GAS6-AS1, a long noncoding RNA, functions as a key candidate gene in atrial fibrillation related stroke determined by ceRNA network analysis and WGCNA

• Published in: BMC medical genomics 2023-03, Vol.16 (1), p.51-51, Article 51
• Main Authors: Li, Rui-Bin, Yang, Xiao-Hong, Zhang, Ji-Dong, Cui, Wei
• Format: Article
• Language: English
• Subjects: Analysis; Antisense RNA; Atrial fibrillation; Atrial Fibrillation - genetics; Cardiac arrhythmia; Care and treatment; Causes of; Cluster analysis; Competing endogenous RNA; Complications and side effects; Datasets; Disease; Fibrillation; GAS6-AS1; Gene expression; Gene Regulatory Networks; Gene set enrichment analysis; Genetic aspects; Humans; Identification and classification; Immune response; Ischemia; Long non-coding RNA; MicroRNAs; MicroRNAs - genetics; Mortality; Non-coding RNA; Protein interaction; Proteins; RNA, Long Noncoding - genetics; RNA, Long Noncoding - metabolism; Software; Stroke; Stroke (Disease); Stroke - genetics; Weighted gene co‑expression network analysis
• ISSN: 1755-8794; 1755-8794
• DOI: 10.1186/s12920-023-01478-y

Stroke attributable to atrial fibrillation (AF related stroke, AFST) accounts for 13 ~ 26% of ischemic stroke. It has been found that AFST patients have a higher risk of disability and mortality than those without AF. Additionally, it's still a great challenge to treat AFST patients because its exact mechanism at the molecular level remains unclear. Thus, it's vital to investigate the mechanism of AFST and search for molecular targets of treatment. Long non-coding RNAs (lncRNAs) are related to the pathogenesis of various diseases. However, the role of lncRNAs in AFST remains unclear. In this study, AFST-related lncRNAs are explored using competing endogenous RNA (ceRNA) network analysis and weighted gene co-expression network analysis (WGCNA). GSE66724 and GSE58294 datasets were downloaded from GEO database. After data preprocessing and probe reannotation, differentially expressed lncRNAs (DELs) and differentially expressed mRNAs (DEMs) between AFST and AF samples were explored. Then, functional enrichment analysis and protein-protein interaction (PPI) network analysis of the DEMs were performed. At the meantime, ceRNA network analysis and WGCNA were performed to identify hub lncRNAs. The hub lncRNAs identified both by ceRNA network analysis and WGCNA were further validated by Comparative Toxicogenomics Database (CTD). In all, 19 DELs and 317 DEMs were identified between the AFST and AF samples. Functional enrichment analysis suggested that the DEMs associated with AFST were mainly enriched in the activation of the immune response. Two lncRNAs which overlapped between the three lncRNAs identified by the ceRNA network analysis and the 28 lncRNAs identified by the WGCNA were screened as hub lncRNAs for further validation. Finally, lncRNA GAS6-AS1 turned out to be associated with AFST by CTD validation. These findings suggested that low expression of GAS6-AS1 might exert an essential role in AFST through downregulating its downstream target mRNAs GOLGA8A and BACH2, and GAS6-AS1 might be a potential target for AFST therapy.