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Many analytical methods used in gut microbiome research focus on either single bacterial taxa or the whole microbiome, ignoring multibacteria relationships (microbial cliques). We present a novel analytical approach to identify microbial cliques within the gut microbiome of children at 9-11 years associated with prenatal lead (Pb) exposure. Data came from a subset of participants ( n = 123) in the Programming Research in Obesity, Growth, Environment and Social Stressors cohort. Pb concentrations were measured in maternal whole blood from the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the gut microbiome. Using a novel analytical approach, Microbial Co-occurrence Analysis (MiCA), we paired a machine learning algorithm with randomization-based inference to first identify microbial cliques that were predictive of prenatal Pb exposure and then estimate the association between prenatal Pb exposure and microbial clique abundance. With second-trimester Pb exposure, we identified a two-taxa microbial clique that included Bifidobacterium adolescentis and Ruminococcus callidus and a three-taxa clique that also included Prevotella clara . Increasing second-trimester Pb exposure was associated with significantly increased odds of having the two-taxa microbial clique below the median relative abundance (odds ratio (OR) = 1.03, 95% confidence interval (CI) [1.01-1.05]). Using a novel combination of machine learning and causal inference, MiCA identified a significant association between second-trimester Pb exposure and the reduced abundance of a probiotic microbial clique within the gut microbiome in late childhood.

In the United States, adolescent obesity is a growing epidemic associated with maladaptive executive functioning. Likewise, data link the microbiome to obesity. Emerging microbiome research has demonstrated an interconnection between the gut microbiome and the brain, indicating a bidirectional communication system within the gut-microbiome-brain axis in the pathophysiology of obesity. This narrative review identifies and summarizes relevant research connecting adolescent obesity as it relates to three core domains of executive functioning and the contribution of the gut microbiome in the relationship between obesity and executive functions in adolescence. The review suggests that (1) the interconnection between obesity, executive function, and the gut microbiome is a bidirectional connection, and (2) the gut microbiome may mediate the neurobiological pathways between obesity and executive function deficits. The findings of this review provide valuable insights into obesity-associated executive function deficits and elucidate the possible mediation role of the gut microbiome., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Social disparities continue to limit universal access to health care, directly impacting both lifespan and quality of life. Concomitantly, the gut microbiome has been associated with downstream health outcomes including the global rise in antibiotic resistance. However, limited evidence exists examining socioeconomic status (SES) associations with gut microbiome composition. To address this, we collected information on the community-level SES, gut microbiota, and other individual cofactors including colonization by multidrug-resistant organisms (MDROs) in an adult cohort from Wisconsin, USA. We found an association between SES and microbial composition that is mediated by food insecurity. Additionally, we observed a higher prevalence of MDROs isolated from individuals with low diversity microbiomes and low neighborhood SES. Our integrated population-based study considers how the interplay of several social and economic factors combine to influence gut microbial composition while providing a framework for developing future interventions to help mitigate the SES health gap., (© 2023. Springer Nature Limited.)

Studies of the health effects of the microbiome often measure overall associations by using diversity metrics, and individual taxa associations in separate analyses, but do not consider the correlated relationships between taxa in the microbiome. In this study, we applied random subset weighted quantile sum regression with repeated holdouts (WQS RSRH ), a mixture method successfully applied to 'omic data to account for relationships between many predictors, to processed amplicon sequencing data from the Human Microbiome Project. We simulated a binary variable associated with 20 operational taxonomic units (OTUs). WQS RSRH was used to test for the association between the microbiome and the simulated variable, adjusted for sex, and sensitivity and specificity were calculated. The WQS RSRH method was also compared to other standard methods for microbiome analysis. The method was further illustrated using real data from the Growth and Obesity Cohort in Chile to assess the association between the gut microbiome and body mass index. In the analysis with simulated data, WQS RSRH predicted the correct directionality of association between the microbiome and the simulated variable, with an average sensitivity and specificity of 75% and 70%, respectively, in identifying the 20 associated OTUs. WQS RSRH performed better than all other comparison methods. In the illustration analysis of the gut microbiome and obesity, the WQS RSRH analysis identified an inverse association between body mass index and the gut microbe mixture, identifying Bacteroides, Clostridium, Prevotella, and Ruminococcus as important genera in the negative association. The application of WQS RSRH to the microbiome allows for analysis of the mixture effect of all the taxa in the microbiome, while simultaneously identifying the most important to the mixture, and allowing for covariate adjustment. It outperformed other methods when using simulated data, and in analysis with real data found results consistent with other study findings.

Background: Streptococcus pneumoniae is a significant global pathogen that colonises the nasopharynx of healthy children. Pneumococcal conjugate vaccines, which reduce nasopharyngeal colonisation of vaccine-type S. pneumoniae, may have broader effects on the nasopharyngeal microbiota; however, data are limited. In Fiji, nasopharyngeal carriage prevalence of S. pneumoniae and other colonising species differ between the two main ethnic groups. Here, we examined the association between the 7-valent pneumococcal conjugate vaccine (PCV7) and the nasopharyngeal microbiota of children in Fiji, including for each of the two main ethnic groups-indigenous Fijians (iTaukei) and Fijians of Indian descent (FID)., Method: The nasopharyngeal microbiota of 132 Fijian children was examined using nasopharyngeal swabs collected from 12-month-old iTaukei and FID children who were vaccinated (3 doses PCV7) or unvaccinated in infancy as part of a phase II randomised controlled trial. Microbiota composition was determined by sequencing the V4 region of the 16S rRNA gene. Species-specific carriage of S. pneumoniae, Haemophilus influenzae, Moraxella catarrhalis and Staphylococcus aureus was determined using real-time quantitative PCR. Associations between microbiota composition and other host and environmental factors were considered in the analysis., Results: PCV7 had no overall impact on microbial diversity or composition. However, ethnic differences were observed in both diversity and composition with iTaukei children having higher relative abundance of Moraxella (p = 0.004) and Haemophilus (p = 0.004) and lower relative abundance of Staphylococcus (p = 0.026), Dolosigranulum (p = 0.004) and Corynebacterium (p = 0.003) compared with FID children. Further, when we stratified by ethnicity, associations with PCV7 could be detected: vaccinated iTaukei children had a lower relative abundance of Streptococcus and Haemophilus compared with unvaccinated iTaukei children (p = 0.022 and p = 0.043, respectively); and vaccinated FID children had a higher relative abundance of Dolosigranulum compared with unvaccinated FID children (p = 0.037). Children with symptoms of an upper respiratory tract infection (URTI) had a significantly different microbiota composition to children without symptoms. The microbiota composition of iTaukei children without URTI symptoms was most similar to the microbiota composition of FID children with URTI symptoms., Conclusions: Associations between PCV7 and nasopharyngeal microbiota differed within each ethnic group. This study highlights the influence that ethnicity and URTIs have on nasopharyngeal microbiota.