Biological psychiatry · 2026
Connection-Level Multi-Omics Reveals Cerebellar-Cortical Dysconnectivity and Divergent Molecular Signatures Across Major Psychiatric Disorders.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Diao Yunheng, Huang Yuanyuan, Zhu Baoyuan, Guo Minxin, Wang Wei, Li Zhaobo, Zhang Xin, Li Kai, Li Wenhao, Wang Hongyu, Zhou Jing, Li Xiaobo, Wu Fengchun, Wu Kai
Аннотация
BACKGROUND: Understanding how disease-related connectome alterations relate to underlying molecular systems remains a major challenge in psychiatric disorders.
METHODS: Here we introduce BrainNetAnno (https://brainnetanno.readthedocs.io/en/latest), an open-source framework for molecular annotation of brain network connections that extends multi-omics mapping from regional nodes to inter-regional edges. We applied this framework to resting-state functional connectivity data from a discovery cohort of 2,453 participants and an independent validation cohort of 442, including individuals with major depressive disorder, schizophrenia, generalized anxiety disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder, and healthy controls.
RESULTS: Our analyses revealed a shared transdiagnostic abnormal connectivity pattern (STACP), characterized by cerebellar-cortical dysconnectivity, alongside distinct disorder-specific connectivity deviations (DSCDs) that exhibited structured inter-disorder relationships, including opposition, partial alignment, and near-orthogonality. These connectivity patterns were differentially associated with molecular systems, with mitochondrial phenotypes linked to the STACP and selected DSCDs, and neurotransmitter receptor/transporter profiles primarily associated with DSCDs.
CONCLUSIONS: These findings establish a robust, connection-level framework for linking large-scale connectome abnormalities to multi-omics molecular systems in psychiatric disorders.
METHODS: Here we introduce BrainNetAnno (https://brainnetanno.readthedocs.io/en/latest), an open-source framework for molecular annotation of brain network connections that extends multi-omics mapping from regional nodes to inter-regional edges. We applied this framework to resting-state functional connectivity data from a discovery cohort of 2,453 participants and an independent validation cohort of 442, including individuals with major depressive disorder, schizophrenia, generalized anxiety disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder, and healthy controls.
RESULTS: Our analyses revealed a shared transdiagnostic abnormal connectivity pattern (STACP), characterized by cerebellar-cortical dysconnectivity, alongside distinct disorder-specific connectivity deviations (DSCDs) that exhibited structured inter-disorder relationships, including opposition, partial alignment, and near-orthogonality. These connectivity patterns were differentially associated with molecular systems, with mitochondrial phenotypes linked to the STACP and selected DSCDs, and neurotransmitter receptor/transporter profiles primarily associated with DSCDs.
CONCLUSIONS: These findings establish a robust, connection-level framework for linking large-scale connectome abnormalities to multi-omics molecular systems in psychiatric disorders.