Reproducibility between preschool and school-age Social Responsiveness Scale forms in the Environmental influences on Child Health Outcomes program.

Evidence suggests core autism trait consistency in older children, but development of these traits is variable in early childhood. The Social Responsiveness Scale (SRS) measures autism-related traits and broader autism phenotype, with two age-dependent forms in childhood (preschool, 2.5-4.5 years; school age, 4-18 years). Score consistency has been observed within forms, though reliability across forms has not been evaluated. Using data from the Environmental Influences on Child Health Outcomes (ECHO) program (n = 853), preschool, and school-age SRS scores were collected via maternal report when children were an average of 3.0 and 5.8 years, respectively. We compared reproducibility of SRS total scores (T-scores) and agreement above a clinically meaningful cutoff (T-scores ≥ 60) and examined predictors of discordance in cutoff scores across forms. Participant scores across forms were similar (mean difference: 3.3 points; standard deviation: 7), though preschool scores were on average lower than school-age scores. Most children (88%) were classified below the cutoff on both forms, and overall concordance was high (92%). However, discordance was higher in cohorts following younger siblings of autistic children (16%). Proportions of children with an autism diagnoses were also higher among those with discordant scores (27%) than among those with concordant scores (4%). Our findings indicate SRS scores are broadly reproducible across preschool and school-age forms, particularly for capturing broader, nonclinical traits, but also suggest that greater variability of autism-related traits in preschool-age children may reduce reliability with later school-age scores for those in the clinical range.

Objective measurement of movement variability using wearable sensors predicts ASD outcomes in infants at high likelihood for ASD and ADHD.

Early motor delays and differences are common among children with autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). Yet, little work has shown whether there are early atypical motor signs that differentiate these groups. Quantitative measures of movement variability hold promise for improving the identification of subtle and specific differences in motor function among infants and toddlers at high likelihood for ASD and ADHD. To this end, we created a novel quantitative measure of movement variability (movement curvature) and conducted a preliminary investigation as to whether this measure improves outcome predictions. We used a wearable triaxial accelerometer to evaluate continuous motion-based activity in infants at high and low likelihood for ASD and ADHD at 12, 18, 24, and 36 months of age. At 36 months, participants were categorized into three outcome groups: ASD (n = 19), ADHD concerns (n = 17), and a comparison group (n = 82). We examined group differences in movement curvature and whether movement curvature is predictive of a later ASD or ADHD concerns classification. We found that movement curvature was significantly lower in infants with later ASD diagnosis at 18, 24, and 36 months of age compared to infants with either ADHD concerns or those in the comparison group. Movement curvature was also a significant predictor of ASD at 18, 24, and 36 months (AUC 0.66-0.71; p = 0.005-0.039) and when adjusting for high ASD likelihood at 18 and 24 months (AUC 0.90, p = 0.05-0.019). These results indicate that lower movement curvature may be a feature of early motor differences in infants with later ASD diagnosis as early as 18 months of age.

Measuring Developmental Delays: Comparison of Parent Report and Direct Testing.

PURPOSE: Developmental assessment is part of a comprehensive autism evaluation. During in-person evaluations, developmental assessment is completed via direct testing by an examiner. In telehealth evaluations, developmental assessment relies on caregiver-report instruments. This study examined correspondence between caregiver report and direct testing of developmental skills. METHODS: Participants were 93 children, aged 18-42 months, undergoing evaluation for possible autism spectrum disorder (ASD). Caregivers were interviewed with the Developmental Profile, 4th edition (DP-4) via telehealth platform and children were tested in person 2-4 weeks later using the Mullen Scales of Early Learning (MSEL). RESULTS: Correlations between the DP-4 and MSEL were high (ranging from 0.50 to 0.82) across standard scores, age equivalents, and functional categories, as well as across individual subtests and overall composite scores. CONCLUSION: The high convergent validity found in this study suggests that the DP-4 provides a suitable proxy for direct developmental testing using the MSEL in the context of telehealth evaluations for ASD in young children, delivering a good estimate of both developmental functioning and presence of delays. TRIAL REGISTRATION: Data were obtained from registered clinical trial NCT05047224, date of registration 2021-09-07.

Utility of the Language Use Inventory in Young Children at Elevated Likelihood of Autism.

PURPOSE: The aims of this study were (a) to evaluate the convergent validity of the Language Use Inventory (LUI) with measures of autism spectrum disorder (ASD) symptoms, language, and social skills and (b) to assess discriminant validity of the LUI with measures of nonlanguage skills, including daily living skills and motor development. METHOD: This study sample included participants from a longitudinal study (n = 239) of infant siblings with elevated familial likelihood of ASD and lower familial likelihood. Assessment measures completed at 36 months included the LUI, the Autism Diagnostic Observation Schedule-Second Edition (ADOS-2), the Mullen Scales of Early Learning, and the Vineland Adaptive Behavior Scales-Second Edition. Bivariate Pearson correlations were estimated between ADOS-2 comparison scores and four language and social skills measures. Additional correlations were estimated between LUI total scores and standard scores from nonlanguage measures. A series of Fisher's Z transformations were applied to evaluate whether bivariate correlations were significantly different. RESULTS: All four language and social skill measures were moderately to strongly associated with each other and ASD symptom severity scores. The correlation between ADOS-2 comparison scores and LUI total scores was significantly stronger than ADOS-2 correlations with all other measures. CONCLUSIONS: Our findings provide support for the LUI as a feasible, pragmatic language-targeted instrument for inclusion in early developmental evaluations prompted by language concerns. Administration of the LUI may accelerate earlier referral for a comprehensive assessment of ASD symptoms. Given the high correlation with ADOS-2 scores, an LUI total score in a clinical range of concern may encourage a clinician to refer families for a full diagnostic evaluation of ASD.

Assessment of Autism Spectrum Disorder.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in social interaction and communication and the presence of restricted interests and repetitive behaviors. The importance of early detection of ASD and subsequent early intervention is well documented. Efforts have been made over the years to clarify ASD diagnostic criteria and develop predictive, accurate screening tools and evidence-based, standardized diagnostic instruments to aid in the identification of ASD. In this article, we review the most recent changes in ASD diagnostic criteria in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision, summarize evidence-based instruments for ASD screening and diagnostic evaluations as well as the assessment of co-occurring conditions in ASD, the impact of COVID-19 on ASD assessment, and directions for future research in the field of ASD assessment.

Brief Report: Single and Repeat Screening with the Modified Checklist for Autism in Toddlers-Revised in Young Children at Higher Likelihood for Autism Spectrum Disorder.

PURPOSE: To compare the utility of single versus repeated autism screening in a sample at higher likelihood (HL) for ASD, following both screen positives and all screen negatives to diagnostic outcome. METHODS: Using a prospective infant sibling design, the current study followed 135 toddlers at HL for ASD and conducted diagnostic evaluations on the full sample at 18, 24, and 36 months. The psychometric properties of the M-CHAT-R using both concurrent and predictive diagnostic evaluations were compared in a group screened once (at 18 months only, n = 60) or twice (at both 18 and 24 months, n = 75). The study also examined consistency in reporting of ASD symptoms across the M-CHAT-R and a developmental concerns interview, comparing the HL group to a group with lower likelihood (LL) for ASD (n = 88). RESULTS: Sensitivity and specificity of the M-CHAT-R were high (75 - 95%), consistent with previous research. Positive predictive value (43 - 76%) was higher in this HL group than in previous community samples. Repeat screening improved sensitivity with little cost to specificity. At both 18 and 24 months, HL parents were more consistent in their reporting on the M-CHAT-R and a concerns interview than LL parents. CONCLUSION: The M-CHAT-R has strong psychometric properties when used with groups at HL for ASD, suggesting that scores over the screening cutoff of 3 should lead to prompt diagnostic evaluation referrals in children with older siblings on the spectrum.

A Comparative Analysis of the Full and Short Versions of the Social Responsiveness Scale in Estimating an Established Autism Risk Factor Association in ECHO: Do we Get the Same Estimates?

PURPOSE: Prior work developed a shortened 16-item version of the Social Responsiveness Scale (SRS), a quantitative measure of social communication and autism spectrum disorder (ASD)-related traits. However, its properties for use in risk factor estimation have not been fully tested compared to the full SRS. We compared the associations between gestational age (previously established risk factor for ASD) and the 65-item "full" and 16-item "short" versions of the SRS to test the shortened version's ability to capture associations in epidemiologic analyses of ASD risk factors. METHODS: We used data from participants in the Environmental influences on Child Health Outcomes (ECHO) Program (n = 2,760). SRS scores were collected via maternal/caregiver report when children were aged 2.5-18 years. We compared estimates of associations between gestational age and preterm birth between the full and short SRS using multivariable linear regression, quantile regression, and prediction methods. RESULTS: Overall, associations based on full and short SRS scores were highly comparable. For example, we observed positive associations between preterm birth with both full ([Formula: see text]=2.8; 95% CI [1.7, 4.0]) and short ([Formula: see text]=2.9; 95% CI [1.6, 4.3]) SRS scores. Quantile regression analyses indicated similar direction and magnitude of associations across the distribution of SRS scores between gestational age with both short and full SRS scores. CONCLUSION: The comparability in estimates obtained for full and short SRS scores with an "established" ASD risk factor suggests ability of the shortened SRS in assessing associations with potential ASD-related risk factors and has implications for large-scale research studies seeking to reduce participant burden.

Latent Class Analysis of Prenatal Substance Exposure and Child Behavioral Outcomes.

OBJECTIVES: To predict behavioral disruptions in middle childhood, we identified latent classes of prenatal substance use. STUDY DESIGN: As part of the Environmental influences on Child Health Outcomes Program, we harmonized prenatal substance use data and child behavior outcomes from 2195 women and their 6- to 11-year-old children across 10 cohorts in the US and used latent class-adjusted regression models to predict parent-rated child behavior. RESULTS: Three latent classes fit the data: low use (90.5%; n = 1986), primarily using no substances; licit use (6.6%; n = 145), mainly using nicotine with a moderate likelihood of using alcohol and marijuana; and illicit use (2.9%; n = 64), predominantly using illicit substances along with a moderate likelihood of using licit substances. Children exposed to primarily licit substances in utero had greater levels of externalizing behavior than children exposed to low or no substances (P = .001, d = .64). Children exposed to illicit substances in utero showed small but significant elevations in internalizing behavior than children exposed to low or no substances (P < .001, d = .16). CONCLUSIONS: The differences in prenatal polysubstance use may increase risk for specific childhood problem behaviors; however, child outcomes appeared comparably adverse for both licit and illicit polysubstance exposure. We highlight the need for similar multicohort, large-scale studies to examine childhood outcomes based on prenatal substance use profiles.

Case report: Transient symptoms of autism spectrum disorder in a 2-year-old boy.

Though early ASD diagnosis is highly stable, this case report describes a rare situation in which symptoms resolved without intervention over a 4 month period. We do not recommend delaying diagnosis in symptomatic children who meet criteria but when major behavioral changes are reported after diagnosis, reevaluation may be beneficial.

Factors related to retention in a longitudinal study of infants at familial risk for autism.

Background: Reporting retention data is critical to determining the soundness of a study's conclusions (internal validity) and broader generalizability (external validity). Although selective attrition can lead to overestimates of effects, biased conclusions, or overly expansive generalizations, retention rates are not reported in many longitudinal studies. Methods: We examined multiple child- and family-level factors potentially associated with retention in a longitudinal study of younger siblings of children with autism spectrum disorder (ASD; n = 304) or typical development (n = 163). The sample was followed from the first year of life to 36 months of age, for up to 7 visits. Results: Of the 467 infant siblings who were consented and participated in at least one research visit, 397 (85.0%) were retained to study completion at 36 months. Retention rates did not differ by familial risk group (ASD-risk vs. Low-risk), sex, race, ethnicity, age at enrollment, number of children in the family, maternal employment, marital status, or parent concerns about the child at enrollment. A stepwise regression model identified 4 variables that, together, provided the most parsimonious predictive model of study retention: maternal education, maternal age at child's birth, travel distance to the study site, and diagnostic outcome classification at the final study visit. Conclusions: The retained and not-retained groups did not differ on most demographic and clinical variables, suggesting few threats to internal and external validity. The significantly higher rate of retention of children diagnosed with ASD (95%) than typically developing children (83%) may, however, present biases when studying recurrence risk. We conclude by describing engagement and tracking methods that can be used to maximize retention in longitudinal studies of children at risk of ASD.

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.

Default mode and fronto-parietal network associations with IQ development across childhood in autism.

BACKGROUND: Intellectual disability affects approximately one third of individuals with autism spectrum disorder (autism). Yet, a major unresolved neurobiological question is what differentiates autistic individuals with and without intellectual disability. Intelligence quotients (IQs) are highly variable during childhood. We previously identified three subgroups of autistic children with different trajectories of intellectual development from early (2-3½ years) to middle childhood (9-12 years): (a) persistently high: individuals whose IQs remained in the normal range; (b) persistently low: individuals whose IQs remained in the range of intellectual disability (IQ < 70); and (c) changers: individuals whose IQs began in the range of intellectual disability but increased to the normal IQ range. The frontoparietal (FPN) and default mode (DMN) networks have established links to intellectual functioning. Here, we tested whether brain regions within the FPN and DMN differed volumetrically between these IQ trajectory groups in early childhood. METHODS: We conducted multivariate distance matrix regression to examine the brain regions within the FPN (11 regions x 2 hemispheres) and the DMN (12 regions x 2 hemispheres) in 48 persistently high (18 female), 108 persistently low (32 female), and 109 changers (39 female) using structural MRI acquired at baseline. FPN and DMN regions were defined using networks identified in Smith et al. (Proc Natl Acad Sci U S A 106:13040-5, 2009). IQ trajectory groups were defined by IQ measurements from up to three time points spanning early to middle childhood (mean age time 1: 3.2 years; time 2: 5.4 years; time 3: 11.3 years). RESULTS: The changers group exhibited volumetric differences in the DMN compared to both the persistently low and persistently high groups at time 1. However, the persistently high group did not differ from the persistently low group, suggesting that DMN structure may be an early predictor for change in IQ trajectory. In contrast, the persistently high group exhibited differences in the FPN compared to both the persistently low and changers groups, suggesting differences related more to concurrent IQ and the absence of intellectual disability. CONCLUSIONS: Within autism, volumetric differences of brain regions within the DMN in early childhood may differentiate individuals with persistently low IQ from those with low IQ that improves through childhood. Structural differences in brain networks between these three IQ-based subgroups highlight distinct neural underpinnings of these autism sub-phenotypes.

Maternal Serum and Placental Metabolomes in Association with Prenatal Phthalate Exposure and Neurodevelopmental Outcomes in the MARBLES Cohort.

Prenatal exposure to phthalates, a family of endocrine-disrupting plasticizers, is associated with disruption of maternal metabolism and impaired neurodevelopment. We investigated associations between prenatal phthalate exposure and alterations of both the maternal third trimester serum metabolome and the placental metabolome at birth, and associations of these with child neurodevelopmental outcomes using data and samples from the Markers of Autism Risk in Babies Learning Early Signs (MARBLES) cohort. The third trimester serum (n = 106) and placental (n = 132) metabolomes were investigated using 1H nuclear magnetic resonance spectroscopy. Children were assessed clinically for autism spectrum disorder (ASD) and cognitive development. Although none of the urinary phthalate metabolite concentrations were associated with maternal serum metabolites after adjustment for covariates, mixture analysis using quantile g-computation revealed alterations in placental metabolites with increasing concentrations of phthalate metabolites that included reduced concentrations of 2-hydoxybutyrate, carnitine, O-acetylcarnitine, glucitol, and N-acetylneuraminate. Child neurodevelopmental outcome was not associated with the third trimester serum metabolome, but it was correlated with the placental metabolome in male children only. Maternal phthalate exposure during pregnancy is associated with differences in the placental metabolome at delivery, and the placental metabolome is associated with neurodevelopmental outcomes in males in a cohort with high familial ASD risk.

Social orienting and initiated joint attention behaviors in 9 to 12 month old children with autism spectrum disorder: A family home movies study.

According to the Social Motivation model children with autism show deficits in social orienting (looking at faces and responding to name) at the end of their first year of life. In this model, those deficits are both the earliest behavioral consequences of an alteration in the dopamine reward system balance and the foundation of the social impairments that characterize this neurodevelopmental disorder. The current study tests two of the main predictions of this model: that social orienting deficits are the first behavioral manifestation of autism, and that they are developmentally related to joint attention deficits. We retrospectively analyzed family home movies of 9- to 12-month-old infants, 29 of whom were later diagnosed with autism and 16 of whom were typically developing. After confirming that the videotapes of both groups were similar in content of the scenes recorded (contexts, type of social activity, etc.), we compared their social orienting (social gaze and responding to name) and joint attention behaviors (gaze alternation and gestures). No significant differences between groups were found in looking at faces, but the group with autism showed deficits in responding to name and initiations of joint attention (IJA). Looking at people was not significantly correlated with IJA behaviors, but response to name was. The lack of group differences in looking at faces between 9 and 12 months, and the existence of IJA difficulties in the ASD group without concurrent impairment in looking at faces, do not support predictions of the Social Motivation model. LAY SUMMARY: Various theories have been proposed to explain the emergence of autism symptoms early in life. This study tested two key predictions of the Social Motivation model. Comparing family movies of children 9- to 12-months-old later diagnosed with autism or with typical development, we did not observe difficulties in looking at other people's faces but children with autism responded to name and used gaze and gestures to direct the adult's attention to events of interest less frequently. This absence of difficulties in looking at faces does not fit with what the Social Motivation model of autism predicts and therefore we must develop alternative explanations.

Placental methylome reveals a 22q13.33 brain regulatory gene locus associated with autism.

BACKGROUND: Autism spectrum disorder (ASD) involves complex genetics interacting with the perinatal environment, complicating the discovery of common genetic risk. The epigenetic layer of DNA methylation shows dynamic developmental changes and molecular memory of in utero experiences, particularly in placenta, a fetal tissue discarded at birth. However, current array-based methods to identify novel ASD risk genes lack coverage of the most structurally and epigenetically variable regions of the human genome. RESULTS: We use whole genome bisulfite sequencing in placenta samples from prospective ASD studies to discover a previously uncharacterized ASD risk gene, LOC105373085, renamed NHIP. Out of 134 differentially methylated regions associated with ASD in placental samples, a cluster at 22q13.33 corresponds to a 118-kb hypomethylated block that replicates in two additional cohorts. Within this locus, NHIP is functionally characterized as a nuclear peptide-encoding transcript with high expression in brain, and increased expression following neuronal differentiation or hypoxia, but decreased expression in ASD placenta and brain. NHIP overexpression increases cellular proliferation and alters expression of genes regulating synapses and neurogenesis, overlapping significantly with known ASD risk genes and NHIP-associated genes in ASD brain. A common structural variant disrupting the proximity of NHIP to a fetal brain enhancer is associated with NHIP expression and methylation levels and ASD risk, demonstrating a common genetic influence. CONCLUSIONS: Together, these results identify and initially characterize a novel environmentally responsive ASD risk gene relevant to brain development in a hitherto under-characterized region of the human genome.

Patterns of objectively measured motor activity among infants developing ASD and concerns for ADHD.

BACKGROUND: Heightened motor activity is a hallmark of attention-deficit/hyperactivity disorder (ADHD), yet high activity levels are also often reported in young children with autism spectrum disorder (ASD). It is currently unclear whether increased motor activity represents a distinct versus shared early predictor of ASD and ADHD; no prior studies have directly examined this prospectively. We investigated differences in longitudinal patterns of objectively measured motor activity during early development. METHODS: Participants included 113 infants at high and low risk for ASD or ADHD. Continuous motion-based activity was recorded using tri-axial accelerometers at 12, 18, 24, and 36 months of age. At 36 months, participants were categorized into one of three outcome groups: ASD (n = 19), ADHD Concerns (n = 17), and Typically Developing (TD; n = 77). Group differences in trajectories of motor activity were examined in structured and semistructured contexts. Associations with behaviors relevant to ASD, ADHD, and general development were also examined. RESULTS: In both structured and semistructured contexts, both the ASD and ADHD Concerns groups exhibited heightened activity relative to the TD group by 18 months; the ASD group exhibited higher activity than the ADHD Concerns group at 24-36 months in the structured context only. Attention/behavior regulation, nonverbal, and verbal development-but not social engagement-were differentially associated with objectively measured activity by outcome group across contexts. CONCLUSIONS: Overactivity may be a shared, rather than distinct, precursor of atypical development in infants/toddlers developing ASD and concerns for ADHD, emerging as early as 18 months. Group differences in overactivity may be context-specific and associated with different underlying mechanisms.

Machine Learning Based Autism Spectrum Disorder Detection from Videos.

Early diagnosis of Autism Spectrum Disorder (ASD) is crucial for best outcomes to interventions. In this paper, we present a machine learning (ML) approach to ASD diagnosis based on identifying specific behaviors from videos of infants of ages 6 through 36 months. The behaviors of interest include directed gaze towards faces or objects of interest, positive affect, and vocalization. The dataset consists of 2000 videos of 3-minute duration with these behaviors manually coded by expert raters. Moreover, the dataset has statistical features including duration and frequency of the above mentioned behaviors in the video collection as well as independent ASD diagnosis by clinicians. We tackle the ML problem in a two-stage approach. Firstly, we develop deep learning models for automatic identification of clinically relevant behaviors exhibited by infants in a one-on-one interaction setting with parents or expert clinicians. We report baseline results of behavior classification using two methods: (1) image based model (2) facial behavior features based model. We achieve 70% accuracy for smile, 68% accuracy for look face, 67% for look object and 53% accuracy for vocalization. Secondly, we focus on ASD diagnosis prediction by applying a feature selection process to identify the most significant statistical behavioral features and a over and under sampling process to mitigate the class imbalance, followed by developing a baseline ML classifier to achieve an accuracy of 82% for ASD diagnosis.

Repetitive behavior with objects in infants developing autism predicts diagnosis and later social behavior as early as 9 months.

We evaluated repetitive behavior with objects in infants at risk for autism spectrum disorder (ASD) from 9 to 36 months of age, and associations between early repetitive behavior and social engagement. Infant siblings of children with ASD (high-risk) or typical development (low-risk) were administered a task eliciting repetitive object use at 9, 12, 15, 18, 24, and 36 months of age. Infants (n = 147) were classified into 1 of 3 outcome groups at 36 months: Low-Risk Non-ASD (n = 58), High-Risk Non-ASD (n = 72), and ASD (n = 17). Behavior was coded from video for frequencies of unusual visual inspection, spinning, and rotating behaviors. Differences in unusual visual inspection were most prominent, consistent, and present earliest: At 9 months, the ASD group engaged in this behavior more frequently than both other groups, persisting through 36 months. Differences in frequencies of spinning and rotating were later-appearing, more time-limited, and/or related to familial ASD risk rather than ultimate diagnosis. Sensitivity and specificity estimates for the presence of unusual visual inspection at 9 months of age were in the moderate range (.60 and .68, respectively) for ASD versus Low-Risk Non-ASD comparisons, generally increasing over time. Unusual visual inspection at 9 months predicted 12-month social behavior controlling for 9-month social behavior, but not vice versa, with no evidence of moderation by ASD diagnosis. In summary, unusual visual inspection of objects is present and stable by 9 months of age in infants developing ASD and predicts reduced social engagement three-months later. Close monitoring of this behavior may aid early detection. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Altered Gray-White Matter Boundary Contrast in Toddlers at Risk for Autism Relates to Later Diagnosis of Autism Spectrum Disorder.

BACKGROUND: Recent neuroimaging studies have highlighted differences in cerebral maturation in individuals with autism spectrum disorder (ASD) in comparison to typical development. For instance, the contrast of the gray-white matter boundary is decreased in adults with ASD. To determine how gray-white matter boundary integrity relates to early ASD phenotypes, we used a regional structural MRI index of gray-white matter contrast (GWC) on a sample of toddlers with a hereditary high risk for ASD. MATERIALS AND METHODS: We used a surface-based approach to compute vertex-wise GWC in a longitudinal cohort of toddlers at high-risk for ASD imaged twice between 12 and 24 months (n = 20). A full clinical assessment of ASD-related symptoms was performed in conjunction with imaging and again at 3 years of age for diagnostic outcome. Three outcome groups were defined (ASD, n = 9; typical development, n = 8; non-typical development, n = 3). RESULTS: ASD diagnostic outcome at age 3 was associated with widespread increases in GWC between age 12 and 24 months. Many cortical regions were affected, including regions implicated in social processing and language acquisition. In parallel, we found that early onset of ASD symptoms (i.e., prior to 18-months) was specifically associated with slower GWC rates of change during the second year of life. These alterations were found in areas mainly belonging to the central executive network. LIMITATIONS: Our study is the first to measure maturational changes in GWC in toddlers who developed autism, but given the limited size of our sample results should be considered exploratory and warrant further replication in independent and larger samples. CONCLUSION: These preliminary results suggest that ASD is linked to early alterations of the gray-white matter boundary in widespread brain regions. Early onset of ASD diagnosis constitutes an independent clinical parameter associated with a specific corresponding neurobiological developmental trajectory. Altered neural migration and/or altered myelination processes potentially explain these findings.

The Early Screening for Autism and Communication Disorders: Field-testing an autism-specific screening tool for children 12 to 36 months of age.

LAY ABSTRACT: There is a critical need for accurate screening tools for autism spectrum disorder in very young children so families can access tailored intervention services as early as possible. However, there are few screeners designed for children 18-24 months. Developing screeners that pick up on the signs of autism spectrum disorder in very young children has proved even more challenging. In this study, we examined a new autism-specific parent-report screening tool, the Early Screening for Autism and Communication Disorders for children between 12 and 36 months of age. Field-testing was done in five sites with 471 children screened for communication delays in primary care or referred for familial risk or concern for autism spectrum disorder. The Early Screening for Autism and Communication Disorders was tested in three age groups: 12-17, 18-23, and 24-36 months. A best-estimate diagnosis of autism spectrum disorder, developmental delay, or typical development was made. Analyses examined all 46 items and identified 30 items that best discriminated autism spectrum disorder from the non-spectrum groups. Cutoffs were established for each age group with good sensitivity and specificity. Results provide preliminary support for the accuracy of the Early Screening for Autism and Communication Disorders as an autism-specific screener in children 12-36 months with elevated risk of communication delay or autism spectrum disorder.