Duan Xujun, Shan Xiaolong, Uddin Lucina Q, Chen Huafu
Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.
Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.
Biol Psychiatry. 2025 Mar 1;97(5):428-438. doi: 10.1016/j.biopsych.2024.08.008. Epub 2024 Aug 23.
Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition. Over the past decade, a considerable number of approaches have been developed to identify potential neuroimaging-based biomarkers of ASD that have uncovered specific neural mechanisms that underlie behaviors associated with ASD. However, the substantial heterogeneity among individuals who are diagnosed with ASD hinders the development of biomarkers. Disentangling the heterogeneity of ASD is pivotal to improving the quality of life for individuals with ASD by facilitating early diagnosis and individualized interventions for those who need support. In this review, we discuss recent advances in neuroimaging that have facilitated the characterization of the heterogeneity of this condition using 3 frameworks: neurosubtyping, dimensional models, and normative models. We also discuss the challenges, possible solutions, and clinical utility of these 3 frameworks. We argue that several factors need to be considered when parsing heterogeneity using neuroimaging, including co-occurring conditions, neurodevelopment, heredity and environment, and multisite and multimodal data. We close with a discussion of future directions for achieving a better understanding of the neural mechanisms that underlie neurodevelopmental heterogeneity and the future of precision medicine in ASD.
自闭症谱系障碍（ASD）是一种终身神经发育疾病。在过去十年中，已经开发出了大量方法来识别基于神经影像学的ASD潜在生物标志物，这些方法揭示了与ASD相关行为背后的特定神经机制。然而，被诊断为ASD的个体之间存在的显著异质性阻碍了生物标志物的开发。理清ASD的异质性对于通过促进早期诊断和为需要支持的个体提供个性化干预来提高ASD患者的生活质量至关重要。在这篇综述中，我们讨论了神经影像学的最新进展，这些进展利用三种框架促进了对这种疾病异质性的表征：神经亚型分类、维度模型和规范模型。我们还讨论了这三种框架的挑战、可能的解决方案和临床应用。我们认为，在使用神经影像学分析异质性时需要考虑几个因素，包括共病情况、神经发育、遗传和环境以及多站点和多模态数据。我们最后讨论了未来的方向，以更好地理解神经发育异质性背后的神经机制以及ASD精准医学的未来。
