Unraveling heterogeneity and treatment of asthma through integrating multi-omics data
Asthma has become one of the most serious chronic respiratory diseases threatening people's lives worldwide. The pathogenesis of asthma is complex and driven by numerous cells and their interactions, which contribute to its genetic and phenotypic heterogeneity. The clinical characteristic is in...
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| Format: | Article |
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Frontiers Media S.A.
2024-11-01
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| Series: | Frontiers in Allergy |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/falgy.2024.1496392/full |
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| author | Wei Zhang Yu Zhang Lifei Li Rongchang Chen Fei Shi Fei Shi |
| author_facet | Wei Zhang Yu Zhang Lifei Li Rongchang Chen Fei Shi Fei Shi |
| author_sort | Wei Zhang |
| collection | DOAJ |
| description | Asthma has become one of the most serious chronic respiratory diseases threatening people's lives worldwide. The pathogenesis of asthma is complex and driven by numerous cells and their interactions, which contribute to its genetic and phenotypic heterogeneity. The clinical characteristic is insufficient for the precision of patient classification and therapies; thus, a combination of the functional or pathophysiological mechanism and clinical phenotype proposes a new concept called “asthma endophenotype” representing various patient subtypes defined by distinct pathophysiological mechanisms. High-throughput omics approaches including genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiome enable us to investigate the pathogenetic heterogeneity of diverse endophenotypes and the underlying mechanisms from different angles. In this review, we provide a comprehensive overview of the roles of diverse cell types in the pathophysiology and heterogeneity of asthma and present a current perspective on their contribution into the bidirectional interaction between airway inflammation and airway remodeling. We next discussed how integrated analysis of multi-omics data via machine learning can systematically characterize the molecular and biological profiles of genetic heterogeneity of asthma phenotype. The current application of multi-omics approaches on patient stratification and therapies will be described. Integrating multi-omics and clinical data will provide more insights into the key pathogenic mechanism in asthma heterogeneity and reshape the strategies for asthma management and treatment. |
| format | Article |
| id | doaj-art-00f1c63142454e259bc3891c97b6d0b4 |
| institution | OA Journals |
| issn | 2673-6101 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Allergy |
| spelling | doaj-art-00f1c63142454e259bc3891c97b6d0b42025-08-20T02:18:58ZengFrontiers Media S.A.Frontiers in Allergy2673-61012024-11-01510.3389/falgy.2024.14963921496392Unraveling heterogeneity and treatment of asthma through integrating multi-omics dataWei Zhang0Yu Zhang1Lifei Li2Rongchang Chen3Fei Shi4Fei Shi5Department of Infectious Diseases, the First Affiliated Hospital (Shenzhen People’s Hospital), School of Medicine, Southern University of Science and Technology, Shenzhen, ChinaDepartment of Infectious Diseases, Shenzhen People’s Hospital (The First Affiliated Hospital, Southern University of Science and Technology; The Second Clinical Medical College, Jinan University), Shenzhen, ChinaKey Laboratory of Shenzhen Respiratory Diseases, Institute of Shenzhen Respiratory Diseases, Department of Respiratory and Critical Care Medicine, Shenzhen People’s Hospital (The First Affiliated Hospital, Southern University of Science and Technology; The Second Clinical Medical College, Jinan University), Shenzhen, ChinaKey Laboratory of Shenzhen Respiratory Diseases, Institute of Shenzhen Respiratory Diseases, Department of Respiratory and Critical Care Medicine, Shenzhen People’s Hospital (The First Affiliated Hospital, Southern University of Science and Technology; The Second Clinical Medical College, Jinan University), Shenzhen, ChinaDepartment of Infectious Diseases, the First Affiliated Hospital (Shenzhen People’s Hospital), School of Medicine, Southern University of Science and Technology, Shenzhen, ChinaDepartment of Infectious Diseases, Shenzhen People’s Hospital (The First Affiliated Hospital, Southern University of Science and Technology; The Second Clinical Medical College, Jinan University), Shenzhen, ChinaAsthma has become one of the most serious chronic respiratory diseases threatening people's lives worldwide. The pathogenesis of asthma is complex and driven by numerous cells and their interactions, which contribute to its genetic and phenotypic heterogeneity. The clinical characteristic is insufficient for the precision of patient classification and therapies; thus, a combination of the functional or pathophysiological mechanism and clinical phenotype proposes a new concept called “asthma endophenotype” representing various patient subtypes defined by distinct pathophysiological mechanisms. High-throughput omics approaches including genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiome enable us to investigate the pathogenetic heterogeneity of diverse endophenotypes and the underlying mechanisms from different angles. In this review, we provide a comprehensive overview of the roles of diverse cell types in the pathophysiology and heterogeneity of asthma and present a current perspective on their contribution into the bidirectional interaction between airway inflammation and airway remodeling. We next discussed how integrated analysis of multi-omics data via machine learning can systematically characterize the molecular and biological profiles of genetic heterogeneity of asthma phenotype. The current application of multi-omics approaches on patient stratification and therapies will be described. Integrating multi-omics and clinical data will provide more insights into the key pathogenic mechanism in asthma heterogeneity and reshape the strategies for asthma management and treatment.https://www.frontiersin.org/articles/10.3389/falgy.2024.1496392/fullasthmaheterogeneitymulti-omicspatient stratificationtreatment |
| spellingShingle | Wei Zhang Yu Zhang Lifei Li Rongchang Chen Fei Shi Fei Shi Unraveling heterogeneity and treatment of asthma through integrating multi-omics data Frontiers in Allergy asthma heterogeneity multi-omics patient stratification treatment |
| title | Unraveling heterogeneity and treatment of asthma through integrating multi-omics data |
| title_full | Unraveling heterogeneity and treatment of asthma through integrating multi-omics data |
| title_fullStr | Unraveling heterogeneity and treatment of asthma through integrating multi-omics data |
| title_full_unstemmed | Unraveling heterogeneity and treatment of asthma through integrating multi-omics data |
| title_short | Unraveling heterogeneity and treatment of asthma through integrating multi-omics data |
| title_sort | unraveling heterogeneity and treatment of asthma through integrating multi omics data |
| topic | asthma heterogeneity multi-omics patient stratification treatment |
| url | https://www.frontiersin.org/articles/10.3389/falgy.2024.1496392/full |
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