Integrative omics redefining allergy mechanisms and precision medicine

Allergic diseases are characterized by heterogeneity driven by complex interactions between genetic, environmental, and immunological factors. Conventional classifications based solely on clinical phenotypes often fails to capture the underlying molecular diversity, thereby limiting therapeutic precision and patient outcomes. Integrative omics—encompassing genomics, transcriptomics, proteomics, metabolomics, and microbiomics—has emerged as a powerful approach to redefine disease mechanisms and advance precision medicine. By integrating high-dimensional molecular data with clinical phenotyping, omics approaches enable the identification of disease endotypes, biomarker discovery, and patient stratification.

This review highlights recent developments in clinical-omics integration, with a focus on atopic dermatitis (AD) as a prototypical allergic disease. Drawing from our studies, we illustrate how tissue-level transcriptomic profiling, combined with unbiased computational analysis, can uncover immunological heterogeneity and treatment-response patterns in AD. Additional examples in asthma and food allergy demonstrate how integrated multi-omics can uncover gene-environment interactions and elucidate mechanisms behind disease severity and health disparities.

We also address practical and ethical challenges in data harmonization, privacy, and interoperability, and underscore the critical role of computational methods and infrastructure development in enabling clinically meaningful interpretation. Importantly, successful translation of multi-omics data into clinical practice requires iterative, interdisciplinary collaboration between clinicians, data scientists, and basic researchers.

By bridging molecular complexity and clinical heterogeneity, integrative omics is reshaping the landscape of allergy research. As technologies evolve, this framework will be crucial for developing predictive models and personalized therapeutic strategies, ultimately bringing us closer to individualized, data-driven care in allergic diseases.