Abstract

   Vitamin C (ascorbic acid) is a nutrient used to treat cardiovascular
   disease (CVD). However, the pharmacological targets of vitamin C and
   the mechanisms underlying the therapeutic effects of vitamin C on CVD
   remain to be elucidated. In this study, we used network pharmacology
   approach to investigate the pharmacological mechanisms of vitamin C for
   the treatment of CVD. The core targets, major hubs, enriched biological
   processes, and key signaling pathways were identified. A
   protein-protein interaction network and an interaction diagram of core
   target-related pathways were constructed. Three core targets were
   identified, including phosphatidylinositol 4,5-bisphosphate 3-kinase
   catalytic subunit alpha isoform, signal transducer and activator of
   transcription-3 (STAT3), and prothrombin. The GO and KEGG analyses
   identified top 20 enriched biological processes and signaling pathways
   involved in the therapeutic effects of vitamin C on CVD. The JAK-STAT,
   STAT, PD1, EGFR, FoxO, and chemokines signaling pathways may be highly
   involved in the protective effects of vitamin C against CVD. In
   conclusion, our bioinformatics analyses provided evidence on the
   possible therapeutic mechanisms of vitamin C in CVD treatment, which
   may contribute to the development of novel drugs for CVD.

   Keywords: vitamin C, cardiovascular disease, network pharmacology,
   inflammation, jak-stat

Introduction

   Cardiovascular disease (CVD) is a leading cause of death worldwide,
   accounting for 205 deaths per 100,000 persons ([30]Yu et al., 2019). It
   represents a substantial proportion of healthcare spending, therefore
   placing an enormous financial burden on patients and their families
   ([31]Evans et al., 2020). CVD is characterized by a cluster of
   disorders in the arteries and heart that result in atherosclerosis,
   hypertension, myocardiopathy, myocardial infarction, and heart failure
   ([32]North and Sinclair, 2012). The mechanism underlying the
   pathogenesis of CVD is complex and has not been fully elucidated
   ([33]Buckley et al., 2019). To develop better treatment for patients
   with CVD, studies have been launched to identify novel therapeutic
   targets for the past two decades ([34]Touzé and Rothwell, 2007;
   [35]O’Donnell and Nabel, 2011; [36]Khera and Kathiresan, 2017). Drugs
   targeting beta receptor, RASS system, P2Y12 receptor, PCSK9, and HMG
   CoA reductase have been shown to decrease cardiovascular morbidity and
   mortality in CVD patients ([37]Ference et al., 2017; [38]Squizzato et
   al., 2017; [39]Blessberger et al., 2018). Despite great advances in
   treatment, CVD remains the dominant cause of mortality worldwide
   ([40]Feng et al., 2019). Hence, there is an urgent need to develop
   novel therapeutic strategies and drugs for the treatment of CVD.

   Vitamin C (ascorbic acid) is a nutrient with radical scavenger activity
   and antioxidant effects ([41]May and Harrison, 2013). Observational
   studies have demonstrated that high vitamin C supplementation is
   inversely correlated with the risk of CVD ([42]Salonen et al., 2003;
   [43]Wang et al., 2013). A systematic meta-analysis of 44 randomized
   controlled trials (RCTs) suggested that vitamin C intake improved left
   ventricular ejection fraction in patients with heart failure ([44]Ashor
   et al., 2014). It has also been shown that vitamin C intake is
   associated with low blood pressure in hypertensive participants
   ([45]Juraschek et al., 2012; [46]Ran et al., 2020). In addition,
   vitamin C supplementation decreased cardiovascular mortality in a
   cohort of Spanish graduates ([47]Martín-Calvo and Martínez-González,
   2017).

   The antioxidant property of vitamin C contributes to the prevention and
   treatment of cardiovascular disorders ([48]Ingles et al., 2020).
   However, the molecular mechanisms remain elusive. Few studies have
   investigated the signaling pathways involved in the effects of vitamin
   C on CVD. The network pharmacology-based approach has been used to
   identify novel therapeutic targets and illustrate the molecular
   mechanisms of vitamin C against sepsis ([49]Li et al., 2020a). We also
   elucidated the pharmacological mechanisms of the active ingredients of
   traditional Chinese medicines on the treatment of CVD ([50]Huang et
   al., 2020).

   In the present study, we investigated the molecular mechanisms
   underlying the protective effects of vitamin C against CVD by using
   network pharmacology approach. Our bioinformatics data may contribute
   to the development of new treatments for CVD for both clinical and
   basic investigators.

Methods

Prediction of Putative Targets of Vitamin C With Therapeutic Potential for
Cardiovascular Disease

   Swiss Target Prediction ([51]http://www.swisstargetprediction.ch),
   DrugBank ([52]http://www.drugbank.ca/) database, and Traditional
   Chinese Medicine Systems Pharmacology (TCMSP,
   [53]http://lsp.nwu.edu.cn/tcmsp.php) were used to obtain all known
   targets of vitamin C. The therapeutic targets for CVD were collected
   using DrugBank database, Online Mendelian Inheritance (OMIM)
   ([54]http://www.omim.org/) database, and GeneCards
   ([55]www.genecards.org/) database. Then the targets of vitamin C with
   therapeutic potential for CVD were identified after eliminating
   duplicates.

Construction of Protein-Protein Interaction Network and Topological Analysis
of Vitamin C Against Cardiovascular Disease

   STRING database was used to construct a target-to-target,
   function-related, protein-protein interaction (PPI) network and to
   obtain general data (tsv.). Protein interactions with a confidence
   score of >0.9 were selected. General data were imported into Cytoscape
   (v3.7.1) to rebuild a PPI network of vitamin C against CVD. The network
   analyzer in Cytoscape was used to analyze the topological parameters,
   including mean and maximum degrees of freedom in the PPI network. The
   upper limit of the screening range was the maximum degree value in the
   topological data, while the lower limit was twice the average degree of
   freedom ([56]Su et al., 2019). The core targets were identified based
   on the above settings.

Functional Processes and Pathway Analysis

   The R packages of ClusterProfiler, enrichplot, and ggplot2 were used
   for Gene Ontology (GO) Biological Function (BP) and Kyoto Encyclopedia
   of Genes and Genomes (KEGG) pathway enrichment analyses of the core
   targets. The cut-off value was set as p < 0.05.

Construction of Network Relationships

   Cytoscape (v3.7.1) software was used for network visualization of the
   targets of vitamin C against CVD. An interaction diagram of core
   target-related GO/KEGG enrichment was generated ([57]Wu et al., 2019).
   The study design is shown in [58]Figure 1.

FIGURE 1.

   [59]FIGURE 1
   [60]Open in a new tab

   A schematic diagram of network pharmacology approach for the
   identification of core targets, major hubs, PPI network, biological
   processes, and key pathways of vitamin C acting on CVD. All known
   targets of vitamin C and CVD were predicted using online databases.
   Then the targets of vitamin C with therapeutic potential for CVD were
   identified. After the construction of a PPI network and the
   identification of the hub targets of vitamin C acting on CVD, GO BP,
   and KEGG pathway enrichment analyses were performed. Finally, a network
   of vitamin C-CVD -GO-KEGG was generated.

Results

Known Targets of Vitamin C With Therapeutic Potential for Cardiovascular
Disease

   A total of 339 known target genes of vitamin C and 802 known
   therapeutic targets for CVD were obtained ([61]Supplementary Tables S1,
   S2). The Venn diagram was plotted using online accessible tools to
   identify the targets of vitamin C against CVD ([62]Figure 2). Finally,
   66 targets of vitamin C with therapeutic potential for CVD were
   identified and then analyzed using STRING database. The
   function-related PPI network is shown in [63]Figure 3.

FIGURE 2.

   FIGURE 2
   [64]Open in a new tab

   The targets of vitamin C with therapeutic potential for CVD were
   identified using the Venn diagram. Swiss Target Prediction, DrugBank
   database, and TCMSP were used to obtain all known targets of vitamin C.
   DrugBank database, OMIM database, and GeneCards database were used to
   collect all therapeutic targets for CVD. A total of 66 targets of
   vitamin C with therapeutic potential for CVD were identified.

FIGURE 3.

   [65]FIGURE 3
   [66]Open in a new tab

   A PPI network of the targets of vitamin C with therapeutic potential
   for CVD was generated. A PPI network of 66 targets was imported into
   STRING database and visualized with the interaction score set to the
   highest confidence (0.900).

Topology Parameter Analysis and Identification of Core Targets

   Cytoscape was used to calculate the topological parameters of the
   interaction network of 66 identified targets ([67]Figure 4). The
   minimum degree of freedom of the target was one and the maximum degree
   of freedom was 21. The screening criteria were set to 12 and 21 for the
   core targets. A total of three core targets were determined, including
   phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha
   isoform (PIK3CA), signal transducer and activator of transcription-3
   (STAT3), and prothrombin (F2) ([68]Figure 5).

FIGURE 4.

   [69]FIGURE 4
   [70]Open in a new tab

   A protein network of known targets of vitamin C with therapeutic
   potential for CVD was generated by Cytoscape. The targets were imported
   into Cytoscape for the analysis of topological parameters. The diagram
   was generated based on topological analysis.

FIGURE 5.

   FIGURE 5
   [71]Open in a new tab

   The hub targets of vitamin C with therapeutic potential for CVD were
   identified using the Cytoscape software. The median and maximum degrees
   of freedom of the target were 1 and 21, respectively. To screen the hub
   targets, the degree of freedom was set to >12.

Gene Ontology Biological Function and Kyoto Encyclopedia of Genes and Genomes
Pathway Enrichment Analysis

   The GO BP and KEGG pathway enrichment analyses of three core targets
   were performed using R language. The enriched biological functions
   included regulation of energy homeostasis, acute-phase response,
   regulation of multicellular organism growth, regulation of
   multicellular organism growth, astrocyte differentiation, negative
   regulation of autophagy, positive regulation of phosphatidylinositol
   3-kinase signaling, positive regulation of receptor signaling pathway
   via JAK-STAT, positive regulation of receptor signaling pathway via
   STAT, acute inflammatory response, regulation of phosphatidylinositol
   3-kinase signaling, regulation of receptor signaling pathway via
   JAK-STAT, multicellular organism growth, regulation of receptor
   signaling pathway via STAT, phosphatidylinositol 3-kinase signaling,
   platelet activation, regulation of generation of precursor metabolites
   and energy, receptor signaling pathway via JAK-STAT, receptor signaling
   pathway via STAT, phosphatidylinositol-mediated signaling, and inositol
   lipid-mediated signaling ([72]Figure 6). The enriched molecular
   signaling pathways of the core targets were involved in acute myeloid
   leukemia, non-small cell lung cancer, prolactin signaling pathway,
   pancreatic cancer, EGFR tyrosine kinase inhibitor resistance, PD-L1
   expression and PD-1 checkpoint pathway in cancer, AGE-RAGE signaling
   pathway in diabetic complications, insulin resistance, HIF-1 signaling
   pathway, growth hormone synthesis, secretion and action, platelet
   activation, FoxO signaling pathway, measles, signaling pathways
   regulating pluripotency of stem cells, phospholipase D signaling
   pathway, Hepatitis C, JAK-STAT signaling pathway, Hepatitis B,
   chemokines signaling pathway, and Kaposi’s sarcoma-associated
   herpesvirus infection ([73]Figure 7).

FIGURE 6.

   [74]FIGURE 6
   [75]Open in a new tab

   GO BP analysis of the core targets. GO BP enrichment analysis of the
   three core targets was performed using R language. (A) The bubble
   diagram shows the top 20 enriched BP. The x-axis represents the gene
   ratio and the intensities of different colors indicate the adjusted
   p-value. (B) The histogram shows the top 20 enriched BP. The x-axis
   represents the enriched gene count and the intensities of different
   colors indicate the adjusted p-value.

FIGURE 7.

   [76]FIGURE 7
   [77]Open in a new tab

   The KEGG pathway enrichment analysis of the core targets. The KEGG
   pathway enrichment analysis was performed using R language. (A) The
   bubble diagram shows the top 20 enriched KEGG pathways. The x-axis
   represents the gene ratio and the intensities of different colors
   indicate the adjusted p-value. (B) The histogram shows the top 20
   enriched KEGG pathways. The x-axis represents the enriched gene count
   and the intensities of different colors indicate the adjusted p-value.

Network Construction

   The network of the core targets of vitamin C with therapeutic potential
   for CVD and the interaction diagram of the core target-related pathways
   were constructed ([78]Figure 8).

FIGURE 8.

   [79]FIGURE 8
   [80]Open in a new tab

   The integrated vitamin C-CVD-GO-KEGG network was visualized by
   Cytoscape. The yellow rectangles represent three core targets. The blue
   rectangles show the top 20 enriched GO BP and KEGG pathways of vitamin
   C acting on CVD.

Discussion

   Oxidative stress and inflammation play a crucial role in the onset and
   progression of atherosclerosis and the development of cardiovascular
   events ([81]Pignatelli et al., 2018; [82]Ilatovskaya et al., 2019).
   Inflammation promotes oxidative stress, which in turn leads to further
   inflammation, therefore establishing a self-perpetuating cycle.
   Methotrexate and doxycycline, two medications with antioxidant
   properties, exhibit therapeutic benefits in patients with CVD, possibly
   by inhibiting inflammation and breaking the self-perpetuating cycle
   ([83]Clemens et al., 2020). Numerous studies have shown that reduced
   inflammation attenuated CVD. Statins reduce both LDL cholesterol and
   high-sensitivity C-reactive protein (hs-CRP), a biomarker of
   inflammation ([84]Ridker et al., 1999; [85]Albert et al., 2001).
   Moreover, a clinical trial showed that treatment with canakinumab, a
   monoclonal antibody targeting interleukin (IL)-1β, significantly
   downregulated hs-CRP and reduced the occurrence of cardiovascular
   events ([86]Harrington 2017; [87]Ridker et al., 2017). However,
   treatment efficacy of other inflammation inhibitors for CVD needs to be
   evaluated in future clinical studies. The role of oxidative stress and
   inflammation in CVD remain to be deeply and systematically
   investigated. The identification of new therapeutic targets and the
   elucidation of novel regulatory mechanisms of existing drugs enable the
   development of treatments for CVD. The network pharmacology approach is
   an innovative method to systematically explore the mechanisms of the
   effects of drugs on disease. It consists of bioinformatics, network
   analysis and integrates multiple sources of information. Hence, network
   approaches can accurately determine potential interactions between drug
   and target, and promote drug discovery. In this study, we used network
   pharmacology to identify the core targets of vitamin C with therapeutic
   potential for CVD and performed GO BP and KEGG enrichment analyses.
   Bioinformatics findings can reveal the proposed pharmacological
   mechanism and strengthen the new ideas for CVD treatment ([88]Zhang et
   al., 2020).

   Previous studies have extensively reported the beneficial effects of
   vitamin C on CVD. However, large RCTs did not identify any benefit of
   vitamin C (and E) intake on CVD ([89]Cook et al., 2007; [90]Sesso et
   al., 2008). Furthermore, a meta-analysis of RCTs showed that vitamin C
   supplementation has no effects on major cardiovascular outcomes such as
   CVD mortality and myocardial infarction ([91]Al-Khudairy et al., 2017).
   There is still a need to identify the role of vitamin C in mitigating
   cancer treatment-induced heart failure ([92]Malik et al., 2020) and
   other risks of CVD, including cardiomyopathies, arrhythmias and
   myocarditis/pericarditis in long-term cancer survivors ([93]Berretta et
   al., 2020). However, the evidence is limited because many trials of
   vitamin C (and E) supplementation did not report protective effects on
   risks of CVD, such as blood pressure, arterial stiffness, endothelial
   function, or left ventricular ejection fraction. These risks of CVD may
   be more sensitive to vitamin C (and E) supplementation because they are
   responsible for the damaging effects of inflammation and oxidative
   stress ([94]Pashkow, 2011). Moreover, they occur in the early stage of
   CVD pathogenesis. The potential protective effects of vitamin C intake
   on CVD remains controversial in both preclinical and clinical studies
   ([95]Morelli et al., 2020). Therefore, to promote novel drug discovery,
   the mechanisms underlying the therapeutic effects of vitamin C on CVD
   should be well determined. Here, three core targets of vitamin C
   against CVD were identified: PIK3CA, STAT3, and F2. The GO analysis
   revealed that the most enriched BP was positive regulation of the STAT
   signaling pathways, which may play a critical role in CVD. The JAK-STAT
   pathway, which can be activated by a range of cytokines (i.e., IL-6,
   IL-2, and interferons), regulate the survival, proliferation, and
   differentiation of various types of cells ([96]Speirs et al., 2018). In
   addition, the excessive activation of the JAK-STAT signaling is a key
   driver of many chronic inflammatory diseases, including CVD ([97]Jones
   et al., 2011; [98]Sansone and Bromberg, 2012). The four JAKs (JAK1-3
   and Tyk2) comprise a family of cytoplasmic tyrosine kinases.
   Inflammatory cytokines, such as IL-6, promote the activation of JAKs,
   leading to subsequent phosphorylation of gp130 on Tyr residues, which
   generates docking sites for SH2-domain-containing STAT proteins
   ([99]Schaper and Rose-John, 2015). JAKs induce Tyr-phosphorylation of
   STATs within their SH2 domains (Tyr701 on STAT1, Tyr705 on STAT3). The
   activated STATs translocate to the nucleus to drive the transcription
   of inflammatory target genes ([100]Mao et al., 2005; [101]O’Shea et
   al., 2013). Vitamin C is a potent anti-inflammatory drug ([102]Williams
   et al., 2019) that has been used to treat inflammatory diseases, such
   as obesity, sepsis, and pneumonia ([103]Gorton and Jarvis, 1999;
   [104]Ellulu., 2017; [105]Marik, 2018). In the present study, we showed
   the therapeutic effects of vitamin C on CVD were associated with its
   anti-inflammatory property, more specifically, the inhibition of the
   JAK-STAT signaling. Therefore, drugs targeting the JAK-STAT signaling
   may be developed for the treatment of CVD.

   In agreement with GO analysis, KEGG pathway enrichment analysis also
   showed that the therapeutic effects of vitamin C on CVD were mainly
   associated with the JAK-STAT signaling pathway, as well as the PD-1
   pathway, EGFR tyrosine kinase inhibitor resistance, the FoxO signaling
   pathway, and the chemokines signaling pathway ([106]Li et al., 2020a;
   [107]Li et al., 2020b). There is crosstalk among STAT, PD-1, EGFR, and
   FoxO signals. It was reported that the upregulation of EGFR promoted
   COPD airway epithelial cells by regulating the FOXO signaling pathway
   ([108]Ganesan et al., 2013). JAK-STAT and EGFR together specify a
   population of cells called the posterior follicle cells to establish
   the embryonic axes ([109]Wittes and Schüpbach, 2019). The expression of
   PD-L1 was induced by EGFR and JAK2/STAT1, while the inhibition of JAK2
   repressed the upregulation of PD-L1 in tumor cells and enhanced their
   immunogenicity ([110]Concha-Benavente et al., 2016). A clinical study
   showed that patients with EGFR mutation had increased PD-L1 expression
   and T cell infiltration ([111]Chen et al., 2020). The activation of
   STAT resulted in upregulated PD-L1 expression and the progression of
   lymphoma ([112]Estrada et al., 2018). The activation of EGFR was
   implicated in CVD via the regulation of blood pressure, endothelial
   dysfunction, neointimal hyperplasia, atherogenesis, and cardiac
   remodeling ([113]Makki et al., 2013). In addition, FOXOs were
   identified as therapeutic targets in several major cardiac diseases,
   such as ischemic cardiac diseases, diabetic cardiomyopathy, and
   myocardial hypertrophy ([114]Xin et al., 2017). The expression level of
   PD-1 can affect the degree of inflammation and the state of coronary
   plaques in atherosclerosis ([115]Sun et al., 2020). The crosstalk among
   these signaling pathways result in excessive inflammation of heart and
   vessels. In this study, we demonstrated that these signaling pathways
   play crucial roles in the progression of CVD. The network pharmacology
   provided a better understanding of the role of inflammation in CVD at
   systematic level. Further studies are needed to determine the role of
   these pathways in CVD and the mechanisms involved in the regulatory
   processes.

   KEGG pathway enrichment showed that the chemokines signaling pathway
   was implicated in the therapeutic effects of vitamin C against CVD. The
   secreted chemokines cause epidermal damage by attracting
   proinflammatory immunocytes ([116]Bellón, 2019). The role of
   immunocytes in CVD has been studied. Neutrophils promote
   atherosclerosis at different stages, including atherogenesis, plaque
   destabilization, and plaque erosion ([117]Silvestre-Roig et al., 2020).
   They are also involved in the pathogenic and repair processes in heart
   failure, myocardial infarction, and neointima formation. A number of
   experimental and clinical studies have indicated that T cells protect
   against cardiovascular disease, particularly atherosclerosis and
   abdominal aortic aneurysm ([118]Meng et al., 2016). Other clinical
   researchers suggested that therapeutic strategies targeting B cells
   might exhibit beneficial effects on CVD ([119]Porsch and Binder, 2019).
   Our data indicated that the blockage of the chemokines signaling
   pathway and immune response could reduce the progression of CVD.
   Because of the crosstalk among inflammation, oxidative stress, immune
   response, and chemokines, combination drug treatment may be a more
   useful approach for the treatment of CVD.

Conclusion

   In summary, we identified three core targets (PIK3CA, STAT3, and F2) of
   vitamin C with therapeutic potential for CVD and showed that the
   protective effects of vitamin C on CVD were attributed to its
   anti-inflammation property. The most enriched pathways were the
   JAK-STAT, PD-1, EGFR, FoxO, and chemokines signaling pathways. Our
   findings may guide further pharmacological investigations on the
   therapeutic effects of vitamin C on CVD and the discovery of new drugs
   for CVD treatment.

Limitation

   There are some limitations to the current study. First, the targets of
   vitamin C with therapeutic potential for CVD were collected using
   public databases, which may lead to inaccurate results. Second, the
   core targets identified in the current study need to be further
   validated. Third, as CVD is a complex process involving different types
   of diseases, the roles of these targets and pathways in specific
   pathological conditions need to be evaluated in both basic scientific
   and clinical studies.

Data Availability Statement

   The original contributions presented in the study are included in the
   article/[120]Supplementary Material, further inquiries can be directed
   to the corresponding author.

Author Contributions

   NZ: designed, drafted, and revised the manuscript. BWH: performed the
   research and wrote the manuscript. WBJ: collected and analyzed the
   data. All the authors read and approved the final manuscript.

Funding

   This research was supported by Natural Science Foundation of Zhejiang
   Province (No. LQ20H020011).

Conflict of Interest

   The authors declare that the research was conducted in the absence of
   any commercial or financial relationships that could be construed as a
   potential conflict of interest.

Supplementary Material

   The Supplementary Material for this article can be found online at:
   [121]https://www.frontiersin.org/articles/10.3389/fphar.2020.591337/ful
   l#supplementary-material.
   [122]Click here for additional data file.^ (16.3KB, xlsx)
   [123]Click here for additional data file.^ (27.4KB, xlsx)

References