Single-Cell Multiomics Reveals Novel Immune Cell Signatures Associated with Early Alzheimer's Disease

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Background Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and a leading cause of dementia worldwide. Increasing evidence indicates that immune dysregulation and chronic neuroinflammation are fundamental contributors to disease initiation and progression, preceding overt neuronal degeneration. Conventional molecular approaches have provided valuable insights into AD pathogenesis but are limited by their inability to resolve cellular heterogeneity. Recent advances in single-cell multiomic technologies have transformed the understanding of immune-cell diversity and molecular mechanisms underlying early Alzheimer's disease. Objectivs This review aims to summarize current evidence regarding the application of single-cell multiomic technologies in identifying novel immune-cell signatures associated with early Alzheimer's disease, highlighting emerging biomarkers, molecular pathways, computational approaches, and potential therapeutic targets. Methods A comprehensive literature review was conducted using PubMed/MEDLINE, Scopus, Web of Science Core Collection, Embase, ScienceDirect, SpringerLink, Wiley Online Library, and Google Scholar to identify peer-reviewed studies published between January 2018 and June 2025. Eligible publications investigating single-cell transcriptomics, epigenomics, spatial transcriptomics, proteomics, and integrated multiomic analyses in Alzheimer's disease were systematically evaluated. Evidence was synthesized narratively according to immune-cell populations, molecular pathways, biomarker discovery, artificial intelligence-assisted analyses, and translational applications. Results A total of 127 eligible studies were included in the qualitative synthesis. The reviewed evidence consistently demonstrated extensive immune-cell heterogeneity within the Alzheimer's disease microenvironment. Disease-associated microglia, reactive astrocytes, infiltrating monocytes, cytotoxic T lymphocytes, regulatory T cells, natural killer cells, and dendritic cells exhibited distinct molecular signatures involving inflammatory signaling, lipid metabolism, complement activation, interferon responses, mitochondrial dysfunction, and chromatin remodeling. Integrated single-cell multiomic platforms, including single-cell RNA sequencing, single-cell ATAC sequencing, spatial transcriptomics, and proteomic profiling, substantially improved the identification of disease-specific biomarkers and regulatory networks. Furthermore, artificial intelligence and machine-learning algorithms enhanced high-dimensional data integration, immune-cell classification, biomarker prediction, and precision disease stratification. Conclusion Single-cell multiomics has fundamentally reshaped the understanding of early Alzheimer's disease by revealing previously unrecognized immune-cell populations and complex neuroimmune interactions that drive disease pathogenesis. The integration of transcriptomic, epigenomic, spatial, proteomic, and computational analyses provide unprecedented opportunities for early diagnosis, biomarker discovery, therapeutic target identification, and personalized immunomodulatory strategies. Continued technological innovation, multicenter validation, and standardized analytical pipelines will be essential for translating these discoveries into routine clinical practice and precision medicine. Keywords: Alzheimer's disease; Single-cell multiomics; Single-cell RNA sequencing; scRNA-seq; scATAC-seq; Spatial transcriptomics; Neuroinflammation; Disease-associated microglia

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