Authors
Yunheng Diao, Yuanyuan Huang, Baoyuan Zhu, Minxin Guo, Wei Wang, Zhaobo Li, Xin Zhang, Kai Li, Wenhao Li, Hongyu Wang, Jing Zhou, Xiaobo Li, Fengchun Wu, Kai Wu
Published in
Biological psychiatry. Oct 03, 2026. Epub Oct 03, 2026.
Abstract
Understanding how disease-related connectome alterations relate to underlying molecular systems remains a major challenge in psychiatric disorders.
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.
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.
These findings establish a robust, connection-level framework for linking large-scale connectome abnormalities to multi-omics molecular systems in psychiatric disorders.
PMID:
42829056
Bibliographic data and abstract were imported from PubMed on 04 Oct 2026.
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