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Updated: Jul 19, 2026

Isolation of Human Atrial Myocytes for Simultaneous Measurements of Ca2+ Transients and Membrane Currents
Published on: July 3, 2013
Identification of basement membrane-associated genes as biomarkers for atrial fibrillation
Luofei Huang1, Min Huang2, Han Li2
1Department of Anesthesiology, Liuzhou Municipal Liutie Central Hospital, Liuzhou, China.
Abstract:
Atrial fibrillation (AF) is the most common persistent arrhythmia, contributing substantially to morbidity, mortality, and healthcare burden. The basement membrane is essential for tissue homeostasis and disease regulation. Exploring the relationship between AF and basement membrane-associated genes may provide new insights into the molecular mechanisms of atrial remodeling and arrhythmogenesis. mRNA expression datasets (GSE31821, GSE41177, GSE79768) were obtained from the Gene Expression Omnibus (GEO). The "merge" function in R was used to identify the overlap between basement membrane-related genes and these datasets. Differentially expressed basement membrane-related genes (DEBMRGs) were analyzed through enrichment analysis. Key target genes were screened using Lasso regression, Random Forest, SVM-RFE, and protein-protein interaction (PPI) network analysis. Mendelian randomization (MR) was applied for validation. Immune cell infiltration and gene set variation analysis (GSVA) were further performed. Fifty-five DEBMRGs were identified. PPI network construction and machine learning approaches consistently highlighted ITGA1 and ITGB5 as central genes. MR analysis supported these findings, showing an odds ratio (OR) of 1.033 [95% CI: 1.028-1.038, P = 1.55 × 10-36] for ITGA1 and an OR of 0.891 [95% CI: 0.862-0.921, P = 7.66 × 10-12] for ITGB5. No evidence of heterogeneity or pleiotropy was detected. Immune infiltration analysis revealed significant immune cell differences between AF and control samples. This study identifies ITGA1 and ITGB5 as basement membrane-associated genes linked to AF, providing novel insight into AF pathogenesis. These genes may represent promising biomarkers and therapeutic targets for AF management.
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