Abstract Mental disorders refer to abnormal states that affect an individual’s thinking, emotion, behavior, and perception, and are generally associated with dysregulation of brain function. They exhibit genetic heterogeneity as well as multi-level structural and functional abnormalities of the brain. Magnetic resonance imaging has been widely applied to detect macroscopic neurophenotypic alterations in patients with psychiatric disorders; however, it remains limited in directly revealing the underlying molecular and cellular mechanisms. Imaging transcriptomics, by integrating whole-brain gene expression atlases with neuroimaging features, offers a novel paradigm for exploring the associations between microscopic genetic expression and macroscopic neuroimaging phenotypes. This review systematically summarizes the methodological framework of imaging transcriptomic association studies and highlights recent advances in their application to psychiatric disorders such as depression. A growing body of evidence has revealed spatial coupling between structural and functional abnormalities in disease-related brain regions and gene expression in synaptic transmission, ion channels, neurodevelopment, and immune signaling. Imaging transcriptomics not only facilitates a multiscale understanding of the pathophysiological mechanisms of psychiatric disorders but also provides potential pathways for disease classification, targeted intervention, and precision diagnosis and treatment. Future research should further promote the integration of longitudinal imaging omics and spatial transcriptomic data to construct translatable multimodal models, thereby accelerating the translation of psychiatric neuroimaging from mechanistic research to clinical application.
Liu et al. (2026) studied this question.