Atypical functional connectivity between the amygdala and visual, salience regions in infants with genetic liability for autism.

The amygdala undergoes a period of overgrowth in the first year of life, resulting in enlarged volume by 12 months in infants later diagnosed with ASD. The overgrowth of the amygdala may have functional consequences during infancy. We investigated whether amygdala connectivity differs in 12-month-olds at high likelihood (HL) for ASD (defined by having an older sibling with autism), compared to those at low likelihood (LL). We examined seed-based connectivity of left and right amygdalae, hypothesizing that the HL and LL groups would differ in amygdala connectivity, especially with the visual cortex, based on our prior reports demonstrating that components of visual circuitry develop atypically and are linked to genetic liability for autism. We found that HL infants exhibited weaker connectivity between the right amygdala and the left visual cortex, as well as between the left amygdala and the right anterior cingulate, with evidence that these patterns occur in distinct subgroups of the HL sample. Amygdala connectivity strength with the visual cortex was related to motor and communication abilities among HL infants. Findings indicate that aberrant functional connectivity between the amygdala and visual regions is apparent in infants with genetic liability for ASD and may have implications for early differences in adaptive behaviors.

Associations between early trajectories of amygdala development and later school-age anxiety in two longitudinal samples.

Amygdala function is implicated in the pathogenesis of autism spectrum disorder (ASD) and anxiety. We investigated associations between early trajectories of amygdala growth and anxiety and ASD outcomes at school age in two longitudinal studies: high- and low-familial likelihood for ASD, Infant Brain Imaging Study (IBIS, n = 257) and typically developing (TD) community sample, Early Brain Development Study (EBDS, n = 158). Infants underwent MRI scanning at up to 3 timepoints from neonate to 24 months. Anxiety was assessed at 6-12 years. Linear multilevel modeling tested whether amygdala volume growth was associated with anxiety symptoms at school age. In the IBIS sample, children with higher anxiety showed accelerated amygdala growth from 6 to 24 months. ASD diagnosis and ASD familial likelihood were not significant predictors. In the EBDS sample, amygdala growth from birth to 24 months was associated with anxiety. More anxious children had smaller amygdala volume and slower rates of amygdala growth. We explore reasons for the contrasting results between high-familial likelihood for ASD and TD samples, grounding results in the broader literature of variable associations between early amygdala volume and later anxiety. Results have the potential to identify mechanisms linking early amygdala growth to later anxiety in certain groups.

Why are only some children with autism spectrum disorder misclassified by the social communication questionnaire? An empirical investigation of individual differences in sensitivity and specificity in a clinic-referred sample.

BACKGROUND: The Social Communication Questionnaire (SCQ) is a checklist for autism spectrum disorder (ASD) commonly used in research and clinical practice. While the original validation study suggested that the SCQ was an accurate ASD screener with satisfactory sensitivity and specificity, subsequent studies have yielded mixed results, with some revealing low sensitivity, low specificity, and low utility in some settings. METHOD: The present study examined the psychometric properties of the SCQ as well as the individual difference characteristics of 187 individuals with and without autism spectrum disorder (ASD) who were misclassified or accurately classified by the SCQ in a clinic-referred sample. RESULTS: The SCQ showed suboptimal sensitivity and specificity, regardless of age and sex. Compared to true positives, individuals classified as false positives displayed greater externalizing and internalizing problems, whereas individuals classified as false negatives displayed better social communication and adaptive skills. CONCLUSIONS: The findings suggest that non-autistic developmental and behavioral individual difference characteristics may explain high rates of misclassification using the SCQ. Clinicians and researchers could consider using the SCQ in combination with other tools for young children with internalizing and externalizing symptoms and other more complex clinical presentations.

Encouraging a Peer in Need: The Impacts of Social Anxiety and Peer Familiarity.

Extant research has produced conflicting findings regarding the link between social fearfulness and prosocial behavior, with some studies reporting negative relations and others reporting null effects. Furthermore, these studies have focused predominantly on toddlerhood, and few have examined prosociality between peers. The present study investigated whether the link between social anxiety and a prosocial behavior (i.e., providing encouragement) varied depending on interpersonal and situational factors (i.e., one's familiarity with a peer, the level of support sought by a peer, respectively). We tested this question using a multimethod approach, which included an ecologically valid stress inducing task and dyadic design with a sample of 9- to 10-year-olds (N = 447). Results revealed that social anxiety was related negatively to providing encouragement among familiar and unfamiliar dyads. In familiar dyads, however, this main effect was qualified by an interaction with the level of support sought by one's peer. Compared to those low in social anxiety, children high in social anxiety provided relatively less encouragement in response to higher levels of support seeking from their peers. The findings are considered in relation to theorizing regarding the effect of overarousal on children's prosocial behavior.

Association of Sex With Neurobehavioral Markers of Executive Function in 2-Year-Olds at High and Low Likelihood of Autism.

Importance: Children with autism and their siblings exhibit executive function (EF) deficits early in development, but associations between EF and biological sex or early brain alterations in this population are largely unexplored. Objective: To investigate the interaction of sex, autism likelihood group, and structural magnetic resonance imaging alterations on EF in 2-year-old children at high familial likelihood (HL) and low familial likelihood (LL) of autism, based on having an older sibling with autism or no family history of autism in first-degree relatives. Design, Setting, and Participants: This prospective cohort study assessed 165 toddlers at HL (n = 110) and LL (n = 55) of autism at 4 university-based research centers. Data were collected from January 1, 2007, to December 31, 2013, and analyzed between August 2021 and June 2022 as part of the Infant Brain Imaging Study. Main Outcomes and Measures: Direct assessments of EF and acquired structural magnetic resonance imaging were performed to determine frontal lobe, parietal lobe, and total cerebral brain volume. Results: A total of 165 toddlers (mean [SD] age, 24.61 [0.95] months; 90 [54%] male, 137 [83%] White) at HL for autism (n = 110; 17 diagnosed with ASD) and LL for autism (n = 55) were studied. The toddlers at HL for autism scored lower than the toddlers at LL for autism on EF tests regardless of sex (mean [SE] B = -8.77 [4.21]; 95% CI, -17.09 to -0.45; η2p = 0.03). With the exclusion of toddlers with autism, no group (HL vs LL) difference in EF was found in boys (mean [SE] difference, -7.18 [4.26]; 95% CI, 1.24-15.59), but EF was lower in HL girls than LL girls (mean [SE] difference, -9.75 [4.34]; 95% CI, -18.32 to -1.18). Brain-behavior associations were examined, controlling for overall cerebral volume and developmental level. Sex differences in EF-frontal (B [SE] = 16.51 [7.43]; 95% CI, 1.36-31.67; η2p = 0.14) and EF-parietal (B [SE] = 17.68 [6.99]; 95% CI, 3.43-31.94; η2p = 0.17) associations were found in the LL group but not the HL group (EF-frontal: B [SE] = -1.36 [3.87]; 95% CI, -9.07 to 6.35; η2p = 0.00; EF-parietal: B [SE] = -2.81 [4.09]; 95% CI, -10.96 to 5.34; η2p = 0.01). Autism likelihood group differences in EF-frontal (B [SE] = -9.93 [4.88]; 95% CI, -19.73 to -0.12; η2p = 0.08) and EF-parietal (B [SE] = -15.44 [5.18]; 95% CI, -25.86 to -5.02; η2p = 0.16) associations were found in girls not boys (EF-frontal: B [SE] = 6.51 [5.88]; 95% CI, -5.26 to 18.27; η2p = 0.02; EF-parietal: B [SE] = 4.18 [5.48]; 95% CI, -6.78 to 15.15; η2p = 0.01). Conclusions and Relevance: This cohort study of toddlers at HL and LL of autism suggests that there is an association between sex and EF and that brain-behavior associations in EF may be altered in children at HL of autism. Furthermore, EF deficits may aggregate in families, particularly in girls.

Quantifying latent social motivation and its associations with joint attention and language in infants at high and low likelihood for autism spectrum disorder.

Social motivation-the psychobiological predisposition for social orienting, seeking social contact, and maintaining social interaction-manifests in early infancy and is hypothesized to be foundational for social communication development in typical and atypical populations. However, the lack of infant social-motivation measures has hindered delineation of associations between infant social motivation, other early-arising social abilities such as joint attention, and language outcomes. To investigate how infant social motivation contributes to joint attention and language, this study utilizes a mixed longitudinal sample of 741 infants at high (HL = 515) and low (LL = 226) likelihood for ASD. Using moderated nonlinear factor analysis (MNLFA), we incorporated items from parent-report measures to establish a novel latent factor model of infant social motivation that exhibits measurement invariance by age, sex, and familial ASD likelihood. We then examined developmental associations between 6- and 12-month social motivation, joint attention at 12-15 months, and language at 24 months of age. On average, greater social-motivation growth from 6-12 months was associated with greater initiating joint attention (IJA) and trend-level increases in sophistication of responding to joint attention (RJA). IJA and RJA were both positively associated with 24-month language abilities. There were no additional associations between social motivation and future language in our path model. These findings substantiate a novel, theoretically driven approach to modeling social motivation and suggest a developmental cascade through which social motivation impacts other foundational skills. These findings have implications for the timing and nature of intervention targets to support social communication development in infancy. HIGHLIGHTS: We describe a novel, theoretically based model of infant social motivation wherein multiple parent-reported indicators contribute to a unitary latent social-motivation factor. Analyses revealed social-motivation factor scores exhibited measurement invariance for a longitudinal sample of infants at high and low familial ASD likelihood. Social-motivation growth from ages 6-12 months is associated with better 12-15-month joint attention abilities, which in turn are associated with greater 24-month language skills. Findings inform timing and targets of potential interventions to support healthy social communication in the first year of life.

Corrigendum: Bias in measurement of autism symptoms by spoken language level and non-verbal mental age in minimally verbal children with neurodevelopmental disorders.

[This corrects the article DOI: 10.3389/fpsyg.2022.927847.].

Social motivation in infancy is associated with familial recurrence of ASD.

Pre-diagnostic deficits in social motivation are hypothesized to contribute to autism spectrum disorder (ASD), a heritable neurodevelopmental condition. We evaluated psychometric properties of a social motivation index (SMI) using parent-report item-level data from 597 participants in a prospective cohort of infant siblings at high and low familial risk for ASD. We tested whether lower SMI scores at 6, 12, and 24 months were associated with a 24-month ASD diagnosis and whether social motivation's course differed relative to familial ASD liability. The SMI displayed good internal consistency and temporal stability. Children diagnosed with ASD displayed lower mean SMI T-scores at all ages and a decrease in mean T-scores across age. Lower group-level 6-month scores corresponded with higher familial ASD liability. Among high-risk infants, strong decline in SMI T-scores was associated with 10-fold odds of diagnosis. Infant social motivation is quantifiable by parental report, differentiates children with versus without later ASD by age 6 months, and tracks with familial ASD liability, consistent with a diagnostic and susceptibility marker of ASD. Early decrements and decline in social motivation indicate increased likelihood of ASD, highlighting social motivation's importance to risk assessment and clarification of the ontogeny of ASD.

Bias in measurement of autism symptoms by spoken language level and non-verbal mental age in minimally verbal children with neurodevelopmental disorders.

Increasing numbers of children with known genetic conditions and/or intellectual disability are referred for evaluation of autism spectrum disorder (ASD), highlighting the need to refine autism symptom measures to facilitate differential diagnoses in children with cognitive and language impairments. Previous studies have reported decreased specificity of ASD screening and diagnostic measures in children with intellectual disability. However, little is known about how cognitive and language abilities impact the measurement of specific ASD symptoms in this group. We aggregated a large sample of young children (N = 1196; aged 31-119 months) to examine measurement invariance of ASD symptoms among minimally verbal children within the context of the Autism Diagnostic Observation Schedule (ADOS) Module 1. Using confirmatory factor analysis (CFA) and moderated non-linear factor analysis (MNLFA), we examined how discrete behaviors were differentially associated with the latent symptom domains of social communication impairments (SCI) and restricted and repetitive behaviors (RRB) across spoken language levels and non-verbal mental age groupings. While the two-factor structure of SCI and RRB held consistently across language and cognitive levels, only partial invariance was observed for both ASD symptom domains of SCI and RRB. Specifically, four out of the 15 SCI items and one out of the three RRB items examined showed differential item functioning between children with "Few to No Words" and those with "Some Words"; and one SCI item and one RRB item showed differential item functioning across non-verbal mental age groups. Moreover, even after adjusting for the differential item functioning to reduce measurement bias across groups, there were still differences in ASD symptom domain scores across spoken language levels. These findings further underscore the influence of spoken language level on measurement of ASD symptoms and the importance of measuring ASD symptoms within refined spoken language levels, even among those with minimal verbal abilities.

A Data-Driven Approach in an Unbiased Sample Reveals Equivalent Sex Ratio of Autism Spectrum Disorder-Associated Impairment in Early Childhood.

BACKGROUND: Sex differences in the prevalence of neurodevelopmental disorders are particularly evident in autism spectrum disorder (ASD). Heterogeneous symptom presentation and the potential of measurement bias hinder early ASD detection in females and may contribute to discrepant prevalence estimates. We examined trajectories of social communication (SC) and restricted and repetitive behaviors (RRBs) in a sample of infant siblings of children with ASD, adjusting for age- and sex-based measurement bias. We hypothesized that leveraging a prospective elevated familial likelihood sample, deriving data-driven behavioral constructs, and accounting for measurement bias would reveal less discrepant sex ratios than are typically seen in ASD. METHODS: We conducted direct assessments of ASD symptoms at 6 to 9, 12 to 15, 24, and 36 to 60 months of age (total nobservations = 1254) with infant siblings of children with ASD (n = 377) and a lower ASD-familial-likelihood comparison group (n = 168; nobservations = 527). We established measurement invariance across age and sex for separate models of SC and RRB. We then conducted latent class growth mixture modeling with the longitudinal data and evaluated for sex differences in trajectory membership. RESULTS: We identified 2 latent classes in the SC and RRB models with equal sex ratios in the high-concern cluster for both SC and RRB. Sex differences were also observed in the SC high-concern cluster, indicating that girls classified as having elevated social concerns demonstrated milder symptoms than boys in this group. CONCLUSIONS: This novel approach for characterizing ASD symptom progression highlights the utility of assessing and adjusting for sex-related measurement bias and identifying sex-specific patterns of symptom emergence.

Subcortical Brain Development in Autism and Fragile X Syndrome: Evidence for Dynamic, Age- and Disorder-Specific Trajectories in Infancy.

OBJECTIVE: Previous research has demonstrated that the amygdala is enlarged in children with autism spectrum disorder (ASD). However, the precise onset of this enlargement during infancy, how it relates to later diagnostic behaviors, whether the timing of enlargement in infancy is specific to the amygdala, and whether it is specific to ASD (or present in other neurodevelopmental disorders, such as fragile X syndrome) are all unknown. METHODS: Longitudinal MRIs were acquired at 6-24 months of age in 29 infants with fragile X syndrome, 58 infants at high likelihood for ASD who were later diagnosed with ASD, 212 high-likelihood infants not diagnosed with ASD, and 109 control infants (1,099 total scans). RESULTS: Infants who developed ASD had typically sized amygdala volumes at 6 months, but exhibited significantly faster amygdala growth between 6 and 24 months, such that by 12 months the ASD group had significantly larger amygdala volume (Cohen's d=0.56) compared with all other groups. Amygdala growth rate between 6 and 12 months was significantly associated with greater social deficits at 24 months when the infants were diagnosed with ASD. Infants with fragile X syndrome had a persistent and significantly enlarged caudate volume at all ages between 6 and 24 months (d=2.12), compared with all other groups, which was significantly associated with greater repetitive behaviors. CONCLUSIONS: This is the first MRI study comparing fragile X syndrome and ASD in infancy, demonstrating strikingly different patterns of brain and behavior development. Fragile X syndrome-related changes were present from 6 months of age, whereas ASD-related changes unfolded over the first 2 years of life, starting with no detectable group differences at 6 months. Increased amygdala growth rate between 6 and 12 months occurs prior to social deficits and well before diagnosis. This gradual onset of brain and behavior changes in ASD, but not fragile X syndrome, suggests an age- and disorder-specific pattern of cascading brain changes preceding autism diagnosis.

Are early social communication skills a harbinger for language development in infants later diagnosed autistic?-A longitudinal study using a standardized social communication assessment.

The early emergence of social communication challenges and their impact on language in infants later diagnosed with autism has sparked many early intervention programs that target social communication skills. While research has consistently shown lower scores on social communication assessments in the first year of life, there is limited research at 12-months exploring associations between different dimensions of social communication and later language. Understanding associations between early social communication skills and language would enhance our ability to choose high priority intervention goals that will impact downstream language skills. The current study used a standardized assessment to profile social communication skills across 516 infants with a high (HL) or low likelihood (LL-Neg) for autism (84% White, 60% Male), based on the presence of a sibling with autism in the family. The primary aim of the study was to profile social communication skill development in the second year of life and to evaluate associations between social communication skills and later language. HL infants who met criteria for autism (HL-ASD, N = 81) demonstrated widespread reductions in social communication skills at 12-months compared to HL infants who did not meet criteria for autism (HL-Neg, N = 277) and LL-Neg (N = 158) infants. Across all infants in the study, those with better social communication skills at 12-months had better language at 24-months. However, within group analyses indicated that infants who met criteria for autism did not show this developmental coupling until 24-months-of-age at which point social communication was positively associated with downstream language skills. The cascading pattern of reduced social communication skills as well as overall significant positive associations with later language provide further evidence for the need to support developing social communication skills prior to formal autism diagnosis, a goal that could possibly be reached through pre-emptive interventions.

Longitudinal Prediction of Infant MR Images With Multi-Contrast Perceptual Adversarial Learning.

The infant brain undergoes a remarkable period of neural development that is crucial for the development of cognitive and behavioral capacities (Hasegawa et al., 2018). Longitudinal magnetic resonance imaging (MRI) is able to characterize the developmental trajectories and is critical in neuroimaging studies of early brain development. However, missing data at different time points is an unavoidable occurrence in longitudinal studies owing to participant attrition and scan failure. Compared to dropping incomplete data, data imputation is considered a better solution to address such missing data in order to preserve all available samples. In this paper, we adapt generative adversarial networks (GAN) to a new application: longitudinal image prediction of structural MRI in the first year of life. In contrast to existing medical image-to-image translation applications of GANs, where inputs and outputs share a very close anatomical structure, our task is more challenging as brain size, shape and tissue contrast vary significantly between the input data and the predicted data. Several improvements over existing GAN approaches are proposed to address these challenges in our task. To enhance the realism, crispness, and accuracy of the predicted images, we incorporate both a traditional voxel-wise reconstruction loss as well as a perceptual loss term into the adversarial learning scheme. As the differing contrast changes in T1w and T2w MR images in the first year of life, we incorporate multi-contrast images leading to our proposed 3D multi-contrast perceptual adversarial network (MPGAN). Extensive evaluations are performed to assess the qualityand fidelity of the predicted images, including qualitative and quantitative assessments of the image appearance, as well as quantitative assessment on two segmentation tasks. Our experimental results show that our MPGAN is an effective solution for longitudinal MR image data imputation in the infant brain. We further apply our predicted/imputed images to two practical tasks, a regression task and a classification task, in order to highlight the enhanced task-related performance following image imputation. The results show that the model performance in both tasks is improved by including the additional imputed data, demonstrating the usability of the predicted images generated from our approach.

Cataloguing and characterizing interests in typically developing toddlers and toddlers who develop ASD.

Intense interests are common in children with and without autism spectrum disorder (ASD), and little research has characterized aspects of interests that are unique to or shared among children with and without ASD. We aimed to characterize interests in a sample of infants at high-familial-risk (HR) and low-familial-risk (LR) for ASD using a novel interview. Participants included HR siblings who were diagnosed with ASD at 24 months (HR-ASD, n = 56), HR siblings who did not receive an ASD diagnosis at 24 months (HR-Neg, n = 187), and a LR comparison group (n = 109). We developed and collected data with the Intense Interests Inventory at 18- and 24-months of age, a semi-structured interview that measures intensity and peculiarity of interests in toddlers and preschool-aged children. Intensity of interests differed by familial risk at 24 months, with HR-ASD and HR-Neg groups demonstrating equivalent intensity of interests that were higher than the LR group. By contrast, peculiarity of interest differed by ASD diagnosis, with the HR-ASD group showing more peculiar interests than the HR-Neg and LR groups at 24 months. At 18 months the HR-ASD group had more peculiar interests than the LR group, though no differences emerged in intensity of interests. This measure may be useful in identifying clinically-relevant features of interests in young children with ASD. We also replicated previous findings of males showing more intense interests at 18 months in our non-ASD sample. These results reveal new information about the nature of interests and preoccupations in the early autism phenotype. LAY SUMMARY: Intense interests are common in young children with autism and their family members. Intense interests are also prevalent among typically-developing children, and especially boys. Here we catalog interests and features of these interests in a large sample of toddlers enriched for autism risk. Children who had family members with autism had more intense interests, and those who developed autism themselves had more unusual interests at 24 months. These results highlight the importance of different aspects of interest in autism.

Towards a Data-Driven Approach to Screen for Autism Risk at 12 Months of Age.

OBJECTIVE: This study aimed to develop a classifier for infants at 12 months of age based on a parent-report measure (the First Year Inventory 2.0 [FYI]), for the following reasons: (1) to classify infants at elevated risk, above and beyond that attributable to familial risk status for ASD; and (2) to serve as a starting point to refine an approach for risk estimation in population samples. METHOD: A total of 54 high-familial risk (HR) infants later diagnosed with ASD (HR-ASD), 183 HR infants not diagnosed with ASD at 24 months of age (HR-Neg), and 72 low-risk controls participated in the study. All infants contributed FYI data at 12 months of age and had a diagnostic assessment for ASD at age 24 months. A data-driven, cross-validated analytic approach was used to develop a classifier to determine screening accuracy (eg, sensitivity) of the FYI to classify HR-ASD and HR-Neg. RESULTS: The newly developed FYI classifier had an estimated sensitivity of 0.71 (95% CI: 0.50, 0.91) and specificity of 0.72 (95% CI: 0.49, 0.91). CONCLUSION: This classifier demonstrates the potential to improve current screening for ASD risk at 12 months of age in infants already at elevated familial risk for ASD, increasing opportunities for detection of autism risk in infancy. Findings from this study highlight the utility of combining parent-report measures with machine learning approaches.

Neural Responses to a Putative Set-shifting Task in Children with Autism Spectrum Disorder.

While much progress has been made toward understanding the neurobiology of social and communication deficits associated with autism spectrum disorder (ASD), less is known regarding the neurobiological basis of restricted and repetitive behaviors (RRBs) central to the ASD diagnosis. Symptom severity for RRBs in ASD is associated with cognitive inflexibility. Thus, understanding the neural mechanisms underlying cognitive inflexibility in ASD is critical for tailoring therapies to treat this understudied yet pervasive symptom. Here we used a set-shifting paradigm adopted from the developmental cognitive neuroscience literature involving flexible switching between stimulus categories to examine task performance and neural responses in children with ASD. Behaviorally, we found little evidence for group differences in performance on the set-shifting task. Compared with typically developing children, children with ASD exhibited greater activation of the parahippocampal gyrus during performance on trials requiring switching. These findings suggest that children with ASD may need to recruit memory-based neural systems to a greater degree when learning to flexibly associate stimuli with responses. LAY SUMMARY: Children with autism often struggle to behave in a flexible way when faced with unexpected challenges. We examined brain responses during a task thought to involve flexible thinking and found that compared with typically developing children, those with autism relied more on brain areas involved in learning and memory to complete the task. This study helps us to understand what types of cognitive tasks are best suited for exploring the neural basis of cognitive flexibility in children with autism. Autism Res 2020, 13: 1501-1515. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Quantitative trait variation in ASD probands and toddler sibling outcomes at 24 months.

BACKGROUND: Younger siblings of children with autism spectrum disorder (ASD) are at increased likelihood of receiving an ASD diagnosis and exhibiting other developmental concerns. It is unknown how quantitative variation in ASD traits and broader developmental domains in older siblings with ASD (probands) may inform outcomes in their younger siblings. METHODS: Participants included 385 pairs of toddler siblings and probands from the Infant Brain Imaging Study. ASD probands (mean age 5.5 years, range 1.7 to 15.5 years) were phenotyped using the Autism Diagnostic Interview-Revised (ADI-R), the Social Communication Questionnaire (SCQ), and the Vineland Adaptive Behavior Scales, Second Edition (VABS-II). Siblings were assessed using the ADI-R, VABS-II, Mullen Scales of Early Learning (MSEL), and Autism Diagnostic Observation Schedule (ADOS) and received a clinical best estimate diagnosis at 24 months using DSM-IV-TR criteria (n = 89 concordant for ASD; n = 296 discordant). We addressed two aims: (1) to determine whether proband characteristics are predictive of recurrence in siblings and (2) to assess associations between proband traits and sibling dimensional outcomes at 24 months. RESULTS: Regarding recurrence risk, proband SCQ scores were found to significantly predict sibling 24-month diagnostic outcome (OR for a 1-point increase in SCQ = 1.06; 95% CI = 1.01, 1.12). Regarding quantitative trait associations, we found no significant correlations in ASD traits among proband-sibling pairs. However, quantitative variation in proband adaptive behavior, communication, and expressive and receptive language was significantly associated with sibling outcomes in the same domains; proband scores explained 9-18% of the variation in cognition and behavior in siblings with ASD. Receptive language was particularly strongly associated in concordant pairs (ICC = 0.50, p < 0.001). CONCLUSIONS: Proband ASD symptomology, indexed by the SCQ, is a predictor of familial ASD recurrence risk. While quantitative variation in social communication and restricted and repetitive behavior were not associated among sibling pairs, standardized ratings of proband language and communication explained significant variation in the same domains in the sibling at 24 months, especially among toddlers with an ASD diagnosis. These data suggest that proband characteristics can alert clinicians to areas of developmental concern for young children with familial risk for ASD.

Parsing Heterogeneity in Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder with Individual Connectome Mapping.

Traditional diagnostic systems for neurodevelopmental disorders define diagnostic categories that are heterogeneous in behavior and underlying neurobiological alterations. The goal of this study was to parse heterogeneity in a core executive function (EF), cognitive flexibility, in children with a range of abilities (N = 132; children with autism spectrum disorder, attention-deficit/hyperactivity disorder [ADHD], and typically developing children) using directed functional connectivity profiles derived from resting-state functional magnetic resonance imaging data. Brain regions activated in response to a cognitive flexibility task in adults were used to guide region-of-interest selection to estimate individual connectivity profiles in this study. We expected to find subgroups of children who differed in their network connectivity metrics and symptom measures. Unexpectedly, we did not find a stable or valid subgrouping solution, which suggests that categorical models of the neural substrates of cognitive flexibility in children may be invalid. Exploratory analyses revealed dimensional associations between network connectivity metrics and ADHD symptomatology and EF ability across the entire sample. Results shed light on the validity of conceptualizing the neural substrates of cognitive flexibility categorically in children. Ultimately, this work may provide a foundation for the development of a revised nosology focused on neurobiological substrates as an alternative to traditional symptom-based classification systems.

Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders.

BACKGROUND: Current diagnostic systems for neurodevelopmental disorders do not have clear links to underlying neurobiology, limiting their utility in identifying targeted treatments for individuals. Here, we aimed to investigate differences in functional brain network integrity between traditional diagnostic categories (autism spectrum disorder [ASD], attention-deficit/hyperactivity disorder [ADHD], typically developing [TD]) and carefully consider the impact of comorbid ASD and ADHD on functional brain network integrity in a sample adequately powered to detect large effects. We also assess the neurobiological separability of a novel, potential alternative categorical scheme based on behavioral measures of executive function. METHOD: Five-minute resting-state fMRI data were obtained from 168 children (128 boys, 40 girls) with ASD, ADHD, comorbid ASD and ADHD, and TD children. Independent component analysis and dual regression were used to compute within- and between-network functional connectivity metrics at the individual level. RESULTS: No significant group differences in within- or between-network functional connectivity were observed between traditional diagnostic categories (ASD, ADHD, TD) even when stratified by comorbidity (ASD + ADHD, ASD, ADHD, TD). Similarly, subgroups classified by executive functioning levels showed no group differences. CONCLUSIONS: Using clinical diagnosis and behavioral measures of executive function, no differences in functional connectivity were observed among the categories examined. Despite our limited ability to detect small- to medium-sized differences between groups, this work contributes to a growing literature suggesting that traditional diagnostic categories do not define neurobiologically separable groups. Future work is necessary to ascertain the validity of the executive function-based nosology, but current results suggest that nosologies reliant on behavioral data alone may not lead to discovery of neurobiologically distinct categories.