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ATHEROSCLEROSIS / BASIC RESEARCH
The underlying mechanisms of FGF2 in carotid atherosclerotic plaque development revealed
by bioinformatics analysis
1
Department of Geriatrics, Tongji Hospital Affiliated to Tongji University Medical School, Shanghai, China
2
Jiading District Nanxiang Town Community Health Service Center, Affiliated to Tongji University Medical School, Shanghai, China
Submission date: 2020-01-12
Final revision date: 2020-09-30
Acceptance date: 2020-10-12
Online publication date: 2021-05-09
Publication date: 2024-08-04
Corresponding author
Wenlin Ma
Geriatrics Department, Tongji Hospital Affiliated to Tongji University Medical School, No. 389 Xincun Road, Putuo District, Shanghai 200065, China, Phone: +86-021-66111457
Geriatrics Department, Tongji Hospital Affiliated to Tongji University Medical School, No. 389 Xincun Road, Putuo District, Shanghai 200065, China, Phone: +86-021-66111457
Arch Med Sci 2024;20(4):1209-1219
KEYWORDS
carotid atherosclerotic plaquefibroblast growth factor 2differential expressioncoexpression analysisatherosclerosis
TOPICS
ABSTRACT
Introduction:
The purpose of this study was to explore the regulatory mechanisms of FGF2 on carotid atherosclerotic plaque development using bioinformatics analysis.
Material and methods:
Expression profiles of 32 atheroma plaque (AP) and 32 paired distant macroscopically intact (DMI) tissues samples in the GSE43292 dataset were downloaded from the Gene Expression Omnibus database. Following identification of differential expression genes (DEGs), correlation analysis of fibroblast growth factor 2 (FGF2) and DEGs was conducted. Subsequently, functional enrichment analysis and the proteinprotein interaction network for FGF2 significantly correlated DEGs were constructed. Then, microRNAs (miRNAs) that regulated FGF2 and regulatory pairs of long noncoding RNA (lncRNA)-miRNA were predicted to construct the lncRNA-miRNA-FGF2 network.
Results:
A total of 101 DEGs between AP and DMI samples were identified, and 31 DEGs were analyzed to have coexpression relationships with FGF2, including 23 positively correlated and 8 negatively correlated DEGs. VAV3 had the lowest r value among all FGF2 negatively correlated DEGs. FGF2 positively correlated DEGs were closely related to “regulation of smooth muscle contraction” (e.g., calponin 1 [CNN1]), while FGF2 negatively correlated DEGs were significantly associated with “platelet activation” (e.g., Vav guanine nucleotide exchange factor 3 [VAV3]). In addition, a total of 12 miRNAs that regulated FGF2 were predicted, and hsa-miR-15a-5p and hsamiR-16-5p were highlighted in the lncRNA-miRNA-FGF2 regulatory network.
Conclusions:
CNN1 might cooperate with FGF2 to regulate smooth muscle contractility during CAP formation. VAV3 might cooperate with FGF2 to be responsible for the development of CAP through participating in platelet activation. Hsa-miR-15a-5p and hsa-miR-16-5p might participate in the development of CAP via regulating FGF2.
The purpose of this study was to explore the regulatory mechanisms of FGF2 on carotid atherosclerotic plaque development using bioinformatics analysis.
Material and methods:
Expression profiles of 32 atheroma plaque (AP) and 32 paired distant macroscopically intact (DMI) tissues samples in the GSE43292 dataset were downloaded from the Gene Expression Omnibus database. Following identification of differential expression genes (DEGs), correlation analysis of fibroblast growth factor 2 (FGF2) and DEGs was conducted. Subsequently, functional enrichment analysis and the proteinprotein interaction network for FGF2 significantly correlated DEGs were constructed. Then, microRNAs (miRNAs) that regulated FGF2 and regulatory pairs of long noncoding RNA (lncRNA)-miRNA were predicted to construct the lncRNA-miRNA-FGF2 network.
Results:
A total of 101 DEGs between AP and DMI samples were identified, and 31 DEGs were analyzed to have coexpression relationships with FGF2, including 23 positively correlated and 8 negatively correlated DEGs. VAV3 had the lowest r value among all FGF2 negatively correlated DEGs. FGF2 positively correlated DEGs were closely related to “regulation of smooth muscle contraction” (e.g., calponin 1 [CNN1]), while FGF2 negatively correlated DEGs were significantly associated with “platelet activation” (e.g., Vav guanine nucleotide exchange factor 3 [VAV3]). In addition, a total of 12 miRNAs that regulated FGF2 were predicted, and hsa-miR-15a-5p and hsamiR-16-5p were highlighted in the lncRNA-miRNA-FGF2 regulatory network.
Conclusions:
CNN1 might cooperate with FGF2 to regulate smooth muscle contractility during CAP formation. VAV3 might cooperate with FGF2 to be responsible for the development of CAP through participating in platelet activation. Hsa-miR-15a-5p and hsa-miR-16-5p might participate in the development of CAP via regulating FGF2.
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