Dataset Information

The Development of Brain Network in Males with Autism Spectrum Disorders from Childhood to Adolescence: Evidence from fNIRS Study.

ABSTRACT: In the current study, functional near-infrared spectroscopy (fNIRS) was used to collect resting-state signals from 77 males with autism spectrum disorders (ASD, age: 6~16.25) and 40 typically developing (TD) males (age: 6~16.58) in the theory-of-mind (ToM) network. The graph theory analysis was used to obtain the brain network properties in ToM network, and the multiple regression analysis demonstrated that males with ASD showed a comparable global network topology, and a similar age-related decrease in the medial prefrontal cortex area (mPFC) compared to TD individuals. Nevertheless, participants with ASD showed U-shaped trajectories of nodal metrics of right temporo-parietal junction (TPJ), and an age-related decrease in the left middle frontal gyrus (MFG), while trajectories of TD participants were opposite. The nodal metrics of the right TPJ was negatively associated with the social deficits of ASD, while the nodal metrics of the left MFG was negatively associated with the communication deficits of ASD. Current findings suggested a distinct developmental trajectory of the ToM network in males with ASD from childhood to adolescence.

SUBMITTER: Cao W

PROVIDER: S-EPMC7830916 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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The Development of Brain Network in Males with Autism Spectrum Disorders from Childhood to Adolescence: Evidence from fNIRS Study.

Cao Wei W Zhu Huilin H Li Yan Y Wang Yu Y Bai Wuxia W Lao Uchong U Zhang Yingying Y Ji Yan Y He Sailing S Zou Xiaobing X

Brain sciences 20210118 1

In the current study, functional near-infrared spectroscopy (fNIRS) was used to collect resting-state signals from 77 males with autism spectrum disorders (ASD, age: 6~16.25) and 40 typically developing (TD) males (age: 6~16.58) in the theory-of-mind (ToM) network. The graph theory analysis was used to obtain the brain network properties in ToM network, and the multiple regression analysis demonstrated that males with ASD showed a comparable global network topology, and a similar age-related dec ...[more]

PMID: 33477412

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Project description:This study aimed to identify determinants of a late autism spectrum disorder diagnosis, including diagnoses made 'very late' (i.e., in adolescence), using the Millennium Cohort Study, a nationally representative population-based cohort in the United Kingdom. Children diagnosed with autism spectrum disorder by age 14 (N = 581) were included and grouped by the parent-reported timing of diagnosis: before school (up to age 5), during primary school (age 5-11) and during secondary school (age 11-14). Predictors of diagnostic timing, at the child, family and school levels, were investigated using multinomial logistic regression. Most (79%) children with autism spectrum disorder were diagnosed after school entry, and 28% were not diagnosed until secondary school. Among those not diagnosed until secondary school, 75% had been identified at age 5 years by a parent and/or teacher as having socio-behavioural difficulties. Being diagnosed after starting school was predicted by living in poverty (adjusted relative risk ratio: primary = 1.90, 95% confidence interval: 1.03-3.53; secondary = 2.15, 1.05-4.42) and/or having no initial parental concerns (primary = 0.32, 0.15-0.70; secondary = 0.19, 0.09-0.43). Having typical-range intelligence also predicted diagnosis during secondary school. The result indicates that those without cognitive delays and poorer children were at risk of 'very late' (i.e. adolescent) diagnosis. Strategies to promote earlier identification, targeting age at primary school entry, could help those more likely to be diagnosed late.Lay abstractDespite policy emphasis on early identification, many children with autism spectrum disorder are diagnosed late, with some being diagnosed as late as in adolescence. However, evidence on what determines the timing of autism spectrum disorder diagnosis including children diagnosed in adolescence is lacking. Understanding these determinants, particularly in those diagnosed later than is ideal, can inform the development of effective strategies to improve earlier identification of autism spectrum disorder. This study used a nationally representative population-based cohort in the United Kingdom to explore child, family and school level predictors of timing of autism spectrum disorder diagnosis. In the United Kingdom, 79% of the children with autism spectrum disorder were diagnosed after entering primary school and 28% during secondary school. Among those not diagnosed until secondary school, 75% had shown social difficulties noticed by parents and/or teachers at age 5 years. The results suggest that healthcare providers should be aware that, even for universal systems of care, those living in poverty and having higher intelligence are most likely to miss out on a timely diagnosis. Strategies to promote earlier identification among school-aged children, including targeting primary school entry age (i.e. around age 5) and that encouraging referrals for a formal assessment at the first report of concerns over the child's social development may benefit those children who would otherwise be diagnosed later.

Project description:The male predominance in the prevalence of autism spectrum disorder (ASD) has motivated research on sex differentiation in ASD. Multiple sources of evidence have suggested a neurophenotypic convergence of ASD-related characteristics and typical sex differences. Two existing, albeit competing, models provide predictions on such neurophenotypic convergence. These two models are testable with neuroimaging. Specifically, the Extreme Male Brain (EMB) model predicts that ASD is associated with enhanced brain maleness in both males and females with ASD (i.e., a shift-towards-maleness). In contrast, the Gender Incoherence (GI) model predicts a shift-towards-maleness in females, yet a shift-towards-femaleness in males with ASD.To clarify whether either model applies to the intrinsic functional properties of the brain in males with ASD, we measured the statistical overlap between typical sex differences and ASD-related atypicalities in resting-state fMRI (R-fMRI) datasets largely available in males. Main analyses focused on two large-scale R-fMRI samples: 357 neurotypical (NT) males and 471 NT females from the 1000 Functional Connectome Project and 360 males with ASD and 403 NT males from the Autism Brain Imaging Data Exchange.Across all R-fMRI metrics, results revealed coexisting, but network-specific, shift-towards-maleness and shift-towards-femaleness in males with ASD. A shift-towards-maleness mostly involved the default network, while a shift-towards-femaleness mostly occurred in the somatomotor network. Explorations of the associated cognitive processes using available cognitive ontology maps indicated that higher-order social cognitive functions corresponded to the shift-towards-maleness, while lower-order sensory motor processes corresponded to the shift-towards-femaleness.The present findings suggest that atypical intrinsic brain properties in males with ASD partly reflect mechanisms involved in sexual differentiation. A model based on network-dependent atypical sex mosaicism can synthesize prior competing theories on factors involved in sex differentiation in ASD.

Dataset Information

The Development of Brain Network in Males with Autism Spectrum Disorders from Childhood to Adolescence: Evidence from fNIRS Study.

Publications

The Development of Brain Network in Males with Autism Spectrum Disorders from Childhood to Adolescence: Evidence from fNIRS Study.

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