Differential cognitive and behavioral development from 6 to 24 months in autism and fragile X syndrome.

BACKGROUND: Specifying early developmental differences among neurodevelopmental disorders with distinct etiologies is critical to improving early identification and tailored intervention during the first years of life. Recent studies have uncovered important differences between infants with fragile X syndrome (FXS) and infants with familial history of autism spectrum disorder who go on to develop autism themselves (FH-ASD), including differences in brain development and behavior. Thus far, there have been no studies longitudinally investigating differential developmental skill profiles in FXS and FH-ASD infants. METHODS: The current study contrasted longitudinal trajectories of verbal (expressive and receptive language) and nonverbal (gross and fine motor, visual reception) skills in FXS and FH-ASD infants, compared to FH infants who did not develop ASD (FH-nonASD) and typically developing controls. RESULTS: Infants with FXS showed delays on a nonverbal composite compared to FH-ASD (as well as FH-nonASD and control) infants as early as 6 months of age. By 12 months an ordinal pattern of scores was established between groups on all domains tested, such that controls > FH-nonASD > FH-ASD > FXS. This pattern persisted through 24 months. Cognitive level differentially influenced developmental trajectories for FXS and FH-ASD. CONCLUSIONS: Our results demonstrate detectable group differences by 6 months between FXS and FH-ASD as well as differential trajectories on each domain throughout infancy. This work further highlights an earlier onset of global cognitive delays in FXS and, conversely, a protracted period of more slowly emerging delays in FH-ASD. Divergent neural and cognitive development in infancy between FXS and FH-ASD contributes to our understanding of important distinctions in the development and behavioral phenotype of these two groups.

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.

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.

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.

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.

Attachment in young children with autism spectrum disorders: an examination of separation and reunion behaviors with both mothers and fathers.

Most studies examining attachment in children with autism spectrum disorder used a strange situation paradigm and have found few significant group differences between children with autism spectrum disorder and comparisons. However, these studies predominantly used formal attachment categorizations (e.g. secure vs insecure), a method that may obscure more nuanced differences between groups. In this study, we utilized a qualitative approach to examine attachment behaviors in young children with autism spectrum disorder. Based on the results of previous studies, we looked at (a) parental gender, (b) child diagnosis, and (c) child cognitive skills to examine the role of these three factors on attachment behaviors elicited during a modified strange situation paradigm. Participants were 2- to 3-year-old children with autism spectrum disorder (n = 166) or nonspectrum disorders (n = 45), as well as a sample of 56 children with typical development. Over the three groups, 393 observations of a modified strange situation paradigm with mothers and 127 observations with fathers were collected. Parental gender, child diagnosis, and child cognitive skills each had significant main effects on attachment behaviors elicited during reunion. These results underscore the importance of the father's role in parent-child interactions, with implications for both clinical and research efforts. In addition, the results emphasize the importance of considering a child's diagnosis and cognitive skills when examining attachment behaviors.