Dataset Information

Greater functional connectivity between sensory networks is related to symptom severity in toddlers with autism spectrum disorder.

ABSTRACT:

Background

Symptoms of autism spectrum disorder (ASD) emerge in the first years of life. Yet, little is known about the organization and development of functional brain networks in ASD proximally to the symptom onset. Further, the relationship between brain network connectivity and emerging ASD symptoms and overall functioning in early childhood is not well understood.

Methods

Resting-state fMRI data were acquired during natural sleep from 24 young children with ASD and 23 typically developing (TD) children, aged 17-45 months. Intrinsic functional connectivity (iFC) within and between resting-state functional networks was derived with independent component analysis (ICA).

Results

Increased iFC between visual and sensorimotor networks was found in young children with ASD compared to TD participants. Within the ASD group, the degree of overconnectivity between visual and sensorimotor networks was associated with greater autism symptoms. Age-related weakening of the visual-auditory between-network connectivity was observed in the ASD but not the TD group.

Conclusions

Taken together, these results provide evidence for disrupted functional network maturation and differentiation, particularly involving visual and sensorimotor networks, during the first years of life in ASD. The observed pattern of greater visual-sensorimotor between-network connectivity associated with poorer clinical outcomes suggests that disruptions in multisensory brain circuitry may play a critical role for early development of behavioral skills and autism symptomatology in young children with ASD.

SUBMITTER: Chen B

PROVIDER: S-EPMC7688487 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Greater functional connectivity between sensory networks is related to symptom severity in toddlers with autism spectrum disorder.

Chen Bosi B Linke Annika A Olson Lindsay L Ibarra Cynthia C Reynolds Sarah S Müller Ralph-Axel RA Kinnear Mikaela M Fishman Inna I

Journal of child psychology and psychiatry, and allied disciplines 20200526 2

<h4>Background</h4>Symptoms of autism spectrum disorder (ASD) emerge in the first years of life. Yet, little is known about the organization and development of functional brain networks in ASD proximally to the symptom onset. Further, the relationship between brain network connectivity and emerging ASD symptoms and overall functioning in early childhood is not well understood.<h4>Methods</h4>Resting-state fMRI data were acquired during natural sleep from 24 young children with ASD and 23 typical ...[more]

PMID: 32452051

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Project description:BACKGROUND:Although temperament has been recognized as an important contributor to childhood psychopathology, its role in emergent autism spectrum phenotypes is not well understood. This study examined whether toddlers with autism spectrum disorder (ASD) display temperamental vulnerabilities compared to toddlers with other developmental challenges, whether these characteristics are distinct from core autism symptoms, if they are stable over time, and if they contribute to social outcomes in preschool. METHODS:Parents of 165 toddlers with ASD, 58 nonverbal ability- and chronological age- (CA) matched developmentally delayed (DD) toddlers, and 92 CA-matched typically developing (TD) toddlers completed the Toddler Behavior Assessment Questionnaire-Supplemental (TBAQ-S) at 26 months (SD = 6; Time 1). TBAQ-S data were also available for a subset of toddlers with ASD (n = 126) at 43 months (SD = 9; Time 2). RESULTS:Compared to the DD and TD groups, toddlers with ASD exhibited vulnerabilities within the Effortful Control domain as well as the Surgency domain. They also displayed greater Negative Emotionality compared to TD peers. In the ASD group, temperamental characteristics were not concurrently related to autism severity or developmental level and individual differences were highly stable over time. Changes in Perceptual Sensitivity, Inhibitory Control, and Low-Intensity Pleasure from age 2 to 3.5 uniquely predicted autism symptom severity and adaptive social skill level at Time 2. CONCLUSIONS:Temperamental vulnerabilities in toddlers with ASD are stable over time and involve attentional and behavioral control as well as affective reactivity. They contribute uniquely to social outcomes in preschool and are likely to signal risk for developing later maladaptive attentional, affective, and behavioral symptoms. Considering biologically based dimensions may shed light on noncore facets of the early ASD phenotype that are potentially relevant to the emergence of comorbid conditions later in childhood.

Project description:BackgroundAutism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition. The degree to which the brain development in ASD deviates from typical brain development, and how this deviation relates to observed behavioral outcomes at the individual level are not well-studied. We hypothesize that the degree of deviation from typical brain development of an individual with ASD would relate to observed symptom severity.MethodsThe developmental changes in anatomical (cortical thickness, surface area, and volume) and diffusion metrics (fractional anisotropy and apparent diffusion coefficient) were compared between a sample of ASD (n?=?247) and typically developing children (TDC) (n?=?220) aged 6-25. Machine learning was used to predict age (brain age) from these metrics in the TDC sample, to define a normative model of brain development. This model was then used to compute brain age in the ASD sample. The difference between chronological age and brain age was considered a developmental deviation index (DDI), which was then correlated with ASD symptom severity.ResultsMachine learning model trained on all five metrics accurately predicted age in the TDC (r?=?0.88) and the ASD (r?=?0.85) samples, with dominant contributions to the model from the diffusion metrics. Within the ASD group, the DDI derived from fractional anisotropy was correlated with ASD symptom severity (r?=?-?0.2), such that individuals with the most advanced brain age showing the lowest severity, and individuals with the most delayed brain age showing the highest severity.LimitationsThis work investigated only linear relationships between five specific brain metrics and only one measure of ASD symptom severity in a limited age range. Reported effect sizes are moderate. Further work is needed to investigate developmental differences in other age ranges, other aspects of behavior, other neurobiological measures, and in an independent sample before results can be clinically applicable.ConclusionsFindings demonstrate that the degree of deviation from typical brain development relates to ASD symptom severity, partially accounting for the observed heterogeneity in ASD. Our approach enables characterization of each individual with reference to normative brain development and identification of distinct developmental subtypes, facilitating a better understanding of developmental heterogeneity in ASD.

Project description:BackgroundAtypical reactions to the sensory environment are often reported in autistic individuals, with a high degree of variability across the sensory modalities. These sensory differences have been shown to promote challenging behaviours and distress in autistic individuals and are predictive of other functions including motor, social, and cognitive abilities. Preliminary research suggests that specific sensory differences may cluster together within individuals creating discrete sensory phenotypes. However, the manner in which these sensory differences cluster, and whether the resulting phenotypes are associated with specific cognitive and social challenges is unclear.MethodsShort sensory profile data from 599 autistic children and adults between the ages of 1 and 21 years were subjected to a K-means cluster analysis. Analysis of variances compared age, adaptive behaviour, and traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder across the resultant clusters.ResultsA five-cluster model was found to minimize error variance and produce five sensory phenotypes: (1) sensory adaptive, (2) generalized sensory differences, (3) taste and smell sensitivity, (4) under-responsive and sensation seeking, and (5) movement difficulties with low energy. Age, adaptive behaviour, and traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder were found to differ significantly across the five phenotypes.LimitationsThe results were based on parent-report measures of sensory processing, adaptive behaviour, traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder, which may limit the generalizability of the findings. Further, not all measures are standardized, or psychometrically validated with an autism population. Autistic individuals with an intellectual disability were underrepresented in this sample. Further, as these data were obtained from established records from a large provincial database, not all measures were completed for all individuals.ConclusionsThese findings suggest that sensory difficulties in autistic individuals can be clustered into sensory phenotypes, and that these phenotypes are associated with behavioural differences. Given the large degree of heterogeneity in sensory difficulties seen in the autistic population, these sensory phenotypes represent an effective way to parse that heterogeneity and create phenotypes that may aid in the development of effective treatments and interventions for sensory difficulties.

Dataset Information

Greater functional connectivity between sensory networks is related to symptom severity in toddlers with autism spectrum disorder.

Background

Methods

Results

Conclusions

Publications

Greater functional connectivity between sensory networks is related to symptom severity in toddlers with autism spectrum disorder.

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