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.

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.

Faecal microbiota transplantation halts progression of human new-onset type 1 diabetes in a randomised controlled trial.

OBJECTIVE: Type 1 diabetes (T1D) is characterised by islet autoimmunity and beta cell destruction. A gut microbiota-immunological interplay is involved in the pathophysiology of T1D. We studied microbiota-mediated effects on disease progression in patients with type 1 diabetes using faecal microbiota transplantation (FMT). DESIGN: Patients with recent-onset (<6 weeks) T1D (18-30 years of age) were randomised into two groups to receive three autologous or allogenic (healthy donor) FMTs over a period of 4 months. Our primary endpoint was preservation of stimulated C peptide release assessed by mixed-meal tests during 12 months. Secondary outcome parameters were changes in glycaemic control, fasting plasma metabolites, T cell autoimmunity, small intestinal gene expression profile and intestinal microbiota composition. RESULTS: Stimulated C peptide levels were significantly preserved in the autologous FMT group (n=10 subjects) compared with healthy donor FMT group (n=10 subjects) at 12 months. Small intestinal Prevotella was inversely related to residual beta cell function (r=-0.55, p=0.02), whereas plasma metabolites 1-arachidonoyl-GPC and 1-myristoyl-2-arachidonoyl-GPC levels linearly correlated with residual beta cell preservation (rho=0.56, p=0.01 and rho=0.46, p=0.042, respectively). Finally, baseline CD4 +CXCR3+T cell counts, levels of small intestinal Desulfovibrio piger and CCL22 and CCL5 gene expression in duodenal biopsies predicted preserved beta cell function following FMT irrespective of donor characteristics. CONCLUSION: FMT halts decline in endogenous insulin production in recently diagnosed patients with T1D in 12 months after disease onset. Several microbiota-derived plasma metabolites and bacterial strains were linked to preserved residual beta cell function. This study provides insight into the role of the intestinal gut microbiome in T1D. TRIAL REGISTRATION NUMBER: NTR3697.

Impact drugs targeting cardiometabolic risk on the gut microbiota.

PURPOSE OF REVIEW: Alterations in the gut microbiome composition or function are associated with risk factors for cardiometabolic diseases, including hypertension, hyperlipidemia and hyperglycemia. Based on recent evidence that also oral medications used to treat these conditions could alter the gut microbiome composition and function and, vice versa, that the gut microbiome could affect the efficacy of these treatments, we reviewed the literature on these observed interactions. RECENT FINDINGS: While the interaction of metformin with the gut microbiome has been studied most, other drugs that target cardiometabolic risk are gaining attention and often showed associations with alterations in microbiome-related features, including alterations in specific microbial taxa or pathways, microbiome composition or microbiome-derived metabolites, while the gut microbiome was also involved in drug metabolism and drug efficacy. As for metformin, for some of them even a potential therapeutic effect via the gut microbiome is postulated. However, exact mechanisms remain to be elucidated. SUMMARY: There is growing interest in clarifying the interactions between the gut microbiome and drugs to treat hypertension, hyperlipidemia and hyperglycemia as well as the first pass effect of microbiome on drug efficacy. While mostly analysed in animal models, also human studies are gaining more and more traction. Improving the understanding of the gut microbiome drug interaction can provide clinical directions for therapy by optimizing drug efficacy or providing new targets for drug development.

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.

Metabolomics in Severe Aortic Stenosis Reveals Intermediates of Nitric Oxide Synthesis as Most Distinctive Markers.

BACKGROUND: Calcific aortic valve disease (CAVD) is a rapidly growing global health problem with an estimated 12.6 million cases globally in 2017 and a 112% increase of deaths since 1990 due to aging and population growth. CAVD may develop into aortic stenosis (AS) by progressive narrowing of the aortic valve. AS is underdiagnosed, and if treatment by aortic valve replacement (AVR) is delayed, this leads to poor recovery of cardiac function, absence of symptomatic improvement and marked increase of mortality. Considering the current limitations to define the stage of AS-induced cardiac remodeling, there is need for a novel method to aid in the diagnosis of AS and timing of intervention, which may be found in metabolomics profiling of patients. METHODS: Serum samples of nine healthy controls and 10 AS patients before and after AVR were analyzed by untargeted mass spectrometry. Multivariate modeling was performed to determine a metabolic profile of 30 serum metabolites which distinguishes AS patients from controls. Human cardiac microvascular endothelial cells (CMECs) were incubated with serum of the AS patients and then stained for ICAM-1 with Western Blot to analyze the effect of AS patient serum on endothelial cell activation. RESULTS: The top 30 metabolic profile strongly distinguishes AS patients from healthy controls and includes 17 metabolites related to nitric oxide metabolism and 12 metabolites related to inflammation, in line with the known pathomechanism for calcific aortic valve disease. Nine metabolites correlate strongly with left ventricular mass, of which three show reversal back to control values after AVR. Western blot analysis of CMECs incubated with AS patient sera shows a significant reduction (14%) in ICAM-1 in AS samples taken after AVR compared to AS patient sera before AVR. CONCLUSION: Our study defined a top 30 metabolic profile with biological and clinical relevance, which may be used as blood biomarker to identify AS patients in need of cardiac surgery. Future studies are warranted in patients with mild-to-moderate AS to determine if these metabolites reflect disease severity and can be used to identify AS patients in need of cardiac surgery.

Donor metabolic characteristics drive effects of faecal microbiota transplantation on recipient insulin sensitivity, energy expenditure and intestinal transit time.

OBJECTIVE: Bariatric surgery improves glucose metabolism. Recent data suggest that faecal microbiota transplantation (FMT) using faeces from postbariatric surgery diet-induced obese mice in germ-free mice improves glucose metabolism and intestinal homeostasis. We here investigated whether allogenic FMT using faeces from post-Roux-en-Y gastric bypass donors (RYGB-D) compared with using faeces from metabolic syndrome donors (METS-D) has short-term effects on glucose metabolism, intestinal transit time and adipose tissue inflammation in treatment-naïve, obese, insulin-resistant male subjects. DESIGN: Subjects with metabolic syndrome (n=22) received allogenic FMT either from RYGB-D or METS-D. Hepatic and peripheral insulin sensitivity as well as lipolysis were measured at baseline and 2 weeks after FMT by hyperinsulinaemic euglycaemic stable isotope (2H2-glucose and 2H5-glycerol) clamp. Secondary outcome parameters were changes in resting energy expenditure, intestinal transit time, faecal short-chain fatty acids (SCFA) and bile acids, and inflammatory markers in subcutaneous adipose tissue related to intestinal microbiota composition. Faecal SCFA, bile acids, glycaemic control and inflammatory parameters were also evaluated at 8 weeks. RESULTS: We observed a significant decrease in insulin sensitivity 2 weeks after allogenic METS-D FMT (median rate of glucose disappearance: from 40.6 to 34.0 µmol/kg/min; p<0.01). Moreover, a trend (p=0.052) towards faster intestinal transit time following RYGB-D FMT was seen. Finally, we observed changes in faecal bile acids (increased lithocholic, deoxycholic and (iso)lithocholic acid after METS-D FMT), inflammatory markers (decreased adipose tissue chemokine ligand 2 (CCL2) gene expression and plasma CCL2 after RYGB-D FMT) and changes in several intestinal microbiota taxa. CONCLUSION: Allogenic FMT using METS-D decreases insulin sensitivity in metabolic syndrome recipients when compared with using post-RYGB-D. Further research is needed to delineate the role of donor characteristics in FMT efficacy in human insulin-resistant subjects. TRIAL REGISTRATION NUMBER: NTR4327.

Oral butyrate does not affect innate immunity and islet autoimmunity in individuals with longstanding type 1 diabetes: a randomised controlled trial.

AIMS/HYPOTHESIS: The pathophysiology of type 1 diabetes has been linked to altered gut microbiota and more specifically to a shortage of intestinal production of the short-chain fatty acid (SCFA) butyrate, which may play key roles in maintaining intestinal epithelial integrity and in human and gut microbial metabolism. Butyrate supplementation can protect against autoimmune diabetes in mouse models. We thus set out to study the effect of oral butyrate vs placebo on glucose regulation and immune variables in human participants with longstanding type 1 diabetes. METHODS: We administered a daily oral dose of 4 g sodium butyrate or placebo for 1 month to 30 individuals with longstanding type 1 diabetes, without comorbidity or medication use, in a randomised (1:1), controlled, double-blind crossover trial, with a washout period of 1 month in between. Participants were randomly allocated to the 'oral sodium butyrate capsules first' or 'oral placebo capsules first' study arm in blocks of five. The clinical investigator received blinded medication from the clinical trial pharmacy. All participants, people doing measurements or examinations, or people assessing the outcomes were blinded to group assignment. The primary outcome was a change in the innate immune phenotype (monocyte subsets and in vitro cytokine production). Secondary outcomes were changes in blood markers of islet autoimmunity (cell counts, lymphocyte stimulation indices and CD8 quantum dot assays), glucose and lipid metabolism, beta cell function (by mixed-meal test), gut microbiota and faecal SCFA. The data was collected at the Amsterdam University Medical Centers. RESULTS: All 30 participants were analysed. Faecal butyrate and propionate levels were significantly affected by oral butyrate supplementation and butyrate treatment was safe. However, this modulation of intestinal SCFAs did not result in any significant changes in adaptive or innate immunity, or in any of the other outcome variables. In our discussion, we elaborate on this important discrepancy with previous animal work. CONCLUSIONS/INTERPRETATION: Oral butyrate supplementation does not significantly affect innate or adaptive immunity in humans with longstanding type 1 diabetes. TRIAL REGISTRATION: Netherlands Trial Register: NL4832 (www.trialregister.nl). DATA AVAILABILITY: Raw sequencing data are available in the European Nucleotide Archive repository (https://www.ebi.ac.uk/ena/browse) under study PRJEB30292. FUNDING: The study was funded by a Le Ducq consortium grant, a CVON grant, a personal ZONMW-VIDI grant and a Dutch Heart Foundation grant.

Untargeted accurate identification of highly pathogenic bacteria directly from blood culture flasks.

To improve the preparedness against exposure to highly pathogenic bacteria and to anticipate the wide variety of bacteria that can cause bloodstream infections (BSIs), a safe, unbiased and highly accurate identification method was developed. Our liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based method can identify highly pathogenic bacteria, their near-neighbors and bacteria that are common causes of BSIs directly from positive blood culture flasks. The developed Peptide-Based Microbe Detection Engine (http://proteome2pathogen.com) relies on a two-step workflow: a genus-level search followed by a species-level search. This strategy enables the rapid identification of microorganisms based on the analyzed proteome. This method was successfully used to identify strains of Bacillus anthracis, Brucella abortus, Brucella melitensis, Brucella suis, Burkholderia pseudomallei, Burkholderia mallei, Francisella tularensis, Yersinia pestis and closely related species from simulated blood culture flasks. This newly developed LC-MS/MS method is a safe and rapid method for accurately identifying bacteria directly from positive blood culture flasks.

Domain intelligible models.

Mining biological information from rich "-omics" datasets is facilitated by organizing features into groups that are related to a biological phenomenon or clinical outcome. For example, microorganisms can be grouped based on a phylogenetic tree that depicts their similarities regarding genetic or physical characteristics. Here, we describe algorithms that incorporate auxiliary information in terms of groups of predictors and the relationships between them into the metagenome learning task to build intelligible models. In particular, our cost function guides the feature selection process using auxiliary information by requiring related groups of predictors to provide similar contributions to the final response. We apply the developed algorithms to a recently published dataset analyzing the effects of fecal microbiota transplantation (FMT) in order to identify factors that are associated with improved peripheral insulin sensitivity, leading to accurate predictions of the response to the FMT.

Intestinal Fungal Dysbiosis Is Associated With Visceral Hypersensitivity in Patients With Irritable Bowel Syndrome and Rats.

BACKGROUND & AIMS: Visceral hypersensitivity is one feature of irritable bowel syndrome (IBS). Bacterial dysbiosis might be involved in the activation of nociceptive sensory pathways, but there have been few studies of the role of the mycobiome (the fungal microbiome) in the development of IBS. We analyzed intestinal mycobiomes of patients with IBS and a rat model of visceral hypersensitivity. METHODS: We used internal transcribed spacer 1-based metabarcoding to compare fecal mycobiomes of 18 healthy volunteers with those of 39 patients with IBS (with visceral hypersensitivity or normal levels of sensitivity). We also compared the mycobiomes of Long-Evans rats separated from their mothers (hypersensitive) with non-handled (normally sensitive) rats. We investigated whether fungi can cause visceral hypersensitivity using rats exposed to fungicide (fluconazole and nystatin). The functional relevance of the gut mycobiome was confirmed in fecal transplantation experiments: adult maternally separated rats were subjected to water avoidance stress (to induce visceral hypersensitivity), then given fungicide and donor cecum content via oral gavage. Other rats subjected to water avoidance stress were given soluble ß-glucans, which antagonize C-type lectin domain family 7 member A (CLEC7A or DECTIN1) signaling via spleen-associated tyrosine kinase (SYK), a SYK inhibitor to reduce visceral hypersensitivity, or vehicle (control). The sensitivity of mast cells to fungi was tested with mesenteric windows (ex vivo) and the human mast cell line HMC-1. RESULTS: α diversity (Shannon index) and mycobiome signature (stability selection) of both groups of IBS patients differed from healthy volunteers, and the mycobiome signature of hypersensitive patients differed from that of normally sensitive patients. We observed mycobiome dysbiosis in rats that had been separated from their mothers compared with non-handled rats. Administration of fungicide to hypersensitive rats reduced their visceral hypersensitivity to normal levels of sensitivity. Administration of cecal mycobiomes from rats that had been separated from their mothers (but not non-handled mycobiome) restored hypersensitivity to distension. Administration of soluble ß-glucans or a SYK inhibitor reduced visceral hypersensitivity, compared with controls. Particulate ß-glucan (a DECTIN-1 agonist) induced mast cell degranulation in mesenteric windows and HMC-1 cells responded to fungal antigens by release of histamine. CONCLUSIONS: In an analysis of patients with IBS and controls, we associated fungal dysbiosis with IBS. In studies of rats, we found fungi to promote visceral hypersensitivity, which could be reduced by administration of fungicides, soluble ß-glucans, or a SYK inhibitor. The intestinal fungi might therefore be manipulated for treatment of IBS-related visceral hypersensitivity.

Fecal Microbiome and Food Allergy in Pediatric Atopic Dermatitis: A Cross-Sectional Pilot Study.

BACKGROUND: Exposure to microbes may be important in the development of atopic disease. Atopic diseases have been associated with specific characteristics of the intestinal microbiome. The link between intestinal microbiota and food allergy has rarely been studied, and the gold standard for diagnosing food allergy (double-blind placebo-controlled food challenge [DBPCFC]) has seldom been used. We aimed to distinguish fecal microbial signatures for food allergy in children with atopic dermatitis (AD). METHODS: Pediatric patients with AD, with and without food allergy, were included in this cross-sectional observational pilot study. AD was diagnosed according to the UK Working Party criteria. Food allergy was defined as a positive DBPCFC or a convincing clinical history, in combination with sensitization to the relevant food allergen. Fecal samples were analyzed using 16S rRNA microbial analysis. Microbial signature species, discriminating between the presence and absence food allergy, were selected by elastic net regression. RESULTS: Eighty-two children with AD (39 girls) with a median age of 2.5 years, and 20 of whom were diagnosed with food allergy, provided fecal samples. Food allergy to peanut and cow's milk was the most common. Six bacterial species from the fecal microbiome were identified, that, when combined, distinguished between children with and without food allergy: Bifidobacterium breve, Bifidobacterium pseudocatenulatum, Bifidobacterium adolescentis, Escherichia coli, Faecalibacterium prausnitzii, and Akkermansia muciniphila (AUC 0.83, sensitivity 0.77, specificity 0.80). CONCLUSIONS: In this pilot study, we identified a microbial signature in children with AD that discriminates between the absence and presence of food allergy. Future studies are needed to confirm our findings.

At least three phenotypes exist among periodontitis patients.

AIM: To identify phenotypes of periodontitis patients by the use of an unsupervised modelling technique (clustering), based on pre-treatment radiographic and microbiological characteristics. MATERIALS AND METHODS: This retrospective study included data from 392 untreated periodontitis patients. Co-regularized spectral clustering algorithm was used to cluster the patients. The resulting clusters were subsequently characterized based on their demographics, radiographic bone loss patterns and microbial data. RESULTS: The vast majority of patients fitted into one of the three main clusters (accuracy 90%). Cluster A (n = 18) was characterized by high prevalence and high proportions of Aggregatibacter actinomycetemcomitans, a trend for a more localized pattern of alveolar bone loss and young individuals. Clusters B (n = 200) and C (n = 135) differed clearly in disease severity patterns and smoking habits, but not in microbiological characteristics. CONCLUSION: On the basis of alveolar bone loss patterns and microbiological data, untreated periodontitis patients can be clustered into at least three phenotypes. These results should be validated in other cohorts, and the clinical utility needs to be explored on the basis of periodontal treatment outcomes and/or disease progression.

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.

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.

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.

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.

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.

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.