A brain structural connectivity biomarker for autism spectrum disorder diagnosis in early childhood

Xi Jiang; Xiao-Jing Shou; Zhongbo Zhao; Yuzhong Chen; Fan-Chao Meng; Jiao Le; Tian-Jia Song; Xin-Jie Xu; Weitong Guo; Xiaoyan Ke; Xiao-E Cai; Weihua Zhao; Juan Kou; Ran Huo; Ying Liu; Hui-Shu Yuan; Yan Xing; Ji-Sheng Han; Song-Ping Han; Yun Li; Hua Lai; Lan Zhang; Mei-Xiang Jia; Jing Liu; Xuan Liu; Keith M Kendrick; Rong Zhang

doi:10.1093/psyrad/kkad005

A brain structural connectivity biomarker for autism spectrum disorder diagnosis in early childhood

Psychoradiology. 2023 Apr 20:3:kkad005. doi: 10.1093/psyrad/kkad005. eCollection 2023.

Authors

Xi Jiang¹, Xiao-Jing Shou^{2

3}, Zhongbo Zhao¹, Yuzhong Chen¹, Fan-Chao Meng², Jiao Le^{1

4}, Tian-Jia Song², Xin-Jie Xu², Weitong Guo¹, Xiaoyan Ke⁵, Xiao-E Cai², Weihua Zhao¹, Juan Kou¹, Ran Huo^{2

6}, Ying Liu⁶, Hui-Shu Yuan⁶, Yan Xing⁷, Ji-Sheng Han², Song-Ping Han⁸, Yun Li⁵, Hua Lai⁴, Lan Zhang⁴, Mei-Xiang Jia⁹, Jing Liu⁹, Xuan Liu¹⁰, Keith M Kendrick¹, Rong Zhang^{2

11

12}

Affiliations

¹ The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.
² Neuroscience Research Institute; Key Laboratory for Neuroscience, Ministry of Education of China; Key Laboratory for Neuroscience, National Committee of Health and Family Planning of China; and Department of Neurobiology, School of Basic Medical Sciences, Peking University, Beijing 100191, China.
³ State Key Laboratory of Cognitive Neuroscience and Learning; Beijing Key Laboratory of Brain Imaging and Connectomics; and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
⁴ Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China.
⁵ Child Mental Health Research Center, Nanjing Brain Hospital Affiliated of Nanjing Medical University, Nanjing 210029, China.
⁶ Radiology Department, Peking University Third Hospital, Beijing 100191, China.
⁷ Department of Pediatrics, Peking University Third Hospital, Beijing 100191, China.
⁸ Wuxi Shenpingxintai Medical Technology Co., Ltd, Wuxi 214091, China.
⁹ Mental Health Institute, Peking University, Key Laboratory of Ministry of Health, The Ministry of Public Health, Beijing 100191, China.
¹⁰ Shandong Ke Luo Ni Ke (CLINIC) Medical Technology Co., Ltd, Dezhou 253011, China.
¹¹ Autism Research Center of Peking University Health Science Center, Beijing 100191, China.
¹² Department of Integration of Chinese and Western Medicine, School of Basic Medical Sciences, Peking University, 100191,Beijing, China.

Abstract

Background: Autism spectrum disorder (ASD) is associated with altered brain development, but it is unclear which specific structural changes may serve as potential diagnostic markers, particularly in young children at the age when symptoms become fully established. Furthermore, such brain markers need to meet the requirements of precision medicine and be accurate in aiding diagnosis at an individual rather than only a group level.

Objective: This study aimed to identify and model brain-wide differences in structural connectivity using diffusion tensor imaging (DTI) in young ASD and typically developing (TD) children.

Methods: A discovery cohort including 93 ASD and 26 TD children and two independent validation cohorts including 12 ASD and 9 TD children from three different cities in China were included. Brain-wide (294 regions) structural connectivity was measured using DTI (fractional anisotropy, FA) together with symptom severity and cognitive development. A connection matrix was constructed for each child for comparisons between ASD and TD groups. Pattern classification was performed on the discovery dataset and the resulting model was tested on the two independent validation datasets.

Results: Thirty-three structural connections showed increased FA in ASD compared to TD children and associated with both autistic symptom severity and impaired general cognitive development. The majority (29/33) involved the frontal lobe and comprised five different networks with functional relevance to default mode, motor control, social recognition, language and reward. Overall, classification achieved very high accuracy of 96.77% in the discovery dataset, and 91.67% and 88.89% in the two independent validation datasets.

Conclusions: Identified structural connectivity differences primarily involving the frontal cortex can very accurately distinguish novel individual ASD from TD children and may therefore represent a robust early brain biomarker which can address the requirements of precision medicine.

Keywords: autism spectrum disorder; brain structural connectivity; diffusion tensor imaging; early childhood; fractional anisotropy; individual diagnosis.