From cellular heterogeneity to precision medicine: single-cell multi-omics in CNS disease research

Single-cell sequencing and multi-omics technologies are revolutionizing research on central nervous system (CNS) diseases by enabling high-resolution analysis of cellular heterogeneity and molecular dynamics. Traditional technologies (e.g., bulk sequencing, routine histology) often lack cellular resolution, fail to capture heterogeneity among individual cells, and struggle to reveal subtle molecular changes in early pathogenesis, limiting their ability to clarify complex CNS disease mechanisms and develop precise diagnostic tools. This review comprehensively summarizes the latest advances in single-cell multi-omics methodologies, including genomics, transcriptomics, proteomics, metabolomics, and spatial omics, and their applications in elucidating the pathogenesis, diagnosis, and treatment of common CNS disorders. Representative diseases such as ischemic stroke, Alzheimer's disease, Parkinson's disease, viral meningitis, bacterial meningitis, multiple sclerosis, autism spectrum disorder, and depression are used as examples to discuss the current status and future prospects of single-cell multi-omics technologies in CNS disease research. Currently, these technologies have enabled the identification of rare pathogenic cell subsets, the mapping of cell-specific molecular pathways, and the discovery of potential diagnostic biomarkers in several common CNS disorders, though their clinical translation is still hindered by technical costs and standardization issues. In the future, the integration of single-cell multi-omics with spatial transcriptomics, artificial intelligence, and clinical data is expected to further decode the complex pathogenesis of CNS disorders, accelerate the development of targeted therapies, and promote the shift toward personalized medicine in CNS disease management-aligning with translational goals of neuropsychopharmacology.