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Editorial
. 2025 Jul;156(1):97-99.
doi: 10.1016/j.jaci.2024.12.1083. Epub 2024 Dec 31.

Multiomic approaches for endotype discovery in allergy/immunology

Yeogha Yoon  1 , Supinda Bunyavanich  2
Affiliations
Editorial

Multiomic approaches for endotype discovery in allergy/immunology

Yeogha Yoon et al. J Allergy Clin Immunol. 2025 Jul.
No abstract available

Keywords: Multiomics; allergy; artificial intelligence; asthma; atopic dermatitis; endotype; epigenome; food allergy; genome; machine learning; metabolome; microbiome; omic; systems biology; transcriptome.

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Conflict of interest statement

Disclosure statement Supported by the National Institutes of Health (grants UM1 AI173380, UM AI182034, R01 AI147028, and R01 AI118833). Disclosure of potential conflict of interest: The authors declare that they have no relevant conflicts of interest.

Figures

Figure 1.
Figure 1.. Endotype discovery with multi-omics.
Large-scale, system-wide data can be generated by omics to capture intrinsic and extrinsic influences on disease and health, spanning the genome to exposome. Thoughtful integration of such multi-omic data using a variety of models can identify endotypes. For clinical impact and broader use, endotypes identified in a discovery cohort benefit from testing in independent cohort(s) for validation and testing of performance.
Figure 2.
Figure 2.. Analytic methods for endotype discovery using multi-omics.
Approaches commonly used in endotype discovery and multi-omic analyses encompass statistical tests, clustering, feature selection, network analysis, and machine learning/artificial intelligence (AI). Arrows indicate possible workflows between different methods.
See this image and copyright information in PMC

References

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