Sequencing-based fine-mapping and in silico functional characterization of the 10q24.32 arsenic metabolism efficiency locus across multiple arsenic-exposed populations.

Inorganic arsenic is highly toxic and carcinogenic to humans. Exposed individuals vary in their ability to metabolize arsenic, and variability in arsenic metabolism efficiency (AME) is associated with risks of arsenic-related toxicities. Inherited genetic variation in the 10q24.32 region, near the arsenic methyltransferase (AS3MT) gene, is associated with urine-based measures of AME in multiple arsenic-exposed populations. To identify potential causal variants in this region, we applied fine mapping approaches to targeted sequencing data generated for exposed individuals from Bangladeshi, American Indian, and European American populations (n = 2,357, 557, and 648 respectively). We identified three independent association signals for Bangladeshis, two for American Indians, and one for European Americans. The size of the confidence sets for each signal varied from 4 to 85 variants. There was one signal shared across all three populations, represented by the same SNP in American Indians and European Americans (rs191177668) and in strong linkage disequilibrium (LD) with a lead SNP in Bangladesh (rs145537350). Beyond this shared signal, differences in LD patterns, minor allele frequency (MAF) (e.g., rs12573221 ~13% in Bangladesh ~0.2% among American Indians), and/or heterogeneity in effect sizes across populations likely contributed to the apparent population specificity of the additional identified signals. One of our potential causal variants influences AS3MT expression and nearby DNA methylation in numerous GTEx tissue types (with rs4919690 as a likely causal variant). Several SNPs in our confidence sets overlap transcription factor binding sites and cis-regulatory elements (from ENCODE). Taken together, our analyses reveal multiple potential causal variants in the 10q24.32 region influencing AME, including a variant shared across populations, and elucidate potential biological mechanisms underlying the impact of genetic variation on AME.

Nonmetastatic Axillary Lymph Nodes Have Distinct Morphology and Immunophenotype in Obese Patients with Breast Cancer at Risk for Metastasis.

Obese patients with breast cancer have worse outcomes than their normal weight counterparts, with a 50% to 80% increased rate of axillary nodal metastasis. Recent studies suggest a link between increased lymph node adipose tissue and breast cancer nodal metastasis. Further investigation into potential mechanisms underlying this link may reveal potential prognostic utility of fat-enlarged lymph nodes in patients with breast cancer. This study used a deep learning model to identify morphologic differences in nonmetastatic axillary nodes between obese, node-positive, and node-negative patients with breast cancer. The model was developed using nested cross-validation on 180 cases and achieved an area under the receiver operator characteristic curve of 0.67 in differentiating patients using hematoxylin and eosin-stained whole slide images. The morphologic analysis of the predictive regions showed an increased average adipocyte size (P = 0.004), increased white space between lymphocytes (P < 0.0001), and increased red blood cells (P < 0.001) in nonmetastatic lymph nodes of node-positive patients. Preliminary immunohistochemistry analysis on a subset of 30 patients showed a trend of decreased CD3 expression and increased leptin expression in fat-replaced axillary lymph nodes of obese, node-positive patients. These findings suggest a novel direction to further investigate the interaction between lymph node adiposity, lymphatic dysfunction, and breast cancer nodal metastases, highlighting a possible prognostic tool for obese patients with breast cancer.

Metabolomic data presents challenges for epidemiological meta-analysis: a case study of childhood body mass index from the ECHO consortium.

INTRODUCTION: Meta-analyses across diverse independent studies provide improved confidence in results. However, within the context of metabolomic epidemiology, meta-analysis investigations are complicated by differences in study design, data acquisition, and other factors that may impact reproducibility. OBJECTIVE: The objective of this study was to identify maternal blood metabolites during pregnancy (> 24 gestational weeks) related to offspring body mass index (BMI) at age two years through a meta-analysis framework. METHODS: We used adjusted linear regression summary statistics from three cohorts (total N = 1012 mother-child pairs) participating in the NIH Environmental influences on Child Health Outcomes (ECHO) Program. We applied a random-effects meta-analysis framework to regression results and adjusted by false discovery rate (FDR) using the Benjamini-Hochberg procedure. RESULTS: Only 20 metabolites were detected in all three cohorts, with an additional 127 metabolites detected in two of three cohorts. Of these 147, 6 maternal metabolites were nominally associated (P < 0.05) with offspring BMI z-scores at age 2 years in a meta-analytic framework including at least two studies: arabinose (Coefmeta = 0.40 [95% CI 0.10,0.70], Pmeta = 9.7 × 10-3), guanidinoacetate (Coefmeta = - 0.28 [- 0.54, - 0.02], Pmeta = 0.033), 3-ureidopropionate (Coefmeta = 0.22 [0.017,0.41], Pmeta = 0.033), 1-methylhistidine (Coefmeta = - 0.18 [- 0.33, - 0.04], Pmeta = 0.011), serine (Coefmeta = - 0.18 [- 0.36, - 0.01], Pmeta = 0.034), and lysine (Coefmeta = - 0.16 [- 0.32, - 0.01], Pmeta = 0.044). No associations were robust to multiple testing correction. CONCLUSIONS: Despite including three cohorts with large sample sizes (N > 100), we failed to identify significant metabolite associations after FDR correction. Our investigation demonstrates difficulties in applying epidemiological meta-analysis to clinical metabolomics, emphasizes challenges to reproducibility, and highlights the need for standardized best practices in metabolomic epidemiology.

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.

Airborne Lead Exposure and Childhood Cognition: The Environmental Influences on Child Health Outcomes (ECHO) Cohort (2003-2022).

Objectives. To examine whether a previously reported association between airborne lead exposure and children's cognitive function replicates across a geographically diverse sample of the United States. Methods. Residential addresses of children (< 5 years) were spatially joined to the Risk-Screening Environmental Indicators model of relative airborne lead toxicity. Cognitive outcomes for children younger than 8 years were available for 1629 children with IQ data and 1476 with measures of executive function (EF; inhibitory control, cognitive flexibility). We used generalized linear models using generalized estimating equations to examine the associations of lead, scaled by interquartile range (IQR), accounting for individual- and area-level confounders. Results. An IQR increase in airborne lead was associated with a 0.74-point lower mean IQ score (b = -0.74; 95% confidence interval = -1.00, -0.48). The association between lead and EF was nonlinear and was modeled with a knot at the 97.5th percentile of lead in our sample. Lead was significantly associated with lower mean inhibitory control but not with cognitive flexibility. This effect was stronger among males for both IQ and inhibitory control. Conclusions. Early-life exposure to airborne lead is associated with lower cognitive functioning. (Am J Public Health. 2024;114(3):309-318. https://doi.org/10.2105/AJPH.2023.307519).

Fruits and vegetables intake and bladder cancer risk: a pooled analysis from 11 case-control studies in the BLadder cancer Epidemiology and Nutritional Determinants (BLEND) consortium.

PURPOSE: High consumption of fruits and vegetables decrease the risk of bladder cancer (BC). The evidence of specific fruits and vegetables and the BC risk is still limited. METHODS: Fruit and vegetable consumptions in relation to BC risk was examined by pooling individual participant data from case-control studies. Unconditional logistic regression was used to estimate study-specific odds ratio's (ORs) with 95% confidence intervals (CIs) and combined using a random-effects model for intakes of total fruits, total vegetables, and subgroups of fruits and vegetables. RESULTS: A total of 11 case-control studies were included, comprising 5637 BC cases and 10,504 controls. Overall, participants with the highest intakes versus the lowest intakes of fruits in total (OR 0.79; 95% CI 0.68-0.91), citrus fruits (OR 0.81; 95% CI 0.65-0.98), pome fruits (OR 0.76; 95% CI 0.65-0.87), and tropical fruits (OR 0.84; 95% CI 0.73-0.94) reduced the BC risk. Greater consumption of vegetables in total, and specifically shoot vegetables, was associated with decreased BC risk (OR 0.82; 95% CI 0.68-0.96 and OR 0.87; 95% CI 0.78-0.96, respectively). Substantial heterogeneity was observed for the associations between citrus fruits and total vegetables and BC risk. CONCLUSION: This comprehensive study provides compelling evidence that the consumption of fruits overall, citrus fruits, pome fruits and tropical fruits reduce the BC risk. Besides, evidence was found for an inverse association between total vegetables and shoot vegetables intake.

Fish intake and mercury exposure in young children.

Fish consumption is one of the main sources of mercury (Hg) exposure, but few studies have examined Hg exposure from fish consumption among children. This study aimed to assess the frequency of fish intake and associations with Hg and other element concentrations among 700 three-year-old children from the New Hampshire Birth Cohort Study. Usual fish intake was derived from a validated food frequency questionnaire (Block Questionnaire for ages 2-7) and toenail element concentrations were determined using ICP-MS. Multiple linear regression analysis was used to assess the association between fish intake and toenail element concentrations. A mixture analysis, using Weighted quantile sum (WQS) regression, was used to estimate the relative contribution of fish consumption to element exposures. Twenty-three percent of children were reported to consume at least one fish meal/week on average during the previous 6 months. In adjusted linear regression models, children with any type of fish consumption versus no consumption had 108% (95% confidence interval (CI: 68%, 153%)) higher toenail Hg concentrations. To a lesser extent, children consuming "other fish (not fried) including tuna" and "fried fish or fish sticks" had 120% (95% CI: 82%, 164%), and 23% (95% CI: 2%, 51%) higher toenail concentrations, respectively, than those consuming no fish. Using WQS regression, Hg was the element most strongly related to fish consumption. Fish intake among young children was related to Hg exposure even at low levels of consumption. Future studies will need to determine the health consequences of this exposure.

Deciduous teeth from the New Hampshire birth cohort study: Early life environmental and dietary predictors of dentin elements.

BACKGROUND: Sparse research exists on predictors of element concentrations measured in deciduous teeth. OBJECTIVE: To estimate associations between maternal/child characteristics, elements measured in home tap water during pregnancy and element concentrations in the dentin of shed deciduous teeth. METHODS: Our analysis included 152 pregnant person-infant dyads followed from the second trimester through the end of the first postnatal year from the New Hampshire Birth Cohort Study. During pregnancy and early infancy, we collected dietary and sociodemographic information via surveys, measured elements in home tap water, and later collected naturally exfoliated teeth from child participants. We measured longitudinal deposition of elements in dentin using LA-ICP-MS. Multivariable linear mixed models were used to estimate associations between predictors and dentin element concentrations. RESULTS: We measured 12 elements in dentin including those previously reported (Ba, Mn, Pb, Sr, Zn) and less frequently reported (Al, As, Cd, Cu, Hg, Li, and W). A doubling of Pb or Sr concentrations in water was associated with higher dentin Pb or Sr respectively in prenatally formed [9% (95%CI: 3%, 15%); 3% (1%, 6%)] and postnatally formed [10% (2%, 19%); 6% (2%, 10%)] dentin. Formula feeding from birth to 6 weeks or 6 weeks to 4 months was associated with higher element concentrations in postnatal dentin within the given time period as compared to exclusive human milk feeding: Sr: 6 weeks: 61% (36%, 90%) and 4 months: 85% (54%, 121%); Ba: 6 weeks: 35% (3.3%, 77%) and 4 months: 42% (10%, 83%); and Li: 6 weeks: 61% (33%, 95%) and 4 months: 58% (31%, 90%). SIGNIFICANCE: These findings offer insights into predictors of dentin elements and potential confounders in exposure-health outcome relationships during critical developmental periods.

Demographic and health characteristics associated with fish and n-3 fatty acid supplement intake during pregnancy: results from pregnancy cohorts in the ECHO programme.

OBJECTIVE: n-3 fatty acid consumption during pregnancy is recommended for optimal pregnancy outcomes and offspring health. We examined characteristics associated with self-reported fish or n-3 supplement intake. DESIGN: Pooled pregnancy cohort studies. SETTING: Cohorts participating in the Environmental influences on Child Health Outcomes (ECHO) consortium with births from 1999 to 2020. PARTICIPANTS: A total of 10 800 pregnant women in twenty-three cohorts with food frequency data on fish consumption; 12 646 from thirty-five cohorts with information on supplement use. RESULTS: Overall, 24·6 % reported consuming fish never or less than once per month, 40·1 % less than once a week, 22·1 % 1-2 times per week and 13·2 % more than twice per week. The relative risk (RR) of ever (v. never) consuming fish was higher in participants who were older (1·14, 95 % CI 1·10, 1·18 for 35-40 v. <29 years), were other than non-Hispanic White (1·13, 95 % CI 1·08, 1·18 for non-Hispanic Black; 1·05, 95 % CI 1·01, 1·10 for non-Hispanic Asian; 1·06, 95 % CI 1·02, 1·10 for Hispanic) or used tobacco (1·04, 95 % CI 1·01, 1·08). The RR was lower in those with overweight v. healthy weight (0·97, 95 % CI 0·95, 1·0). Only 16·2 % reported n-3 supplement use, which was more common among individuals with a higher age and education, a lower BMI, and fish consumption (RR 1·5, 95 % CI 1·23, 1·82 for twice-weekly v. never). CONCLUSIONS: One-quarter of participants in this large nationwide dataset rarely or never consumed fish during pregnancy, and n-3 supplement use was uncommon, even among those who did not consume fish.

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.

The Environmental Influences on Child Health Outcomes (ECHO)-Wide Cohort.

The Environmental Influences on Child Health Outcomes (ECHO)-Wide Cohort Study (EWC), a collaborative research design comprising 69 cohorts in 31 consortia, was funded by the National Institutes of Health (NIH) in 2016 to improve children's health in the United States. The EWC harmonizes extant data and collects new data using a standardized protocol, the ECHO-Wide Cohort Data Collection Protocol (EWCP). EWCP visits occur at least once per life stage, but the frequency and timing of the visits vary across cohorts. As of March 4, 2022, the EWC cohorts contributed data from 60,553 children and consented 29,622 children for new EWCP data and biospecimen collection. The median (interquartile range) age of EWCP-enrolled children was 7.5 years (3.7-11.1). Surveys, interviews, standardized examinations, laboratory analyses, and medical record abstraction are used to obtain information in 5 main outcome areas: pre-, peri-, and postnatal outcomes; neurodevelopment; obesity; airways; and positive health. Exposures include factors at the level of place (e.g., air pollution, neighborhood socioeconomic status), family (e.g., parental mental health), and individuals (e.g., diet, genomics).

Information enhanced model selection for Gaussian graphical model with application to metabolomic data.

In light of the low signal-to-noise nature of many large biological data sets, we propose a novel method to learn the structure of association networks using Gaussian graphical models combined with prior knowledge. Our strategy includes two parts. In the first part, we propose a model selection criterion called structural Bayesian information criterion, in which the prior structure is modeled and incorporated into Bayesian information criterion. It is shown that the popular extended Bayesian information criterion is a special case of structural Bayesian information criterion. In the second part, we propose a two-step algorithm to construct the candidate model pool. The algorithm is data-driven and the prior structure is embedded into the candidate model automatically. Theoretical investigation shows that under some mild conditions structural Bayesian information criterion is a consistent model selection criterion for high-dimensional Gaussian graphical model. Simulation studies validate the superiority of the proposed algorithm over the existing ones and show the robustness to the model misspecification. Application to relative concentration data from infant feces collected from subjects enrolled in a large molecular epidemiological cohort study validates that metabolic pathway involvement is a statistically significant factor for the conditional dependence between metabolites. Furthermore, new relationships among metabolites are discovered which can not be identified by the conventional methods of pathway analysis. Some of them have been widely recognized in biological literature.

Prenatal Exposure to Per- and Polyfluoroalkyl Substances and Childhood Autism-related Outcomes.

BACKGROUND: Epidemiologic evidence linking prenatal exposure to per- and polyfluoroalkyl substances (PFAS) with altered neurodevelopment is inconclusive, and few large studies have focused on autism-related outcomes. We investigated whether blood concentrations of PFAS in pregnancy are associated with child autism-related outcomes. METHODS: We included 10 cohorts from the National Institutes of Health (NIH)-funded Environmental influences on Child Health Outcomes (ECHO) program (n = 1,429). We measured 14 PFAS analytes in maternal blood collected during pregnancy; eight analytes met detection criteria for analysis. We assessed quantitative autism-related traits in children via parent report on the Social Responsiveness Scale (SRS). In multivariable linear models, we examined relationships of each PFAS (natural log-transformed) with SRS scores. We further modeled PFAS as a complex mixture using Bayesian methods and examined modification of these relationships by child sex. RESULTS: Most PFAS in maternal blood were not associated with child SRS T-scores. Perfluorononanoic acid (PFNA) showed the strongest and most consistent association: each 1-unit increase in ln-transformed PFNA was associated with greater autism-related traits (adjusted ß [95% confidence interval (CI)] = 1.5 [-0.1, 3.0]). The summed mixture, which included six PFAS detected in >70% of participants, was not associated with SRS T-scores (adjusted ß [95% highest posterior density interval] = 0.7 [-1.4, 3.0]). We did not observe consistent evidence of sex differences. CONCLUSIONS: Prenatal blood concentrations of PFNA may be associated with modest increases in child autism-related traits. Future work should continue to examine the relationship between exposures to both legacy and emerging PFAS and additional dimensional, quantitative measures of childhood autism-related outcomes.

Impact of sedentary behavior and emotional support on prenatal psychological distress and birth outcomes during the COVID-19 pandemic.

Abstract. BACKGROUND: Studies have reported mixed findings regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on pregnant women and birth outcomes. This study used a quasi-experimental design to account for potential confounding by sociodemographic characteristics. METHODS: Data were drawn from 16 prenatal cohorts participating in the Environmental influences on Child Health Outcomes (ECHO) program. Women exposed to the pandemic (delivered between 12 March 2020 and 30 May 2021) (n = 501) were propensity-score matched on maternal age, race and ethnicity, and child assigned sex at birth with 501 women who delivered before 11 March 2020. Participants reported on perceived stress, depressive symptoms, sedentary behavior, and emotional support during pregnancy. Infant gestational age (GA) at birth and birthweight were gathered from medical record abstraction or maternal report. RESULTS: After adjusting for propensity matching and covariates (maternal education, public assistance, employment status, prepregnancy body mass index), results showed a small effect of pandemic exposure on shorter GA at birth, but no effect on birthweight adjusted for GA. Women who were pregnant during the pandemic reported higher levels of prenatal stress and depressive symptoms, but neither mediated the association between pandemic exposure and GA. Sedentary behavior and emotional support were each associated with prenatal stress and depressive symptoms in opposite directions, but no moderation effects were revealed. CONCLUSIONS: There was no strong evidence for an association between pandemic exposure and adverse birth outcomes. Furthermore, results highlight the importance of reducing maternal sedentary behavior and encouraging emotional support for optimizing maternal health regardless of pandemic conditions.

A prospective study of the infant gut microbiome in relation to vaccine response.

BACKGROUND: The establishment of the gut microbiome plays a key symbiotic role in the developing immune system; however, its influence on vaccine response is yet uncertain. We prospectively investigated the composition and diversity of the early-life gut microbiome in relation to infant antibody response to two routinely administered vaccines. METHODS: Eighty-three infants enrolled in the New Hampshire Birth Cohort Study were included in the analysis. We collected blood samples at 12 months of age and assayed the isolated serum to quantify total IgG and measured antibody to pneumococcal capsular polysaccharide and tetanus toxoid. Stool samples were collected from infants at 6 weeks of age and sequenced using 16S rRNA, and a subset of 61 samples were sequenced using shotgun metagenomics sequencing. RESULTS: We observed differences in beta diversity for 16S 6-week stool microbiota and pneumococcal and tetanus IgG antibody responses. Metagenomics analyses identified species and metabolic pathways in 6-week stool associated with tetanus antibody response, in particular, negative associations with the relative abundance of Aeriscardovia aeriphila species and positive associations with the relative abundance of species associated with CDP-diacylglycerol biosynthesis pathways. CONCLUSIONS: The early gut microbiome composition may influence an infant's vaccine response. IMPACT: Early intestinal microbiome acquisition plays a critical role in immune maturation and in both adaptive and innate immune response in infancy. We identified associations between early life microbiome composition and response to two routinely administered vaccines-pneumococcal capsular polysaccharide and tetanus toxoid-measured at approximately 1 year of age. Our findings highlight the potential impact of the gut microbiome on infant immune response that may open up opportunities for future interventions.

Associations of maternal plasma and umbilical cord plasma metabolomics profiles with birth anthropometric measures.

BACKGROUND: The metabolomics profiles of maternal plasma during pregnancy and cord plasma at birth might influence fetal growth and birth anthropometry. The objective was to examine how maternal plasma and umbilical cord plasma metabolites are associated with newborn anthropometric measures, a known predictor of future health outcomes. METHODS: Pregnant women between 24 and 28 weeks of gestation were recruited as part of a prospective cohort study. Blood samples from 413 women at enrollment and 787 infant cord blood samples were analyzed using the Biocrates AbsoluteIDQ® p180 kit. Multivariable linear regression models were used to examine associations of cord and maternal metabolites with infant anthropometry at birth. RESULTS: In cord blood samples from this rural cohort from New Hampshire of largely white residents, 13 metabolites showed negative associations, and 10 metabolites showed positive associations with birth weight Z-score. Acylcarnitine C5 showed negative association, and 4 lysophosphatidylcholines showed positive associations with birth length Z-score. Maternal blood metabolites did not significantly correlate with birth weight and length Z-scores. CONCLUSIONS: Consistent findings were observed for several acylcarnitines that play a role in utilization of energy sources, and a lysophosphatidylcholine that is part of oxidative stress and inflammatory response pathways in cord plasma samples. IMPACT: The metabolomics profiles of maternal plasma during pregnancy and cord plasma at birth may influence fetal growth and birth anthropometry. This study examines the independent effects of maternal gestational and infant cord blood metabolomes across different classes of metabolites on birth anthropometry. Acylcarnitine species were negatively associated and glycerophospholipids species were positively associated with weight and length Z-scores at birth in the cord plasma samples, but not in the maternal plasma samples. This study identifies lipid metabolites in infants that possibly may affect early growth.

Placental microRNAs relate to early childhood growth trajectories.

BACKGROUND: Poor placental function is a common cause of intrauterine growth restriction, which in turn is associated with increased risks of adverse health outcomes. Our prior work suggests that birthweight and childhood obesity-associated genetic variants functionally impact placental function and that placental microRNA are associated with birthweight. To address the influence of the placenta beyond birth, we assessed the relationship between placental microRNAs and early childhood growth. METHODS: Using the SITAR package, we generated two parameters that describe individual weight trajectories of children (0-5 years) in the New Hampshire Birth Cohort Study (NHBCS, n = 238). Using negative binomial generalized linear models, we identified placental microRNAs that relate to growth parameters (FDR < 0.1), while accounting for sex, gestational age at birth, and maternal parity. RESULTS: Genes targeted by the six growth trajectory-associated microRNAs are enriched (FDR < 0.05) in growth factor signaling (TGF/beta: miR-876; EGF/R: miR-155, Let-7c; FGF/R: miR-155; IGF/R: Let-7c, miR-155), calmodulin signaling (miR-216a), and NOTCH signaling (miR-629). CONCLUSIONS: Growth-trajectory microRNAs target pathways affecting placental proliferation, differentiation and function. Our results suggest a role for microRNAs in regulating placental cellular dynamics and supports the Developmental Origins of Health and Disease hypothesis that fetal environment can have impacts beyond birth. IMPACT: We found that growth trajectory associated placenta microRNAs target genes involved in signaling pathways central to the formation, maintenance and function of placenta; suggesting that placental cellular dynamics remain critical to infant growth to term and are under the control of microRNAs. Our results contribute to the existing body of research suggesting that the placenta plays a key role in programming health in the offspring. This is the first study to relate molecular patterns in placenta, specifically microRNAs, to early childhood growth trajectory.

Human placental microRNAs dysregulated by cadmium exposure predict neurobehavioral outcomes at birth.

BACKGROUND: Prenatal cadmium (Cd) exposure has been implicated in both placental toxicity and adverse neurobehavioral outcomes. Placental microRNAs (miRNAs) may function to developmentally program adverse pregnancy and newborn health outcomes in response to gestational Cd exposure. METHODS: In a subset of the Rhode Island Child Health Study (RICHS, n = 115) and the New Hampshire Birth Cohort Study (NHBCS, = 281), we used small RNA sequencing and trace metal analysis to identify Cd-associated expression of placental miRNAs using negative binomial generalized linear models. We predicted mRNAs targeted by Cd-associated miRNAs and relate them to neurobehavioral outcomes at birth through the integration of transcriptomic data and summary scores from the NICU Network Neurobehavioral Scale (NNNS). RESULTS: Placental Cd concentrations are significantly associated with the expression level of five placental miRNAs in NHBCS, with similar effect sizes in RICHS. These miRNA target genes overrepresented in nervous system development, and their expression is correlated with NNNS metrics suggestive of atypical neurobehavioral outcomes at birth. CONCLUSIONS: Gestational Cd exposure is associated with the expression of placental miRNAs. Predicted targets of these miRNAs are involved in nervous system development and may also regulate placental physiology, allowing their dysregulation to modify developmental programming of early life health outcomes. IMPACT: This research aims to address the poor understanding of the molecular mechanisms governing adverse pregnancy and newborn health outcomes in response to Gestational cadmium (Cd) exposure. Our results outline a robust relationship between Cd-associated placental microRNA expression and NICU Network Neurobehavioral Scales (NNNS) at birth indicative of atypical neurobehavior. This study utilized healthy mother-infant cohorts to describe the role of Cd-associated dysregulation of placental microRNAs as a potential mechanism by which adverse neurobehavioral outcomes are developmentally programmed.

Impact of the COVID-19 pandemic on children's sleep habits: an ECHO study.

BACKGROUND: Sleep in childhood is affected by behavioral, environmental, and parental factors. We propose that these factors were altered during the COVID-19 pandemic. This study investigates sleep habit changes during the pandemic in 528 children 4-12 years old in the US, leveraging data from the Environmental Influences on Child Health Outcomes (ECHO) Program. METHODS: Data collection occurred in July 2019-March 2020 (pre-pandemic) and two pandemic periods: December 2020-April 2021 and May-August 2021. Qualitative interviews were performed in 38 participants. RESULTS: We found no changes in sleep duration, but a shift to later sleep midpoint during the pandemic periods. There was an increase in latency at the first pandemic collection period but no increase in the frequency of bedtime resistance, and a reduced frequency of naps during the pandemic. Qualitative interviews revealed that parents prioritized routines to maintain sleep duration but were more flexible regarding timing. Children from racial/ethnic minoritized communities slept less at night, had later sleep midpoint, and napped more frequently across all collection periods, warranting in-depth investigation to examine and address root causes. CONCLUSIONS: The COVID-19 pandemic significantly impacted children sleep, but parental knowledge of the importance of sleep might have played a significant protective role. IMPACT: During the COVID-19 pandemic, US children changed their sleep habits, going to bed and waking up later, but their sleep duration did not change. Sleep latency was longer. Parental knowledge of sleep importance might have played a protective role. Regardless of data collection periods, children from racial/ethnic minoritized communities slept less and went to bed later. This is one of the first study on this topic in the US, including prospective pre-pandemic qualitative and quantitative data on sleep habits. Our findings highlight the pandemic long-term impact on childhood sleep. Results warrants further investigations on implications for overall childhood health.

Prenatal and perinatal factors associated with neonatal neurobehavioral profiles in the ECHO Program.

BACKGROUND: Single-cohort studies have identified distinct neurobehavioral profiles that are associated with prenatal and neonatal factors based on the NICU Network Neurobehavioral Scale (NNNS). We examined socioeconomic, medical, and substance use variables as predictors of NNNS profiles in a multi-cohort study of preterm and term-born infants with different perinatal exposures. METHODS: We studied 1112 infants with a neonatal NNNS exam from the Environmental influences on Child Health Outcomes (ECHO) consortium. We used latent profile analysis to characterize infant neurobehavioral profiles and generalized estimating equations to determine predictors of NNNS profiles. RESULTS: Six distinct neonatal neurobehavioral profiles were identified, including two dysregulated profiles: a hypo-aroused profile (16%) characterized by lethargy, hypotonicity, and nonoptimal reflexes; and a hyper-aroused profile (6%) characterized by high arousal, excitability, and stress, with low regulation and poor movement quality. Infants in the hypo-aroused profile were more likely to be male, have younger mothers, and have mothers who were depressed prenatally. Infants in the hyper-aroused profile were more likely to be Hispanic/Latino and have mothers who were depressed or used tobacco prenatally. CONCLUSIONS: We identified two dysregulated neurobehavioral profiles with distinct perinatal antecedents. Further understanding of their etiology could inform targeted interventions to promote positive developmental outcomes. IMPACT: Prior research on predictors of neonatal neurobehavior have included single-cohort studies, which limits generalizability of findings. In a multi-cohort study of preterm and term-born infants, we found six distinct neonatal neurobehavioral profiles, with two profiles being identified as dysregulated. Hypo- and hyper-aroused neurobehavioral profiles had distinct perinatal antecedents. Understanding perinatal factors associated with dysregulated neurobehavior could help promote positive developmental outcomes.