Particulate Matter, DNA Methylation in Nitric Oxide Synthase, and Childhood Respiratory Disease

Background: Air pollutants have been associated with childhood asthma and wheeze. Epigenetic regulation of nitric oxide synthase—the gene responsible for nitric oxide production—may be affected by air pollutants and contribute to the pathogenesis of asthma and wheeze. Objective: Our goal was to investigate the association between air pollutants, DNA methylation, and respiratory outcomes in children. Methods: Given residential address and buccal sample collection date, we estimated 7-day, 1-month, 6-month, and 1-year cumulative average $PM_{2.5}$ and $PM_{10}$ (particulate matter ≤ 2.5 and ≤ 10 µm aerodynamic diameter, respectively) exposures for 940 participants in the Children’s Health Study. Methylation of 12 CpG sites in three NOS (nitric oxide synthase) genes was measured using a bisulfite-polymerase chain reaction Pyrosequencing assay. Beta regression models were used to estimate associations between air pollutants, percent DNA methylation, and respiratory outcomes. Results: A 5-µg/$m^3$ increase in $PM_{2.5}$ was associated with a 0.20% [95% confidence interval (CI): –0.32, –0.07] to 1.0% (95% CI: –1.61, –0.56) lower DNA methylation at NOS2A position 1, 0.06% (95% CI: –0.18, 0.06) to 0.58% (95% CI: –1.13, –0.02) lower methylation at position 2, and 0.34% (95% CI: –0.57, –0.11) to 0.89% (95% CI: –1.57, –0.21) lower methylation at position 3, depending on the length of exposure and CpG locus. One-year $PM_{2.5}$ exposure was associated with 0.33% (95% CI: 0.01, 0.65) higher in average DNA methylation of 4 loci in the NOS2A CpG island. A 5-µg/$m^3$ increase in 7-day and 1-year $PM_{2.5}$ was associated with 0.6% (95% CI: 0.13, 0.99) and 2.8% (95% CI: 1.77, 3.75) higher NOS3 DNA methylation. No associations were observed for NOS1. $PM_{10}$ showed similar but weaker associations with DNA methylation in these genes. Conclusions: $PM_{2.5}$ exposure was associated with percent DNA methylation of several CpG loci in NOS genes, suggesting an epigenetic mechanism through which these pollutants may alter production of nitric oxide

Racial and Geographic Variation in Effects of Maternal Education and Neighborhood-Level Measures of Socioeconomic Status on Gestational Age at Birth: Findings From the ECHO Cohorts

Preterm birth occurs at excessively high and disparate rates in the United States. In 2016, the National Institutes of Health (NIH) launched the Environmental influences on Child Health Outcomes (ECHO) program to investigate the influence of early life exposures on child health. Extant data from the ECHO cohorts provides the opportunity to examine racial and geographic variation in effects of individual- and neighborhood-level markers of socioeconomic status (SES) on gestational age at birth. The objective of this study was to examine the association between individual-level (maternal education) and neighborhood-level markers of SES and gestational age at birth, stratifying by maternal race/ethnicity, and whether any such associations are modified by US geographic region. Twenty-six ECHO cohorts representing 25,526 mother-infant pairs contributed to this disseminated meta-analysis that investigated the effect of maternal prenatal level of education (high school diploma, GED, or less; some college, associate\u27s degree, vocational or technical training [reference category]; bachelor\u27s degree, graduate school, or professional degree) and neighborhood-level markers of SES (census tract [CT] urbanicity, percentage of black population in CT, percentage of population below the federal poverty level in CT) on gestational age at birth (categorized as preterm, early term, full term [the reference category], late, and post term) according to maternal race/ethnicity and US region. Multinomial logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CIs). Cohort-specific results were meta-analyzed using a random effects model. For women overall, a bachelor\u27s degree or above, compared with some college, was associated with a significantly decreased odds of preterm birth (aOR 0.72; 95% CI: 0.61-0.86), whereas a high school education or less was associated with an increased odds of early term birth (aOR 1.10, 95% CI: 1.00-1.21). When stratifying by maternal race/ethnicity, there were no significant associations between maternal education and gestational age at birth among women of racial/ethnic groups other than non-Hispanic white. Among non-Hispanic white women, a bachelor\u27s degree or above was likewise associated with a significantly decreased odds of preterm birth (aOR 0.74 (95% CI: 0.58, 0.94) as well as a decreased odds of early term birth (aOR 0.84 (95% CI: 0.74, 0.95). The association between maternal education and gestational age at birth varied according to US region, with higher levels of maternal education associated with a significantly decreased odds of preterm birth in the Midwest and South but not in the Northeast and West. Non-Hispanic white women residing in rural compared to urban CTs had an increased odds of preterm birth; the ability to detect associations between neighborhood-level measures of SES and gestational age for other race/ethnic groups was limited due to small sample sizes within select strata. Interventions that promote higher educational attainment among women of reproductive age could contribute to a reduction in preterm birth, particularly in the US South and Midwest. Further individual-level analyses engaging a diverse set of cohorts are needed to disentangle the complex interrelationships among maternal education, neighborhood-level factors, exposures across the life course, and gestational age at birth outcomes by maternal race/ethnicity and US geography

Physics-Informed Deep Learning to Reduce the Bias in Joint Prediction of Nitrogen Oxides

Atmospheric nitrogen oxides (NOx) primarily from fuel combustion have recognized acute and chronic health and environmental effects. Machine learning (ML) methods have significantly enhanced our capacity to predict NOx concentrations at ground-level with high spatiotemporal resolution but may suffer from high estimation bias since they lack physical and chemical knowledge about air pollution dynamics. Chemical transport models (CTMs) leverage this knowledge; however, accurate predictions of ground-level concentrations typically necessitate extensive post-calibration. Here, we present a physics-informed deep learning framework that encodes advection-diffusion mechanisms and fluid dynamics constraints to jointly predict NO2 and NOx and reduce ML model bias by 21-42%. Our approach captures fine-scale transport of NO2 and NOx, generates robust spatial extrapolation, and provides explicit uncertainty estimation. The framework fuses knowledge-driven physicochemical principles of CTMs with the predictive power of ML for air quality exposure, health, and policy applications. Our approach offers significant improvements over purely data-driven ML methods and has unprecedented bias reduction in joint NO2 and NOx prediction

Prenatal Tobacco Smoke Exposure Is Associated with Childhood DNA CpG Methylation

Background: Smoking while pregnant is associated with a myriad of negative health outcomes in the child. Some of the detrimental effects may be due to epigenetic modifications, although few studies have investigated this hypothesis in detail.Objectives: To characterize site-specific epigenetic modifications conferred by prenatal smoking exposure within asthmatic children.Methods: Using Illumina HumanMethylation27 microarrays, we estimated the degree of methylation at 27,578 distinct DNA sequences located primarily in gene promoters using whole blood DNA samples from the Childhood Asthma Management Program (CAMP) subset of Asthma BRIDGE childhood asthmatics (n = 527) ages 5–12 with prenatal smoking exposure data available. Using beta-regression, we screened loci for differential methylation related to prenatal smoke exposure, adjusting for gender, age and clinical site, and accounting for multiple comparisons by FDR.Results: Of 27,578 loci evaluated, 22,131 (80%) passed quality control assessment and were analyzed. Sixty-five children (12%) had a history of prenatal smoke exposure. At an FDR of 0.05, we identified 19 CpG loci significantly associated with prenatal smoke, of which two replicated in two independent populations. Exposure was associated with a 2% increase in mean CpG methylation in FRMD4A (p = 0.01) and Cllorf52 (p = 0.001) compared to no exposure. Four additional genes, XPNPEP1, PPEF2, SMPD3 and CRYGN, were nominally associated in at least one replication group.Conclusions: These data suggest that prenatal exposure to tobacco smoke is associated with reproducible epigenetic changes that persist well into childhood. However, the biological significance of these altered loci remains unknown.</p

Prenatal metal(loid) mixtures and birth weight for gestational age: A pooled analysis of three cohorts participating in the ECHO program

Background: A growing number of studies have identified both toxic and essential metals which influence fetal growth. However, most studies have conducted single-cohort analyses, which are often limited by narrow exposure ranges, and evaluated metals individually. The objective of the current study was to conduct an environmental mixture analysis of metal impacts on fetal growth, pooling data from three geographically and demographically diverse cohorts in the United States participating in the Environmental Influences on Child Health Outcomes program. Methods: The pooled sample (N = 1,002) included participants from the MADRES, NHBCS, and PROTECT cohorts. Associations between seven metals (antimony, cadmium, cobalt, mercury, molybdenum, nickel, tin) measured in maternal urine samples collected during pregnancy (median: 16.0 weeks gestation) and birth weight for gestational age z-scores (BW for GA) were investigated using Bayesian Kernel Machine Regression (BKMR). Models were also stratified by cohort and infant sex to investigate possible heterogeneity. Chromium and uranium concentrations fell below the limits of detection for most participants and were evaluated separately as binary variables using pooled linear regression models. Results: In the pooled BKMR analysis, antimony, mercury, and tin were inversely and linearly associated with BW for GA, while a positive linear association was identified for nickel. The inverse association between antimony and BW for GA was observed in both males and females and for all three cohorts but was strongest for MADRES, a predominantly low-income Hispanic cohort in Los Angeles. A reverse j-shaped association was identified between cobalt and BW for GA, which was driven by female infants. Pooled associations were null for cadmium, chromium, molybdenum, and uranium, and BKMR did not identify potential interactions between metal pairs. Conclusions: Findings suggest that antimony, an understudied metalloid, may adversely impact fetal growth. Cohort- and/or sex-dependent associations were identified for many of the metals, which merit additional investigation

Prenatal Tobacco Smoke Exposure Is Associated with Childhood DNA CpG Methylation

Background: Smoking while pregnant is associated with a myriad of negative health outcomes in the child. Some of the detrimental effects may be due to epigenetic modifications, although few studies have investigated this hypothesis in detail. Objectives: To characterize site-specific epigenetic modifications conferred by prenatal smoking exposure within asthmatic children. Methods: Using Illumina HumanMethylation27 microarrays, we estimated the degree of methylation at 27,578 distinct DNA sequences located primarily in gene promoters using whole blood DNA samples from the Childhood Asthma Management Program (CAMP) subset of Asthma BRIDGE childhood asthmatics (n = 527) ages 5–12 with prenatal smoking exposure data available. Using beta-regression, we screened loci for differential methylation related to prenatal smoke exposure, adjusting for gender, age and clinical site, and accounting for multiple comparisons by FDR. Results: Of 27,578 loci evaluated, 22,131 (80%) passed quality control assessment and were analyzed. Sixty-five children (12%) had a history of prenatal smoke exposure. At an FDR of 0.05, we identified 19 CpG loci significantly associated with prenatal smoke, of which two replicated in two independent populations. Exposure was associated with a 2% increase in mean CpG methylation in FRMD4A (p = 0.01) and Cllorf52 (p = 0.001) compared to no exposure. Four additional genes, XPNPEP1, PPEF2, SMPD3 and CRYGN, were nominally associated in at least one replication group. Conclusions: These data suggest that prenatal exposure to tobacco smoke is associated with reproducible epigenetic changes that persist well into childhood. However, the biological significance of these altered loci remains unknown

Newborn DNA-methylation, childhood lung function, and the risks of asthma and COPD across the life course

Rationale: We aimed to identify differentially methylated regions (DMRs) in cord blood DNA associated with childhood lung function, asthma and chronic obstructive pulmonary disease (COPD) across the life course. Methods: We meta-analysed epigenome-wide data of 1688 children from five cohorts to identify cord blood DMRs and their annotated genes, in relation to forced expiratory volume in 1 s (FEV1), FEV1/forced vital capacity (FVC) ratio and forced expiratory flow at 75% of FVC at ages 7-13 years. Identified DMRs were explored for associations with childhood asthma, adult lung function and COPD, gene expression and involvement in biological processes. Results: We identified 59 DMRs associated with childhood lung function, of which 18 were associated with childhood asthma and nine with COPD in adulthood. Genes annotated to the top 10 identified DMRs were HOXA5, PAOX, LINC00602, ABCA7, PER3, CLCA1, VENTX, NUDT12, PTPRN2 and TCL1A. Differential gene expression in blood was observed for 32 DMRs in childhood and 18 in adulthood. Genes related with 16 identified DMRs were associated with respiratory developmental or pathogenic pathways. Interpretation: Our findings suggest that the epigenetic status of the newborn affects respiratory health and disease across the life course

Opportunities for understanding the COVID-19 pandemic and child health in the United States: the Environmental influences on Child Health Outcomes (ECHO) program

Objective Ongoing pediatric cohort studies offer opportunities to investigate the impact of the COVID-19 pandemic on children's health. With well-characterized data from tens of thousands of US children, the Environmental influences on Child Health Outcomes (ECHO) Program offers such an opportunity. Methods ECHO enrolled children and their caregivers from community- and clinic-based pediatric cohort studies. Extant data from each of the cohorts were pooled and harmonized. In 2019, cohorts began collecting data under a common protocol, and data collection is ongoing with a focus on early life environmental exposures and five child health domains: birth outcomes, neurodevelopment, obesity, respiratory, and positive health. In April of 2020, ECHO began collecting a questionnaire designed to assess COVID-19 infection and the pandemic's impact on families. We describe and summarize the characteristics of children who participated in the ECHO Program during the COVID-19 pandemic and novel opportunities for scientific advancement. Results This sample (n = 13,725) was diverse by child age (31% early childhood, 41% middle childhood, and 16% adolescence up to age 21), sex (49% female), race (64% White, 15% Black, 3% Asian, 2% American Indian or Alaska Native, <1% Native Hawaiian or Pacific Islander, 10% Multiple race and 2% Other race), Hispanic ethnicity (22% Hispanic), and were similarly distributed across the four United States Census regions and Puerto Rico. Conclusion ECHO data collected during the pandemic can be used to conduct solution-oriented research to inform the development of programs and policies to support child health during the pandemic and in the post-pandemic era