ArticleFrontiers in immunology2024
Single cell multi-omic analysis identifies key genes differentially expressed in innate lymphoid cells from COVID-19 patients.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Heterogeneity and clinical relevance of group 2 innate lymphoid cells subsets in nasal polyps.The Journal of allergy and clinical immunology · 2026Article
- A protocol for high-quality single-cell RNA sequencing with cell surface protein quantification.Blood science (Baltimore, Md.) · 2026Article
- Multiple omics-based machine learning reveals peripheral blood immune cell landscape during acute rejection of kidney transplantation and constructs a precise non-invasive diagnostic strategy.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Article
- Prolonged airway explant culture enables study of health, disease, and viral pathogenesis.Science advances · 2025Article
- Single-Cell Analysis: A Method for In-Depth Phenotyping of Cells Involved in Asthma.International journal of molecular sciences · 2024Review
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Authors and funding
15 authors.
Funding
Abstract
Introduction: Innate lymphoid cells (ILCs) are enriched at mucosal surfaces where they respond rapidly to environmental stimuli and contribute to both tissue inflammation and healing. Methods: To gain insight into the role of ILCs in the pathology and recovery from COVID-19 infection, we employed a multi-omics approach consisting of Abseq and targeted mRNA sequencing to respectively probe the surface marker expression, transcriptional profile and heterogeneity of ILCs in peripheral blood of patients with COVID-19 compared with healthy controls. Results: We found that the frequency of ILC1 and ILC2 cells was significantly increased in COVID-19 patients. Moreover, all ILC subsets displayed a significantly higher frequency of CD69-expressing cells, indicating a heightened state of activation. ILC2s from COVID-19 patients had the highest number of significantly differentially expressed (DE) genes. The most notable genes DE in COVID-19 vs healthy participants included a) genes associated with responses to virus infections and b) genes that support ILC self-proliferation, activation and homeostasis. In addition, differential gene regulatory network analysis revealed ILC-specific regulons and their interactions driving the differential gene expression in each ILC. Discussion: Overall, this study provides mechanistic insights into the characteristics of ILC subsets activated during COVID-19 infection.
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