Subtypes of Toddlers with Autism Spectrum Disorders: Implications for Early and Future Diagnosis

Autism spectrum disorders (ASDs) are a group of disorders that affect social, communication, and behavioral development. Identification of clinically distinct subtypes of ASDs, especially in the developmental period when delays or deficits are first recognized (i.e., in the first few years of life), can lend clues to etiology and trajectory and enhance current knowledge on early manifestations of the disorders. Moreover, identification of clinically distinct subtypes of ASDs may inform early identification efforts. Past research suggests that social relations, verbal abilities, nonverbal abilities, and the presence of certain stereotyped interests and behaviors (SIB) may be important factors in delineating subtypes of ASDs in toddlers. Yet there is no published study that examines empirically derived subtypes in a sample of such young children. Therefore, the purpose of this study was to determine whether clinically distinct subtypes can be derived from a sample of toddlers who fail an autism screen and are subsequently diagnosed with developmental concerns, including an ASD. Results found that subtypes delineated by social-communicative maturity were found in both of the aforementioned samples of children. Furthermore, the ASD only sample was also distinguished by rate and intensity of certain types of SIB. Implications for autism theory, early identification, and early intervention are discussed

Homogeneous Subgroups of Young Children with Autism Improve Phenotypic Characterization in the Study to Explore Early Development

The objective of this study was to identify homogenous classes of young children with autism spectrum disorder (ASD) to improve phenotypic characterization. Children were enrolled in the Study to Explore Early Development between 2 and 5 years of age. 707 children were classified with ASD after a comprehensive evaluation with strict diagnostic algorithms. Four classes of children with ASD were identified from latent class analysis: mild language delay with cognitive rigidity, mild language and motor delay with dysregulation, general developmental delay, and significant developmental delay with repetitive motor behaviors. We conclude that a four-class phenotypic model of children with ASD best describes our data and improves phenotypic characterization of young children with ASD. Implications for screening, diagnosis, and research are discussed

Incorporating Technology Into the iCook 4-H Program, a Cooking Intervention for Adults and Children: Randomized Controlled Trial

Background: Families who cook, eat, and play together have been found to have more positive health outcomes. Interventions are needed that effectively increase these health-related behaviors. Technology is often incorporated in health-related interventions but is not always independently assessed. Objective: The objective of this study was to describe challenges and facilitators to incorporating technology into the iCook 4-H intervention program. Methods: Dyads (n=228) composed of children (mean 9.4, SD 0.7 years old) and an adult primary meal preparer (mean 39.0, SD 8 years) were randomly assigned to a control (n=77) or treatment group (n=151). All treatment group dyads participated in 6 in-person sessions designed to increase families cooking, eating, and playing together. We incorporated Web-based between-session technological components related to the curriculum content throughout the intervention. Assessments were completed by both groups at baseline and at 4, 12, and 24 months; they included measured anthropometrics for children, and online surveys about camera and website skill and use for dyads. Session leaders and participants completed open-ended process evaluations after each session about technological components. We computed chi-square analysis for sex differences in technological variables. We tested relationships between video posting frequency and outcomes of interest (cooking frequency, self-efficacy, and skills; dietary intake; and body mass index) with Spearman correlations. Process evaluations and open-ended survey responses were thematically analyzed for beneficial and inhibiting factors, including technological components in the curriculum. Results: Only 78.6% (81/103) of children and 68.3% (71/104) of adults reported always being comfortable accessing the internet postintervention. Boys reported being more comfortable than girls with technological tasks (P\u3c.05). Children who posted more videos had a higher level of cooking skills at 4 months postintervention (r=.189, P=.05). Barriers to website usage reported most frequently by children were lack of accessibility, remembering, interactivity, motivation, time, and lack of parental encouragement. Conclusions: Incorporating technological supports, such as cameras and websites, into children’s programs may help produce improved outcomes. Identifying barriers to and patterns of technology usage need to be considered when developing future child health promotion interventions

Autism Spectrum Disorder Symptoms Among Children Enrolled in the Study to Explore Early Development (SEED)

This study examined the phenotypic profiles of children aged 30–68 months in the Study to Explore Early Development (SEED). Children classified as autism spectrum disorder (ASD), developmental delay (DD) with ASD symptoms, DD without ASD symptoms, and population comparison (POP) differed significantly from each other on cognitive, adaptive, behavioral, and social functioning and the presence of parent-reported conditions. Children with ASD and DD with ASD symptoms had mild to severe ASD risk on several measures compared to children with other DD and POP who had little ASD risk across measures. We conclude that children in SEED have varying degrees of ASD impairment and associated deficits. SEED thus provides a valuable sample to explore ASD phenotypes and inform risk factor analyses

Pre- and Postnatal Fine Particulate Matter Exposure and Childhood Cognitive and Adaptive Function

Increasing evidence exists for an association between early life fine particulate matter (PM2.5) exposure and several neurodevelopmental outcomes, including autism spectrum disorder (ASD); however, the association between PM2.5 and adaptive and cognitive function remains poorly understood. Participants included 658 children with ASD, 771 with a non-ASD developmental disorder, and 849 population controls from the Study to Explore Early Development. Adaptive functioning was assessed in ASD cases using the Vineland Adaptive Behavior Scales (VABS); cognitive functioning was assessed in all groups using the Mullen Scales of Early Learning (MSEL). A satellite-based model was used to assign PM2.5 exposure averages during pregnancy, each trimester, and the first year of life. Linear regression was used to estimate beta coefficients and 95% confidence intervals, adjusting for maternal age, education, prenatal tobacco use, race-ethnicity, study site, and season of birth. PM2.5 exposure was associated with poorer VABS scores for several domains, including daily living skills and socialization. Associations were present between prenatal PM2.5 and lower MSEL scores for all groups combined; results were most prominent for population controls in stratified analyses. These data suggest that early life PM2.5 exposure is associated with specific aspects of cognitive and adaptive functioning in children with and without ASD

The Study to Explore Early Development (SEED): A Multisite Epidemiologic Study of Autism by the Centers for Autism and Developmental Disabilities Research and Epidemiology (CADDRE) Network

The Study to Explore Early Development (SEED), a multisite investigation addressing knowledge gaps in autism phenotype and etiology, aims to: (1) characterize the autism behavioral phenotype and associated developmental, medical, and behavioral conditions and (2) investigate genetic and environmental risks with emphasis on immunologic, hormonal, gastrointestinal, and sociodemographic characteristics. SEED uses a case–control design with population-based ascertainment of children aged 2–5 years with an autism spectrum disorder (ASD) and children in two control groups—one from the general population and one with non-ASD developmental problems. Data from parent-completed questionnaires, interviews, clinical evaluations, biospecimen sampling, and medical record abstraction focus on the prenatal and early postnatal periods. SEED is a valuable resource for testing hypotheses regarding ASD characteristics and causes

Economic impacts of the COVID-19 pandemic on families of children with autism and other developmental disabilities

BackgroundTo control the spread of the coronavirus disease (COVID-19), many jurisdictions throughout the world enacted public health measures that had vast socio-economic implications. In emergency situations, families of children with developmental disabilities (DDs), including autism, may experience increased difficulty accessing therapies, economic hardship, and caregiver stress, with the potential to exacerbate autism symptoms. Yet, limited research exists on the economic impacts of the COVID-19 pandemic on families of children with autism or another DD compared to families of children from the general population.ObjectivesTo assess impact of the COVID-19 pandemic related to parental employment and economic difficulties in families of children with autism, another DD, and in the general population, considering potential modification by socioeconomic disadvantage before the pandemic and levels of child behavioral and emotional problems.MethodsThe Study to Explore Early Development (SEED) is a multi-site, multi-phase, case-control study of young children with autism or another DD as compared to a population comparison group (POP). During January-July 2021, a COVID-19 Impact Assessment Questionnaire was sent to eligible participants (n=1,789) who had enrolled in SEED Phase 3 from September 2017-March 2020. Parents completed a questionnaire on impacts of the pandemic in 2020 and completed the Child Behavior Checklist (CBCL) to measure behavioral and emotional health of their child during this time. Multiple logistic regression models were built for employment reduction, increased remote work, difficulty paying bills, or fear of losing their home. Covariates include group status (autism, DD, POP), household income at enrollment, child’s race and ethnicity, and binary CBCL Total Problems T-score (<60 vs. ≥60). Unadjusted and adjusted odds ratios (aOR) and 95% confidence intervals (CI) were calculated.ResultsThe study included 274 children with autism, 368 children with another DD, and 385 POP children. The mean age of 6.1 years (standard deviation, 0.8) at the COVID-19 Impact Assessment did not differ between study groups. Parents of children with autism were less likely to transition to remote work (aOR [95% CI] = 0.6 [0.4, 1.0]) and more likely to report difficulty paying bills during the pandemic (1.8 [1.2, 2.9]) relative to parents of POP children. Lower income was associated with greater employment reduction, difficulty paying bills, and fear of losing their home, but inversely associated with transitioning to remote work. Parents of non-Hispanic (NH) Black children experienced greater employment reduction compared to parents of NH White children (1.9 [1.1, 3.0]). Parents from racial and ethnic minority groups were more likely to experience difficulty paying bills and fear losing their home, relative to NH White parents. Caregivers of children with CBCL scores in the clinical range were more likely to fear losing their home (2.1 [1.3, 3.4]).ConclusionThese findings suggest that families of children with autism, families of lower socio-economic status, and families of racial and ethnic minority groups experienced fewer work flexibilities and greater financial distress during the pandemic. Future research can be used to assess if these impacts are sustained over time

The genetic determinants of recurrent somatic mutations in 43,693 blood genomes

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences

Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value OBFC1indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated our TL polygenic trait scores (PTS) were associated with increased risk of cancer-related phenotypes