA methylation profiles from paired liver biopsies of study participants before and after FMTs. We applied a multi-omics machine learning approach to identify changes in the gut microbiome, peripheral blood metabolome and liver DNA methylome, and analyzed cross-omics correlations. Vegan allogenic donor FMT compared to autologous FMT induced distinct differential changes in I) gut microbiota profiles, including increased abundance of Eubacterium siraeum and potential probiotic Blautia wexlerae; II) plasma metabolites, including altered levels of phenylacetylcarnitine (PAC) and phenylacetylglutamine (PAG) both from gut-derived phenylacetic acid, and of several choline-derived long-chain acylcholines; and III) hepatic DNA methylation profiles, most importantly in Threonyl-TRNA Synthetase 1 (TARS) and Zinc finger protein 57 (ZFP57). Multi-omics analysis showed that Gemmiger formicillis and Firmicutes bacterium_CAG_170 positively correlated with both PAC and PAG. E siraeum negatively correlated with DNA methylation of cg16885113 in ZFP57. Alterations in gut microbiota composition by FMT caused widespread changes in plasma metabolites (e.g. PAC, PAG, and choline-derived metabolites) and liver DNA methylation profiles in individuals with NAFLD. These results indicate that FMTs might induce metaorganismal pathway changes, from the gut bacteria to the liver.

Gut microbiome transitions across generations in different ethnicities in an urban setting-the HELIUS study.

BACKGROUND: During the course of history, various important lifestyle changes have caused profound transitions of the gut microbiome. These include the introduction of agriculture and animal husbandry, a shift from a nomadic to a more sedentary lifestyle, and recently increased levels of urbanization and a transition towards a more Western lifestyle. The latter is linked with shifts in the gut microbiome that have a reduced fermentative capability and which are commonly associated with diseases of affluence. In this study, in which 5193 subjects are included, we investigated the direction of microbiome shifts that occur in various ethnicities living in Amsterdam by comparing 1st and 2nd generation participants. We furthermore validated part of these findings with a cohort of subjects that moved from rural Thailand to the USA. RESULTS: The abundance of the Prevotella cluster, which includes P. copri and the P. stercorea trophic network, diminished in the 2nd generation Moroccans and Turks but also in younger Dutch, whilst the Western-associated Bacteroides/Blautia/Bifidobacterium (BBB) cluster, which has an inverse correlation with α-diversity, increased. At the same time, the Christensenellaceae/Methanobrevibacter/Oscillibacter trophic network, which is positively associated with α-diversity and a healthy BMI, decreased in younger Turks and Dutch. Large compositional shifts were not observed in South-Asian and African Surinamese, in whom the BBB cluster is already dominant in the 1st generation, but ASV-level shifts towards certain species, associated amongst others with obesity, were observed. CONCLUSION: The Moroccan and Turkish populations, but also the Dutch population are transitioning towards a less complex and fermentative less capable configuration of the gut microbiota, which includes a higher abundance of the Western-associated BBB cluster. The Surinamese, whom have the highest prevalence of diabetes and other diseases of affluence, are already dominated by the BBB cluster. Given the continuous increase in diseases of affluence, this devolution towards low-diversity and fermentatively less capable gut microbiome compositions in urban environments is a worrying development. Video Abstract.

Long-term Temporal Stability of Peripheral Blood DNA Methylation Profiles in Patients With Inflammatory Bowel Disease.

BACKGROUND & AIMS: There is great current interest in the potential application of DNA methylation alterations in peripheral blood leukocytes (PBLs) as biomarkers of susceptibility, progression, and treatment response in inflammatory bowel disease (IBD). However, the intra-individual stability of PBL methylation in IBD has not been characterized. Here, we studied the long-term stability of all probes located on the Illumina HumanMethylation EPIC BeadChip array. METHODS: We followed a cohort of 46 adult patients with IBD (36 Crohn's disease [CD], 10 ulcerative colitis [UC]; median age, 44 years; interquartile range [IQR] 27-56 years; 50% female) that received standard care follow-up at the Amsterdam University Medical Centers. Paired PBL samples were collected at 2 time points with a median of 7 years (range, 2-9 years) in between. Differential methylation and intra-class correlation (ICC) analyses were used to identify time-associated differences and temporally stable CpGs, respectively. RESULTS: Around 60% of all EPIC array loci presented poor intra-individual stability (ICC <0.50); 78.114 (≈9%) showed good (ICC, 0.75-0.89), and 41.274 (≈5%) showed excellent (ICC ≥0.90) stability, between both measured time points. Focusing on previously identified consistently differentially methylated positions indicated that 22 CD-, 11 UC-, and 24 IBD-associated loci demonstrated high stability (ICC ≥0.75) over time; of these, we observed a marked stability of CpG loci associated to the HLA genes. CONCLUSIONS: Our data provide insight into the long-term stability of the PBL DNA methylome within an IBD context, facilitating the selection of biologically relevant and robust IBD-associated epigenetic biomarkers with increased potential for independent validation. These data also have potential implications in understanding disease pathogenesis.

Novel DNA methylome biomarkers associated with adalimumab response in rheumatoid arthritis patients.

Background and aims: Rheumatoid arthritis (RA) patients are currently treated with biological agents mostly aimed at cytokine blockade, such as tumor necrosis factor-alpha (TNFα). Currently, there are no biomarkers to predict therapy response to these agents. Here, we aimed to predict response to adalimumab (ADA) treatment in RA patients using DNA methylation in peripheral blood (PBL). Methods: DNA methylation profiling on whole peripheral blood from 92 RA patients before the start of ADA treatment was determined using Illumina HumanMethylationEPIC BeadChip array. After 6 months, treatment response was assessed according to the European Alliance of Associations for Rheumatology (EULAR) criteria for disease activity. Patients were classified as responders (Disease Activity Score in 28 Joints (DAS28) < 3.2 or decrease of 1.2 points) or as non-responders (DAS28 > 5.1 or decrease of less than 0.6 points). Machine learning models were built through stability-selected gradient boosting to predict response prior to ADA treatment with predictor DNA methylation markers. Results: Of the 94 RA patients, we classified 49 and 43 patients as responders and non-responders, respectively. We were capable of differentiating responders from non-responders with a high performance (area under the curve (AUC) 0.76) using a panel of 27 CpGs. These classifier CpGs are annotated to genes involved in immunological and pathophysiological pathways related to RA such as T-cell signaling, B-cell pathology, and angiogenesis. Conclusion: Our findings indicate that the DNA methylome of PBL provides discriminative capabilities in discerning responders and non-responders to ADA treatment and may therefore serve as a tool for therapy prediction.

Gut Microbiota in Nutrition and Health with a Special Focus on Specific Bacterial Clusters.

Health is influenced by how the gut microbiome develops as a result of external and internal factors, such as nutrition, the environment, medication use, age, sex, and genetics. Alpha and beta diversity metrics and (enterotype) clustering methods are commonly employed to perform population studies and to analyse the effects of various treatments, yet, with the continuous development of (new) sequencing technologies, and as various omics fields as a result become more accessible for investigation, increasingly sophisticated methodologies are needed and indeed being developed in order to disentangle the complex ways in which the gut microbiome and health are intertwined. Diseases of affluence, such as type 2 diabetes (T2D) and cardiovascular diseases (CVD), are commonly linked to species associated with the Bacteroides enterotype(s) and a decline of various (beneficial) complex microbial trophic networks, which are in turn linked to the aforementioned factors. In this review, we (1) explore the effects that some of the most common internal and external factors have on the gut microbiome composition and how these in turn relate to T2D and CVD, and (2) discuss research opportunities enabled by and the limitations of some of the latest technical developments in the microbiome sector, including the use of artificial intelligence (AI), strain tracking, and peak to trough ratios.

Gut microbiome associations with host genotype vary across ethnicities and potentially influence cardiometabolic traits.

Previous studies in mainly European populations have reported that the gut microbiome composition is associated with the human genome. However, the genotype-microbiome interaction in different ethnicities is largely unknown. We performed a large fecal microbiome genome-wide association study of a single multiethnic cohort, the Healthy Life in an Urban Setting (HELIUS) cohort (N = 4,117). Mendelian randomization was performed using the multiethnic Pan-UK Biobank (N = 460,000) to dissect potential causality. We identified ethnicity-specific associations between host genomes and gut microbiota. Certain microbes were associated with genotype in multiple ethnicities. Several of the microbe-associated loci were found to be related to immune functions, interact with glutamate and the mucus layer, or be expressed in the gut or brain. Additionally, we found that gut microbes potentially influence cardiometabolic health factors such as BMI, cholesterol, and blood pressure. This provides insight into the relationship of ethnicity and gut microbiota and into the possible causal effects of gut microbes on cardiometabolic traits.

Recent insights into the role of microbiome in the pathogenesis of obesity.

Obesity is a risk factor for many chronic diseases and its rising prevalence the last couple of decades is a healthcare concern in many countries. Obesity is a multifactorial problem that is not only limited in its causation by diet and lack of exercise. Genetics but also environmental factors such as the gut microbiome should similarly be taken into account. A plethora of articles have been published, that from various different angles, attempt to disentangle the complex interaction between gut microbiota and obesity. Examples range from the effect of the gut microbiota on the host immune system to the pathophysiological pathways in which microbial-derived metabolites affect obesity. Various discordant gut microbiota findings are a result of this complexity. In this review, in addition to summarizing the classical role of the gut microbiome in the pathogenesis of obesity, we attempt to view both the healthy and obesogenic effects of the gut microbiota as a consequence of the presence or absence of collective guilds/trophic networks. Lastly, we propose avenues and strategies for the future of gut microbiome research concerning obesity.

Epigenetic Signatures Discriminate Patients With Primary Sclerosing Cholangitis and Ulcerative Colitis From Patients With Ulcerative Colitis.

Background: Primary sclerosing cholangitis (PSC) is a chronic inflammatory liver disease affecting the intra- and extrahepatic bile ducts, and is strongly associated with ulcerative colitis (UC). In this study, we explored the peripheral blood DNA methylome and its immune cell composition in patients with PSC-UC, UC, and healthy controls (HC) with the aim to develop a predictive assay in distinguishing patients with PSC-UC from those with UC alone. Methods: The peripheral blood DNA methylome of male patients with PSC and concomitant UC, UC and HCs was profiled using the Illumina HumanMethylation Infinium EPIC BeadChip (850K) array. Differentially methylated CpG position (DMP) and region (DMR) analyses were performed alongside gradient boosting classification analyses to discern PSC-UC from UC patients. As observed differences in the DNA methylome could be the result of differences in cellular populations, we additionally employed mass cytometry (CyTOF) to characterize the immune cell compositions. Results: Genome wide methylation analysis did not reveal large differences between PSC-UC and UC patients nor HCs. Nonetheless, using gradient boosting we were capable of discerning PSC-UC from UC with an area under the receiver operator curve (AUROC) of 0.80. Four CpG sites annotated to the NINJ2 gene were found to strongly contribute to the predictive performance. While CyTOF analyses corroborated the largely similar blood cell composition among patients with PSC-UC, UC and HC, a higher abundance of myeloid cells was observed in UC compared to PSC-UC patients. Conclusion: DNA methylation enables discerning PSC-UC from UC patients, with a potential for biomarker development.

Targeted proteomics improves cardiovascular risk prediction in secondary prevention.

AIMS: Current risk scores do not accurately identify patients at highest risk of recurrent atherosclerotic cardiovascular disease (ASCVD) in need of more intensive therapeutic interventions. Advances in high-throughput plasma proteomics, analysed with machine learning techniques, may offer new opportunities to further improve risk stratification in these patients. METHODS AND RESULTS: Targeted plasma proteomics was performed in two secondary prevention cohorts: the Second Manifestations of ARTerial disease (SMART) cohort (n = 870) and the Athero-Express cohort (n = 700). The primary outcome was recurrent ASCVD (acute myocardial infarction, ischaemic stroke, and cardiovascular death). Machine learning techniques with extreme gradient boosting were used to construct a protein model in the derivation cohort (SMART), which was validated in the Athero-Express cohort and compared with a clinical risk model. Pathway analysis was performed to identify specific pathways in high and low C-reactive protein (CRP) patient subsets. The protein model outperformed the clinical model in both the derivation cohort [area under the curve (AUC): 0.810 vs. 0.750; P < 0.001] and validation cohort (AUC: 0.801 vs. 0.765; P < 0.001), provided significant net reclassification improvement (0.173 in validation cohort) and was well calibrated. In contrast to a clear interleukin-6 signal in high CRP patients, neutrophil-signalling-related proteins were associated with recurrent ASCVD in low CRP patients. CONCLUSION: A proteome-based risk model is superior to a clinical risk model in predicting recurrent ASCVD events. Neutrophil-related pathways were found in low CRP patients, implying the presence of a residual inflammatory risk beyond traditional NLRP3 pathways. The observed net reclassification improvement illustrates the potential of proteomics when incorporated in a tailored therapeutic approach in secondary prevention patients.

Fecal microbiota transplantation as tool to study the interrelation between microbiota composition and miRNA expression.

The intestinal gut microbiota is important for human metabolism and immunity and can be influenced by many host factors. A recently emerged host factor is secreted microRNA (miRNA). Previously, it has been shown that secreted miRNAs can influence the growth of certain bacteria and conversely, that shifts in the microbiota can alter the composition of secreted miRNAs. Here, we sought to further investigate the interaction between the gut microbiota and secreted miRNAs by the use of fecal microbiota transplantation (FMT). Subjects with the metabolic syndrome received either an autologous (n = 4) or allogenic (n = 14) FMT. Fecal samples were collected at baseline and 6 weeks after FMT, from which the microbiome and miRNA composition were determined via 16S rRNA sequencing and miRNA sequencing, respectively. We observed a significant correlation between the fecal miRNA expression and microbiota composition, both before and after FMT. Our results suggest that the FMT-induced shift in microbiota altered the fecal miRNA profile, indicated by correlations between differentially abundant microbes and miRNAs. This idea of a shift in miRNA composition driven by changes in the microbiota was further strengthened by the absence of a direct effect of specific miRNAs on the growth of specific bacterial strains.

Duodenal Anaerobutyricum soehngenii infusion stimulates GLP-1 production, ameliorates glycaemic control and beneficially shapes the duodenal transcriptome in metabolic syndrome subjects: a randomised double-blind placebo-controlled cross-over study.

OBJECTIVE: Although gut dysbiosis is increasingly recognised as a pathophysiological component of metabolic syndrome (MetS), the role and mode of action of specific gut microbes in metabolic health remain elusive. Previously, we identified the commensal butyrogenic Anaerobutyricum soehngenii to be associated with improved insulin sensitivity in subjects with MetS. In this proof-of-concept study, we investigated the potential therapeutic effects of A. soehngenii L2-7 on systemic metabolic responses and duodenal transcriptome profiles in individuals with MetS. DESIGN: In this randomised double-blind placebo-controlled cross-over study, 12 male subjects with MetS received duodenal infusions of A. soehngenii/ placebo and underwent duodenal biopsies, mixed meal tests (6 hours postinfusion) and 24-hour continuous glucose monitoring. RESULTS: A. soehngenii treatment provoked a markedly increased postprandial excursion of the insulinotropic hormone glucagon-like peptide 1 (GLP-1) and an elevation of plasma secondary bile acids, which were positively associated with GLP-1 levels. Moreover, A. soehngenii treatment robustly shaped the duodenal expression of 73 genes, with the highest fold induction in the expression of regenerating islet-protein 1B (REG1B)-encoding gene. Strikingly, duodenal REG1B expression positively correlated with GLP-1 levels and negatively correlated with peripheral glucose variability, which was significantly diminished in the 24 hours following A. soehngenii intake. Mechanistically, Reg1B expression is induced upon sensing butyrate or bacterial peptidoglycan. Importantly, A. soehngenii duodenal administration was safe and well tolerated. CONCLUSIONS: A single dose of A. soehngenii improves peripheral glycaemic control within 24 hours; it specifically stimulates intestinal GLP-1 production and REG1B expression. Further studies are needed to delineate the specific pathways involved in REG1B induction and function in insulin sensitivity. TRIAL REGISTRATION NUMBER: NTR-NL6630.

Distinct Metabolomic Signatures in Preclinical and Obstructive Hypertrophic Cardiomyopathy.

Hypertrophic Cardiomyopathy (HCM) is a common inherited heart disease with poor risk prediction due to incomplete penetrance and a lack of clear genotype-phenotype correlations. Advanced imaging techniques have shown altered myocardial energetics already in preclinical gene variant carriers. To determine whether disturbed myocardial energetics with the potential to serve as biomarkers are also reflected in the serum metabolome, we analyzed the serum metabolome of asymptomatic carriers in comparison to healthy controls and obstructive HCM patients (HOCM). We performed non-quantitative direct-infusion high-resolution mass spectrometry-based untargeted metabolomics on serum from fasted asymptomatic gene variant carriers, symptomatic HOCM patients and healthy controls (n = 31, 14 and 9, respectively). Biomarker panels that discriminated the groups were identified by performing multivariate modeling with gradient-boosting classifiers. For all three group-wise comparisons we identified a panel of 30 serum metabolites that best discriminated the groups. These metabolite panels performed equally well as advanced cardiac imaging modalities in distinguishing the groups. Seven metabolites were found to be predictive in two different comparisons and may play an important role in defining the disease stage. This study reveals unique metabolic signatures in serum of preclinical carriers and HOCM patients that may potentially be used for HCM risk stratification and precision therapeutics.

Effects of fecal microbiota transplant on DNA methylation in subjects with metabolic syndrome.

Accumulating evidence shows that microbes with their theater of activity residing within the human intestinal tract (i.e., the gut microbiome) influence host metabolism. Some of the strongest results come from recent fecal microbial transplant (FMT) studies that relate changes in intestinal microbiota to various markers of metabolism as well as the pathophysiology of insulin resistance. Despite these developments, there is still a limited understanding of the multitude of effects associated with FMT on the general physiology of the host, beyond changes in gut microbiome composition. We examined the effect of either allogenic (lean donor) or autologous FMTs on the gut microbiome, plasma metabolome, and epigenomic (DNA methylation) reprogramming in peripheral blood mononuclear cells in individuals with metabolic syndrome measured at baseline (pre-FMT) and after 6 weeks (post-FMT). Insulin sensitivity was determined with a stable isotope-based 2 step hyperinsulinemic clamp and multivariate machine learning methodology was used to uncover discriminative microbes, metabolites, and DNA methylation loci. A larger gut microbiota shift was associated with an allogenic than with autologous FMT. Furthemore, the data results of the the allogenic FMT group data indicates that the introduction of new species can potentially modulate the plasma metabolome and (as a result) the epigenome. Most notably, the introduction of Prevotella ASVs directly correlated with methylation of AFAP1, a gene involved in mitochondrial function, insulin sensitivity, and peripheral insulin resistance (Rd, rate of glucose disappearance). FMT was found to have notable effects on the gut microbiome but also on the host plasma metabolome and the epigenome of immune cells providing new avenues of inquiry in the context of metabolic syndrome treatment for the manipulation of host physiology to achieve improved insulin sensitivity.