# Human Systems Immunology in the Omics Era: Challenges, Methods, and Emerging Directions

**Authors:** Lennart Riemann, Reinhold Förster

PMC · DOI: 10.1002/eji.70164 · European Journal of Immunology · 2026-03-13

## TL;DR

This paper reviews how modern technologies and analytical methods are helping scientists better understand the complex human immune system and its role in disease.

## Contribution

The paper provides a comprehensive roadmap for addressing analytical challenges in systems immunology using high-throughput omics data.

## Key findings

- High-throughput omics technologies enable comprehensive study of immune responses in human cohorts.
- Analytical challenges like batch effects and interindividual heterogeneity require robust statistical strategies.
- Systems immunology advances are improving biomarker discovery and precision medicine in immunological diseases.

## Abstract

The human immune system is a highly complex, dynamic, and heterogeneous network shaped by genetic, environmental, and temporal influences. Advances in high‐throughput omics technologies have transformed our ability to study this complexity directly and comprehensively in human cohorts. These developments have positioned systems immunology as a powerful framework for investigating coordinated immune responses, identifying regulatory mechanisms, and linking molecular patterns to clinical phenotypes. However, the analytical challenges inherent to large‐scale, multimodal datasets—including batch effects, small sample sizes, high dimensionality, and substantial interindividual heterogeneity—require rigorous study design, robust statistical modeling, and thoughtful data analysis strategies. In this review, we summarize key technological foundations enabling modern human systems immunology, outline common analytical pitfalls and effective mitigation approaches, discuss data integration concepts, and highlight emerging opportunities in the field. Together, these technological and analytical advances are redefining how immune function is measured and interpreted in real‐world human biology and hold significant promise for enhancing mechanistic insight, biomarker discovery, and precision medicine across immunological diseases and interventions.

Systems immunology provides a transformative framework for decoding human immune complexity. This review evaluates high‐throughput technologies and provides a roadmap for navigating analytical challenges—such as batch effects and interindividual heterogeneity—to successfully translate multimodal data into meaningful biological insights.

## Full-text entities

- **Genes:** IFNG (interferon gamma) [NCBI Gene 3458] {aka IFG, IFI, IMD69}
- **Diseases:** pulmonary fibrosis (MESH:D011658), SARS-CoV-2 infection (MESH:D000086382), immune-mediated diseases (MESH:C567355), inflammation (MESH:D007249), cytomegalovirus infection (MESH:D003586), allergies (MESH:D004342), non-small-cell lung cancer (MESH:D002289), Immune dysregulation (OMIM:614878), kidney stone disease (MESH:D007669), acute myeloid leukemia (MESH:D015470), chronic (MESH:D002908), glioblastoma (MESH:D005909), Cancer (MESH:D009369), AI (MESH:C538142), autoimmune disease (MESH:D001327), noncommunicable diseases (MESH:D000073296)
- **Species:** Homo sapiens (human, species) [taxon 9606], Human immunodeficiency virus 1 (no rank) [taxon 11676], Mus musculus (house mouse, species) [taxon 10090]

## Full text

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## Figures

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## References

104 references — full list in the complete paper: https://tomesphere.com/paper/PMC12988318/full.md

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Source: https://tomesphere.com/paper/PMC12988318