Multi-Omics and AI Redefine Human Systems Immunology to Predict Disease Risk and Vaccine Success

Researchers use multi-omics and AI to map the human immune system, identifying individual "set points" to predict disease risk and personalized treatment success.

By: AXL Media

Published: Apr 30, 2026, 5:03 AM EDT

Source: Information for this report was sourced from News Medical Life Sciences and the European Journal of Immunology

Systems Immunology Transitions to Real-World Human Data

A comprehensive review published in the European Journal of Immunology on April 29, 2026, highlights how human systems immunology is fundamentally changing our understanding of disease. Unlike traditional research that relies heavily on animal models, systems immunology focuses on high-throughput data derived directly from human biospecimens. This approach is critical because, while animal models are essential for basic mechanics, they fail to replicate the vast genetic diversity and environmental exposures that shape human immunity. By analyzing blood, mucosal swabs, and cerebrospinal fluid, researchers can now identify molecular signatures that predict the longevity of vaccine protection and the likelihood of treatment resistance in cancer patients.

The Power of Layered Single-Cell Technologies

Modern multi-omics technologies have moved beyond simple gene expression analysis to provide a layered, three-dimensional view of immune behavior. Techniques such as single-cell RNA sequencing (scRNA-seq) allow scientists to identify rare immune cells that were previously hidden in "bulk" samples. More advanced methods, including CITE-seq (Cellular Indexing of Transcriptomes and Epitopes) and scATAC-seq, now enable the simultaneous measurement of gene regulation, protein expression, and chromatin accessibility within the same individual cell. This level of detail helps researchers map the internal decision-making processes of immune cells as they respond to pathogens or malignant tumors.

Spatial Transcriptomics and Tissue Microenvironments

One of the most significant emerging directions in the field is spatial transcriptomics, which allows researchers to map where immune cells are located within a specific tissue. In both cancer and chronic inflammatory diseases, the physical location of a cell relative to its neighbors—the "immune niche"—often dictates its function and effectiveness. By combining spatial data with large-scale databases like The Cancer Genome Atlas (TCGA) and the COVID-19 Multi-omics Blood Atlas (COMBATdb), scientists are building comprehensive maps of tissue microenvironments. These maps help clarify why some immune cells successfully infiltrate tumors while others remain trapped on the periphery, leading to therapeutic failure.