The potential importance of the built-environment microbiome and its impact on human health.

There is increasing evidence that interactions between microbes and their hosts not only play a role in determining health and disease but also in emotions, thought, and behavior. Built environments greatly influence microbiome exposures because of their built-in highly specific microbiomes coproduced with myriad metaorganisms including humans, pets, plants, rodents, and insects. Seemingly static built structures host complex ecologies of microorganisms that are only starting to be mapped. These microbial ecologies of built environments are directly and interdependently affected by social, spatial, and technological norms. Advances in technology have made these organisms visible and forced the scientific community and architects to rethink gene-environment and microbe interactions respectively. Thus, built environment design must consider the microbiome, and research involving host-microbiome interaction must consider the built-environment. This paradigm shift becomes increasingly important as evidence grows that contemporary built environments are steadily reducing the microbial diversity essential for human health, well-being, and resilience while accelerating the symptoms of human chronic diseases including environmental allergies, and other more life-altering diseases. New models of design are required to balance maximizing exposure to microbial diversity while minimizing exposure to human-associated diseases. Sustained trans-disciplinary research across time (evolutionary, historical, and generational) and space (cultural and geographical) is needed to develop experimental design protocols that address multigenerational multispecies health and health equity in built environments.

Antibiotics taken within the first year of life are linked to infant gut microbiome disruption and elevated atopic dermatitis risk.

BACKGROUND: Atopic dermatitis (AD) is the most common chronic inflammatory skin disease in both pediatric and adult populations. The development of AD has been linked to antibiotic usage, which causes perturbation of the microbiome and has been associated with abnormal immune system function. However, imbalances in the gut microbiome itself associated with antibiotic usage have been inconsistently linked to AD. OBJECTIVES: This study aimed to elucidate the timing and specific factors mediating the relationship between systemic (oral or intravenous) antibiotic usage and AD. METHODS: We used statistical modeling and differential analysis to link CHILD Cohort Study participants' history of antibiotic usage and early-life gut microbiome alterations to AD. RESULTS: Here we report that systemic antibiotics during the first year of life, as compared to later, are associated with AD risk (adjusted odds ratio [aOR] = 1.81; 95% CI: 1.28-2.57; P < .001), with an increased number of antibiotic courses corresponding to a dose response-like increased risk of AD risk (1 course: aOR: 1.67; 95% CI: 1.17-2.38; 2 or more courses: aOR: 2.16; 95% CI: 1.30-3.59). Further, we demonstrate that microbiome alterations associated with both AD and systemic antibiotic usage fully mediate the effect of antibiotic usage on the development of AD (ßindirect = 0.072; P < .001). Alterations in the 1-year infant gut microbiome of participants who would later develop AD included increased Tyzzerella nexilis, increased monosaccharide utilization, and parallel decreased Bifidobacterium and Eubacterium spp, and fermentative pathways. CONCLUSIONS: These findings indicate that early-life antibiotic usage, especially in the first year of life, modulates key gut microbiome components that may be used as markers to predict and possibly prevent the development of AD.

Early prediction of pediatric asthma in the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort using machine learning.

BACKGROUND: Early identification of children at risk of asthma can have significant clinical implications for effective intervention and treatment. This study aims to disentangle the relative timing and importance of early markers of asthma. METHODS: Using the CHILD Cohort Study, 132 variables measured in 1754 multi-ethnic children were included in the analysis for asthma prediction. Data up to 4 years of age was used in multiple machine learning models to predict physician-diagnosed asthma at age 5 years. Both predictive performance and variable importance was assessed in these models. RESULTS: Early-life data (≤1 year) has limited predictive ability for physician-diagnosed asthma at age 5 years (area under the precision-recall curve (AUPRC) < 0.35). The earliest reliable prediction of asthma is achieved at age 3 years, (area under the receiver-operator curve (AUROC) > 0.90) and (AUPRC > 0.80). Maternal asthma, antibiotic exposure, and lower respiratory tract infections remained highly predictive throughout childhood. Wheezing status and atopy are the most important predictors of early childhood asthma from among the factors included in this study. CONCLUSIONS: Childhood asthma is predictable from non-biological measurements from the age of 3 years, primarily using parental asthma and patient history of wheezing, atopy, antibiotic exposure, and lower respiratory tract infections. IMPACT: Machine learning models can predict physician-diagnosed asthma in early childhood (AUROC > 0.90 and AUPRC > 0.80) using ≥3 years of non-biological and non-genetic information, whereas prediction with the same patient information available before 1 year of age is challenging. Wheezing, atopy, antibiotic exposure, lower respiratory tract infections, and the child's mother having asthma were the strongest early markers of 5-year asthma diagnosis, suggesting an opportunity for earlier diagnosis and intervention and focused assessment of patients at risk for asthma, with an evolving risk stratification over time.

Examining psychosocial pathways to explain the link between breastfeeding practices and child behaviour in a longitudinal cohort.

OBJECTIVE: Breastfeeding is associated with reduced postpartum depression, stronger parent-child relationships, and fewer behavioral disorders in early childhood. We tested the mediating roles of postpartum depression and parent-child relationship in the association between breastfeeding practices and child behavior. STUDY DESIGN: We used standardized questionnaire data from a subset of the CHILD Cohort Study (n = 1,573) to measure postpartum depression at 6 months, 1 year and 2 years, parent-child relationship 1 year and 2 years, and child behavior at 5 years using the Child Behavior Checklist (range 0-100). Breastfeeding practices were measured at 3 months (none, partial, some expressed, all direct at the breast), 6 months (none, partial, exclusive), 12 months, and 24 months (no, yes). Confounders included birth factors, maternal characteristics, and socioeconomic status. RESULTS: Breast milk feeding at 3 or 6 months was associated with - 1.13 (95% CI: -2.19-0.07) to -2.14 (95% CI: -3.46, -0.81) lower (better) child behavior scores. Reduced postpartum depression at 6 months mediated between 11.5% and 16.6% of the relationship between exclusive breast milk feeding at 3 months and better child behavior scores. Together, reduced postpartum depression at 1 year and reduced parent-child dysfunction at 2 years mediated between 21.9% and 32.1% of the relationship between breastfeeding at 12 months and better child behavior scores. CONCLUSION: Postpartum depression and parent-child relationship quality partially mediate the relationship between breastfeeding practices and child behavior. Breastfeeding, as well as efforts to support parental mental health and parent-child relationships, may help to improve child behavior.

The hygiene hypothesis, the COVID pandemic, and consequences for the human microbiome.

The COVID-19 pandemic has the potential to affect the human microbiome in infected and uninfected individuals, having a substantial impact on human health over the long term. This pandemic intersects with a decades-long decline in microbial diversity and ancestral microbes due to hygiene, antibiotics, and urban living (the hygiene hypothesis). High-risk groups succumbing to COVID-19 include those with preexisting conditions, such as diabetes and obesity, which are also associated with microbiome abnormalities. Current pandemic control measures and practices will have broad, uneven, and potentially long-term effects for the human microbiome across the planet, given the implementation of physical separation, extensive hygiene, travel barriers, and other measures that influence overall microbial loss and inability for reinoculation. Although much remains uncertain or unknown about the virus and its consequences, implementing pandemic control practices could significantly affect the microbiome. In this Perspective, we explore many facets of COVID-19-induced societal changes and their possible effects on the microbiome, and discuss current and future challenges regarding the interplay between this pandemic and the microbiome. Recent recognition of the microbiome's influence on human health makes it critical to consider both how the microbiome, shaped by biosocial processes, affects susceptibility to the coronavirus and, conversely, how COVID-19 disease and prevention measures may affect the microbiome. This knowledge may prove key in prevention and treatment, and long-term biological and social outcomes of this pandemic.

The human gut microbiome and health inequities.

Individuals who are minoritized as a result of race, sexual identity, gender, or socioeconomic status experience a higher prevalence of many diseases. Understanding the biological processes that cause and maintain these socially driven health inequities is essential for addressing them. The gut microbiome is strongly shaped by host environments and affects host metabolic, immune, and neuroendocrine functions, making it an important pathway by which differences in experiences caused by social, political, and economic forces could contribute to health inequities. Nevertheless, few studies have directly integrated the gut microbiome into investigations of health inequities. Here, we argue that accounting for host-gut microbe interactions will improve understanding and management of health inequities, and that health policy must begin to consider the microbiome as an important pathway linking environments to population health.

Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies.

BACKGROUND: Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence. METHODS AND FINDINGS: We conducted a two-stage individual participant data (IPD) meta-analysis using data from 253,810 mother-child dyads from 16 general population-based cohort studies in Europe (Denmark, Finland, France, Italy, Norway, Portugal, Spain, the Netherlands, United Kingdom), North America (Canada), and Australasia (Australia) to estimate the association of GA with body mass index (BMI) and overweight (including obesity) adjusted for the following maternal characteristics as potential confounders: education, height, prepregnancy BMI, ethnic background, parity, smoking during pregnancy, age at child's birth, gestational diabetes and hypertension, and preeclampsia. Pregnancy and birth cohort studies from the LifeCycle and the EUCAN-Connect projects were invited and were eligible for inclusion if they had information on GA and minimum one measurement of BMI between infancy and adolescence. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). GA was positively associated with BMI in the first decade of life, with the greatest increase in mean BMI z-score during early infancy (0.02, 95% confidence interval (CI): 0.00; 0.05, p < 0.05) per week of increase in GA, while in adolescence, preterm individuals reached similar levels of BMI (0.00, 95% CI: -0.01; 0.01, p 0.9) as term counterparts. The association between GA and overweight revealed a similar pattern of association with an increase in odds ratio (OR) of overweight from late infancy through mid-childhood (OR 1.01 to 1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with the risk of overweight (OR 0.98 [95% CI: 0.97; 1.00], p 0.1) per week of increase in GA. Although based on only four cohorts (n = 32,089) that reached the age of adolescence, data suggest that individuals born very preterm may be at increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08], p < 0.05) compared with term counterparts. Findings were consistent across cohorts and sensitivity analyses despite considerable heterogeneity in cohort characteristics. However, residual confounding may be a limitation in this study, while findings may be less generalisable to settings in low- and middle-income countries. CONCLUSIONS: This study based on data from infancy through adolescence from 16 cohort studies found that GA may be important for body size in infancy, but the strength of association attenuates consistently with age. By adolescence, preterm individuals have on average a similar mean BMI to peers born at term.

Correction: Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies.

[This corrects the article DOI: 10.1371/journal.pmed.1004036.].

Early sex-dependent differences in metabolic profiles of overweight and adiposity in young children: a cross-sectional analysis.

BACKGROUND: Childhood obesity is a global health concern and can lead to lifetime cardiometabolic disease. New advances in metabolomics can provide biochemical insights into the early development of obesity, so we aimed to characterize serum metabolites associated with overweight and adiposity in early childhood and to stratify associations by sex. METHODS: Nontargeted metabolite profiling was conducted in the Canadian CHILD birth cohort (discovery cohort) at age 5 years (n = 900) by multisegment injection-capillary electrophoresis-mass spectrometry. Clinical outcome was defined using novel combined measures of overweight (WHO-standardized body mass index ≥ 85th percentile) and/or adiposity (waist circumference ≥ 90th percentile). Associations between circulating metabolites and child overweight/adiposity (binary and continuous outcomes) were determined by multivariable linear and logistic regression, adjusting for covariates and false discovery rate, and by subsequent sex-stratified analysis. Replication was assessed in an independent replication cohort called FAMILY at age 5 years (n = 456). RESULTS: In the discovery cohort, each standard deviation (SD) increment of branched-chain and aromatic amino acids, glutamic acid, threonine, and oxoproline was associated with 20-28% increased odds of overweight/adiposity, whereas each SD increment of the glutamine/glutamic acid ratio was associated with 20% decreased odds. All associations were significant in females but not in males in sex-stratified analyses, except for oxoproline that was not significant in either subgroup. Similar outcomes were confirmed in the replication cohort, where associations of aromatic amino acids, leucine, glutamic acid, and the glutamine/glutamic acid ratio with childhood overweight/adiposity were independently replicated. CONCLUSIONS: Our findings show the utility of combining measures of both overweight and adiposity in young children. Childhood overweight/adiposity at age 5 years has a specific serum metabolic phenotype, with the profile being more prominent in females compared to males.

The Relationship Between Diet, Gut Microbiota, and Serum Metabolome of South Asian Infants at 1 Year.

BACKGROUND: Diet is known to affect the gut microbiota and the serum metabolome in adults, but this has not been fully explored in infants. Infancy is an important developmental period that may influence a person's long-term health. Infant development can be affected by diet, which also interacts with the developing gut microbiota. OBJECTIVES: This study aimed to explore the associations between diet, the gut microbiota, and the serum metabolome of 1-y-old infants with the overarching goal of identifying serum biomarkers of diet and/or the gut microbiota. METHODS: We derived dietary patterns of 1-y-old infants (n = 182) participating in the Canadian South Asian Birth Cohort (START) study. We compared gut microbiota α-diversity and ß-diversity and taxa relative abundance from 16S rRNA gene profiles with dietary patterns (PERMANOVA, Envfit) and investigated diet-serum metabolite associations using a multivariate analysis (partial least squares-discriminant analysis) and univariate analysis (t test). We explored the effect of nondietary factors on diet-serum metabolite relationships by incorporating diet, the gut microbiota, and maternal, perinatal, and infant characteristics in a multivariable forward stepwise regression. We replicated this analysis in White European infants, from the CHILD Cohort Study (n = 81). RESULTS: A dietary pattern characterized by formula consumption and negatively associated with breastfeeding most strongly predicted variation in the gut microbiota (R2 = 0.109) and serum metabolome (R2 = 0.547). Breastfed participants showed higher abundance of microbes from the genera Bifidobacterium (3.29 log2-fold) and Lactobacillus (7.93 log2-fold) and higher median concentrations of the metabolites S-methylcysteine (1.38 µM) and tryptophan betaine (0.43 µM) than nonbreastfed participants. Formula consuming infants showed higher median concentrations of branched-chain/aromatic amino acids (average 48.3 µM) than non-formula-consuming infants. CONCLUSIONS: Formula consumption and breastfeeding most strongly predicted the serum metabolites of 1-y-old infants, even when the gut microbiota, solid food consumption, and other covariates were considered.

Human milk: From complex tailored nutrition to bioactive impact on child cognition and behavior.

Human milk is a highly complex liquid food tailor-made to match an infant's needs. Beyond documented positive effects of breastfeeding on infant and maternal health, there is increasing evidence that milk constituents also impact child neurodevelopment. Non-nutrient milk bioactives would contribute to the (long-term) development of child cognition and behavior, a process termed 'Lactocrine Programming'. In this review we discuss the current state of the field on human milk composition and its links with child cognitive and behavioral development. To promote state-of-the-art methodologies and designs that facilitate data pooling and meta-analytic endeavors, we present detailed recommendations and best practices for future studies. Finally, we determine important scientific gaps that need to be filled to advance the field, and discuss innovative directions for future research. Unveiling the mechanisms underlying the links between human milk and child cognition and behavior will deepen our understanding of the broad functions of this complex liquid food, as well as provide necessary information for designing future interventions.

Wheeze trajectories: Determinants and outcomes in the CHILD Cohort Study.

BACKGROUND: Wheezing in early life is associated with asthma in adulthood; however, the determinants of wheezing trajectories and their associations with asthma and lung function in childhood remain poorly understood. OBJECTIVE: In the CHILD Cohort Study, we aimed to identify wheezing trajectories and examine the associations between these trajectories, risk factors, and clinical outcomes at age 5 years. METHODS: Wheeze data were collected at 8 time points from 3 months to 5 years of age. We used group-based trajectory models to derive wheeze trajectories among 3154 children. Associations with risk factors and clinical outcomes were analyzed by weighted regression models. RESULTS: We identified 4 trajectories: a never/infrequent trajectory, transient wheeze, intermediate-onset (preschool) wheeze, and persistent wheeze. Higher body mass index was a common risk factor for all wheeze trajectories compared with that in the never/infrequent group. The unique predictors for specific wheeze trajectories included male sex, lower respiratory tract infections, and day care attendance for transient wheeze; paternal history of asthma, atopic sensitization, and child genetic risk score of asthma for intermediate wheeze; and maternal asthma for persistent wheeze. Blood eosinophil counts were higher in children with the intermediate wheeze trajectory than in those children with the other trajectories at the ages of 1 and 5 years. All wheeze trajectories were associated with decreased lung function and increased risk of asthma at age 5 years. CONCLUSIONS: We identified 4 distinct trajectories in children from 3 months to 5 years of age, reflecting different phenotypes of early childhood wheeze. These trajectories were characterized by different biologic and physiologic traits and risk factors.

DNA methylation changes in cord blood and the developmental origins of health and disease - a systematic review and replication study.

BACKGROUND: Environmental exposures in utero which modify DNA methylation may have a long-lasting impact on health and disease in offspring. We aimed to identify and replicate previously published genomic loci where DNA methylation changes are attributable to in utero exposures in the NutriGen birth cohort studies Alliance. METHODS: We reviewed the literature to identify differentially methylated sites of newborn DNA which are associated with the following five traits of interest maternal diabetes, pre-pregnancy body mass index (BMI), diet during pregnancy, smoking, and gestational age. We then attempted to replicate these published associations in the Canadian Healthy Infant Longitudinal Development (CHILD) and the South Asian birth cohort (START) cord blood epigenome-wide data. RESULTS: We screened 68 full-text articles and identified a total of 17 cord blood epigenome-wide association studies (EWAS) of the traits of interest. Out of the 290 CpG sites reported, 19 were identified in more than one study; all of them associated with maternal smoking. In CHILD and START EWAS, thousands of sites associated with gestational age were identified and maintained significance after correction for multiple testing. In CHILD, there was differential methylation observed for 8 of the published maternal smoking sites. No other traits tested (i.e., folate levels, gestational diabetes, birthweight) replicated in the CHILD or START cohorts. CONCLUSIONS: Maternal smoking during pregnancy and gestational age are strongly associated with differential methylation in offspring cord blood, as assessed in the EWAS literature and our birth cohorts. There are a limited number of reported methylation sites associated in more than two independent studies related to pregnancy. Additional large studies of diverse populations with fine phenotyping are needed to produce robust epigenome-wide data in order to further elucidate the effect of intrauterine exposures on the infants' methylome.

From Birth to Overweight and Atopic Disease: Multiple and Common Pathways of the Infant Gut Microbiome.

BACKGROUND & AIMS: Few studies, even those with cohort designs, test the mediating effects of infant gut microbes and metabolites on the onset of disease. We undertook such a study. METHODS: Using structural equation modeling path analysis, we tested directional relationships between first pregnancy, birth mode, prolonged labor and breastfeeding; infant gut microbiota, metabolites, and IgA; and childhood body mass index and atopy in 1667 infants. RESULTS: After both cesarean birth and prolonged labor with a first pregnancy, a higher Enterobacteriaceae/Bacteroidaceae ratio at 3 months was the dominant path to overweight; higher Enterobacteriaceae/Bacteroidaceae ratios and Clostridioides difficile colonization at 12 months were the main pathway to atopic sensitization. Depletion of Bifidobacterium after prolonged labor was a secondary pathway to overweight. Influenced by C difficile colonization at 3 months, metabolites propionate and formate were secondary pathways to child outcomes, with a key finding that formate was at the intersection of several paths. CONCLUSIONS: Pathways from cesarean section and first pregnancy to child overweight and atopy share many common mediators of the infant gut microbiome, notably C difficile colonization.

Longitudinal body mass index trajectories at preschool age: children with rapid growth have differential composition of the gut microbiota in the first year of life.

BACKGROUND/OBJECTIVE: The steep rise in childhood obesity has emerged as a worldwide public health problem. The first 4 years of life are a critical window where long-term developmental patterns of body mass index (BMI) are established and a critical period for microbiota maturation. Understanding how the early-life microbiota relate to preschool growth may be useful for identifying preventive interventions for childhood obesity. We aim to investigate whether longitudinal shifts within the bacterial community between 3 months and 1 year of life are associated with preschool BMI z-score trajectories. METHODS: BMI trajectories from birth to 5 years of age were identified using group-based trajectory modeling in 3059 children. Their association with familial and environmental factors were analyzed. Infant gut microbiota at 3 months and 1 year was defined by 16S RNA sequencing and changes in diversity and composition within each BMIz trajectory were analyzed. RESULTS: Four BMIz trajectories were identified: low stable, normative, high stable, and rapid growth. Infants in the rapid growth trajectory were less likely to have been breastfed, and gained less microbiota diversity in the first year of life. Relative abundance of Akkermansia increased with age in children with stable growth, but decreased in those with rapid growth, abundance of Ruminococcus and Clostridium at 1 year were elevated in children with rapid growth. Children who were breastfed at 6 months had increased levels of Sutterella, and decreased levels of Ruminococcus and Clostridium. CONCLUSION: This study provides new insights into the relationship between the gut microbiota in infancy and patterns of growth in a cohort of preschool Canadian children. We highlight that rapid growth since birth is associated with bacteria shown in animal models to have a causative role in weight gain. Our findings support a novel avenue of research targeted on tangible interventions to reduce childhood obesity.

Lung clearance index predicts persistence of preschool wheeze.

BACKGROUND: The lung clearance index (LCI) is a measure of pulmonary function. Variable feasibility (50->80%) in preschool children has been reported. There are limited studies exploring its relationship to respiratory symptoms and how it predicts persistent wheeze. We aimed to assess the association with respiratory symptoms in preschool-aged children with LCI and determine its utility in predicting persistent wheeze. METHODS: LCI was measured in a subcohort of the CHILD Cohort Study at age 3 years using SF6  multiple breath washout test mass spectrometry. Respiratory symptom phenotypes at age 3 were derived from children's respiratory symptoms reported by their parents. Responses were used to categorize children into 4 symptom groups: recurrent wheeze (3RW), recurrent cough (3RC), infrequent symptoms (IS), and no current symptoms (NCS). At age 5 years, these children were seen by a specialist clinician and assessed for persistent wheeze (PW). RESULTS: At age 3 years, 69% (234/340) had feasible LCI. Excluding two children with missing data, 232 participants were categorized as follows: 33 (14%) 3RW; 28 (12%) 3RC; 17 (7%) IS; and 154 (66%) NCS. LCI z-score at age 3 years was highest in children with 3RW compared to 3RC (mean (SD): 1.14 (1.56) vs. 0.09 (0.95), p < .01), IS (mean (SD): -0.14 (0.59), p < .01), and NCS (mean (SD): -0.08 (1.06), p < .01). LCI z-score at age 3 was predictive of persistent wheeze at age 5 (PW) (AUROC: 0.87). CONCLUSIONS: LCI at age 3 was strongly associated with recurrent wheeze at age 3, and predictive of its persistence to age 5.

Development and Validation of SDBeasy Score as a Predictor of Behavioral Outcomes in Childhood.

Rationale: There are limited tools to identify which children are at greatest risk for developing sleep-disordered breathing (SDB)-associated behavioral morbidity.Objectives: To examine associations between age of onset and duration of parent-reported symptoms of SDB and behavioral problems at the age of 5 years.Methods: Data were collected and analyses were completed for participants in the CHILD (Canadian Healthy Infant Longitudinal Development) cohort at the Edmonton and Toronto sites. We generated an SDBeasy score on the basis of the age of onset and duration of SDB symptoms as reported by parents completing the Pediatric Sleep Questionnaire. Using CHILD-Edmonton data, we completed multivariate linear regression to determine whether the SDBeasy score was associated with behavioral problems at the age 5 years of age as assessed by using the Child Behavior Checklist (CBCL). We then validated the SDBeasy score using CHILD-Toronto data.Measurements and Main Results: At the 5-year visit, 581 of 716 (81%) CHILD-Edmonton participants still enrolled had CBCL data. Of the 581 children with data, 77% (446 of 581) had an SDBeasy score of 0 (never had SDB symptoms), whereas 20 of 581 children (3.4%) had persistent SDB symptoms from infancy through 5 years of age (SDBeasy score of 24). Children had a 0.35-point-higher CBCL total behavioral score at 5 years for each 1-point increase in their SDBeasy score (95% confidence interval, 0.24-0. 5; P < 0.01). We found consistent results among CHILD-Toronto participants; children had a 0.26-point-higher CBCL total behavioral score at 5 years for each 1-point increase in their SDBeasy score (95% confidence interval, 0.08-0.44; P = 0.005).Conclusions: The SDBeasy score, based on the Pediatric Sleep Questionnaire, enables identification of children with higher behavioral-problem scores.

Maternal body mass index, offspring body mass index, and blood pressure at 18 years: a causal mediation analysis.

OBJECTIVE: Understanding the natural history of hypertension is key to identifying prevention strategies. Previous work suggests that in utero exposures and offspring anthropometrics may play a role. This study examined the relationship between maternal pre-pregnancy body mass index (BMI) and the mediating role of childhood and adolescent BMI on offspring blood pressure at 18 years. METHODS: We performed multivariable regression and causal mediation analyses within 3217 mother - offspring pairs from the Avon Longitudinal Study of Parents and Children prospective birth cohort. The main exposure was maternal pre-pregnancy BMI, and the outcome was offspring blood pressure at 18 years of age categorized as normal or elevated. Latent trajectory analysis was used to quantify the mediator, offspring BMI trajectories, derived from multiple measurements throughout childhood and adolescence. Mediation analyses were repeated using current offspring BMI at 18 years as a continuous variable. RESULTS: Multivariable logistic regression revealed that for every 1 unit increase in maternal BMI, the risk of elevated blood pressure at 18 years of age increased by 5% (aOR: 1.05, 95% CI: 1.03-1.07; p < 0.001). The strength of this association was reduced after adjusting for offspring BMI trajectory (aOR: 1.03, 95% CI: 1.00-1.05; p = 0.017) and eliminated after adjusting for offspring BMI at 18 years (aOR: 1.00; 95% CI: 0.98-1.03; p = 0.70). Causal mediation analysis confirmed offspring BMI at 18 years as a mediator, where BMI trajectory accounted for 46% of the total effect of maternal BMI on elevated offspring blood pressure and current BMI account for nearly the entire effect. CONCLUSIONS: Maternal pre-pregnancy BMI is associated with an increased risk of elevated blood pressure in offspring at 18 years of age although it appears to be entirely mediated by offspring BMI.

Breastfeeding and the developmental origins of mucosal immunity: how human milk shapes the innate and adaptive mucosal immune systems.

PURPOSE OF REVIEW: Breastfeeding provides passive immunity while the neonatal immune system matures, and may also protect against chronic immune-mediated conditions long after weaning. This review summarizes current knowledge and new discoveries about human milk and mucosal immunity. RECENT FINDINGS: New data suggest that certain microbes in maternal milk may seed and shape the infant gut microbiota, which play a key role in regulating gut barrier integrity and training the developing immune system. Human milk oligosaccharides, best known for their prebiotic functions, have now been shown to directly modulate gene expression in mast and goblet cells in the gastrointestinal tract. Epidemiologic data show a reduced risk of peanut sensitization among infants breastfed by peanut-consuming mothers, suggesting a role for milk-borne food antigens in tolerance development. Cross-fostering experiments in mice suggest the soluble Toll-like receptor 2, found in human milk, may be critical in this process. Finally, interest in human milk antibodies surged during the pandemic with the identification of neutralizing severe acute respiratory syndrome coronavirus 2 antibodies in maternal milk following both natural infection and vaccination. SUMMARY: Human milk provides critical immune protection and stimulation to breastfed infants. Understanding the underlying mechanisms could identify new therapeutic targets and strategies for disease prevention across the lifespan.

Sex-specific associations of human milk long-chain polyunsaturated fatty acids and infant allergic conditions.

BACKGROUND: Polyunsaturated fatty acids (PUFAs) may influence immune development. We examined the association of PUFAs in human milk with food sensitization and atopic dermatitis among breastfed infants. METHODS: In a selected subgroup of 1109 mother-infant dyads from the CHILD Cohort Study, human milk was analyzed by gas-liquid chromatography to quantify PUFAs including arachidonic acid (ARA) and docosahexaenoic acid (DHA). At 1 year of age, food sensitization was determined by skin-prick testing for egg, peanut, cow's milk, and soybean, and atopic dermatitis was diagnosed by pediatricians. Logistic regression analyses controlled for breastfeeding exclusivity, family history of atopy, and other potential confounders. RESULTS: Overall, 184 infants (17%) were sensitized to one or more food allergens and 160 (14%) had atopic dermatitis. Sex-specific associations were observed between these conditions and milk PUFAs. Girls receiving human milk with lower proportions of DHA had lower odds of food sensitization (aOR 0.35; 95% CI 0.12, 0.99 for lowest vs highest quintile), and a clear dose-dependent association was observed for the ARA/DHA ratio (aOR 2.98; 95% CI 1.10, 8.06 for lowest vs highest quintile). These associations were not seen in boys. Similar sex-specific tendencies were observed for atopic dermatitis. CONCLUSIONS: Human milk PUFA proportions and their ratios are associated with infant atopic conditions in a sex-specific manner. In female infants, a higher ratio of ARA/DHA may reduce the risk of food sensitization and atopic dermatitis. Further research is needed to determine the underlying mechanisms and clinical relevance of this sex-specific association.