Co-occurring Psychopathology in Children With and Without Autism Spectrum Disorder (ASD): Differences by Sex in the ECHO Cohorts.

Purpose: Our goals were to: 1) examine the occurrence of behavioral and emotional symptoms in children on the autism spectrum in a large national sample, stratifying by sex, and 2) evaluate whether children with increased autism-related social communication deficits also experience more behavioral and emotional problems.

Methods:  Participants (n = 7,998) were from 37 cohorts from the Environmental influences on Child Health Outcomes (ECHO) Program. Cross-sectional information on demographic factors, parent-report of an ASD diagnosis by clinician, Social Responsiveness Scale (SRS) scores, and Child Behavior Checklist (CBCL) scores were obtained for children aged 2.

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.

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.

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

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).

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.

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

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. This study used pooled data from 50 cohorts in the Environmental influences on Child Health Outcomes Program.

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).

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.

Gene-Centric Analysis of Preeclampsia Identifies Maternal Association at .

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 <10 was performed in independent European samples from the SOPHIA (Study of Pregnancy Hypertension in Iowa) and Inova cohorts (212 cases, 456 controls).

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.

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.

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.