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. 2024 Sep 28;14(1):22536.
doi: 10.1038/s41598-024-73691-3.

Identification of biological significance of different stages of varicose vein development based on mRNA sequencing

Meng-Jie Shi  1 , Yan Yan  1 , Fei Liu  1 , Jin-Xing Zhao  1 , Feng Hou  1 , Shi-Cai He  1 , Rui-Peng Zhang  1 , Hui Wang  2
Affiliations

Identification of biological significance of different stages of varicose vein development based on mRNA sequencing

Meng-Jie Shi et al. Sci Rep. .

Abstract

Normal veins could develop to varicose vein (VV) by some risk factors, and might further progress to shallow vein thrombosis (SVT). However, the molecular mechanism of key genes associated with the progression and regression of VV are still not thorough enough. In this study, the healthy control (HC), VV, and SVT vascular samples were collected for transcriptome sequencing. The differentially expressed genes (DEGs) were screened by "DESeq2", including DEGs1 (HC vs. VV), DEGs2 (HC vs. SVT) and DEGs3 (VV vs. SVT). And their functional enrichment analyses were conducted by "ClusterProfiler". The receiver operating characteristic (ROC) curve was used to obtain the key genes (KGs) of the pathogenesis of VV and SVT. The qRT-PCR assay was performed to validate the expressions of KGs. Immune cell infiltration analyses were conducted based on ssGSEA method. The competitive endogenous RNAs (ceRNAs) regulatory network was constructed. The target drugs of KGs were predicted using DrugBank database. The biofunctions of DACT3 were further investigated through a series of experiments in vitro. All of these DEGs were associated with inflammation and immunity related functions. Immune cell infiltration was significantly different between VV and SVT. Six key genes including PLP2, DACT3, LRRC25, PILRA, MSX1 and APOD that were associated with the progression and regression of VV were screened. The expression of LRRC25 and PILRA was significantly negatively associated with central memory T cell, and significantly positively associated with B cell. Besides, XIST was the critical regulator of multiple KGs. Cimetidine was potential drug for VV and SVT therapy. Overexpression of DACT3 significantly inhibited the proliferation and migration of vascular smooth muscle cells (VSMCs), and affected their cell cycle and phenotypic transition. This study identified six key genes associated with the progression and regression of VV. Among them, DACT3 was proved to hinder VV progression. These findings may help to deepen understanding its underlying mechanisms.

Keywords: Function; Gene regulation; Immune; Shallow vein thrombosis; Varicose vein.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Identification of VV-related DEGs and the corresponding enrichment analyses. (A–C) The differential expression landscapes between VV and other clinical samples (Control and SVT). (D–F) Go and KEGG biological analyses of DEGs. VV varicose vein, SVT shallow vein thrombosis, DEGs differentially expressed genes.
Fig. 2
Fig. 2
The effects of core DEGs on immune cells in VV and SVT. (A) The heatmap of immune cell proportion between different clinical samples. (B) The differences in the infiltration levels of five immune cells between normal, VV and SVT samples. (C) The expressive heatmap of immune markers between different clinical samples. (D) The differences in the expressions of several immune markers between normal, VV and SVT samples. *P<0.05, **P<0.01, ***P<0.001; NS no significance.
Fig. 3
Fig. 3
Identification of core genes in VV progression. (A) The intersection between three types of DEGs. (B–D) Go and KEGG biological analyses of core genes based on Metascape database. VV varicose vein, SVT shallow vein thrombosis, DEGs differentially expressed genes.
Fig. 4
Fig. 4
Clinical and immune values of core genes. (A) Diagnostic accuracy of core genes in VV. (B) Diagnostic accuracy of core genes in the process of VV progressing to SVT. (C,D) The expressive correlations between two types of DEGs and five immune cells. (E) Diagnostic accuracy of core genes in VV and SVT. (F,G) The expressive correlations between six critical genes and five immune cells.
Fig. 5
Fig. 5
The ceRNA-miRNA-mRNA regulatory network of six critical genes.
Fig. 6
Fig. 6
The drug prediction of core genes based on DGIdb database. (A) The drug prediction of core differential genes between VV and normal samples. (B) The drug prediction of core differential genes between SVT and normal samples. (C) The drug prediction of core differential genes between VV and SVT samples.
Fig. 7
Fig. 7
Validation the expressions of core genes in the process of occurrence and development of VV. *P<0.05, **P<0.01, ***P<0.001; NS no significance.
Fig. 8
Fig. 8
The biofunctions of DACT3 in VV. (A) Western blot detections on 4 pairs of clinical samples for confirming the DACT3 expressions in VV; (B,C) The tests of transfection efficiency via PCR and Western blot assays; (D) The effects of DACT3 on the proliferation of VSMCs as CCK8 assay determined; (E) The effects of DACT3 on the cell cycle of VSMCs as flow cytometric analysis determined; (F) Quantitative analysis of flow cytometry; (G) The effects of DACT3 on the migration of VSMCs as transwell assay determined; (H) Cell counting of transwell migration assay; (I) The effects of DACT3 on the vascular phenotype transition; VV varicose vein, sh-DACT3 short-hairpin target DACT3, OE-DACT3 overexpression of DACT3,VSMCs vascular smooth muscle cells; *P<0.05, **P<0.01, ***P<0.001.
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