Introduction

The new coronavirus pneumonia disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is a severe respiratory disease, with the first case identified in December 2019. It has now spread worldwide and poses a serious threat to public health and economic conditions (Wiersinga et al. 2020; Coronaviridae Study Group of the International Committee on Taxonomy of Viruses 2020; Dhama et al. 2020; Bchetnia et al. 2020; Weston and Frieman 2020; Ahsan et al. 2021). After the COVID-19 outbreak, effective diagnostic methods and infectious disease control measures, such as new coronavirus nucleic acid detection, urban blockade and use of masks, were implemented throughout the country, which decreased the spread of the disease in some countries and regions (Lian et al. 2020). Despite the rapid and effective containment of COVID-19 outbreaks in multiple regions, the global spread of COVID-19 has not been effectively controlled in all affected countries to date (Zhang et al. 2020a). According to the data provided by the World Health Organization, as of 22 December 2020, 78,299,811 confirmed cases of COVID-19 and more than 1.7 million deaths were reported worldwide (Ahamad et al. 2020; Aktar et al. 2021; Uddin et al. 2021). In addition, by the end of May 2021, approximately, 169 million COVID-19 cases and more than 3.5 million deaths had been confirmed worldwide (Aktar et al. 2021; Auwul et al. 2021). COVID-19 has emerged as one of the most devastating and long-lasting epidemics affecting human health in the 21st century. Therefore, effectively controlling and treating COVID-19 are grave concerns worldwide. Unlike other severe infectious diseases, COVID-19 lacks a typical clinical presentation. Respiratory symptoms and others reported to be related to COVID-19 include fever, cough, headache, conjunctivitis, diarrhoea and muscle or systemic pain (Rothan and Byrareddy 2020; Pascarella et al. 2020), which may be similar to the symptoms of other respiratory infections. Some patients may not have any symptoms after infection but may spread the disease. Moreover, specific drugs for treating COVID-19 have not yet been developed for clinical use, thus making the rapid diagnosis, effective control and treatment of COVID-19 difficult. Therefore, the identification of novel biomarkers at different omic levels (genomic, transcriptional or proteomic) may facilitate large-scale screening, diagnosis and treatment of COVID-19 (Chen et al. 2021), which is crucial to reveal the underlying pathogenesis of COVID-19, develop novel therapeutic strategies, discover potential therapeutic targets and improve therapeutic efficacy.

Ion channels are specific membrane proteins present in all cell membranes and some organelle membranes (e.g., mitochondria, Golgi apparatus, endoplasmic reticulum and lysosomes) (Wu et al. 2019; Tao et al. 2016). Ion channel genes encode these specific membrane proteins (mainly pore-forming membrane proteins) expressed in each living cell, which are oligomeric protein complexes composed of multiple subunits with ion-selective and voltage-gating properties (Noskov and Roux 2007). These membrane proteins can precisely control the passive influx and efflux of signalling ions into and out of the cell, thereby regulating ion concentrations inside and outside the cell membrane, membrane potential and volume size of the cell (Kondratskyi et al. 2018). Ion channels are involved in various physiological activities (Becchetti 2011), including muscle contraction, hormone secretion, cell proliferation and immune responses (Camerino et al. 2008; Fiske et al. 2006; Roger et al. 2006), and play an important role in maintaining homeostasis of the intracellular environment. Ion channels include sodium (Na +), potassium (K +), calcium (Ca +) and chloride (Cl-) ions and nonspecific cation channels (Lu et al. 2021a). Because ion channels play a key role in diverse biological functions, abnormal expression of ion channel genes plays a crucial role in many diseases (Sun et al. 2020). Ion channel genes are closely associated with tumour initiation and progression {e.g., breast cancer (Nelson et al. 2014), lung cancer (Ko et al. 2014), liver cancer (Lu et al. 2021b) and gastric cancer (Anderson et al. 2019)}, epilepsy (Oyrer et al. 2018), kidney stones, hypertension, insulin secretion deficiency and cardiac arrhythmias (Jentsch et al. 2004). However, limited information is available regarding the molecular characteristics of ion channel genes involved in COVID-19. In addition to impairing the respiratory system, COVID-19 has been reported to present in multiple organs to produce various clinical manifestations, including cardiovascular, urological, musculoskeletal, and neurological symptoms (Chen et al. 2020), whereas ion channels are known to be highly enriched in the nervous system and cardiac organs. It has been suggested that ion channels may be involved in the inflammation, pain, fever, anosmia, ageusia, respiratory, cardiovascular, gastrointestinal and neurological complications caused by COVID-19 infection (Jaffal and Abbas 2021). Epilepsy has been reported in the literature to occur with COVID-19 infection (Nikbakht et al. 2020), and epilepsy is currently considered to be an ion channel-related disorder. Therefore, exploring the relevant features of ion channels in COVID-19 and understanding their biological mechanisms are crucial for the treatment of COVID-19.

In this study, we adopted an analytical strategy involving an integrated bioinformatic approach to explore the mechanism of ion channel-related genes in COVID-19. We used biological datasets and several online databases to identify relevant features of ion channel genes in COVID-19 and identified 29 ion channel-related differentially expressed genes (DEGs) in COVID-19. Based on this, several bioinformatic analyses were performed to understand the involvement of these genes in the biological processes of the organism. In addition, we attempted to elucidate the pathogenic molecular mechanisms of these genes in COVID-19 and predict potential therapeutic agents. These differential genes have good application prospects for the diagnosis and treatment of COVID-19 and provide new perspectives for the discovery of potential biomarkers and drug targets of COVID-19.

Methods

Data Sources

To analyse the biological mechanisms and potential therapeutic targets of ion channel-related genes present in COVID-19, we obtained gene expression datasets (GSE152418 and GSE171110) from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). GSE152418 is based on the Illumina NovaSeq 6000 (Homo sapiens) (GPL24676) platform for RNA-sequencing (RNA-Seq) data on COVID-19. This dataset contains information on 17 patients with COVID-19 and 17 healthy subjects, with samples collected from peripheral blood mononuclear cells (PBMCs), and was derived from the research contributions of Arunachalam et al. (2020). GSE171110 is based on the Illumina HiSeq 2500 (Homo sapiens) (GPL16791) platform for RNA-Seq data on COVID-19. This dataset contains information on 44 patients with COVID-19 and 10 healthy subjects, with samples collected from whole blood tissue, and was derived from the research contributions of Lévy et al. (2021). Table 1 shows the basic information of both datasets. Ion channel genes were downloaded from the HUGO Gene Nomenclature Committee (HGNC) database (http://www.genenames.org/), and a total of 330 ion channel genes were obtained.

Table 1 Two RNA-seq transcriptome datasets and differential gene number information for COVID-19
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Screening of Differential Genes

To identify ion channel-related DEGs, we downloaded the RStudio software (version 2022.02.0 + 443) (https://www.rstudio.com/), which is run on the R software (version 4.1.3) (https://www.r-project.org/). The RNA-Seq data of patients with COVID-19 (GSE152418 and GSE171110) were processed using RStudio based on the edgeR R package (version 3.36.0). The cut-off criteria of false discovery rate (FDR) < 0.05 and absolute value of log2-fold change (|logFC|) ≥ 1.0 were used to screen for significant DEGs in the abovementioned datasets. A Venn diagram was created using the VennDiagram R package (version 1.7.3) to show interacting genes by considering the intersection of DEGs obtained for each of the GSE152418 and GSE171110 datasets with the 330 ion channel-related genes. These interacting DEGs were used for subsequent analyses. Volcano plots were drawn using the EnhancedVolcano R package (version 1.12.0) to show the differential genes in the GSE152418 and GSE171110 datasets.

Functional and Pathway Enrichment Analyses

A comprehensive gene set enrichment web tool, Enrichr (https://maayanlab.cloud/Enrichr/), was used for functional annotation and pathway enrichment analysis of DEGs (Chen et al. 2013; Kuleshov et al. 2016; ** of human protein-protein interactions by mass spectrometry. Mol Syst Biol 3:89. https://doi.org/10.1038/msb4100134 " href="/article/10.1007/s10528-022-10280-x#ref-CR42" id="ref-link-section-d5196068e794">2007; Ben-Hur and Noble 2005). We input the 29 identified DEGs into the STRING database (https://string-db.org/) to generate PPI networks (Szklarczyk et al. 2017). Furthermore, we downloaded the Cytoscape software (version 3.9.1) (https://cytoscape.org/) and imported the constructed PPI networks into this software for further processing and analysis (Shannon et al. 2003; Smoot et al. 2011). The Cytoscape software is an open platform that includes a number of plug-ins with scalable visualisation options and network analysis (Shannon et al. 2003). We used the cytoHubba plug-in in the Cytoscape software (http://apps.cytoscape.org/apps/cytohubba) to screen for hub genes. CytoHubba is a plug-in for ranking and extracting central, potential or targeted elements of a biological network based on various network features and contains 11 methods to score networks based on different perspectives, with the best one being Maximal Clique Centrality (MCC) at present (Chin et al. 2014). We used the MCC method to identify the top 10 hub genes in the PPI network.

Transcriptional and Post-transcriptional Regulatory Networks Analyses

Transcription factors (TFs) are proteins that attach to specific genes and control the rate of transcription of genetic information (Caramori et al. 2013). MicroRNAs (miRNAs) are a class of short, endogenously initiated and non-coding RNAs that repress or degrade messenger RNAs (mRNAs) through translation, thereby controlling gene expression at the post-transcriptional level (Cai et al. 2009). TFs and miRNAs are essential for molecular biology research. We used the online web tool NetworkAnalyst (Zhou et al. 2020). In addition to investigating protein–drug interactions, we screened for candidates that could affect COVID-19. We considered the screened 10 hub genes as drug targets and performed drug-target enrichment analysis using the online web tool Enrichr based on DSigDB. The results showed that the drugs gabapentin, gabapentin enacarbil, pregabalin, guanidine hydrochloride and 4-aminopyridine, which act on five pivotal genes, namely, CACNA2D1, CACNA1A, CACNA1E, KCNA2 and KCNA5, respectively, may be potential drugs for the treatment of patients with COVID-19. Table 6 provides relevant information regarding these drugs.

Table 6 List of the predicted drugs identified from protein–drug interaction enrichment analysis
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Discussion

COVID-19 is an emerging and rapidly growing pandemic with increasing infection and mortality rates worldwide (Team CC-R, 2020). COVID-19 has spread worldwide and poses a significant threat to humans. The current situation has prompted researchers to discover effective treatments against COVID-19 (Kumar et al. 2021). The causative agent of COVID-19, SARS-CoV-2, is highly pathogenic to humans. However, it is currently poorly understood, and specific treatments for COVID-19 remain unexplored. Hence, it is difficult to overcome this life-threatening prevalent disease (Li et al. 2021). Therefore, it is important to use bioinformatic methods to analyse the characteristics and pathogenesis of COVID-19 and discover novel therapeutic targets for the development of effective drugs and vaccines, thus providing a basis for public health decision-making (Ma et al. 2021). Ion channels are pore-forming membrane proteins that allow the passage of ions through the channel pore. Their functions include establishing the resting membrane potential (Abdul Kadir et al. 2018), sha** action potentials and other electrical signals by controlling ion flow across cell membranes, controlling ion flow in secretory and epithelial cells and regulating cell volume. Ion channels play an important role in various biological functions (Sun et al. 2020). However, the role of ion channel genes in COVID-19 remains unclear.

In this study, we used an integrated bioinformatic approach to gain insights into the associated features of ion channel-related genes in COVID-19. A total of 29 ion channel-related DEGs were identified in two RNA-Seq datasets (GSE152418 and GSE171110) containing data derived from the blood tissues of 61 patients with COVID-19 and 27 healthy subjects and including 330 ion channel gene sets. To examine the biological significance of these DEGs in the pathogenesis of COVID-19, we performed GO and pathway analyses on the DEGs. GO is a general theoretical model in gene regulation that outlines the functions of genes and their interrelationships (Al-Mustanjid et al. 2020). It develops progressively through the acquisition of biological knowledge regarding gene function and its regulation based on linguistic relationships among various ontological categories (Rana et al. 2019). The GO database was used as an annotation source for ontology to analyse the three categories, namely, BP, CC and MF, of the target genes. According to GO term interpretation, BP is the molecular activity, CC is the cellular structure in which genes regulate their function and MF is a description of activity at the molecular level (Moni and Lio 2015). Pathway analysis is a modern scientific strategy that helps to understand and reveal how biologically or molecularly complex diseases are connected and is the best way to obtain an organism’s response triggered by internal changes (Rana et al. 2020). In this study, GO enrichment analysis revealed that the DEGs were integral components of the plasma membrane (CC) and were significantly enriched in relevant functions such as inorganic cation transmembrane transport (BP) and ion channel activity (MF), and these processes mainly involved calcium and potassium channels. Furthermore, pathway enrichment analysis revealed that the DEGs were significantly enriched in pathways related to nicotine addiction (KEGG), calcium regulation in the cardiac cell (WikiPathways) and the neuronal system (Reactome). Calcium channels are activated upon membrane depolarisation to conduct calcium ions into the cell and organelles while initiating many physiological responses, including secretion, contraction and gene transcription (Zamponi et al. 2015). Calcium channel mutations and their dysfunctions have been associated with several diseases, such as disorders of the cardiovascular system {e.g., hypertension, arrhythmias and heart failure (Liao and Soong 2010; Venetucci et al. 2012)}, periodic skeletal muscle paralysis (Jurkat-Rott and Lehmann-Horn 2006), impaired insulin release and islets β-cell apoptosis in patients with diabetes (Yang et al. 2014), chronic pain and migraine (Bourinet et al. 2014; Kowalska et al. 2021) and numerous brain disorders (Heyes et al. 2015; Ortner and Striessnig 2016). However, the mechanism of action of calcium channels in COVID-19 remains unclear. Several studies (Neuraz et al. 2020; Peng et al. 2021; Kow et al. 2022) have suggested that the use of calcium channel blockers (CCBs), which reduce mortality in patients with COVID-19, has a therapeutic effect on COVID-19. However, other studies have reported (Mancia et al. 2020) that CCBs have no significant therapeutic effect on COVID-19 but increase the risk of tracheal intubation and death in patients with COVID-19 (Mendez et al. 2021). Potassium channels are located on the cell membrane and control the efflux and influx of potassium ions out of and into the cell (Kuang et al. 2015). They play a crucial role in both excitable and non-excitable cells. They are found in almost all species except some parasites (Kuo et al. 2005). The role of potassium channels in COVID-19 remains unknown; however, several studies have highlighted that multiple anti-COVID-19 drugs and inflammatory cytokines can interfere with cardiac potassium channels, such as the use of antibiotics (azithromycin and fluoroquinolones), antimalarials (hydroxychloroquine and chloroquine) and antivirals (lopinavir/ritonavir and atazanavir). In addition, some tyrosine kinase inhibitors (vandetanib) can inhibit hERG potassium channels and/or impair channel transport, thereby causing prolongation of the QT interval and increasing the risk of ventricular arrhythmias (Carpenter et al. 2020; Cubeddu et al. 2022). The smoke of inhaled cigarettes contains nicotine. Smoke particles carry nicotine to the pulmonary organs and are rapidly absorbed into the pulmonary venous circulation and subsequently into the arterial circulation, from where they move rapidly to the brain and bind to nicotinic cholinergic receptors (ligand-gated ion channels that normally bind to acetylcholine), producing and maintaining tobacco addiction (nicotine addiction) by acting on nicotinic cholinergic receptors in the brain and triggering the release of dopamine and other neurotransmitters, which is a major cause of disability and premature death in patients (Benowitz 2010). Although the association of smoking with the morbidity and mortality of a wide range of respiratory infections is well recognised, it remains unclear in COVID-19. Studies have suggested that active smokers do not have a high prevalence of COVID-19, which may be related to the ability of smoking to modulate angiotensin-converting enzyme-2 (ACE2) expression; however, the exact effects remain unclear (Usman et al. 2021). A recent study reported that smoking and nicotine may upregulate ACE2 (Brake et al. 2020). If smoking can upregulate ACE2, it may be a protective factor for COVID-19 (Verdecchia et al. 2020). However, studies published before the COVID-19 pandemic have reported that smoking and nicotine contribute to the downregulation of ACE2 (Oakes et al. 2018), which may promote increased expression of ACE2 receptors and viral receptors in smokers, thus increasing the opportunity for SARS-CoV-2 to invade the body (Berlin et al. 2020). However, the role of nicotine in COVID-19 requires further investigation. The regulatory role of calcium ions as intracellular second messengers (Bers 2008) in the heart is self-evident. It is well known that myocardial contraction is controlled by intracellular calcium ion concentration changes. The concentration of calcium ions in cardiomyocytes should be high enough to activate contractile proteins to pump blood out of the heart. During diastole, the concentration of calcium ions in cardiomyocytes should decrease to a sufficiently low level, which in turn relaxes the heart muscles so that the heart chamber becomes congested (Eisner 2018). This process relies on the regulation of calcium ion concentration, in which calcium channels play an important role. Studies have suggested a potential susceptibility of cardiomyocytes to COVID-19 (Yang et al. 2021). Cardiomyocytes contain abundant calcium ion channels; therefore, calcium regulation in cardiomyocytes may be one of the mechanisms of myocardial injury in patients with COVID-19. Ion channel-related genes, initially considered to be associated with inherited excitability disorders in the muscle and heart, play an important role in the molecular diagnosis of central nervous system diseases (Noebels 2017). Ion channels underlie the genesis of nerve impulses and are therefore an important component of the nervous system. Related studies have reported that SARS-CoV-2 can invade the nervous system (Liu et al. 2021; Mukerji and Solomon 2021) and heart (Van Cleemput et al. 2021) in humans. In this study, enrichment analysis suggested that ion channel-related genes play an important role. Overall, the results of GO and pathway analyses in this study partly explained the molecular basis and mechanism of action of the identified DEGs in the pathogenesis of COVID-19.

PPI networks are used to decode the key signalling molecules in molecular networks (Rahman et al. 2019). In this study, PPI network analysis revealed the most important hub proteins. We built a PPI network based on the 29 DEGs and screened 10 hub genes from them, which may be key drug targets or biomarkers for COVID-19. The KCNA2 gene encodes potassium voltage-gated channel subfamily A member 2, which is a member of the oscillator-like delayed rectifier potassium channel family (Corbett et al. 2016). It is mainly expressed in axons and presynaptic terminals in the central nervous system (Gu et al. 2003; Lorincz and Nusser 2008). It is now known that KCNA2 mutations can cause various neurological disorders, such as epileptic encephalopathy, mental retardation and motor disorders caused by cerebellar dysfunction (Doring et al. 2021). The KCNJ4 gene encodes potassium voltage-gated channel subfamily J member 4, which is an inward rectifier potassium channel family member. Studies have shown that KCNJ4 is associated with the progression and poor prognosis of lung adenocarcinoma (Wu and Yu 2019), dilated cardiomyopathy (Szuts et al. 2013) and prostate cancer (Kim et al. 2016). The CACNA1A gene encodes a subunit of the voltage-dependent P/Q-type calcium channel α-1A (Zhang et al. 2020b), and the CACNA1E gene encodes a subunit of the voltage-dependent R-type calcium channel α-1E (Helbig et al. 2018). These genes are widely expressed throughout the central nervous system and are strongly associated with epilepsy and intellectual developmental disorders (Hommersom et al. 2021; Royer-Bertrand et al. 2021). In addition, CACNA1E is of potential therapeutic value in non-small cell lung cancer (Gao et al. 2022). The NALCN gene encodes a non-selective cation channel that conducts a permanent sodium leak current and regulates the resting membrane potential and neuronal excitability associated with respiration, locomotion and circadian rhythms (Bramswig et al. 2018; Lutas et al. 2016; Shi et al. 2016). NALCN is essential for mammalian survival; however, the gating, ion selectivity and pharmacological properties of NALCN remain unclear (Chua et al. 2020; Kschonsak et al. 2020). The KCNA5 gene encodes potassium voltage-gated channel subfamily A member 5, which is involved in the regulation of several functions including cardiac action potential, vascular smooth muscle cell activity, insulin release and tumour cell proliferation (Bossini-Castillo et al. 2012; Ahmed et al. 2016). The CACNA2D1 gene encodes a calcium voltage-gated channel α2δ-1 subunit, which enhances channel transport, increases the expression of functional calcium channels at the plasma membrane and affects the biophysical properties of the channel (Dolphin 2012). It has been widely implicated in the regulation of neuronal excitability, action potential firing patterns and neurotransmission in nociceptive pathways (Gribkoff 2006). The TRPC1 gene encodes the transient C-potential subfamily channel 1 (Zeng et al. 2021), which is involved in the regulation of intracellular calcium ion concentration and plays an important role in cell proliferation, differentiation, apoptosis and migration and is expressed in almost all normal tissues and many tumours (Berridge et al. 2000; Zeng et al. 2020). Neurological symptoms have been suggested as potential complications of COVID-19, and cerebellar ataxia is a rare post-infectious or post-parainfection immune-mediated phenomenon associated with COVID-19 (Chan et al. 2021). The DEGs identified in this study may act as a ‘bridge’ in these diseases. Finally, we used DSigDB to identify drugs that may target the five screened pivotal genes, namely, CACNA2D1, CACNA1A, CACNA1E, KCNA2 and KCNA5. These drugs included gabapentin, gabapentin enacarbil, pregabalin, guanidine hydrochloride and 4-aminopyridine. Among these drugs, gabapentin can treat cough induced by acute and chronic COVID-19 infection, thereby reducing clinical symptoms (Song et al. 2021). Pregabalin may play a role in reducing the mortality of COVID-19 (Oddy et al. 2021). Guanidine alkaloids may have strong antiviral activity, thus providing a basis for the study of anti-COVID-19 (El-Demerdash et al. 2021). Further biological and clinical studies of these candidates are recommended to evaluate their potential therapeutic significance in patients with COVID-19.

In this study, we used bioinformatic analyses to investigate the features of ion channel-related genes associated with COVID-19 to identify key candidate genes and their regulatory molecules, examine the gene–disease association and discover potential therapeutic agents. To improve the reliability of the results, we used two datasets with data derived from blood tissues for analysis to avoid the influence of sample size and different tissue samples on the results. However, this study has some limitations owing to the lack of clinical validation of the identified molecules. Therefore, further validation is required to interpret the results.

Conclusions

In this study, we examined the molecular features of ion channel genes associated with COVID-19. On analysing the RNA-Seq transcriptome datasets (GSE152418 and GSE171110) and 330 ion channel-related genes downloaded from the HGNC database, we identified 29 DEGs. GO analysis revealed that these DEGs were integral components of the plasma membrane (CC) and were enriched in inorganic cation transmembrane transport (BP) and ion channel activity (MF). Pathway analysis revealed that the DEGs were enriched in pathways related to nicotine addiction (KEGG), calcium regulation in the cardiac cell (WikiPathways) and the neuronal system (Reactome). PPI networks were constructed using 29 DEGs, and 10 important hub genes (KCNA2, KCNJ4, CACNA1A, CACNA1E, NALCN, KCNA5, CACNA2D1, TRPC1, TRPM3 and KCNN3) were identified. Significant TFs (FOXC1, GATA2, HINFP, USF2, JUN and NFKB1) and miRNAs (hsa-mir-146a-5p, hsa-mir-27a-3p, hsa-mir-335-5p, hsa-let-7b-5p and hsa-mir-129–2-3p) were identified through the TF–DEG and DEG–miRNA networks. The DEG–disease association network revealed that intellectual disability and cerebellar ataxia were highly associated with these DEGs. Drug–target enrichment analysis based on DSigDB identified relevant drugs (gabapentin, gabapentin enacarbil, pregabalin, guanidine hydrochloride and 4-aminopyridine) targeting five hub genes (CACNA2D1, CACNA1A, CACNA1E, KCNA2 and KCNA5, respectively), which may have potential value for the treatment of COVID-19. Because the present study was based on bioinformatic analyses, further clinical studies should be performed to validate the identified molecular features. We hope that the results of this study will be helpful for the rapid control of COVID-19.