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Conventional dendritic cell 2 links the genetic causal association from allergic asthma to COVID-19: a Mendelian randomization and transcriptomic study

Hua Liu, Siting Huang, Liting Yang, Hongshu Zhou, Bo Chen, Lisha Wu, Liyang Zhang

2024Journal Of Big Data13 citationsDOIOpen Access PDF

Abstract

Abstract Recent evidence suggests that allergic asthma (AA) decreases the risk of Coronavirus Disease 2019 (COVID-19). However, the reasons remain unclear. Here, we systematically explored data from GWAS (18 cohorts with 11,071,744 samples), bulk transcriptomes (3 cohorts with 601 samples), and single-cell transcriptomes (2 cohorts with 29 samples) to reveal the immune mechanisms that connect AA and COVID-19. Two-sample Mendelian randomization (MR) analysis identified a negative causal correlation from AA to COVID-19 hospitalization (OR = 0.968, 95% CI 0.940–0.997, P = 0.031). This correlation was bridged through white cell count. Furthermore, machine learning identified dendritic cells (DCs) as the most discriminative immunocytes in AA and COVID-19. Among five DC subtypes, only conventional dendritic cell 2 (cDC2) exhibited differential expression between AA/COVID-19 and controls (P < 0.05). Subsequently, energy metabolism, intercellular communication, cellular stemness and differentiation, and molecular docking analyses were performed. cDC2s exhibited more differentiation, increased numbers, and enhanced activation in AA exacerbation, while they showed less differentiation, reduced number, and enhanced activation in severe COVID-19. The capacity of cDC2 for differentiation and SARS-CoV-2 antigen presentation may be enhanced through ZBTB46, EXOC4, TLR1, and TNFSF4 gene mutations in AA. Taken together, cDC2 links the genetic causality from AA to COVID-19. Future strategies for COVID-19 prevention, intervention, and treatment could be stratified according to AA and guided with DC-based therapies. Graphical Abstract

Topics & Concepts

Mendelian randomizationCoronavirus disease 2019 (COVID-19)Association (psychology)Genome-wide association study2019-20 coronavirus outbreakTranscriptomeAsthmaComputational biologyComputer scienceBiologyMedicineGeneticsSingle-nucleotide polymorphismGenotypeImmunologyVirologyGenetic variantsPsychologyGeneInternal medicineDiseaseOutbreakPsychotherapistGene expressionInfectious disease (medical specialty)IL-33, ST2, and ILC PathwaysAsthma and respiratory diseasesSingle-cell and spatial transcriptomics
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