Integrative multi-omics and machine learning identify CHRNA1 putative circadian-immune hub in COPD - Lan Zhang; Zhifei Li; Tiansheng Xia; Tingting Yang; Jia Fu; Yan Lu; Jiayi Xu; Kaiyu Han (PLoS ONE, 2026)
Background Circadian rhythm disruption is increasingly recognized as a contributor to chronic inflammatory disorders; however, its specific significance and underlying mechanisms in chronic obstructive pulmonary disease (COPD) remain unclear. This study aimed to identify circadian rhythm-associated biomarkers in COPD and explore their diagnostic value, immune correlations, and therapeutic potential. Methods This study integrated four lung transcriptomic datasets from the public GEO database (GSE151052, GSE38974, and GSE76925 as the discovery set, and GSE47460 as the validation set). Differentially expressed circadian rhythm‑related genes (DECRRGs) were identified by intersecting differentially expressed genes with circadian rhythm‑related genes. Functional enrichment analyses (GO and KEGG) were performed, and three machine learning algorithms were applied to screen for signature DECRRGs. An exploratory risk stratification model based on multivariate logistic regression was constructed and evaluated. Immune cell infiltration was assessed using CIBERSORT, and single-cell RNA sequencing analysis was conducted to localize the distribution of key circadian rhythm genes within specific lung cell populations. Finally, the expression of a core gene CHRNA1 was validated by qRT-PCR in peripheral blood samples from COPD patients and healthy controls. Results We identified eight circadian rhythm-associated feature genes, among which CHRNA1 emerged as a consistently upregulated hub gene in COPD. An exploratory risk stratification model based on these genes exhibited good discriminatory ability in the discovery cohort (AUC = 0.856, 95% CI: 0.806–0.902). Differential expression of CHRNA1 was validated in an independent cohort and correlated significantly with pro-inflammatory immune infiltration, including increased M1 macrophages and CD8 ⁺ T cells. Single-cell transcriptomics further localized CHRNA1 expression predominantly within B cells in COPD lung tissue. In silico drug screening and ceRNA network analysis predicted potential therapeutics (e.g., amitriptyline, rocuronium bromide) and regulatory miRNAs/lncRNAs. Finally, qRT-PCR confirmed a marked upregulation of CHRNA1 in peripheral blood from COPD patients ( *p* < 0.0001). Conclusions Our findings suggest that CHRNA1 may serve as a candidate circadian rhythm‑associated immunomodulator in COPD. It demonstrates consistent upregulation across cohorts and shows a significant association with pro‑inflammatory immune infiltration. Single-cell analysis revealed that CHRNA1 is predominantly expressed in pulmonary B cells. The exploratory risk stratification model and predicted therapeutic candidates highlight the translational potential of targeting circadian disruption in COPD, though prospective validation is needed before clinical application.