ORIGINAL RESEARCH article
Front. Immunol.
Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1575490
This article is part of the Research TopicAdvancing biomarker discovery through multi-scale and multi-omics integration in immune disordersView all articles
Disease association study of Autoimmune and autoinflammatory diseases (AIIDs) by integrating Multi-Modal Data and Hierarchical Ontologies
Provisionally accepted
- 1Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China
- 2Department of Rheumatology and Immunology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, Shanghai Municipality, China
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Background: Autoimmune and autoinflammatory diseases (AIIDs) are characterized by significant heterogeneity and comorbidities, complicating their mechanisms and classification. Disease associations studies, or diseasome, facilitate the exploration of disease mechanisms and development of novel therapeutic strategies. However, the diseasome for AIIDs is still in its infancy. To address this gap, we developed a novel framework that utilizes multi-modal data and biomedical ontologies to explore AIID associations. Methods: We curated disease terms from Mondo/DO/MeSH/ICD, and three specialized AIID knowledge bases, creating an integrated repository of 484 autoimmune diseases (ADs), 110 autoinflammatory diseases (AIDs), and 284 associated diseases. By leveraging genetic, transcriptomic (bulk and single-cell), and phenotypic data, we built multi-layered AIID association networks and an integrated network supported by cross-scale evidence. Our ontology-aware disease similarity (OADS) strategy incorporates not only multi-modal data, but also continuous biomedical ontologies. Results: Network modularity analysis identified 10 robust disease communities and their representative phenotypes and dysfunctional pathways. Focusing on 10 highly concerning AIIDs, such as Behçet's disease and Systemic lupus erythematosus, we provide insights into the information flow from genetic susceptibilities to transcriptional dysregulation, alteration in immune microenvironment, and clinical phenotypes, and thus the mechanisms underlying comorbidity. For instance, in systemic sclerosis and psoriasis, dysregulated genes like CCL2 and CCR7 contribute to fibroblast activation and the infiltration of CD4+ T and NK cells through IL-17 signaling pathway, PPAR signaling pathway, leading to skin involvement and arthritis
Keywords: Autoimmune Diseases, Autoinflammatory diseases, Diseasome, disease association, Multi-modal data integration, ontology
Received: 12 Feb 2025; Accepted: 15 May 2025.
Copyright: © 2025 Liu, Su, Zhu and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yuan-Yuan Li, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China
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