The composition and metabolic potential of the human small intestinal microbiota within the context of inflammatory bowel disease

BACKGROUND AND AIMS: The human gastrointestinal tract harbours distinct microbial communities essential for health. Little is known about small intestinal communities, despite the small intestine playing a fundamental role in nutrient absorption and host-microbe immune homeostasis. We aimed to explore the small intestine microbial composition and metabolic potential, in the context of inflammatory bowel disease (IBD). METHODS: Metagenomes derived from faecal samples and extensive phenotypes were collected from 57 individuals with an ileostomy or ileoanal pouch, and compared with 1178 general population and 478 IBD faecal metagenomes. Microbiome features were identified using MetaPhAn2 and HUMAnN2, and association analyses were performed using multivariate linear regression. RESULTS: Small intestinal samples had a significantly lower bacterial diversity, compared with the general population and, to a lesser extent, IBD samples. Comparing bacterial composition, small intestinal samples clustered furthest from general population samples and closest to IBD samples with intestinal resections. Veillonella atypica, Streptococcus salivarius and Actinomyces graevenitzii were among the species significantly enriched in the small intestine. Predicted metabolic pathways in the small intestine are predominantly involved in simple carbohydrate and energy metabolism, but also suggest a higher proinflammatory potential. CONCLUSION: We described the bacterial composition and metabolic potential of the small intestinal microbiota. The colonic microbiome of IBD patients, particularly with intestinal resections, showed resemblance to that of the small intestine. Moreover, several features characterising the small intestinal microbiome have been previously associated with IBD. These results highlight the importance of studying the small intestinal microbiota to gain new insight into disease pathogenesis

Patient attitudes towards faecal sampling for gut microbiome studies and clinical care reveal positive engagement and room for improvement

Faecal sample collection is crucial for gut microbiome research and its clinical applications. However, while patients and healthy volunteers are routinely asked to provide stool samples, their attitudes towards sampling remain largely unknown. Here, we investigate the attitudes of 780 Dutch patients, including participants in a large Inflammatory Bowel Disease (IBD) gut microbiome cohort and population controls, in order to identify barriers to sample collection and provide recommendations for gut microbiome researchers and clinicians. We sent questionnaires to 660 IBD patients and 112 patients with other disorders who had previously been approached to participate in gut microbiome studies. We also conducted 478 brief interviews with participants in our general population cohort who had collected stool samples. Statistical analysis of the data was performed using R. 97.4% of respondents reported that they had willingly participated in stool sample collection for gut microbiome research, and most respondents (82.9%) and interviewees (95.6%) indicated willingness to participate again, with their motivations for participating being mainly altruistic (57.0%). Responses indicated that storing stool samples in the home freezer for a prolonged time was the main barrier to participation (52.6%), but clear explanations of the sampling procedures and their purpose increased participant willingness to collect and freeze samples (P = 0.046, P = 0.003). To account for participant concerns, gut microbiome researchers establishing cohorts and clinicians trying new faecal tests should provide clear instructions, explain the rationale behind their protocol, consider providing a small freezer and inform patients about study outcomes. By assessing the attitudes, motives and barriers surrounding participation in faecal sample collection, we provide important information that will contribute to the success of gut microbiome research and its near-future clinical applications

Long-term dietary patterns are associated with pro-inflammatory and anti-inflammatory features of the gut microbiome

Objective The microbiome directly affects the balance of pro-inflammatory and anti-inflammatory responses in the gut. As microbes thrive on dietary substrates, the question arises whether we can nourish an anti-inflammatory gut ecosystem. We aim to unravel interactions between diet, gut microbiota and their functional ability to induce intestinal inflammation. Design We investigated the relation between 173 dietary factors and the microbiome of 1425 individuals spanning four cohorts: Crohn's disease, ulcerative colitis, irritable bowel syndrome and the general population. Shotgun metagenomic sequencing was performed to profile gut microbial composition and function. Dietary intake was assessed through food frequency questionnaires. We performed unsupervised clustering to identify dietary patterns and microbial clusters. Associations between diet and microbial features were explored per cohort, followed by a meta-analysis and heterogeneity estimation. Results We identified 38 associations between dietary patterns and microbial clusters. Moreover, 61 individual foods and nutrients were associated with 61 species and 249 metabolic pathways in the meta-analysis across healthy individuals and patients with IBS, Crohn's disease and UC (false discovery rate Conclusion We identified dietary patterns that consistently correlate with groups of bacteria with shared functional roles in both, health and disease. Moreover, specific foods and nutrients were associated with species known to infer mucosal protection and anti-inflammatory effects. We propose microbial mechanisms through which the diet affects inflammatory responses in the gut as a rationale for future intervention studies

Faecal metabolome and its determinants in inflammatory bowel disease

OBJECTIVE: Inflammatory bowel disease (IBD) is a multifactorial immune-mediated inflammatory disease of the intestine, comprising Crohn's disease and ulcerative colitis. By characterising metabolites in faeces, combined with faecal metagenomics, host genetics and clinical characteristics, we aimed to unravel metabolic alterations in IBD.DESIGN: We measured 1684 different faecal metabolites and 8 short-chain and branched-chain fatty acids in stool samples of 424 patients with IBD and 255 non-IBD controls. Regression analyses were used to compare concentrations of metabolites between cases and controls and determine the relationship between metabolites and each participant's lifestyle, clinical characteristics and gut microbiota composition. Moreover, genome-wide association analysis was conducted on faecal metabolite levels.RESULTS: We identified over 300 molecules that were differentially abundant in the faeces of patients with IBD. The ratio between a sphingolipid and L-urobilin could discriminate between IBD and non-IBD samples (AUC=0.85). We found changes in the bile acid pool in patients with dysbiotic microbial communities and a strong association between faecal metabolome and gut microbiota. For example, the abundance of Ruminococcus gnavus was positively associated with tryptamine levels. In addition, we found 158 associations between metabolites and dietary patterns, and polymorphisms near NAT2 strongly associated with coffee metabolism.CONCLUSION: In this large-scale analysis, we identified alterations in the metabolome of patients with IBD that are independent of commonly overlooked confounders such as diet and surgical history. Considering the influence of the microbiome on faecal metabolites, our results pave the way for future interventions targeting intestinal inflammation.</p

Long-Term Dietary Patterns Are Reflected in the Plasma Inflammatory Proteome of Patients with Inflammatory Bowel Disease

Diet plays an important role in the development and progression of inflammatory bowel disease (IBD, comprising Crohn's disease (CD) and ulcerative colitis (UC)). However, little is known about the extent to which different diets reflect inflammation in IBD beyond measures such as faecal calprotectin or C-reactive protein. In this study, we aimed to unravel associations between dietary patterns and circulating inflammatory proteins in patients with IBD. Plasma concentrations of 73 different inflammation-related proteins were measured in 454 patients with IBD by proximity extension assay (PEA) technology. Food frequency questionnaires (FFQ) were used to assess habitual diet. Principal component analysis (PCA) was performed to extract data-driven dietary patterns. To identify associations between dietary patterns and plasma proteins, we used general linear models adjusting for age, sex, BMI, plasma storage time, smoking, surgical history and medication use. Stratified analyses were performed for IBD type, disease activity and protein intake. A high-sugar diet was strongly inversely associated with fibroblast growth factor-19 (FGF-19) independent of IBD type, disease activity, surgical history and deviance from recommended protein intake (false discovery rate (FDR) &lt; 0.05). Conversely, a Mediterranean-style pattern was associated with higher FGF-19 levels (FDR &lt; 0.05). A pattern characterised by high alcohol and coffee intake was positively associated with CCL11 (eotaxin-1) levels and with lower levels of IL-12B (FDR &lt; 0.05). All results were replicated in CD, whereas only the association with FGF-19 was significant in UC. Our study suggests that dietary habits influence distinct circulating inflammatory proteins implicated in IBD and supports the pro- and anti-inflammatory role of diet. Longitudinal measurements of inflammatory markers, also postprandial, are needed to further elucidate the diet-inflammation relationship

Effect of host genetics on the gut microbiome in 7,738 participants of the Dutch Microbiome Project

Host genetics are known to influence the gut microbiome, yet their role remains poorly understood. To robustly characterize these effects, we performed a genome-wide association study of 207 taxa and 205 pathways representing microbial composition and function in 7,738 participants of the Dutch Microbiome Project. Two robust, study-wide significant (P < 1.89 × 10-10) signals near the LCT and ABO genes were found to be associated with multiple microbial taxa and pathways and were replicated in two independent cohorts. The LCT locus associations seemed modulated by lactose intake, whereas those at ABO could be explained by participant secretor status determined by their FUT2 genotype. Twenty-two other loci showed suggestive evidence (P < 5 × 10-8) of association with microbial taxa and pathways. At a more lenient threshold, the number of loci we identified strongly correlated with trait heritability, suggesting that much larger sample sizes are needed to elucidate the remaining effects of host genetics on the gut microbiome

How the Emotional Content of Discourse Affects Language Comprehension

Emotion effects on cognition have often been reported. However, only few studies investigated emotional effects on subsequent language processing, and in most cases these effects were induced by non-linguistic stimuli such as films, faces, or pictures. Here, we investigated how a paragraph of positive, negative, or neutral emotional valence affects the processing of a subsequent emotionally neutral sentence, which contained either semantic, syntactic, or no violation, respectively, by means of event-related brain potentials (ERPs). Behavioral data revealed strong effects of emotion; error rates and reaction times increased significantly in sentences preceded by a positive paragraph relative to negative and neutral ones. In ERPs, the N400 to semantic violations was not affected by emotion. In the syntactic experiment, however, clear emotion effects were observed on ERPs. The left anterior negativity (LAN) to syntactic violations, which was not visible in the neutral condition, was present in the negative and positive conditions. This is interpreted as reflecting modulatory effects of prior emotions on syntactic processing, which is discussed in the light of three alternative or complementary explanations based on emotion-induced cognitive styles, working memory, and arousal models. The present effects of emotion on the LAN are especially remarkable considering that syntactic processing has often been regarded as encapsulated and autonomous

Predictors of children's secondhand smoke exposure at home: a systematic review and narrative synthesis of the evidence

BACKGROUND: Children's exposure to secondhand smoke (SHS) has been causally linked to a number of childhood morbidities and mortalities. Over 50% of UK children whose parents are smokers are regularly exposed to SHS at home. No previous review has identified the factors associated with children's SHS exposure in the home. AIM: To identify by systematic review, the factors which are associated with children's SHS exposure in the home, determined by parent or child reports and/or biochemically validated measures including cotinine, carbon monoxide or home air particulate matter. METHODS: Electronic searches of MEDLINE, EMBASE, PsychINFO, CINAHL and Web of Knowledge to July 2014, and hand searches of reference lists from publications included in the review were conducted. FINDINGS: Forty one studies were included in the review. Parental smoking, low socioeconomic status and being less educated were all frequently and consistently found to be independently associated with children's SHS exposure in the home. Children whose parents held more negative attitudes towards SHS were less likely to be exposed. Associations were strongest for parental cigarette smoking status; compared to children of non-smokers, those whose mothers or both parents smoked were between two and 13 times more likely to be exposed to SHS. CONCLUSION: Multiple factors are associated with child SHS exposure in the home; the best way to reduce child SHS exposure in the home is for smoking parents to quit. If parents are unable or unwilling to stop smoking, they should instigate smoke-free homes. Interventions targeted towards the socially disadvantaged parents aiming to change attitudes to smoking in the presence of children and providing practical support to help parents smoke outside the home may be beneficial

The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests

Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a "SQLite" relational database or "ASCII" flat file version (at https://doi.org/10.5880/PIK.2020.006/; Reyer et al., 2020). The data policies of the individual contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R package (https://CRAN.R- project.org/package=ProfoundData; Silveyra Gonzalez et al., 2020), which provides basic functions to explore, plot and extract the data for model set-up, calibration and evaluation.Peer reviewe