Single-cell multiomics has emerged as a transformative approach in clinical immunology, enabling comprehensive profiling of immune cells by integrating transcriptomic, epigenomic, proteomic, and metabolic information at single-cell resolution. This review outlines the evolution of single-cell technologies and highlights the principles and methodological frameworks underpinning multiomic integration. Major applications in clinical immunology are discussed, with emphasis placed on immune cell heterogeneity in health and disease and its relevance to autoimmune and inflammatory disorders, tumour immunology, infectious diseases, vaccinology, and transplantation tolerance. Advances in single-cell multiomics have provided critical insights into disease mechanisms, immune dysregulation, and therapeutic responses, supporting biomarker discovery and precision immunotherapy. The review also addresses computational strategies for data integration, visualization, and interpretation, along with current analytical and translational challenges. Future directions include spatial multiomics, AI-driven analytics, and clinically scalable platforms, highlighting the transformative potential of single-cell multiomics in immune profiling and personalized medicine.
Chowdhury et al. (2026) studied this question.