Association of maternal education, neighborhood deprivation, and racial segregation with gestational age at birth by maternal race/ethnicity and United States Census region in the ECHO cohorts.

Background: In the United States, disparities in gestational age at birth by maternal race, ethnicity, and geography are theorized to be related, in part, to differences in individual- and neighborhood-level socioeconomic status (SES). Yet, few studies have examined their combined effects or whether associations vary by maternal race and ethnicity and United States Census region. Methods: We assembled data from 34 cohorts in the Environmental influences on Child Health Outcomes (ECHO) program representing 10,304 participants who delivered a liveborn, singleton infant from 2000 through 2019. We investigated the combined associations of maternal education level, neighborhood deprivation index (NDI), and Index of Concentration at the Extremes for racial residential segregation (ICERace) on gestational weeks at birth using linear regression and on gestational age at birth categories (preterm, early term, post-late term relative to full term) using multinomial logistic regression. Results: After adjustment for NDI and ICERace, gestational weeks at birth was significantly lower among those with a high school diploma or less (-0.31 weeks, 95% CI: -0.44, -0.18), and some college (-0.30 weeks, 95% CI: -0.42, -0.18) relative to a master's degree or higher. Those with a high school diploma or less also had an increased odds of preterm (aOR 1.59, 95% CI: 1.20, 2.10) and early term birth (aOR 1.26, 95% CI: 1.05, 1.51). In adjusted models, NDI quartile and ICERace quartile were not associated with gestational weeks at birth. However, higher NDI quartile (most deprived) associated with an increased odds of early term and late term birth, and lower ICERace quartile (least racially privileged) associated with a decreased odds of late or post-term birth. When stratifying by region, gestational weeks at birth was lower among those with a high school education or less and some college only among those living in the Northeast or Midwest. When stratifying by race and ethnicity, gestational weeks at birth was lower among those with a high school education or less only for the non-Hispanic White category. Conclusion: In this study, maternal education was consistently associated with shorter duration of pregnancy and increased odds of preterm birth, including in models adjusted for NDI and ICERace.

A mixed-methods analysis to understand the implementation of a multistakeholder research consortium: Environmental influences on child health outcomes (ECHO).

Introduction: Large, transdisciplinary research consortia have increasingly been called upon to address complex and challenging health problems. The National Institutes of Health's (NIH) Environmental influences on Child Health Outcomes (ECHO) Program developed multisite collaboration strategies to promote impactful collaborative observational research on child health. Team science and implementation science offer theoretical and methodological structure to answer questions about the strategies that facilitate successful consortia. We sought to characterize the elements and conditions that influence the implementation of a complex, interdisciplinary longitudinal research program, ECHO. Methods: Informed by the Practical, Robust, Implementation and Sustainability Model, our ethnographic research included semi-structured interviews with internal stakeholders and program evaluation metrics. We conducted template and matrix analysis and triangulated the qualitative and quantitative data to understand the implementation of ECHO. Results: Between February and May 2022, we conducted 24 virtual interviews with representatives from ECHO components. The main cross-cutting topics that emerged from thematic analysis were collaboration and team science; communication and decision-making; data processes and harmonization; and diversity, equity, and inclusion. Both the qualitative and secondary quantitative evaluation data provided insights into the reach, adoption, implementation, and effectiveness of the program. Conclusion: A large, multidisciplinary research consortium such as ECHO has produced conceptual, instrumental, capacity building, and connectivity impact for internal and external stakeholders. Facilitators included infrastructure that supported collaboration and learning, alignment of data processes, and harmonization. Opportunities for enhanced impact include multidisciplinary, multimethod communication strategies, and alignment of research priorities.

Depression, Anxiety, Energy, and Fatigue Among Nurses Who Cared for Patients During the COVID-19 Pandemic: A Cross-Sectional Study.

Purpose of Study: Nurses around the world have faced challenges during the coronavirus disease 2019 (COVID-19) pandemic. This study examined the association between depression and anxiety and trait energy and trait fatigue, and baseline health status and work characteristics. Design of Study: A cross-sectional study. Methods: A survey was conducted to collect self-reported data from nurses involved in patient care in Northern Virginia. Depression and anxiety were assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) depression and anxiety scales. To measure trait energy and trait fatigue, the Mental and Physical State and Trait Energy and Fatigue Scale (MPSTEFS) was used. Findings: There was a significant association between depression and energy (b=-0.46, t = -1.78, p < .001) and loneliness (b=1.38, t = 4.00, p < .001) and increased alcohol use (b=2.11, t = 2.04, p = .045). We also found that nurses with depression were significantly more likely to seek mental health counseling (b=-2.91, t = 2.54, p = 0.013), which was also the case for anxiety (b=3.13, t = 2.14, p = .036). Conclusions: Our study highlights the mental health burden among nurses who worked in the early phase of the COVID-19 pandemic and its association with increased alcohol use and loneliness. The findings may help healthcare leaders identify early signals of deterioration in nurses' well-being.

Maternal stress and early childhood BMI among US children from the Environmental influences on Child Health Outcomes (ECHO) program.

BACKGROUND: We aimed to understand the association between maternal stress in the first year of life and childhood body mass index (BMI) from 2 to 4 years of age in a large, prospective United States-based consortium of cohorts. METHODS: We used data from the Environmental influences on Child Health Outcomes program. The main exposure was maternal stress in the first year of life measured with the Perceived Stress Scale (PSS). The main outcome was the first childhood BMI percentile after age 2 until age 4 years. We used an adjusted linear mixed effects model to examine associations between BMI and PSS quartile. RESULTS: The mean BMI percentile in children was 59.8 (SD 30) measured at 3.0 years (SD 1) on average. In both crude models and models adjusted for maternal BMI, age, race, ethnicity, infant birthweight, and health insurance status, no linear associations were observed between maternal stress and child BMI. CONCLUSIONS: Among 1694 maternal-infant dyads, we found no statistically significant relationships between maternal perceived stress in the first year of life and child BMI after 2 through 4 years. IMPACT: Although existing literature suggests relationships between parental stress and childhood BMI, we found no linear associations between maternal stress in the first year of life and childhood BMI at 2-4 years of age among participants in ECHO cohorts. Higher maternal stress was significantly associated with Hispanic ethnicity, Black race, and public health insurance. Our analysis of a large, nationally representative sample challenges assumptions that maternal stress in the first year of life, as measured by a widely used scale, is associated with offspring BMI.

Sociodemographic Variation in Children's Health Behaviors During the COVID-19 Pandemic.

Background: Societal changes during the COVID-19 pandemic may affect children's health behaviors and exacerbate disparities. This study aimed to describe children's health behaviors during the COVID-19 pandemic, how they vary by sociodemographic characteristics, and the extent to which parent coping strategies mitigate the impact of pandemic-related financial strain on these behaviors. Methods: This study used pooled data from 50 cohorts in the Environmental influences on Child Health Outcomes Program. Children or parent proxies reported sociodemographic characteristics, health behaviors, and parent coping strategies. Results: Of 3315 children aged 3-17 years, 49% were female and 57% were non-Hispanic white. Children of parents who reported food access as a source of stress were 35% less likely to engage in a higher level of physical activity. Children of parents who changed their work schedule to care for their children had 82 fewer min/day of screen time and 13 more min/day of sleep compared with children of parents who maintained their schedule. Parents changing their work schedule were also associated with a 31% lower odds of the child consuming sugar-sweetened beverages. Conclusions: Parents experiencing pandemic-related financial strain may need additional support to promote healthy behaviors. Understanding how changes in parent work schedules support shorter screen time and longer sleep duration can inform future interventions.

Prenatal Antidepressant Exposures and Autism Spectrum Disorder or Traits: A Retrospective, Multi-Cohort Study.

Prenatal antidepressant exposure has been associated with increased risk for neurodevelopmental disorders in childhood, including autism spectrum disorder (ASD). The current study utilized multi-cohort data from the Environmental influences on Child Health Outcomes (ECHO) program (N = 3129) to test for this association, and determine whether the association remained after adjusting for maternal prenatal depression and other potential confounders. Antidepressants and a subset of selective serotonin reuptake inhibitors (SSRIs) were examined in relation to binary (e.g., diagnostic) and continuous measures of ASD and ASD related traits (e.g., social difficulties, behavior problems) in children 1.5 to 12 years of age. Child sex was tested as an effect modifier. While prenatal antidepressant exposure was associated with ASD related traits in univariate analyses, these associations were statistically non-significant in models that adjusted for prenatal maternal depression and other maternal and child characteristics. Sex assigned at birth was not an effect modifier for the prenatal antidepressant and child ASD relationship. Overall, we found no association between prenatal antidepressant exposures and ASD diagnoses or traits. Discontinuation of antidepressants in pregnancy does not appear to be warranted on the basis of increased risk for offspring ASD.

Characteristics of Environmental influences on Child Health Outcomes (ECHO) Cohorts Recruited During Pregnancy.

PURPOSE: The objective of this study was to characterize the study designs, recruitment strategies, and other study characteristics among cohorts that initiated during pregnancy as part of the Environmental influences on Child Health Outcomes (ECHO) program. METHODS: ECHO research programs (cohorts) were reviewed. Only those who had or were currently recruiting during pregnancy were surveyed in 2018 about research recruitment strategies (participant incentives, study burden, community collaboration, and cultural adaptations). Data are presented with cohort characteristics (location, inclusion and exclusion criteria, sociodemographics, medical information, behavioral factors, and biospecimens). RESULTS: Forty-seven of the 84 ECHO pediatric cohorts recruited during pregnancy. Findings demonstrate various recruitment strategies, domains of data collection, and biospecimen collection are all characteristics of successful cohorts. CLINICAL IMPLICATIONS: These data that include over 50,000 children from families across the country, many in underserved areas, will be used for research with the potential to lead to profound policy changes. Prenatal conditions such as maternal age, obesity, depression, and drug use can be examined using study data, including biological markers, from pregnancy through childbirth and into childhood and will inform national policies on the role of early life exposures and underlying mechanisms of disease progression.

Genomic and molecular characterization of preterm birth.

Preterm birth (PTB) complications are the leading cause of long-term morbidity and mortality in children. By using whole blood samples, we integrated whole-genome sequencing (WGS), RNA sequencing (RNA-seq), and DNA methylation data for 270 PTB and 521 control families. We analyzed this combined dataset to identify genomic variants associated with PTB and secondary analyses to identify variants associated with very early PTB (VEPTB) as well as other subcategories of disease that may contribute to PTB. We identified differentially expressed genes (DEGs) and methylated genomic loci and performed expression and methylation quantitative trait loci analyses to link genomic variants to these expression and methylation changes. We performed enrichment tests to identify overlaps between new and known PTB candidate gene systems. We identified 160 significant genomic variants associated with PTB-related phenotypes. The most significant variants, DEGs, and differentially methylated loci were associated with VEPTB. Integration of all data types identified a set of 72 candidate biomarker genes for VEPTB, encompassing genes and those previously associated with PTB. Notably, PTB-associated genes RAB31 and RBPJ were identified by all three data types (WGS, RNA-seq, and methylation). Pathways associated with VEPTB include EGFR and prolactin signaling pathways, inflammation- and immunity-related pathways, chemokine signaling, IFN-γ signaling, and Notch1 signaling. Progress in identifying molecular components of a complex disease is aided by integrated analyses of multiple molecular data types and clinical data. With these data, and by stratifying PTB by subphenotype, we have identified associations between VEPTB and the underlying biology.

Gene-Centric Analysis of Preeclampsia Identifies Maternal Association at PLEKHG1.

The genetic susceptibility to preeclampsia, a pregnancy-specific complication with significant maternal and fetal morbidity, has been poorly characterized. To identify maternal genes associated with preeclampsia risk, we assembled 498 cases and 1864 controls of European ancestry from preeclampsia case-control collections in 5 different US sites (with additional matched population controls), genotyped samples on a cardiovascular gene-centric array composed of variants from ≈2000 genes selected based on prior genetic studies of cardiovascular and metabolic diseases and performed case-control genetic association analysis on 27 429 variants passing quality control. In silico replication testing of 9 lead signals with P<10-4 was performed in independent European samples from the SOPHIA (Study of Pregnancy Hypertension in Iowa) and Inova cohorts (212 cases, 456 controls). Multiethnic assessment of lead signals was then performed in samples of black (26 cases, 136 controls), Hispanic (132 cases, 468 controls), and East Asian (9 cases, 80 controls) ancestry. Multiethnic meta-analysis (877 cases, 3004 controls) revealed a study-wide statistically significant association of the rs9478812 variant in the pleiotropic PLEKHG1 gene (odds ratio, 1.40 [1.23-1.60]; Pmeta=5.90×10-7). The rs9478812 effect was even stronger in the subset of European cases with known early-onset preeclampsia (236 cases diagnosed <37 weeks, 1864 controls; odds ratio, 1.59 [1.27-1.98]; P=4.01×10-5). PLEKHG1 variants have previously been implicated in genome-wide association studies of blood pressure, body weight, and neurological disorders. Although larger studies are required to further define maternal preeclampsia heritability, this study identifies a novel maternal risk locus for further investigation.

New observations on maternal age effect on germline de novo mutations.

Germline mutations are the source of evolution and contribute substantially to many health-related processes. Here we use whole-genome deep sequencing data from 693 parents-offspring trios to examine the de novo point mutations (DNMs) in the offspring. Our estimate for the mutation rate per base pair per generation is 1.05 × 10(-8), well within the range of previous studies. We show that maternal age has a small but significant correlation with the total number of DNMs in the offspring after controlling for paternal age (0.51 additional mutations per year, 95% CI: 0.29, 0.73), which was not detectable in the smaller and younger parental cohorts of earlier studies. Furthermore, while the total number of DNMs increases at a constant rate for paternal age, the contribution from the mother increases at an accelerated rate with age.These observations have implications related to the incidence of de novo mutations relating to maternal age.

Utility of whole-genome sequencing for detection of newborn screening disorders in a population cohort of 1,696 neonates.

PURPOSE: To assess the potential of whole-genome sequencing (WGS) to replicate and augment results from conventional blood-based newborn screening (NBS). METHODS: Research-generated WGS data from an ancestrally diverse cohort of 1,696 infants and both parents of each infant were analyzed for variants in 163 genes involved in disorders included or under discussion for inclusion in US NBS programs. WGS results were compared with results from state NBS and related follow-up testing. RESULTS: NBS genes are generally well covered by WGS. There is a median of one (range: 0-6) database-annotated pathogenic variant in the NBS genes per infant. Results of WGS and NBS in detecting 28 state-screened disorders and four hemoglobin traits were concordant for 88.6% of true positives (n = 35) and 98.9% of true negatives (n = 45,757). Of the five infants affected with a state-screened disorder, WGS identified two whereas NBS detected four. WGS yielded fewer false positives than NBS (0.037 vs. 0.17%) but more results of uncertain significance (0.90 vs. 0.013%). CONCLUSION: WGS may help rule in and rule out NBS disorders, pinpoint molecular diagnoses, and detect conditions not amenable to current NBS assays.

Germline variation in cancer-susceptibility genes in a healthy, ancestrally diverse cohort: implications for individual genome sequencing.

Technological advances coupled with decreasing costs are bringing whole genome and whole exome sequencing closer to routine clinical use. One of the hurdles to clinical implementation is the high number of variants of unknown significance. For cancer-susceptibility genes, the difficulty in interpreting the clinical relevance of the genomic variants is compounded by the fact that most of what is known about these variants comes from the study of highly selected populations, such as cancer patients or individuals with a family history of cancer. The genetic variation in known cancer-susceptibility genes in the general population has not been well characterized to date. To address this gap, we profiled the nonsynonymous genomic variation in 158 genes causally implicated in carcinogenesis using high-quality whole genome sequences from an ancestrally diverse cohort of 681 healthy individuals. We found that all individuals carry multiple variants that may impact cancer susceptibility, with an average of 68 variants per individual. Of the 2,688 allelic variants identified within the cohort, most are very rare, with 75% found in only 1 or 2 individuals in our population. Allele frequencies vary between ancestral groups, and there are 21 variants for which the minor allele in one population is the major allele in another. Detailed analysis of a selected subset of 5 clinically important cancer genes, BRCA1, BRCA2, KRAS, TP53, and PTEN, highlights differences between germline variants and reported somatic mutations. The dataset can serve a resource of genetic variation in cancer-susceptibility genes in 6 ancestry groups, an important foundation for the interpretation of cancer risk from personal genome sequences.