Identifying and as two hub genes in aortic dissection and function analysis by integrating RNA sequencing and single-cell RNA sequencing data.

Front Cardiovasc Med

Department of Physiology and Pathophysiology, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University School of Basic Medical Sciences, Beijing, China.

Published: October 2024

AI Article Synopsis

  • The study investigates the mechanisms behind aortic dissection (AD) by analyzing public RNA sequencing datasets to identify key hub genes that could aid in diagnosis and treatment.
  • Researchers used multiple analytical methods to screen for overlapping genes and created a protein-protein interaction network, ultimately identifying five top hub genes linked to AD.
  • Further examination revealed specific hub genes upregulated in certain cell types associated with AD, suggesting they play roles in inflammation, glycolysis, tissue remodeling, and angiogenesis.

Article Abstract

Objective: Aortic dissection (AD) is a severe aortic disease with high mortality, and its pathogenesis remains elusive. To explore the regulatory mechanisms of AD, we integrated public RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) datasets to screen the hub genes of AD and further analyzed their functions, which may provide references to the diagnosis and treatment of AD.

Methods: Four AD-related datasets were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis and differential expression analysis were applied to identify overlapping genes in dataset GSE153434. Protein-protein interaction (PPI) network was constructed based on overlapping genes. Five methods (closeness, degree, EPC, MCC, and MNN) were used to pick hub genes. The receiver operating characteristic curve was used to evaluate the diagnostic efficiency of the hub genes in extra datasets GSE98770 and GSE52093. scRNA-seq dataset GSE213740 was used to explore the expression and function of the hub genes at the single-cell level. Quantitative real-time polymerase chain reaction was used to verify the expression of hub genes in beta-aminopropionitrile (BAPN)-induced mouse thoracic aortic aneurysm and dissection (TAAD) model.

Results: A total of 71 overlapping genes were screened by intersecting the significant genes in the pink module and the differentially expressed genes. A PPI network with 45 nodes and 74 edges was generated, and five top hub genes (, , , , and ) were identified. All the hub genes had area under the curve values above 0.55. scRNA-seq data analysis showed that was significantly upregulated in macrophages and was significantly upregulated in vascular smooth muscle cells (SMCs) of the ascending aortas in AD patients. HIF1A may transcriptionally regulate multiple downstream target genes involving inflammation (, , and ), glycolysis (, , and ), tissue remodeling (), and angiogenesis ( and ). HGF may participate in the signaling among SMCs, fibroblasts, and endothelial cells through binding to different receptors (MET, EGFR, IGF1R, and KDR). The mRNA expression of , , and their target genes, including , , , , , and , was significantly upregulated in aortic tissues of BAPN-treated mice.

Conclusion: By integrating RNA-seq and scRNA-seq data, we identified and as two hub genes with good diagnostic efficiency for AD. HIF1A in macrophages may promote AD formation by promoting inflammation, glycolysis, tissue remodeling, and angiogenesis, and HGF may mediate signaling among SMCs, fibroblasts, and endothelial cells in the development of AD.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11521845PMC
http://dx.doi.org/10.3389/fcvm.2024.1475991DOI Listing

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