ERJ open research · 2026
Airway smooth muscle in asthma: insights from a transcriptomic meta-analysis.
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Roy Saptarshi, Mandal Rahul Shubhra, Kurian Sunil, Sharma Pawan
Аннотация
BACKGROUND: Airway smooth muscle (ASM) cells are central to bronchoconstriction and airway hyperresponsiveness in asthma, yet a comprehensive view of their transcriptional landscape has been lacking.
METHODS: We performed a meta-analysis of publicly available transcriptomic datasets comparing ASM cells isolated from individuals with asthma with those from healthy controls. We included studies that met predefined inclusion criteria, comprising primary human ASM cells isolated from 26 asthma and 32 healthy control subjects. Each dataset was analysed separately, followed by meta-analysis of differentially expressed genes (DEGs). Heterogenicity assessment, pathway enrichment and single-sample gene set enrichment analysis were performed. DEGs were further matched with genome-wide association studies (GWASs) of asthma.
RESULTS: This study identified 150 genes that were consistently dysregulated in asthma-derived ASM cells, compared with those from healthy controls. NLRP2 showed the greatest upregulation in asthma as measured by pooled log2 fold change (effect size) in asthma, whereas ABI3 was the most downregulated. Pathway analysis highlighted prominent perturbation of interleukin (IL)-4 and IL-13 signalling. 13 DEGs overlapped with loci reported earlier in a GWAS asthma database, which further underscores our findings.
CONCLUSIONS: To the best of our knowledge, this is the first meta-analysis of ASM transcriptomes to delineate a core set of genes and pathways underlying asthma-related airway remodelling. These findings refine our understanding of ASM-specific molecular networks and may guide targeted therapeutics for asthma in future.
METHODS: We performed a meta-analysis of publicly available transcriptomic datasets comparing ASM cells isolated from individuals with asthma with those from healthy controls. We included studies that met predefined inclusion criteria, comprising primary human ASM cells isolated from 26 asthma and 32 healthy control subjects. Each dataset was analysed separately, followed by meta-analysis of differentially expressed genes (DEGs). Heterogenicity assessment, pathway enrichment and single-sample gene set enrichment analysis were performed. DEGs were further matched with genome-wide association studies (GWASs) of asthma.
RESULTS: This study identified 150 genes that were consistently dysregulated in asthma-derived ASM cells, compared with those from healthy controls. NLRP2 showed the greatest upregulation in asthma as measured by pooled log2 fold change (effect size) in asthma, whereas ABI3 was the most downregulated. Pathway analysis highlighted prominent perturbation of interleukin (IL)-4 and IL-13 signalling. 13 DEGs overlapped with loci reported earlier in a GWAS asthma database, which further underscores our findings.
CONCLUSIONS: To the best of our knowledge, this is the first meta-analysis of ASM transcriptomes to delineate a core set of genes and pathways underlying asthma-related airway remodelling. These findings refine our understanding of ASM-specific molecular networks and may guide targeted therapeutics for asthma in future.