Integrated single-cell and bulk transcriptome analysis reveal lactate metabolism-related signature and T cell alteration in atrial fibrillation.

Background: Atrial fibrillation (AF) is linked to modifications in T cell-mediated immunity. Although lactate metabolism influences T cell differentiation and function, its specific role in AF and associated immune processes remains inadequately understood. Methods: We performed an integrated transcriptomic analysis utilizing both bulk and single-nucleus RNA sequencing data derived from hearts exhibiting AF and those in sinus rhythm. Genes associated with lactate metabolism were curated from the MsigDB, and key genes were identified through Weighted Gene Co-expression Network Analysis and differential expression analysis. A diagnostic model based on machine learning was developed, and gene expression was further validated using qRT-PCR in a mouse model of AF. T cell heterogeneity was evaluated using the Seurat package, and intercellular communication was inferred using CellChat. Results: In AF, six key genes related to lactate metabolism showed transcriptomic changes linked to the AF phenotype and CD4+/CD8+ T cell populations. A diagnostic model using these genes achieved an AUC of 0.909 in external datasets. Single-nucleus RNA sequencing identified a reduced metabolism-related T cell subset (CLM-T) in AF, with increased CD45 and thrombospondin signaling between CLM-T and other T cell subclusters. qRT-PCR in a mouse AF model confirmed significant gene upregulation in atrial tissue. Conclusion: This study synthesizes bulk and single-cell transcriptomic analyses to identify genes associated with lactate metabolism as potential biomarkers for AF and to elucidate T cell alterations in AF. These findings offer novel insights into the pathogenesis of AF and suggest potential strategies for its diagnosis.