Age-atypical brain functional networks in autism spectrum disorder: a normative modeling approach

Anhang Jiang; Xuefeng Ma; Shuang Li; Lingxiao Wang; Bo Yang; Shizhen Wang; Mei Li; Guangheng Dong

doi:10.1017/S0033291724000138

Age-atypical brain functional networks in autism spectrum disorder: a normative modeling approach

Published online by Cambridge University Press: 02 April 2024

Anhang Jiang

Xuefeng Ma ,

Shuang Li ,

Bo Yang ,

Mei Li and

Anhang Jiang: Affiliation:
Department of Psychology, Yunnan Normal University, Kunming, Yunnan Province, P.R. China Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, P.R. China
Xuefeng Ma: Affiliation:
Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, P.R. China
Shuang Li: Affiliation:
Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, P.R. China
Lingxiao Wang: Affiliation:
Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, P.R. China Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang Province, China
Bo Yang: Affiliation:
Department of Psychology, Yunnan Normal University, Kunming, Yunnan Province, P.R. China
Shizhen Wang: Affiliation:
Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, P.R. China
Mei Li: Affiliation:
Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, P.R. China Center for Mental Health Education and Counselling, Hangzhou Normal University, Hangzhou, Zhejiang Province, P.R. China
Guangheng Dong*: Affiliation:
Department of Psychology, Yunnan Normal University, Kunming, Yunnan Province, P.R. China
*: Corresponding author: Guangheng Dong; Email: dongguangheng@hznu.edu.cn

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Abstract
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Abstract

Background

Despite extensive research into the neural basis of autism spectrum disorder (ASD), the presence of substantial biological and clinical heterogeneity among diagnosed individuals remains a major barrier. Commonly used case‒control designs assume homogeneity among subjects, which limits their ability to identify biological heterogeneity, while normative modeling pinpoints deviations from typical functional network development at individual level.

Methods

Using a world-wide multi-site database known as Autism Brain Imaging Data Exchange, we analyzed individuals with ASD and typically developed (TD) controls (total n = 1218) aged 5–40 years, generating individualized whole-brain network functional connectivity (FC) maps of age-related atypicality in ASD. We then used local polynomial regression to estimate a networkwise normative model of development and explored correlations between ASD symptoms and brain networks.

Results

We identified a subset exhibiting highly atypical individual-level FC, exceeding 2 standard deviation from the normative value. We also identified clinically relevant networks (mainly default mode network) at cohort level, since the outlier rates decreased with age in TD participants, but increased in those with autism. Moreover, deviations were linked to severity of repetitive behaviors and social communication symptoms.

Conclusions

Individuals with ASD exhibit distinct, highly individualized trajectories of brain functional network development. In addition, distinct developmental trajectories were observed among ASD and TD individuals, suggesting that it may be challenging to identify true differences in network characteristics by comparing young children with ASD to their TD peers. This study enhances understanding of the biological heterogeneity of the disorder and can inform precision medicine.

Keywords

autism functional network heterogeneity Neuroimaging normative model

Type: Original Article
Information: Psychological Medicine , First View , pp. 1 - 12

DOI: https://doi.org/10.1017/S0033291724000138 [Opens in a new window]
Copyright: Copyright © The Author(s), 2024. Published by Cambridge University Press

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Footnotes

Co-first authors.

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