Patterns of infant fecal metabolite concentrations and social behavioral development in toddlers.

BACKGROUND: Gut-derived metabolites, products of microbial and host co-metabolism, may inform mechanisms underlying children's neurodevelopment. We investigated whether infant fecal metabolites were related to toddler social behavior. METHODS: Stool samples collected from 6-week-olds (n = 86) and 1-year-olds (n = 209) in the New Hampshire Birth Cohort Study (NHBCS) were analyzed using nuclear magnetic resonance spectroscopy metabolomics. Autism-related behavior in 3-year-olds was assessed by caregivers using the Social Responsiveness Scale (SRS-2). To assess the association between metabolites and SRS-2 scores, we used a traditional single-metabolite approach, quantitative metabolite set enrichment (QEA), and self-organizing maps (SOMs). RESULTS: Using a single-metabolite approach and QEA, no individual fecal metabolite or metabolite set at either age was associated with SRS-2 scores. Using the SOM method, fecal metabolites of six-week-olds organized into four profiles, which were unrelated to SRS-2 scores. In 1-year-olds, one of twelve fecal metabolite profiles was associated with fewer autism-related behaviors, with SRS-2 scores 3.4 (95%CI: -7, 0.2) points lower than the referent group. This profile had higher concentrations of lactate and lower concentrations of short chain fatty acids than the reference. CONCLUSIONS: We uncovered metabolic profiles in infant stool associated with subsequent social behavior, highlighting one potential mechanism by which gut bacteria may influence neurobehavior. IMPACT: Differences in host and microbial metabolism may explain variability in neurobehavioral phenotypes, but prior studies do not have consistent results. We applied three statistical techniques to explore fecal metabolite differences related to social behavior, including self-organizing maps (SOMs), a novel machine learning algorithm. A 1-year-old fecal metabolite pattern characterized by high lactate and low short-chain fatty acid concentrations, identified using SOMs, was associated with social behavior less indicative of autism spectrum disorder. Our findings suggest that social behavior may be related to metabolite profiles and that future studies may uncover novel findings by applying the SOM algorithm.

Maternal-Infant Factors in Relation to Extracellular Vesicle and Particle miRNA in Prenatal Plasma and in Postpartum Human Milk.

MicroRNAs (miRNA) in extracellular vesicles and particles (EVPs) in maternal circulation during pregnancy and in human milk postpartum are hypothesized to facilitate maternal-offspring communication via epigenetic regulation. However, factors influencing maternal EVP miRNA profiles during these two critical developmental windows remain largely unknown. In a pilot study of 54 mother-child dyads in the New Hampshire Birth Cohort Study, we profiled 798 EVP miRNAs, using the NanoString nCounter platform, in paired maternal second-trimester plasma and mature (6-week) milk samples. In adjusted models, total EVP miRNA counts were lower for plasma samples collected in the afternoon compared with the morning (p = 0.024). Infant age at sample collection was inversely associated with total miRNA counts in human milk EVPs (p = 0.040). Milk EVP miRNA counts were also lower among participants who were multiparous after delivery (p = 0.047), had a pre-pregnancy BMI > 25 kg/m2 (p = 0.037), or delivered their baby via cesarean section (p = 0.021). In post hoc analyses, we also identified 22 specific EVP miRNA that were lower among participants who delivered their baby via cesarean section (Q < 0.05). Target genes of delivery mode-associated miRNAs were over-represented in pathways related to satiety signaling in infants (e.g., CCKR signaling) and mammary gland development and lactation (e.g., FGF signaling, EGF receptor signaling). In conclusion, we identified several key factors that may influence maternal EVP miRNA composition during two critical developmental windows, which should be considered in future studies investigating EVP miRNA roles in maternal and child health.

Impact of antibiotics on off-target infant gut microbiota and resistance genes in cohort studies.

BACKGROUND: Young children are frequently exposed to antibiotics, with the potential for collateral consequences to the gut microbiome. The impact of antibiotic exposures to off-target microbes (i.e., bacteria not targeted by treatment) and antibiotic resistance genes (ARGs) is poorly understood. METHODS: We used metagenomic sequencing data from paired stool samples collected prior to antibiotic exposure and at 1 year from over 200 infants and a difference-in-differences approach to assess the relationship between subsequent exposures and the abundance or compositional diversity of microbes and ARGs while adjusting for covariates. RESULTS: By 1 year, the abundance of multiple species and ARGs differed by antibiotic exposure. Compared to infants never exposed to antibiotics, Bacteroides vulgatus relative abundance increased by 1.72% (95% CI: 0.19, 3.24) while Bacteroides fragilis decreased by 1.56% (95% CI: -4.32, 1.21). Bifidobacterium species also exhibited opposing trends. ARGs associated with exposure included class A beta-lactamase gene CfxA6. Among infants attending day care, Escherichia coli and ARG abundance were both positively associated with antibiotic use. CONCLUSION: Novel findings, including the importance of day care attendance, were identified through considering microbiome data at baseline and post-intervention. Thus, our study design and approach have important implications for future studies evaluating the unintended impacts of antibiotics. IMPACT: The impact of antibiotic exposure to off-target microbes and antibiotic resistance genes in the gut is poorly defined. We quantified these impacts in two cohort studies using a difference-in-differences approach. Novel to microbiome studies, we used pre/post-antibiotic data to emulate a randomized controlled trial. Compared to infants unexposed to antibiotics between baseline and 1 year, the relative abundance of multiple off-target species and antibiotic resistance genes was altered. Infants who attended day care and were exposed to antibiotics within the first year had a higher abundance of Escherichia coli and antibiotic resistance genes; a novel finding warranting further investigation.

Contribution of gut bacteria to arsenic metabolism in the first year of life in a prospective birth cohort.

Gut bacteria are at the interface of environmental exposures and their impact on human systems, and may alter host absorption, metabolism, and excretion of toxic chemicals. We investigated whether arsenic-metabolizing bacterial gene pathways related to urinary arsenic concentrations. In the New Hampshire Birth Cohort Study, urine and stool samples were obtained at six weeks (n = 186) and one year (n = 190) of age. Inorganic arsenic (iAs), monomethylarsonic acid (MMA), dimethylarsinic acid (DMA), and arsenobetaine (AsB) were quantified in infant urine samples using high-performance liquid chromatography with inductively coupled plasma mass spectrometry. Total arsenic exposure (tAs) was summarized as Σ(iAs, MMA, DMA) and log2-transformed. Fecal microbial DNA underwent metagenomic sequencing and the relative abundance of bacterial gene pathways were grouped as KEGG Orthologies (KOs) using BioBakery algorithms. Arsenic metabolism KOs with >80% prevalence were log2-transformed and modeled continuously using linear regression, those with <10% were not evaluated and those with 10-80% prevalence were analyzed dichotomously (detect/non-detect) using logistic regression. In the first set of models, tAs was regressed against KO relative abundance or detection adjusting for age at sample collection and child's sex. Effect modification by delivery mode was assessed in stratified models. In the second set of models, the association between the relative abundance/detection of the KOs and arsenic speciation (%iAs, %MMA, %DMA) was quantified with linear regression. Urinary tAs was associated with the increased relative abundance/detection odds of several arsenic-related KOs, including K16509, an arsenate reductase transcriptional regulator, with stronger associations among six-week-olds than one-year-olds. K16509 was also associated with decreased %MMA and increased %DMA at six weeks and one year. Notably, many associations were stronger among operatively-delivered than vaginally-delivered infants. Our findings suggest associations between arsenic-metabolizing bacteria in the infant gut microbiome and urinary arsenic excretion.

The infant gut resistome is associated with E. coli and early-life exposures.

BACKGROUND: The human gut microbiome harbors a collection of bacterial antimicrobial resistance genes (ARGs) known as the resistome. The factors associated with establishment of the resistome in early life are not well understood. We investigated the early-life exposures and taxonomic signatures associated with resistome development over the first year of life in a large, prospective cohort in the United States. Shotgun metagenomic sequencing was used to profile both microbial composition and ARGs in stool samples collected at 6 weeks and 1 year of age from infants enrolled in the New Hampshire Birth Cohort Study. Negative binomial regression and statistical modeling were used to examine infant factors such as sex, delivery mode, feeding method, gestational age, antibiotic exposure, and infant gut microbiome composition in relation to the diversity and relative abundance of ARGs. RESULTS: Metagenomic sequencing was performed on paired samples from 195 full term (at least 37 weeks' gestation) and 15 late preterm (33-36 weeks' gestation) infants. 6-week samples compared to 1-year samples had 4.37 times (95% CI: 3.54-5.39) the rate of harboring ARGs. The majority of ARGs that were at a greater relative abundance at 6 weeks (chi-squared p < 0.01) worked through the mechanism of antibiotic efflux. The overall relative abundance of the resistome was strongly correlated with Proteobacteria (Spearman correlation = 78.9%) and specifically Escherichia coli (62.2%) relative abundance in the gut microbiome. Among infant characteristics, delivery mode was most strongly associated with the diversity and relative abundance of ARGs. Infants born via cesarean delivery had a trend towards a higher risk of harboring unique ARGs [relative risk = 1.12 (95% CI: 0.97-1.29)] as well as having an increased risk for overall ARG relative abundance [relative risk = 1.43 (95% CI: 1.12-1.84)] at 1 year compared to infants born vaginally. CONCLUSIONS: Our findings suggest that the developing infant gut resistome may be alterable by early-life exposures. Establishing the extent to which infant characteristics and early-life exposures impact the resistome can ultimately lead to interventions that decrease the transmission of ARGs and thus the risk of antibiotic resistant infections.

Associations between the gut microbiome and metabolome in early life.

BACKGROUND: The infant intestinal microbiome plays an important role in metabolism and immune development with impacts on lifelong health. The linkage between the taxonomic composition of the microbiome and its metabolic phenotype is undefined and complicated by redundancies in the taxon-function relationship within microbial communities. To inform a more mechanistic understanding of the relationship between the microbiome and health, we performed an integrative statistical and machine learning-based analysis of microbe taxonomic structure and metabolic function in order to characterize the taxa-function relationship in early life. RESULTS: Stool samples collected from infants enrolled in the New Hampshire Birth Cohort Study (NHBCS) at approximately 6-weeks (n = 158) and 12-months (n = 282) of age were profiled using targeted and untargeted nuclear magnetic resonance (NMR) spectroscopy as well as DNA sequencing of the V4-V5 hypervariable region from the bacterial 16S rRNA gene. There was significant inter-omic concordance based on Procrustes analysis (6 weeks: p = 0.056; 12 months: p = 0.001), however this association was no longer significant when accounting for phylogenetic relationships using generalized UniFrac distance metric (6 weeks: p = 0.376; 12 months: p = 0.069). Sparse canonical correlation analysis showed significant correlation, as well as identifying sets of microbe/metabolites driving microbiome-metabolome relatedness. Performance of machine learning models varied across different metabolites, with support vector machines (radial basis function kernel) being the consistently top ranked model. However, predictive R2 values demonstrated poor predictive performance across all models assessed (avg: - 5.06% -- 6 weeks; - 3.7% -- 12 months). Conversely, the Spearman correlation metric was higher (avg: 0.344-6 weeks; 0.265-12 months). This demonstrated that taxonomic relative abundance was not predictive of metabolite concentrations. CONCLUSIONS: Our results suggest a degree of overall association between taxonomic profiles and metabolite concentrations. However, lack of predictive capacity for stool metabolic signatures reflects, in part, the possible role of functional redundancy in defining the taxa-function relationship in early life as well as the bidirectional nature of the microbiome-metabolome association. Our results provide evidence in favor of a multi-omic approach for microbiome studies, especially those focused on health outcomes.

Validation of a novel murine wound model of Acinetobacter baumannii infection.

Patients recovering from traumatic injuries or surgery often require weeks to months of hospitalization, increasing the risk for wound and surgical site infections caused by ESKAPE pathogens, which include A. baumannii (the ESKAPE pathogens are Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species). As new therapies are being developed to counter A. baumannii infections, animal models are also needed to evaluate potential treatments. Here, we present an excisional, murine wound model in which a diminutive inoculum of a clinically relevant, multidrug-resistant A. baumannii isolate can proliferate, form biofilms, and be effectively treated with antibiotics. The model requires a temporary, cyclophosphamide-induced neutropenia to establish an infection that can persist. A 6-mm-diameter, full-thickness wound was created in the skin overlying the thoracic spine, and after the wound bed was inoculated, it was covered with a dressing for 7 days. Uninoculated control wounds healed within 13 days, whereas infected, placebo-treated wounds remained unclosed beyond 21 days. Treated and untreated wounds were assessed with multiple quantitative and qualitative techniques that included gross pathology, weight loss and recovery, wound closure, bacterial burden, 16S rRNA community profiling, histopathology, peptide nucleic acid-fluorescence in situ hybridization, and scanning electron microscopy assessment of biofilms. The range of differences that we are able to identify with these measures in antibiotic- versus placebo-treated animals provides a clear window within which novel antimicrobial therapies can be assessed. The model can be used to evaluate antimicrobials for their ability to reduce specific pathogen loads in wounded tissues and clear biofilms. Ultimately, the mouse model approach allows for highly powered studies and serves as an initial multifaceted in vivo assessment prior to testing in larger animals.

Identification of small molecules inhibiting diguanylate cyclases to control bacterial biofilm development.

Biofilm formation by pathogenic bacteria is an important virulence factor in the development of numerous chronic infections, thereby causing a severe health burden. Many of these infections cannot be resolved, as bacteria in biofilms are resistant to the host's immune defenses and antibiotic therapy. An urgent need for new strategies to treat biofilm-based infections is critically needed. Cyclic di-GMP (c-di-GMP) is a widely conserved second-messenger signal essential for biofilm formation. The absence of this signalling system in higher eukaryotes makes it an attractive target for the development of new anti-biofilm agents. In this study, the results of an in silico pharmacophore-based screen to identify small-molecule inhibitors of diguanylate cyclase (DGC) enzymes that synthesize c-di-GMP are described. Four small molecules, LP 3134, LP 3145, LP 4010 and LP 1062 that antagonize these enzymes and inhibit biofilm formation by Pseudomonas aeruginosa and Acinetobacter baumannii in a continuous-flow system are reported. All four molecules dispersed P. aeruginosa biofilms and inhibited biofilm development on urinary catheters. One molecule dispersed A. baumannii biofilms. Two molecules displayed no toxic effects on eukaryotic cells. These molecules represent the first compounds identified from an in silico screen that are able to inhibit DGC activity to prevent biofilm formation.

Plasma concentrations of multiple oxysterols and risk of colorectal adenomas.

Oxysterols are metabolites of cholesterol that regulate homeostasis of cholesterol, fatty acids, and glucose. These metabolites are generated throughout the body, either enzymatically or from oxidative stress, and are detectable in peripheral circulation. We previously reported that circulating 27-hydroxycholesterol (27-OHC), an endogenous selective estrogen receptor modulator, may be a risk factor for colorectal adenomas. Here, in addition to 27-OHC, we report on four other circulating oxysterols: 25-hydroxycholesterol (25-OHC), 24(S)-hydroxycholesterol (24(S)-OHC), 7ɑ-hydroxycholesterol (7ɑ-OHC), and 4ß-hydroxycholesterol (4ß-OHC). Oxysterol concentrations were measured using liquid chromatography-mass spectrometry from fasting plasma collected at baseline from 1,246 participants of the Vitamin D/Calcium Polyp Prevention Study, a multicenter adenoma chemoprevention trial. To evaluate multiple oxysterols simultaneously, we used both log-linear regression and Bayesian kernel machine regression (BKMR) models developed for analyses of complex mixtures adjusted for potential confounding factors. Higher circulating 7ɑ-OHC was associated with higher adenoma risk (BKMR-based multivariable-adjusted risk ratios, RR, for the 75th vs. 25th percentile, 1.22; 95% credible interval, CI, 1.04-1.42). In contrast, higher circulating 4ß-OHC was associated with lower risk of these polyps (RR, 0.84; 95% CI, 0.71-0.99). The positive association with advanced adenoma risk that we previously reported for circulating 27-OHC persisted when controlling for other oxysterols (RR, 1.26; 95% CI, 0.98-1.62), including among those with advanced adenomas at baseline (RR, 1.75; 95% CI, 1.01-3.06).

Potential to Enhance Large Scale Molecular Assessments of Skin Photoaging through Virtual Inference of Spatial Transcriptomics from Routine Staining.

The advent of spatial transcriptomics technologies has heralded a renaissance in research to advance our understanding of the spatial cellular and transcriptional heterogeneity within tissues. Spatial transcriptomics allows investigation of the interplay between cells, molecular pathways, and the surrounding tissue architecture and can help elucidate developmental trajectories, disease pathogenesis, and various niches in the tumor microenvironment. Photoaging is the histological and molecular skin damage resulting from chronic/acute sun exposure and is a major risk factor for skin cancer. Spatial transcriptomics technologies hold promise for improving the reliability of evaluating photoaging and developing new therapeutics. Challenges to current methods include limited focus on dermal elastosis variations and reliance on self-reported measures, which can introduce subjectivity and inconsistency. Spatial transcriptomics offers an opportunity to assess photoaging objectively and reproducibly in studies of carcinogenesis and discern the effectiveness of therapies that intervene in photoaging and preventing cancer. Evaluation of distinct histological architectures using highly-multiplexed spatial technologies can identify specific cell lineages that have been understudied due to their location beyond the depth of UV penetration. However, the cost and interpatient variability using state-of-the-art assays such as the 10x Genomics Spatial Transcriptomics assays limits the scope and scale of large-scale molecular epidemiologic studies. Here, we investigate the inference of spatial transcriptomics information from routine hematoxylin and eosin-stained (H&E) tissue slides. We employed the Visium CytAssist spatial transcriptomics assay to analyze over 18,000 genes at a 50-micron resolution for four patients from a cohort of 261 skin specimens collected adjacent to surgical resection sites for basal cell and squamous cell keratinocyte tumors. The spatial transcriptomics data was co-registered with 40x resolution whole slide imaging (WSI) information. We developed machine learning models that achieved a macro-averaged median AUC and F1 score of 0.80 and 0.61 and Spearman coefficient of 0.60 in inferring transcriptomic profiles across the slides, and accurately captured biological pathways across various tissue architectures.

Bacterial Modification of the Association Between Arsenic and Autism-Related Social Behavior Scores.

Arsenic is related to neurodevelopmental outcomes and is associated with the composition of the gut microbiome. Data on the modifying role of the microbiome are limited. We probed suggestive relationships between arsenic and social behaviors to quantify the modifying role of the infant gut microbiome. We followed children for whom arsenic concentrations were quantified in 6-week-old toenail clippings. Scores on the Social Responsiveness Scale (SRS-2), which measures autism-related social behaviors, were provided by caregivers when the child was approximately 3 years of age. Metagenomic sequencing was performed on infant stools collected at 6 weeks and 1 year of age. To evaluate modification by the top ten most abundant species and functional pathways, we modeled SRS-2 total T-scores as a function of arsenic concentrations, microbiome features dichotomized at their median, and an interaction between exposure and the microbiome, adjusting for other trace elements and sociodemographic characteristics. As compared to the standardized population (SRS-2 T-scores = 50), participants in our study had lower SRS-2 scores (n = 78, mean = 44, SD = 5).The relative abundances of several functional pathways identified in 6-week stool samples modified the arsenic-SRS-2 association, including the pathways of valine and isoleucine biosynthesis; we observed no association among those with high relative abundance of each pathway [ß = - 0.67 (95% CI - 1.46, 0.12)], and an adverse association [ß = 1.67 (95% CI 0.3, 3.04), pinteraction= 0.05] among infants with low relative abundance. Our findings indicate the infant gut microbiome may alter neurodevelopmental susceptibility to environmental exposures.

Periconceptional and Prenatal Exposure to Metals and Extracellular Vesicle and Particle miRNAs in Human Milk: A Pilot Study.

Human milk is a rich source of microRNAs (miRNAs), which can be transported by extracellular vesicles and particles (EVPs) and are hypothesized to contribute to maternal-offspring communication and child development. Environmental contaminant impacts on EVP miRNAs in human milk are largely unknown. In a pilot study of 54 mother-child pairs from the New Hampshire Birth Cohort Study, we examined relationships between five metals (arsenic, lead, manganese, mercury, and selenium) measured in maternal toenail clippings, reflecting exposures during the periconceptional and prenatal periods, and EVP miRNA levels in human milk. 798 miRNAs were profiled using the NanoString nCounter platform; 200 miRNAs were widely detectable and retained for downstream analyses. Metal-miRNA associations were evaluated using covariate-adjusted robust linear regression models. Arsenic exposure during the periconceptional and prenatal periods was associated with lower total miRNA content in human milk EVPs (PBonferroni < 0.05). When evaluating miRNAs individually, 13 miRNAs were inversely associated with arsenic exposure, two in the periconceptional period and 11 in the prenatal period (PBonferroni < 0.05). Other metal-miRNA associations were not statistically significant after multiple testing correction (PBonferroni ≥ 0.05). Many of the arsenic-associated miRNAs are involved in lactation and have anti-inflammatory properties in the intestine and tumor suppressive functions in breast cells. Our findings raise the possibility that periconceptional and prenatal arsenic exposure may reduce levels of multiple miRNAs in human milk EVPs. However, larger confirmatory studies, which can apply environmental mixture approaches, evaluate potential effect modifiers of these relationships, and examine possible downstream consequences for maternal and child health and breastfeeding outcomes, are needed.

Early-life exposure to per- and polyfluoroalkyl substances and infant gut microbial composition.

Human milk is rich in essential nutrients and immune-activating compounds but is also a source of toxicants including per- and polyfluoroalkyl substances (PFAS). Evidence suggests that immune-related effects of PFAS may, in part, be due to alterations of the microbiome. We aimed to identify the association between milk PFAS exposure and the infant gut microbiome. Methods: PFAS [perfluorooctane sulfonic acid (PFOS) and perfluorooctanoate (PFOA)] were quantified in milk from ~6 weeks postpartum using high-performance liquid chromatography with tandem mass spectrometry. A molar sum (ΣPFAS) was calculated. Caregivers collected infant stool samples at 6 weeks (n = 116) and/or 1 year postpartum (n = 119). Stool DNA underwent metagenomic sequencing. We estimated the association of PFAS with diversity and relative abundances of species with linear regression. Single- and multi-PFAS models adjusted for potential confounders in complete case analyses and with imputed missing covariate data for 6-week and 1-year microbiomes separately. We assessed sensitive populations with stratification. Results: PFOS and PFOA were detected in 94% and 83% of milk samples, respectively. PFOS was associated with increased diversity at 6 weeks among infants fed exclusively human milk [ß = 0.24 per PFOS doubling, (95% CI = 0.03, 0.45), P = 0.03] and born to primiparous mothers [ß = 0.37 (0.06, 0.67), P = 0.02]. Estimates were strongest in multi-PFAS models and among complete cases. ΣPFAS was associated with Bacteroides vulgatus relative abundance at 1 year [(ß = -2.34% per doubling (-3.63, -1.05), FDR q = 0.099]. Conclusions: PFAS may increase infant gut microbiome diversity and alter the relative abundance of biologically relevant bacteria. Additional analyses may identify related health outcomes.

Assessing tobacco smoke exposure in pregnancy from self-report, urinary cotinine and NNAL: a validation study using the New Hampshire Birth Cohort Study.

OBJECTIVES: Accurate assessment of tobacco smoke exposure is key to evaluate its effects. We sought to validate and establish cut-offs for self-reported smoking and secondhand smoke (SHS) exposure during pregnancy using urinary cotinine and 4-(methylnitrosamino)-1-(-3-pyridyl)-1-butanol (NNAL) in a large contemporary prospective study from the USA, with lower smoking prevalence than has previously been evaluated. DESIGN: Prospective birth cohort. SETTING: Pregnancy clinics in New Hampshire and Vermont, USA. PARTICIPANTS: 1396 women enrolled in the New Hampshire Birth Cohort Study with self-reported smoking, urinary cotinine, NNAL and pregnancy outcomes. PRIMARY AND SECONDARY OUTCOME MEASURES: Cut-offs for urinary cotinine and NNAL concentrations were estimated from logistic regression models using Youden's method to predict SHS and active smoking. Cotinine and NNAL were each used as the exposure in separate multifactorial models for pregnancy outcomes. RESULTS: Self-reported maternal smoking was: 72% non-smokers, 5.7% ex-smokers, 6.4% SHS exposure, 6.2% currently smoked, 10% unreported. Cotinine and NNAL levels were low and highly intercorrelated (r=0.91). Geometric mean cotinine, NNAL were 0.99 ng/mL, 0.05 pmol/mL, respectively. Cotinine cut-offs for SHS, current smoking were 1.2 ng/mL and 1.8 ng/mL (area under curve (AUC) 95% CI: 0.52 (0.47 to 0.57), 0.90 (0.85 to 0.94)). NNAL cut-off for current smoking was 0.09 pmol/mL (AUC=0.82 (95% CI 0.77 to 0.87)). Using cotinine and NNAL cut-offs combined gave similar AUC to cotinine alone, 0.87 (95% CI 0.82 to 0.91). Cotinine and NNAL gave almost identical effect estimates when modelling pregnancy outcomes. CONCLUSIONS: In this population, we observed high concordance between self-complete questionnaire smoking data and urinary cotinine and NNAL. With respect to biomarkers, either cotinine or NNAL can be used as a measure of tobacco smoke exposure overall but only cotinine can be used to detect SHS.

Metagenomic analysis reveals associations between salivary microbiota and body composition in early childhood.

Several studies have shown that body mass index is strongly associated with differences in gut microbiota, but the relationship between body weight and oral microbiota is less clear especially in young children. We aimed to evaluate if there is an association between child growth and the saliva microbiome. We hypothesized that associations between growth and the saliva microbiome would be moderate, similarly to the association between growth and the gut microbiome. For 236 toddlers participating in the New Hampshire Birth Cohort Study, we characterized the association between multiple longitudinal anthropometric measures of body height, body weight and body mass. Body Mass Index (BMI) z-scores were calculated, and dual-energy x-ray absorptiometry (DXA) was used to estimate body composition. Shotgun metagenomic sequencing of saliva samples was performed to taxonomically and functionally profile the oral microbiome. We found that within-sample diversity was inversely related to body mass measurements while community composition was not associated. Although the magnitude of associations were small, some taxa were consistently associated with growth and modified by sex. Certain taxa were associated with decreased weight or growth (including Actinomyces odontolyticus and Prevotella melaninogenica) or increased growth (such as Streptococcus mitis and Corynebacterium matruchotii) across anthropometric measures. Further exploration of the functional significance of this relationship will enhance our understanding of the intersection between weight gain, microbiota, and energy metabolism and the potential role of these relationships on the onset of obesity-associated diseases in later life.

Association of demographic and health characteristics with circulating oxysterol concentrations.

BACKGOUND: Circulating oxysterols, cholesterol metabolites with important signaling functions, are increasingly being recognized as candidate biomarkers for several diseases, but associations with demographic and health characteristics remain poorly described. OBJECTIVE: This study aims to characterize associations of major circulating oxysterols with sex, age, race/ethnicity, body mass index (BMI), lifestyle factors, and use of common medications. METHODS: We measured plasma concentrations of 27-hydroxycholesterol (27-OHC), 25-hydroxycholesterol (25-OHC), 24(S)-hydroxycholesterol (24(S)-OHC), 7ɑ-hydroxycholesterol (7ɑ-OHC), and 4ß-hydroxycholesterol (4ß-OHC) from 1,440 participants of a completed clinical trial for the chemoprevention of colorectal adenomas. Adjusted percent difference in means were calculated using linear regression. RESULTS: Women had 18% (95% CI, 14%, 22%) lower 27-OHC and 21% (15%, 27%) higher 4ß-OHC than men. Blacks had 15% (7%, 23%) higher 4ß-OHC than Non-Hispanic Whites, and Asian or Pacific Islanders had 19% (2%, 35%) higher 7ɑ-OHC than Non-Hispanic Whites. Individuals of BMI ≥35 kg/m2 had 33% (25%, 41%) lower 4ß-OHC than those <25 kg/m2. Current smokers had 15% (5%, 24%) higher 7ɑ-OHC than never smokers, and daily alcohol drinkers had 17% (10%, 24%) higher 7ɑ-OHC than never drinkers. Statin use was associated with lower concentrations of all 5 oxysterols. Differences in mean <15% were found for characteristics such as age, total dietary energy intake, physical activity, diabetes, and anti-inflammatory drug use. CONCLUSION: Circulating oxysterols are uniquely associated with multiple demographic and health characteristics.

Circulating 27-hydroxycholesterol and Risk of Colorectal Adenomas and Serrated Polyps.

The oxysterol 27-hydroxycholesterol (27-OHC) is an endogenous selective estrogen receptor modulator implicated in breast cancer etiology. It is unknown whether circulating 27-OHC is associated with colorectal neoplasia risk. Circulating 27-OHC was measured using LC/MS in fasting plasma collected at baseline from participants of the Vitamin D/Calcium Polyp Prevention Study, a completed randomized clinical trial. Participants were between 45 and 75 years old, recently diagnosed with ≥1 colorectal adenoma, and followed for new colorectal polyps during colonoscopic surveillance. Adjusted risk ratios (RR) with 95% confidence intervals (CI) of new colorectal polyps were estimated for quartiles of circulating 27-OHC using log-linear regression for repeated outcomes. Polyp phenotypes included any adenomas, advanced adenomas, hyperplastic polyps, and sessile serrated adenomas/polyps. Circulating 27-OHC was measured at baseline for 1,246 participants. Compared with participants with circulating 27-OHC below the first quartile (<138 ng/mL), those with circulating 27-OHC at or above the fourth quartile (≥201 ng/mL) had 24% higher risk of adenomas (RR, 1.24; 95% CI, 1.05-1.47) and 89% higher risk of advanced adenomas (RR, 1.89; 95% CI, 1.17-3.06). Stronger associations were observed among participants with advanced adenomas at baseline. Circulating 27-OHC was not associated with risk of hyperplastic polyps (RR, 0.90; 95% CI, 0.66-1.22) or sessile serrated adenomas/polyps (RR, 1.02; 95% CI, 0.50-2.07). Circulating 27-OHC may be a risk factor for colorectal adenomas but not serrated polyps. PREVENTION RELEVANCE: This study found that plasma concentration of 27-hydroxycholesterol, a metabolite of cholesterol that regulates lipid metabolism and acts as a selective estrogen receptor modulator, is associated with the risk of developing precursor lesions for colorectal cancer.

Nutrient-toxic element mixtures and the early postnatal gut microbiome in a United States longitudinal birth cohort.

BACKGROUND: The infant microbiome contributes to health status across the lifespan, but environmental factors affecting microbial communities are poorly understood, particularly when toxic and essential elements interact. OBJECTIVE: We aimed to identify the associations between a spectrum of other early-postnatal nutrient or toxic elemental exposures measured and the infant gut microbiome. METHODS: Our analysis included 179 six-week-old infants from the New Hampshire Birth Cohort Study. Eleven elements were measured in infant toenail clippings. The gut microbiome was assessed using 16S rRNA V4-V5 hypervariable region targeted sequencing. Multivariable zero-inflated logistic normal regression (MZILN) was used to model the association between element concentrations and taxon relative abundance. To explore interactive and nonlinear associations between the exposures and specific taxa we employed Bayesian Kernel Machine Regression (BKMR). Effect modification by delivery mode, feeding mode, peripartum antibiotic exposure, and infant sex was assessed with stratified models. RESULTS: We found a negative association between arsenic and microbial diversity in the full population that was accentuated among infants exposed to peripartum antibiotics. Arsenic, cadmium, copper, iron, lead, manganese, nickel, selenium, tin, and zinc were each associated with differences in at least one taxon in the full study population, with most of the related taxa belonging to the Bacteroides and Lactobacillales. In stratified analyses, mercury, in addition to the other elements, was associated with specific taxa. Bifidobacterium, which associated negatively with zinc in MZILN and BKMR models, had a quadratic association with arsenic concentrations. These associations varied with the concentration of the other element. CONCLUSIONS: Early postnatal toxic and nutrient elemental exposures are associated with differences in the infant microbiome. Further research is needed to clarify the whether these alterations are a biomarker of exposure or if they have implications for child and lifelong health.