Alterations in the gut microbiome implicate key taxa and metabolic pathways across inflammatory arthritis phenotypes.

Musculoskeletal diseases affect up to 20% of adults worldwide. The gut microbiome has been implicated in inflammatory conditions, but large-scale metagenomic evaluations have not yet traced the routes by which immunity in the gut affects inflammatory arthritis. To characterize the community structure and associated functional processes driving gut microbial involvement in arthritis, the Inflammatory Arthritis Microbiome Consortium investigated 440 stool shotgun metagenomes comprising 221 adults diagnosed with rheumatoid arthritis, ankylosing spondylitis, or psoriatic arthritis and 219 healthy controls and individuals with joint pain without an underlying inflammatory cause. Diagnosis explained about 2% of gut taxonomic variability, which is comparable in magnitude to inflammatory bowel disease. We identified several candidate microbes with differential carriage patterns in patients with elevated blood markers for inflammation. Our results confirm and extend previous findings of increased carriage of typically oral and inflammatory taxa and decreased abundance and prevalence of typical gut clades, indicating that distal inflammatory conditions, as well as local conditions, correspond to alterations to the gut microbial composition. We identified several differentially encoded pathways in the gut microbiome of patients with inflammatory arthritis, including changes in vitamin B salvage and biosynthesis and enrichment of iron sequestration. Although several of these changes characteristic of inflammation could have causal roles, we hypothesize that they are mainly positive feedback responses to changes in host physiology and immune homeostasis. By connecting taxonomic alternations to functional alterations, this work expands our understanding of the shifts in the gut ecosystem that occur in response to systemic inflammation during arthritis.

IL-1-driven stromal-neutrophil interactions define a subset of patients with inflammatory bowel disease that does not respond to therapies.

Current inflammatory bowel disease (IBD) therapies are ineffective in a high proportion of patients. Combining bulk and single-cell transcriptomics, quantitative histopathology and in situ localization across three cohorts of patients with IBD (total n = 376), we identify coexpressed gene modules within the heterogeneous tissular inflammatory response in IBD that map to distinct histopathological and cellular features (pathotypes). One of these pathotypes is defined by high neutrophil infiltration, activation of fibroblasts and vascular remodeling at sites of deep ulceration. Activated fibroblasts in the ulcer bed display neutrophil-chemoattractant properties that are IL-1R, but not TNF, dependent. Pathotype-associated neutrophil and fibroblast signatures are increased in nonresponders to several therapies across four independent cohorts (total n = 343). The identification of distinct, localized, tissular pathotypes will aid precision targeting of current therapeutics and provides a biological rationale for IL-1 signaling blockade in ulcerating disease.

Endocannabinoid system mediates the association between gut-microbial diversity and anhedonia/amotivation in a general population cohort.

Anhedonia and amotivation are debilitating symptoms and represent unmet therapeutic needs in a range of clinical conditions. The gut-microbiome-endocannabinoid axis might represent a potential modifiable target for interventions. Based on results obtained from animal models, we tested the hypothesis that the endocannabinoid system mediates the association between gut-microbiome diversity and anhedonia/amotivation in a general population cohort. We used longitudinal data collected from 786 volunteer twins recruited as part the TwinsUK register. Our hypothesis was tested with a multilevel mediation model using family structure as random intercept. The model was set using alpha diversity (within-individual gut-microbial diversity) as predictor, serum and faecal levels of the endocannabinoid palmitoylethanolamide (PEA) as mediator, and anhedonia/amotivation as outcome. PEA is considered the endogenous equivalent of cannabidiol, with increased serum levels believed to have anti-depressive effects, while increased stool PEA levels, reflecting increased excretion, are believed to have opposite, detrimental, effects on mental health. We therefore expected that either reduced serum PEA or increased stool PEA would mediate the association between microbial diversity and anhedonia amotivation. Analyses were adjusted for obesity, diet, antidepressant use, sociodemographic and technical covariates. Data were imputed using multiple imputation by chained equations. Mean age was 65.2 ± 7.6; 93% of the sample were females. We found a direct, significant, association between alpha diversity and anhedonia/amotivation (ß = -0.37; 95%CI: -0.71 to -0.03; P = 0.03). Faecal, but not serum, levels of the endocannabinoid palmitoylethanolamide (PEA) mediated this association: the indirect effect was significant (ß = -0.13; 95%CI: -0.24 to -0.01; P = 0.03), as was the total effect (ß = -0.38; 95%CI: -0.72 to -0.04; P = 0.03), whereas the direct effect of alpha diversity on anhedonia/amotivation was attenuated fully (ß = -0.25; 95%CI: -0.60 to 0.09; P = 0.16). Our results suggest that gut-microbial diversity might contribute to anhedonia/amotivation via the endocannabinoid system. These findings shed light on the biological underpinnings of anhedonia/amotivation and suggest the gut microbiota-endocannabinoid axis as a promising therapeutic target in an area of unmet clinical need.

Accurate identification and quantification of commensal microbiota bound by host immunoglobulins.

BACKGROUND: Identifying which taxa are targeted by immunoglobulins can uncover important host-microbe interactions. Immunoglobulin binding of commensal taxa can be assayed by sorting bound bacteria from samples and using amplicon sequencing to determine their taxonomy, a technique most widely applied to study Immunoglobulin A (IgA-Seq). Previous experiments have scored taxon binding in IgA-Seq datasets by comparing abundances in the IgA bound and unbound sorted fractions. However, as these are relative abundances, such scores are influenced by the levels of the other taxa present and represent an abstract combination of these effects. Diversity in the practical approaches of prior studies also warrants benchmarking of the individual stages involved. Here, we provide a detailed description of the design strategy for an optimised IgA-Seq protocol. Combined with a novel scoring method for IgA-Seq datasets that accounts for the aforementioned effects, this platform enables accurate identification and quantification of commensal gut microbiota targeted by host immunoglobulins. RESULTS: Using germ-free and Rag1-/- mice as negative controls, and a strain-specific IgA antibody as a positive control, we determine optimal reagents and fluorescence-activated cell sorting (FACS) parameters for IgA-Seq. Using simulated IgA-Seq data, we show that existing IgA-Seq scoring methods are influenced by pre-sort relative abundances. This has consequences for the interpretation of case-control studies where there are inherent differences in microbiota composition between groups. We show that these effects can be addressed using a novel scoring approach based on posterior probabilities. Finally, we demonstrate the utility of both the IgA-Seq protocol and probability-based scores by examining both novel and published data from in vivo disease models. CONCLUSIONS: We provide a detailed IgA-Seq protocol to accurately isolate IgA-bound taxa from intestinal samples. Using simulated and experimental data, we demonstrate novel probability-based scores that adjust for the compositional nature of relative abundance data to accurately quantify taxon-level IgA binding. All scoring approaches are made available in the IgAScores R package. These methods should improve the generation and interpretation of IgA-Seq datasets and could be applied to study other immunoglobulins and sample types. Video abstract.

Large-scale association analyses identify host factors influencing human gut microbiome composition.

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 × 10-8) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 × 10-20), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 × 10-10 < P < 5 × 10-8) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis.

Associations between UK tap water and gut microbiota composition suggest the gut microbiome as a potential mediator of health differences linked to water quality.

Tap water composition has been widely linked to differences in human health, however the biological pathways underlying this association are less clearly defined. We provide the first investigation of the potential for the gut microbiota to mediate this association. Tap water samples and drinking habits from 85 Mono-zygotic twins with existing faecal microbiota profiles from around the UK were used to assess associations of water composition with the gut microbiome. Water composition was captured using the first 3 principle components (PCs) from multiple factor analysis of ion concentrations, additionally estimating average daily dose (ADD) of the primary three solutes contributing to its variance: chloride, sulphate and sodium. Geographic differences in water composition were assessed. We used measures of faecal microbial diversity, between-individual differences in composition and differences in taxa abundance estimated from 16S rRNA sequencing data. Differences between twin pairs were also considered. We observed significant associations of sodium ADD with microbiota diversity (Chao1), chloride, sodium and sulphate ADD with dissimilarity between samples, and significant associations for all PCs and ADD-adjusted solutes with abundances of individual microbial taxa. These results support the hypothesis that the gut microbiota could mediate the effects of tap water composition on host health, warranting further investigation into tap-water as an influencer of microbiota composition.

Socioeconomic Status and the Gut Microbiome: A TwinsUK Cohort Study.

Socioeconomic inequalities in health and mortality are well established, but the biological mechanisms underlying these associations are less understood. In parallel, the gut microbiome is emerging as a potentially important determinant of human health, but little is known about its broader environmental and social determinants. We test the association between gut microbiota composition and individual- and area-level socioeconomic factors in a well-characterized twin cohort. In this study, 1672 healthy volunteers from twin registry TwinsUK had data available for at least one socioeconomic measure, existing fecal 16S rRNA microbiota data, and all considered co-variables. Associations with socioeconomic status (SES) were robust to adjustment for known health correlates of the microbiome; conversely, these health-microbiome associations partially attenuated with adjustment for SES. Twins discordant for IMD (Index of Multiple Deprivation) were shown to significantly differ by measures of compositional dissimilarity, with suggestion the greater the difference in twin pair IMD, the greater the dissimilarity of their microbiota. Future research should explore how SES might influence the composition of the gut microbiota and its potential role as a mediator of differences associated with SES.

An Investigation Into Physical Frailty as a Link Between the Gut Microbiome and Cognitive Health.

The preservation of cognitive abilities with aging is a priority both for individuals and nations given the aging populations of many countries. Recently the gut microbiome has been identified as a new territory to explore in relation to cognition. Experiments using rodents have identified a link between the gut microbiome and cognitive function, particularly that low microbial diversity leads to poor cognition function. Similar studies in humans could identify novel targets to encourage healthy cognition in an aging population. Here, we investigate the association of gut microbiota and cognitive function in a human cohort considering the influence of physical frailty. We analyzed 16S rRNA gene sequence data, derived from fecal samples obtained from 1,551 individuals over the age of 40. Cognitive data was collected using four cognitive tests: verbal fluency (n = 1,368), Deary-Liewald Reaction Time Test (DLRT; n = 873), Mini Mental State Examination (recall; n = 1,374) and Paired Associates Learning from the Cambridge Neuropsychological Test Automated Battery (CANTAB-PAL; n = 405). We use mixed effects models to identify associations with alpha diversity, operational taxonomic units (OTUs) and taxa and performed further analyses adjusting for physical frailty. We then repeated the analyses in a subset of individuals with dietary data, also excluding those using medications shown to influence gut microbiome composition. DLRT and verbal fluency were negatively associated with alpha diversity of the gut microbiota (False-Discovery Rate, FDR, p < 0.05). However, when considering frailty as a covariate, only associations between the DLRT and diversity measures remained. Repeating analyses excluding Proton pump inhibitor (PPI) and antibiotic users and accounting for diet, we similarly observe significant negative associations between the DLRT and alpha diversity measures and a further negative association between DLRT and the abundance of the order Burkholderiales that remains significant after adjusting for host frailty. This highlights the importance of considering concurrent differences in physical health in studies of cognitive performance and suggests that physical health has a relatively larger association with the gut microbiome. However, the frailty independent cognitive-gut microbiota associations that were observed might represent important targets for further research, with potential for use in diagnostic surveillance in cognitive aging and interventions to improve vitality.

Gut microbiota associations with common diseases and prescription medications in a population-based cohort.

The human gut microbiome has been associated with many health factors but variability between studies limits exploration of effects between them. Gut microbiota profiles are available for >2700 members of the deeply phenotyped TwinsUK cohort, providing a uniform platform for such comparisons. Here, we present gut microbiota association analyses for 38 common diseases and 51 medications within the cohort. We describe several novel associations, highlight associations common across multiple diseases, and determine which diseases and medications have the greatest association with the gut microbiota. These results provide a reference for future studies of the gut microbiome and its role in human health.

Meta-analysis of human genome-microbiome association studies: the MiBioGen consortium initiative.

BACKGROUND: In recent years, human microbiota, especially gut microbiota, have emerged as an important yet complex trait influencing human metabolism, immunology, and diseases. Many studies are investigating the forces underlying the observed variation, including the human genetic variants that shape human microbiota. Several preliminary genome-wide association studies (GWAS) have been completed, but more are necessary to achieve a fuller picture. RESULTS: Here, we announce the MiBioGen consortium initiative, which has assembled 18 population-level cohorts and some 19,000 participants. Its aim is to generate new knowledge for the rapidly developing field of microbiota research. Each cohort has surveyed the gut microbiome via 16S rRNA sequencing and genotyped their participants with full-genome SNP arrays. We have standardized the analytical pipelines for both the microbiota phenotypes and genotypes, and all the data have been processed using identical approaches. Our analysis of microbiome composition shows that we can reduce the potential artifacts introduced by technical differences in generating microbiota data. We are now in the process of benchmarking the association tests and performing meta-analyses of genome-wide associations. All pipeline and summary statistics results will be shared using public data repositories. CONCLUSION: We present the largest consortium to date devoted to microbiota-GWAS. We have adapted our analytical pipelines to suit multi-cohort analyses and expect to gain insight into host-microbiota cross-talk at the genome-wide level. And, as an open consortium, we invite more cohorts to join us (by contacting one of the corresponding authors) and to follow the analytical pipeline we have developed.

American Gut: an Open Platform for Citizen Science Microbiome Research.

Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. IMPORTANCE We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.

The fecal metabolome as a functional readout of the gut microbiome.

The human gut microbiome plays a key role in human health 1 , but 16S characterization lacks quantitative functional annotation 2 . The fecal metabolome provides a functional readout of microbial activity and can be used as an intermediate phenotype mediating host-microbiome interactions 3 . In this comprehensive description of the fecal metabolome, examining 1,116 metabolites from 786 individuals from a population-based twin study (TwinsUK), the fecal metabolome was found to be only modestly influenced by host genetics (heritability (H2) = 17.9%). One replicated locus at the NAT2 gene was associated with fecal metabolic traits. The fecal metabolome largely reflects gut microbial composition, explaining on average 67.7% (±18.8%) of its variance. It is strongly associated with visceral-fat mass, thereby illustrating potential mechanisms underlying the well-established microbial influence on abdominal obesity. Fecal metabolic profiling thus is a novel tool to explore links among microbiome composition, host phenotypes, and heritable complex traits.

Use of dietary indices to control for diet in human gut microbiota studies.

BACKGROUND: Environmental factors have a large influence on the composition of the human gut microbiota. One of the most influential and well-studied is host diet. To assess and interpret the impact of non-dietary factors on the gut microbiota, we endeavoured to determine the most appropriate method to summarise community variation attributable to dietary effects. Dietary habits are multidimensional with internal correlations. This complexity can be simplified by using dietary indices that quantify dietary variance in a single measure and offer a means of controlling for diet in microbiota studies. However, to date, the applicability of different dietary indices to gut microbiota studies has not been assessed. Here, we use food frequency questionnaire (FFQ) data from members of the TwinsUK cohort to create three different dietary measures applicable in western-diet populations: The Healthy Eating Index (HEI), the Mediterranean Diet Score (MDS) and the Healthy Food Diversity index (HFD-Index). We validate and compare these three indices to determine which best summarises dietary influences on gut microbiota composition. RESULTS: All three indices were independently validated using established measures of health, and all were significantly associated with microbiota measures; the HEI had the highest t values in models of alpha diversity measures, and had the highest number of associations with microbial taxa. Beta diversity analyses showed the HEI explained the greatest variance of microbiota composition. In paired tests between twins discordant for dietary index score, the HEI was associated with the greatest variation of taxa and twin dissimilarity. CONCLUSIONS: We find that the HEI explains the most variance in, and has the strongest association with, gut microbiota composition in a western (UK) population, suggesting that it may be the best summary measure to capture gut microbiota variance attributable to habitual diet in comparable populations.

Detection of stable community structures within gut microbiota co-occurrence networks from different human populations.

Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa. The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples. Here, we present an approach to identify comparable communities within different gut microbiota co-occurrence networks, and demonstrate its use by comparing the gut microbiota community structures of three geographically diverse populations. We combine gut microbiota profiles from 2,764 British, 1,023 Dutch, and 639 Israeli individuals, derive co-occurrence networks between their operational taxonomic units, and detect comparable communities within them. Comparing populations we find that community structure is significantly more similar between datasets than expected by chance. Mapping communities across the datasets, we also show that communities can have similar associations to host phenotypes in different populations. This study shows that the community structure within the gut microbiota is stable across populations, and describes a novel approach that facilitates comparative community-centric microbiome analyses.

Heritable components of the human fecal microbiome are associated with visceral fat.

Obesity and its associated diseases are one of the major causes of death worldwide. The gut microbiota has been identified to have essential regulatory effects on human metabolism and obesity in particular. In a recent study we provided some insights into the link between the gut microbiota (GM) and adiposity, as well as host genetic modulation of these processes. Our results identify novel evidence of association between 6 adiposity phenotypes and faecal microbial operational taxonomic units (OTUs). Accumulation of visceral fat, a key risk factor for cardio-metabolic disease, has the strongest and most pervasive signature on the gut microbiota of the factors we examined. Furthermore, we observe that the adiposity-associated OTUs were classified as heritable and in some cases were also associated with host genetic variation at obesity-associated human candidate genes FHIT, TDRG1 and ELAVL4. This addendum confirms our previously published results in the TwinsUK cohort using a different approach to OTU clustering and multivariate analysis, and discusses further the importance of considering the GM as a complex ecosystem.

Hippurate as a metabolomic marker of gut microbiome diversity: Modulation by diet and relationship to metabolic syndrome.

Reduced gut microbiome diversity is associated with multiple disorders including metabolic syndrome (MetS) features, though metabolomic markers have not been investigated. Our objective was to identify blood metabolite markers of gut microbiome diversity, and explore their relationship with dietary intake and MetS. We examined associations between Shannon diversity and 292 metabolites profiled by the untargeted metabolomics provider Metabolon Inc. in 1529 females from TwinsUK using linear regressions adjusting for confounders and multiple testing (Bonferroni: P < 1.71 × 10-4). We replicated the top results in an independent sample of 420 individuals as well as discordant identical twin pairs and explored associations with self-reported intakes of 20 food groups. Longitudinal changes in circulating levels of the top metabolite, were examined for their association with food intake at baseline and with MetS at endpoint. Five metabolites were associated with microbiome diversity and replicated in the independent sample. Higher intakes of fruit and whole grains were associated with higher levels of hippurate cross-sectionally and longitudinally. An increasing hippurate trend was associated with reduced odds of having MetS (OR: 0.795[0.082]; P = 0.026). These data add further weight to the key role of the microbiome as a potential mediator of the impact of dietary intake on metabolic status and health.

Omega-3 fatty acids correlate with gut microbiome diversity and production of N-carbamylglutamate in middle aged and elderly women.

Omega-3 fatty acids may influence human physiological parameters in part by affecting the gut microbiome. The aim of this study was to investigate the links between omega-3 fatty acids, gut microbiome diversity and composition and faecal metabolomic profiles in middle aged and elderly women. We analysed data from 876 twins with 16S microbiome data and DHA, total omega-3, and other circulating fatty acids. Estimated food intake of omega-3 fatty acids were obtained from food frequency questionnaires. Both total omega-3and DHA serum levels were significantly correlated with microbiome alpha diversity (Shannon index) after adjusting for confounders (DHA Beta(SE) = 0.13(0.04), P = 0.0006 total omega-3: 0.13(0.04), P = 0.001). These associations remained significant after adjusting for dietary fibre intake. We found even stronger associations between DHA and 38 operational taxonomic units (OTUs), the strongest ones being with OTUs from the Lachnospiraceae family (Beta(SE) = 0.13(0.03), P = 8 × 10-7). Some of the associations with gut bacterial OTUs appear to be mediated by the abundance of the faecal metabolite N-carbamylglutamate. Our data indicate a link between omega-3 circulating levels/intake and microbiome composition independent of dietary fibre intake, particularly with bacteria of the Lachnospiraceae family. These data suggest the potential use of omega-3 supplementation to improve the microbiome composition.

Shotgun Metagenomics of 250 Adult Twins Reveals Genetic and Environmental Impacts on the Gut Microbiome.

The gut microbiota has been typically viewed as an environmental factor for human health. Twins are well suited for investigating the concordance of their gut microbiomes and decomposing genetic and environmental influences. However, existing twin studies utilizing metagenomic shotgun sequencing have included only a few samples. Here, we sequenced fecal samples from 250 adult twins in the TwinsUK registry and constructed a comprehensive gut microbial reference gene catalog. We demonstrate heritability of many microbial taxa and functional modules in the gut microbiome, including those associated with diseases. Moreover, we identified 8 million SNPs in the gut microbiome and observe a high similarity in microbiome SNPs between twins that slowly decreases after decades of living apart. The results shed new light on the genetic and environmental influences on the composition and function of the gut microbiome that could relate to risk of complex diseases.

Heritable components of the human fecal microbiome are associated with visceral fat.

BACKGROUND: Variation in the human fecal microbiota has previously been associated with body mass index (BMI). Although obesity is a global health burden, the accumulation of abdominal visceral fat is the specific cardio-metabolic disease risk factor. Here, we explore links between the fecal microbiota and abdominal adiposity using body composition as measured by dual-energy X-ray absorptiometry in a large sample of twins from the TwinsUK cohort, comparing fecal 16S rRNA diversity profiles with six adiposity measures. RESULTS: We profile six adiposity measures in 3666 twins and estimate their heritability, finding novel evidence for strong genetic effects underlying visceral fat and android/gynoid ratio. We confirm the association of lower diversity of the fecal microbiome with obesity and adiposity measures, and then compare the association between fecal microbial composition and the adiposity phenotypes in a discovery subsample of twins. We identify associations between the relative abundances of fecal microbial operational taxonomic units (OTUs) and abdominal adiposity measures. Most of these results involve visceral fat associations, with the strongest associations between visceral fat and Oscillospira members. Using BMI as a surrogate phenotype, we pursue replication in independent samples from three population-based cohorts including American Gut, Flemish Gut Flora Project and the extended TwinsUK cohort. Meta-analyses across the replication samples indicate that 8 OTUs replicate at a stringent threshold across all cohorts, while 49 OTUs achieve nominal significance in at least one replication sample. Heritability analysis of the adiposity-associated microbial OTUs prompted us to assess host genetic-microbe interactions at obesity-associated human candidate loci. We observe significant associations of adiposity-OTU abundances with host genetic variants in the FHIT, TDRG1 and ELAVL4 genes, suggesting a potential role for host genes to mediate the link between the fecal microbiome and obesity. CONCLUSIONS: Our results provide novel insights into the role of the fecal microbiota in cardio-metabolic disease with clear potential for prevention and novel therapies.