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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

OUP accepted manuscript

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.

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.

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.

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.

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.

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.

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.

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.

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.

P1755Plasma proteomics in healthy individuals predict myocardial infarction

Background

Currently used models to predict cardiovascular event risk have limited value. It has been shown repetitively that the addition of single biomarkers has modest impact. Recently we observed that a model consisting of a larger array of plasma proteins performed very well in predicting the presence of vulnerable plaques in primary prevention patients. However, the validation of this protein panel in predicting cardiovascular outcomes remains to be established.

Purpose

This study investigated the ability of a 384 preselected protein biomarkers to predict acute myocardial infarction, using state-of-the-art machine learning techniques. Secondly, we compared the performance of this multi-protein risk model to traditional risk engines.

Methods

We selected 822 subjects from the EPIC-Norfolk prospective cohort study, of whom 411 suffered a myocardial infarction during follow-up (median 15 years) compared to 411 controls who remained event-free (median follow-up 20 years). The 384 proteins were measured using proximity extension assay technology. Machine learning algorithms (random forests) were used for the prediction of acute myocardial infarction (ICD code I21–22). Performance of the model was tested against and on top of traditional risk factors for cardiovascular disease (refit Framingham). All performance measurements were averaged over several stability selection routines.

Results

Prediction of myocardial infarction using a machine-learning model consisting of 50 plasma proteins resulted in a ROC AUC of 0.74±0.14, in comparison to 0.69±0.17 using traditional risk factors (refit Framingham. Combining the proteins and refit Framingham resulted in a ROC AUC of 0.74±0.15. Focussing on events occurring within 3 years after baseline blood withdrawal, the ROC AUC increased to 0.80±0.09 using 50 plasma proteins, as opposed to 0.67±0.22 using refit Framingham (figure). Combining the protein model with refit Framingham resulted in a ROC AUC of 0.82±0.11 for these events.

Diagnostic performance events <3yrs

Conclusion

High-throughput proteomics outperforms traditional risk factors in prediction of acute myocardial infarction. Prediction of myocardial infarction occurring within 3 years after inclusion showed highest performance. Availability of affordable proteomic approaches and developed machine learning pave the path for clinical implementation of these models in cardiovascular risk prediction.

Acknowledgement/Funding

This study was funded by an ERA-CVD grant (JTC2017) and EU Horizon 2020 grant (REPROGRAM, 667837)

Does disease start in the mouth, the gut or both?

Oral bacteria colonize the gut more frequently than previously thought.

Predictive value of targeted proteomics for coronary plaque morphology in patients with suspected coronary artery disease

Background

Risk stratification is crucial to improve tailored therapy in patients with suspected coronary artery disease (CAD). This study investigated the ability of targeted proteomics to predict presence of high-risk plaque or absence of coronary atherosclerosis in patients with suspected CAD, defined by coronary computed tomography angiography (CCTA).

Methods

Patients with suspected CAD (n = 203) underwent CCTA. Plasma levels of 358 proteins were used to generate machine learning models for the presence of CCTA-defined high-risk plaques or complete absence of coronary atherosclerosis. Performance was tested against a clinical model containing generally available clinical characteristics and conventional biomarkers.

Findings

A total of 196 patients with analyzable protein levels (n = 332) was included for analysis. A subset of 35 proteins was identified predicting the presence of high-risk plaques. The developed machine learning model had fair diagnostic performance with an area under the curve (AUC) of 0·79 ± 0·01, outperforming prediction with generally available clinical characteristics (AUC = 0·65 ± 0·04, p < 0·05). Conversely, a different subset of 34 proteins was predictive for the absence of CAD (AUC = 0·85 ± 0·05), again outperforming prediction with generally available characteristics (AUC = 0·70 ± 0·04, p < 0·05).

Interpretation

Using machine learning models, trained on targeted proteomics, we defined two complementary protein signatures: one for identification of patients with high-risk plaques and one for identification of patients with absence of CAD. Both biomarker subsets were superior to generally available clinical characteristics and conventional biomarkers in predicting presence of high-risk plaque or absence of coronary atherosclerosis. These promising findings warrant external validation of the value of targeted proteomics to identify cardiovascular risk in outcome studies.

Fund

This study was supported by an unrestricted research grant from HeartFlow Inc. and partly supported by a European Research Area Network on Cardiovascular Diseases (ERA-CVD) grant (ERA CVD JTC2017, OPERATION). Funders had no influence on trial design, data evaluation, and interpretation.

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.

Dominant effect of relative tropical Atlantic warming on major hurricane occurrence

Here we explore factors potentially linked to the enhanced major hurricane activity in the Atlantic Ocean during 2017. Using a suite of high-resolution model experiments, we show that the increase in 2017 major hurricanes was not primarily caused by La Niña conditions in the Pacific Ocean but rather triggered mainly by pronounced warm sea surface conditions in the tropical North Atlantic. Further, we superimpose a similar pattern of North Atlantic surface warming on data for long-term increasing sea surface temperature (a product of increases in greenhouse gas concentrations and decreases in aerosols) to show that this warming trend will likely lead to even higher numbers of major hurricanes in the future. The key factor controlling Atlantic major hurricane activity appears to be the degree to which the tropical Atlantic warms relative to the rest of the global ocean.

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.

Reversal of visceral hypersensitivity in rat by Menthacarin® , a proprietary combination of essential oils from peppermint and caraway, coincides with mycobiome modulation

BACKGROUND

Irritable bowel syndrome (IBS) is a common gastrointestinal disorder associated with altered gastrointestinal microflora and increased nociception to colonic distension. This visceral hypersensitivity can be reversed in our rat maternal separation model by fungicides. Menthacarin^® is a proprietary combination of essential oils from Mentha x piperita L. and Carum carvi. Because these oils exhibit antifungal and antibacterial properties, we investigated whether Menthacarin^® can reverse existing visceral hypersensitivity in maternally separated rats.

METHODS

In non-handled and maternally separated rats, we used the visceromotor responses to colorectal distension as measure for visceral sensitivity. We evaluated this response before and 24 hours after water-avoidance stress and after 7 days treatment with Menthacarin^® or control. The pre- and post-treatment mycobiome and microbiome were characterized by sequencing of fungal internal transcribed spacer 1 (ITS-1) and bacterial 16s rDNA regions. In vitro antifungal and antimicrobial properties of Menthacarin^® were studied with radial diffusion assay.

KEY RESULTS

Menthacarin^® inhibited in vitro growth of yeast and bacteria. Water-avoidance caused visceral hypersensitivity in maternally separated rats, and this was reversed by treatment. Multivariate analyses of ITS-1 and 16S high throughput data showed that maternal separation, induced changes in the myco- and microbiome. Menthacarin^® treatment of non-handled and maternally separated rats shifted the mycobiomes to more similar compositions.

CONCLUSIONS & INFERENCES

The development of visceral hypersensitivity in maternally separated rats and the Menthacarin^® -mediated reversal of hypersensitivity is associated with changes in the mycobiome. Therefore, Menthacarin^® may be a safe and effective treatment option that should be tested for IBS.

Duodenal L cell density correlates with features of metabolic syndrome and plasma metabolites

BACKGROUND

Enteroendocrine cells are essential for the regulation of glucose metabolism, but it is unknown whether they are associated with clinical features of metabolic syndrome (MetS) and fasting plasma metabolites.

OBJECTIVE

We aimed to identify fasting plasma metabolites that associate with duodenal L cell, K cell and delta cell densities in subjects with MetS with ranging levels of insulin resistance.

RESEARCH DESIGN AND METHODS

In this cross-sectional study, we evaluated L, K and delta cell density in duodenal biopsies from treatment-naïve males with MetS using machine-learning methodology.

RESULTS

We identified specific clinical biomarkers and plasma metabolites associated with L cell and delta cell density. L cell density was associated with increased plasma metabolite levels including symmetrical dimethylarginine, 3-aminoisobutyric acid, kynurenine and glycine. In turn, these L cell-linked fasting plasma metabolites correlated with clinical features of MetS.

CONCLUSIONS

Our results indicate a link between duodenal L cells, plasma metabolites and clinical characteristics of MetS. We conclude that duodenal L cells associate with plasma metabolites that have been implicated in human glucose metabolism homeostasis. Disentangling the causal relation between L cells and these metabolites might help to improve the (small intestinal-driven) pathophysiology behind insulin resistance in human obesity.

Effect of Vegan Fecal Microbiota Transplantation on Carnitine- and Choline-Derived Trimethylamine-N-Oxide Production and Vascular Inflammation in Patients With Metabolic Syndrome

BACKGROUND

Intestinal microbiota have been found to be linked to cardiovascular disease via conversion of the dietary compounds choline and carnitine to the atherogenic metabolite TMAO (trimethylamine-N-oxide). Specifically, a vegan diet was associated with decreased plasma TMAO levels and nearly absent TMAO production on carnitine challenge.

METHODS AND RESULTS

We performed a double-blind randomized controlled pilot study in which 20 male metabolic syndrome patients were randomized to single lean vegan-donor or autologous fecal microbiota transplantation. At baseline and 2 weeks thereafter, we determined the ability to produce TMAO from d6-choline and d3-carnitine (eg, labeled and unlabeled TMAO in plasma and 24-hour urine after oral ingestion of 250 mg of both isotope-labeled precursor nutrients), and fecal samples were collected for analysis of microbiota composition. 18F-fluorodeoxyglucose positron emission tomography/computed tomography scans of the abdominal aorta, as well as ex vivo peripheral blood mononuclear cell cytokine production assays, were performed. At baseline, fecal microbiota composition differed significantly between vegans and metabolic syndrome patients. With vegan-donor fecal microbiota transplantation, intestinal microbiota composition in metabolic syndrome patients, as monitored by global fecal microbial community structure, changed toward a vegan profile in some of the patients; however, no functional effects from vegan-donor fecal microbiota transplantation were seen on TMAO production, abdominal aortic 18F-fluorodeoxyglucose uptake, or ex vivo cytokine production from peripheral blood mononuclear cells.

CONCLUSIONS

Single lean vegan-donor fecal microbiota transplantation in metabolic syndrome patients resulted in detectable changes in intestinal microbiota composition but failed to elicit changes in TMAO production capacity or parameters related to vascular inflammation.

CLINICAL TRIAL REGISTRATION

URL: http://www.trialregister.nl. Unique identifier: NTR 4338.

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.

Distinct fecal and oral microbiota composition in human type 1 diabetes, an observational study

OBJECTIVE

Environmental factors driving the development of type 1 diabetes (T1D) are still largely unknown. Both animal and human studies have shown an association between altered fecal microbiota composition, impaired production of short-chain fatty acids (SCFA) and T1D onset. However, observational evidence on SCFA and fecal and oral microbiota in adults with longstanding T1D vs healthy controls (HC) is lacking.

RESEARCH DESIGN AND METHODS

We included 53 T1D patients without complications or medication and 50 HC matched for age, sex and BMI. Oral and fecal microbiota, fecal and plasma SCFA levels, markers of intestinal inflammation (fecal IgA and calprotectin) and markers of low-grade systemic inflammation were measured.

RESULTS

Oral microbiota were markedly different in T1D (eg abundance of Streptococci) compared to HC. Fecal analysis showed decreased butyrate producing species in T1D and less butyryl-CoA transferase genes. Also, plasma levels of acetate and propionate were lower in T1D, with similar fecal SCFA. Finally, fecal strains Christensenella and Subdoligranulum correlated with glycemic control, inflammatory parameters and SCFA.

CONCLUSIONS

We conclude that T1D patients harbor a different amount of intestinal SCFA (butyrate) producers and different plasma acetate and propionate levels. Future research should disentangle cause and effect and whether supplementation of SCFA-producing bacteria or SCFA alone can have disease-modifying effects in T1D.

Improvement of Insulin Sensitivity after Lean Donor Feces in Metabolic Syndrome Is Driven by Baseline Intestinal Microbiota Composition

The intestinal microbiota has been implicated in insulin resistance, although evidence regarding causality in humans is scarce. We therefore studied the effect of lean donor (allogenic) versus own (autologous) fecal microbiota transplantation (FMT) to male recipients with the metabolic syndrome. Whereas we did not observe metabolic changes at 18 weeks after FMT, insulin sensitivity at 6 weeks after allogenic FMT was significantly improved, accompanied by altered microbiota composition. We also observed changes in plasma metabolites such as γ-aminobutyric acid and show that metabolic response upon allogenic FMT (defined as improved insulin sensitivity 6 weeks after FMT) is dependent on decreased fecal microbial diversity at baseline. In conclusion, the beneficial effects of lean donor FMT on glucose metabolism are associated with changes in intestinal microbiota and plasma metabolites and can be predicted based on baseline fecal microbiota composition.

Identification of microorganisms grown in blood culture flasks using liquid chromatography–tandem mass spectrometry

Aim: Bloodstream infections are a common cause of disease and a fast and accurate identification of the causative agent or agents of bloodstream infections would aid the start of adequate treatment. Materials & methods: A liquid chromatography–tandem mass spectrometry (LC–MS/MS) shotgun proteomics method was developed for the identification of bacterial species directly from blood cultures that were simulated by inoculating blood culture bottles with single or multiple clinically relevant microorganisms. Results: Using LC–MS/MS, the single species were correctly identified in 100% of the blood cultures, whereas for polymicrobial infections, 78% of both species were correctly identified in blood cultures. Conclusion: The LC–MS/MS method allows for the identification of the causative agent of positive blood cultures.

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 β-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 β-glucans or a SYK inhibitor reduced visceral hypersensitivity, compared with controls. Particulate β-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 β-glucans, or a SYK inhibitor. The intestinal fungi might therefore be manipulated for treatment of IBS-related visceral hypersensitivity.

Hawkmoths use nectar sugar to reduce oxidative damage from flight

Nectar-feeding animals have among the highest recorded metabolic rates. High aerobic performance is linked to oxidative damage in muscles. Antioxidants in nectar are scarce to nonexistent. We propose that nectarivores use nectar sugar to mitigate the oxidative damage caused by the muscular demands of flight. We found that sugar-fed moths had lower oxidative damage to their flight muscle membranes than unfed moths. Using respirometry coupled with δ¹³C analyses, we showed that moths generate antioxidant potential by shunting nectar glucose to the pentose phosphate pathway (PPP), resulting in a reduction in oxidative damage to the flight muscles. We suggest that nectar feeding, the use of PPP, and intense exercise are causally linked and have allowed the evolution of powerful fliers that feed on nectar.