Fecal microbiota is associated with extraintestinal manifestations in inflammatory bowel disease.

INTRODUCTION: A large proportion of patients with inflammatory bowel disease (IBD) experience IBD-related inflammatory conditions outside of the gastrointestinal tract, termed extraintestinal manifestations (EIMs) which further decreases quality of life and, in extreme cases, can be life threatening. The pathogenesis of EIMs remains unknown, and although gut microbiota alterations are a well-known characteristic of patients with IBD, its relationship with EIMs remains sparsely investigated. This study aimed to compare the gut microbiota of patients with IBD with and without EIMs. METHODS: A total of 131 Danish patients with IBD were included in the study, of whom 86 had a history of EIMs (IBD-EIM) and 45 did not (IBD-C). Stool samples underwent 16S rRNA sequencing. Amplicon sequence variants (ASVs) were mapped to the Silva database. Diversity indices and distance matrices were compared between IBD-EIM and IBD-C. Differentially abundant ASVs were identified using a custom multiple model statistical analysis approach, and modules of co-associated bacteria were identified using sparse correlations for compositional data (SparCC) and related to patient EIM status. RESULTS: Patients with IBD and EIMs exhibited increased disease activity, body mass index, increased fecal calprotectin levels and circulating monocytes and neutrophils. Microbiologically, IBD-EIM exhibited lower fecal microbial diversity than IBD-C (Mann-Whitney's test, p = .01) and distinct fecal microbiota composition (permutational multivariate analysis of variance; weighted UniFrac, R2 = 0.018, p = .01). A total of 26 ASVs exhibited differential relative abundances between IBD-EIM and IBD-C, including decreased Agathobacter and Blautia and increased Eggerthella lenta in the IBD-EIM group. SparCC analysis identified 27 bacterial co-association modules, three of which were negatively related to EIM (logistic regression, p < .05) and included important health-associated bacteria, such as Agathobacter and Faecalibacterium. CONCLUSIONS: The fecal microbiota in IBD patients with EIMs is distinct from that in IBD patients without EIM and could be important for EIM pathogenesis.

Alteration in the gut microbiome is associated with changes in bone metabolism after laparoscopic sleeve gastrectomy.

Laparoscopic sleeve gastrectomy (LSG), the most common bariatric surgical procedure, leads to durable weight loss and improves obesity-related comorbidities. However, it induces abnormalities in bone metabolism. One unexplored potential contributor is the gut microbiome, which influences bone metabolism and is altered after surgery. We characterized the relationship between the gut microbiome and skeletal health in severe obesity and after LSG. In a prospective cohort study, 23 adults with severe obesity underwent skeletal health assessment and stool collection preoperatively and 6 mo after LSG. Gut microbial diversity and composition were characterized using 16S rRNA gene sequencing, and fecal concentrations of short-chain fatty acids (SCFA) were measured with LC-MS/MS. Spearman's correlations and PERMANOVA analyses were applied to assess relationships between the gut microbiome and bone health measures including serum bone turnover markers (C-terminal telopeptide of type 1 collagen [CTx] and procollagen type 1 N-terminal propeptide [P1NP]), areal BMD, intestinal calcium absorption, and calciotropic hormones. Six months after LSG, CTx and P1NP increased (by median 188% and 61%, P < .01) and femoral neck BMD decreased (mean -3.3%, P < .01). Concurrently, there was a decrease in relative abundance of the phylum Firmicutes. Although there were no change in overall microbial diversity or fecal SCFA concentrations after LSG, those with greater within-subject change in gut community microbial composition (ß-diversity) postoperatively had greater increases in P1NP level (ρ = 0.48, P = .02) and greater bone loss at the femoral neck (ρ = -0.43, P = .04). In addition, within-participant shifts in microbial richness/evenness (α-diversity) were associated with changes in IGF-1 levels (ρ = 0.56, P < .01). The lower the postoperative fecal butyrate concentration, the lower the IGF-1 level (ρ = 0.43, P = .04). Meanwhile, the larger the decrease in butyrate concentration, the higher the postoperative CTx (ρ = -0.43, P = .04). These findings suggest that LSG-induced gut microbiome alteration may influence skeletal outcomes postoperatively, and microbial influences on butyrate formation and IGF-1 are possible mechanisms.

Laparoscopic sleeve gastrectomy (LSG), the most common bariatric surgical procedure, is a highly effective treatment for obesity because it produces dramatic weight loss and improves obesity-related medical conditions. However, it also results in abnormalities in bone metabolism. It is important to understand how LSG affects the skeleton, so that bone loss after surgery might be prevented. We studied adult men and women before and 6 mo after LSG, and we explored the relationship between the altered gut bacteria and bone metabolism changes. We found that: Those with greater shifts in their gut bacterial composition had more bone loss.Butyrate, a metabolite produced by gut bacteria from fermentation of dietary fiber, was associated with less bone breakdown and higher IGF-1 level (a bone-building hormone). We conclude that changes in the gut bacteria may contribute to the negative skeletal impact of LSG and reduced butyrate production by the gut bacteria leading to lower IGF-1 levels is a possible mechanism.

Early-life nasal microbiota dynamics relate to longitudinal respiratory phenotypes in urban children.

BACKGROUND: Five distinct respiratory phenotypes based on latent classes of longitudinal patterns of wheezing, allergic sensitization. and pulmonary function measured in urban children from ages from 0 to 7 years have previously been described. OBJECTIVE: Our aim was to determine whether distinct respiratory phenotypes are associated with early-life upper respiratory microbiota development and environmental microbial exposures. METHODS: Microbiota profiling was performed using 16S ribosomal RNA-based sequencing of nasal samples collected at age 12 months (n = 120) or age 36 months (n = 142) and paired house dust samples collected at 3 months (12-month, n = 73; 36-month, n = 90) from all 4 centers in the Urban Environment and Childhood Asthma (URECA) cohort. RESULTS: In these high-risk urban children, nasal microbiota increased in diversity between ages 12 and 36 months (ß = 2.04; P = .006). Age-related changes in microbiota evenness differed significantly by respiratory phenotypes (interaction P = .0007), increasing most in the transient wheeze group. At age 12 months, respiratory illness (R2 = 0.055; P = .0001) and dominant bacterial genus (R2 = 0.59; P = .0001) explained variance in nasal microbiota composition, and enrichment of Moraxella and Haemophilus members was associated with both transient and high-wheeze respiratory phenotypes. By age 36 months, nasal microbiota was significantly associated with respiratory phenotypes (R2 = 0.019; P = .0376), and Moraxella-dominated microbiota was associated specifically with atopy-associated phenotypes. Analysis of paired house dust and nasal samples indicated that 12 month olds with low wheeze and atopy incidence exhibited the largest number of shared bacterial taxa with their environment. CONCLUSION: Nasal microbiota development over the course of early childhood and composition at age 3 years are associated with longitudinal respiratory phenotypes. These data provide evidence supporting an early-life window of airway microbiota development that is influenced by environmental microbial exposures in infancy and associates with wheeze- and atopy-associated respiratory phenotypes through age 7 years.

Short-chain fatty acid producers in the gut are associated with pediatric multiple sclerosis onset.

OBJECTIVE: The relationship between multiple sclerosis and the gut microbiome has been supported by animal models in which commensal microbes are required for the development of experimental autoimmune encephalomyelitis. However, observational study findings in humans have only occasionally converged when comparing multiple sclerosis cases and controls which may in part reflect confounding by comorbidities and disease duration. The study of microbiome in pediatric-onset multiple sclerosis offers unique opportunities as it is closer to biological disease onset and minimizes confounding by comorbidities and environmental exposures. METHODS: A multicenter case-control study in which 35 pediatric-onset multiple sclerosis cases were 1:1 matched to healthy controls on age, sex, self-reported race, ethnicity, and recruiting site. Linear mixed effects models, weighted correlation network analyses, and PICRUSt2 were used to identify microbial co-occurrence networks and for predicting functional abundances based on marker gene sequences. RESULTS: Two microbial co-occurrence networks (one reaching significance after adjustment for multiple comparisons; q < 0.2) were identified, suggesting interdependent bacterial taxa that exhibited association with disease status. Both networks indicated a potentially protective effect of higher relative abundance of bacteria observed in these clusters. Functional predictions from the significant network suggested a contribution of short-chain fatty acid producers through anaerobic fermentation pathways in healthy controls. Consistent family-level findings from an independent Canadian-US study (19 case/control pairs) included Ruminococaccaeae and Lachnospiraceae (p < 0.05). Macronutrient intake was not significantly different between cases and controls, minimizing the potential for dietary confounding. INTERPRETATION: Our results suggest that short-chain fatty acid producers may be important contributors to multiple sclerosis onset.

Heritable vaginal bacteria influence immune tolerance and relate to early-life markers of allergic sensitization in infancy.

Maternal asthma status, prenatal exposures, and infant gut microbiota perturbation are associated with heightened risk of atopy and asthma risk in childhood, observations hypothetically linked by intergenerational microbial transmission. Using maternal vaginal (n = 184) and paired infant stool (n = 172) samples, we identify four compositionally and functionally distinct Lactobacillus-dominated vaginal microbiota clusters (VCs) that relate to prenatal maternal health and exposures and infant serum immunoglobulin E (IgE) status at 1 year. Variance in bacteria shared between mother and infant pairs relate to VCs, maternal allergy/asthma status, and infant IgE levels. Heritable bacterial gene pathways associated with infant IgE include fatty acid synthesis and histamine and tryptophan degradation. In vitro, vertically transmitted Lactobacillus jensenii strains induce immunosuppressive phenotypes on human antigen-presenting cells. Murine supplementation with L. jensenii reduces lung eosinophils, neutrophilic expansion, and the proportion of interleukin-4 (IL-4)+ CD4+ T cells. Thus, bacterial and atopy heritability are intimately linked, suggesting a microbial component of intergenerational disease transmission.

The Microbiome as a Gateway to Prevention of Allergic Disease Development.

Allergic diseases exclusively affect tissues that face environmental challenges and harbor endogenous bacterial microbiota. The microbes inhabiting the affected tissues may not be mere bystanders in this process but actively affect the risk of allergic sensitization, disease development, and exacerbation or abatement of symptoms. Experimental evidence provides several plausible means by which the human microbiota could influence the development of allergic diseases including, but not limited to, effects on antigen presentation and induction of tolerance and allergen permeation by endorsing or disrupting epithelial barrier integrity. Epidemiological evidence attests to the significance of age-appropriate, nonpathogenic microbiota development in skin, gastrointestinal tract, and airways for protection against allergic disease development. Thus, there exist potential targets for preventive actions either in the prenatal or postnatal period. These could include maternal dietary interventions, antibiotic stewardship for both the mother and infant, reducing elective cesarean deliveries, and understanding barriers to breastfeeding and timing of food diversification. In here, we will review the current understanding and evidence of allergy-associated human microbiota patterns, their role in the development of allergic diseases, and how we could harness these associations to our benefit against allergies.

Seasonal airway microbiome and transcriptome interactions promote childhood asthma exacerbations.

BACKGROUND: Seasonal variation in respiratory illnesses and exacerbations in pediatric populations with asthma is well described, though whether upper airway microbes play season-specific roles in these events is unknown. OBJECTIVE: We hypothesized that nasal microbiota composition is seasonally dynamic and that discrete microbe-host interactions modify risk of asthma exacerbation in a season-specific manner. METHODS: Repeated nasal samples from children with exacerbation-prone asthma collected during periods of respiratory health (baseline; n = 181 samples) or first captured respiratory illness (n = 97) across all seasons, underwent bacterial (16S ribosomal RNA gene) and fungal (internal transcribed spacer region 2) biomarker sequencing. Virus detection was performed by multiplex PCR. Paired nasal transcriptome data were examined for seasonal dynamics and integrative analyses. RESULTS: Upper airway bacterial and fungal microbiota and rhinovirus detection exhibited significant seasonal dynamics. In seasonally adjusted analysis, variation in both baseline and respiratory illness microbiota related to subsequent exacerbation. Specifically, in the fall, when respiratory illness and exacerbation events were most frequent, several Moraxella and Haemophilus members were enriched both in virus-positive respiratory illnesses and those that progressed to exacerbations. The abundance of 2 discrete bacterial networks, characteristically comprising either Streptococcus or Staphylococcus, exhibited opposing interactions with an exacerbation-associated SMAD3 nasal epithelial transcriptional module to significantly increase the odds of subsequent exacerbation (odds ratio = 14.7, 95% confidence interval = 1.50-144, P = .02; odds ratio = 39.17, 95% confidence interval = 2.44-626, P = .008, respectively). CONCLUSIONS: Upper airway microbiomes covary with season and with seasonal trends in respiratory illnesses and asthma exacerbations. Seasonally adjusted analyses reveal specific bacteria-host interactions that significantly increase risk of asthma exacerbation in these children.

Moraxella-dominated pediatric nasopharyngeal microbiota associate with upper respiratory infection and sinusitis.

BACKGROUND: Distinct bacterial upper airway microbiota structures have been described in pediatric populations, and relate to risk of respiratory viral infection and, exacerbations of asthma. We hypothesized that distinct nasopharyngeal (NP) microbiota structures exist in pediatric populations, relate to environmental exposures and modify risk of acute sinusitis or upper respiratory infection (URI) in children. METHODS: Bacterial 16S rRNA profiles from nasopharyngeal swabs (n = 354) collected longitudinally over a one-year period from 58 children, aged four to seven years, were analyzed and correlated with environmental variables, URI, and sinusitis outcomes. RESULTS: Variance in nasopharyngeal microbiota composition significantly related to clinical outcomes, participant characteristics and environmental exposures including dominant bacterial genus, season, daycare attendance and tobacco exposure. Four distinct nasopharyngeal microbiota structures (Cluster I-IV) were evident and differed with respect to URI and sinusitis outcomes. These clusters were characteristically either dominated by Moraxella with sparse underlying taxa (Cluster I), comprised of a non-dominated, diverse microbiota (Cluster II), dominated by Alloiococcus/Corynebacterium (Cluster III), or by Haemophilus (Cluster IV). Cluster I was associated with increased risk of URI and sinusitis (RR = 1.18, p = 0.046; RR = 1.25, p = 0.009, respectively) in the population studied. CONCLUSION: In a pediatric population, URI and sinusitis associate with the presence of Moraxella-dominated NP microbiota.