The goal of the work is to decipher the mechanisms connecting Covid-19 to comorbidity that may lead to mortality. An attempt was committed with the following objectives: (i) Retrieval and classification of TC-genes, (ii) analysing BPs, MPs and CCs of the targets, (iii) determining the selective diseases linking Covid-19, (iv) identifying the common TC-genes among them, (v) elucidating the connection between the disorders through the critical overlapping TC-genes.
3.1 Collection of the TC-genes. Following the search as described in materials and methods, 757 clinical entries were retrieved (Table S1). Text mining of PubMed led to the retrieval of 480 unique PMIDs (Table S2). PMID is a collection of a unique PubMed reference number issued by the NIH National Library of Medicine. After removing the redundancy, 156 TC-genes associated with Covid-19 are considered for the work.
3.2 Classification of the TC-genes. The 156 targets are classified based on the pathways they are involved in (Table S3). Based on the best relevance, neuronal system heads the list adopted by TC-genes (Fig. 1). Transmission across the chemical synapse, neurotransmitter receptors and postsynaptic signal communication are the characteristics of the neuronal system and are among principal pathways of the targets (Fig. 1). Assembly and cell surface presentation of NMDA (N-methyl-D-aspartate receptor), a glutamate receptor and ion channel present in nerve cells are furthermore among the top relevant ones associated with Covid-19 (Table S4). This suggests that the top relevant p are chiefly connected to nervous system-related functions.
Besides nervous system and SARS-CoV infections, TC-genes encoded for signalling transduction represent the prevalent ones as per relevance. For example; HSP90, MAPK1/MAPK3, P13K/AKT and cytokine function are among the relevant signalling pathways. Cytokine signalling like interleukin (IL)-4, IL-13 and IL-10 are among the top 20 pathways extracted as per relevance. However, certain signalling pathways are part of the immune system as well. Therefore, this sub-section suggests that most relevant pathways assign frequent targets and there are a few selective pathways involved in the process.
Based on the number of TC-genes in the pathways, the majority (> 50%) of them participate in signal transduction (Fig. 2). It is followed by the immune and neuronal system. Within the immune system, more than half of the signalling is related to cytokines, like IL-4, IL-13, IL-6R, 1L6, IL1R and IL-10 (Table S4). A small segment of TC-genes is in infection and metabolism of proteins, which are obvious processes in virus susceptible cells. Nearly half of the signal transduction TC-genes are overlapping with the immune system. Contrarily, only one-fifth (20%) of them are common to the neuronal system. Immune and neuronal systems are connected through signal transduction. These top three pathways share mere one-tenth (~7%) of the TC-genes (Table S5, Fig. 2). Following the analysis, the sub-section suggests that the majority of the TC-genes share certain pathways, irrespective of many possibilities.
3.3 GO analysis. Analysing the top 20 BPs of TC-genes, most of them are related to signalling. Most signalling cascade involves neurons and immune system (Table 1). Therefore, comply with the results gained from the independent study involving the network-based pathway analysis in the previous sub-section. The CCs of the TC-genes include mainly the component of the plasma membrane and are related to neurons (Table 2). Broadly, signal transduction is the most preferred MFs associated with the TC-genes (Table 3). The sub-section suggests that only certain BPs, CCs and MFs are involved in Covid-19 progression, despite multiple likelihoods.
3.4 Association of Covid-19 with diseases. The disease-disease association is deciphered by analysing the network of common genes. Among top 20 diseases; HTN, neurovascular disease, arterial and autoimmune disorders show the maximum number of common Covid-19 associated targets (Table S6 and Fig. 3). They are followed by rheumatic (RC), cerebrovascular and central nervous system disorder (Fig. 3). Considering the relevance of the association between the diseases and Covid-19, HTN tops the chart (Fig. 3). If both the p-value and number of overlapped targets are considered, then also HTN is most closely related to Covid-19 (Fig. 3). Covid-19 represents the first in the list followed by infections caused by orthocoronavirinae subfamily and nidovirales order viruses, however, are ignored as SARS-CoV-2 is a virus. Therefore, it is not surprising if they are at the top hit diseases.
The five most relevant, diverse diseases considered for the study are Covid-19, HTN, RC, CNS demyelinating autoimmune (CNS_DA) and bone inflammation (BIN). 148 TC-genes are common among the top three health conditions; HTN, RC and Covid-19. However, only 7 TC-genes are overlapping between the Covid-19 and RC but are unassociated with HTN (Table S6, Fig. 4). More than two-third (~80 %) of the TC-genes are also associated with CNS_DA and BIN (Table S6, Fig. 4). The top five relevant diseases concerning Covid-19 suggests that nearly half of them are frequent to HTN, BIN, CNS_DA and ischemic (IC). To our surprise, pairwise relationships between them indicate that more than one-tenth (20) of the TC-genes are common among HTN, BIN and CNS_DA excluding the selective cardiovascular disease. Contrarily, a similar percentage of TC-genes are also present among HTN, BIN and IC but not with the CNS_DA (Fig. 4). This suggests that the BIN and HTN have a relation with IC and CNS_DA, but may additionally include certain targets not associated with each other. The sub-section indicates that more than half of the TC-genes are common among the HTN, BIN, IC and CNS_DA. These TC-genes are listed in Table S7 and Fig. 4.
The network of these common TC-genes is represented in Fig. 5A. The common TC-genes mainly facilitate signalling involving cytokines/chemokines. Top 9 common TC-genes as per the size of the nodes (clustering coefficient in brackets; descending order) are as follows: DRD2 (dopamine receptor 2, 0.85) followed by IL6 (0.75), SLC6A4 (solute carrier family 6 members 4, 0.73), VEGFA (vascular endothelial growth factor A, 0.71), CXCL8 (C-X-C motif chemokine ligand 8, 0.69), OPRM1 (opioid receptor mu 1, 0.67), PIK3CD (phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit delta, 0.72), ACE (angiotensin I converting enzyme, 0.45), and GABR# (gamma-aminobutyric acid receptor#) (Fig. 6i and Fig. 6ii). The symbol ( # ) represents types of GABRs. The protein name and Ensembl id of all the TC-genes considered for the study are mentioned in Table S3.
Although the top 9 common TC-genes shown in Fig. 5B, 6i and 6ii are broadly involved in distinct pathways (Table S5) but are connected as first neighbours in general. For example, DRD2 has interactions with PIK3CD, OPRM1, CXCL8, SLC6A4, GABR# and ACE pathway members (Fig. 6iA). Likewise, the interaction of OPRM1, DRD2, ACE, HTR2A, IL6 and GABR# with SLC6A4 is highlighted in Fig. 6iiB. The function of IL6 is broadly affected by the expression of SLC6A4, CXCL8, VEGFA, NR3C1, and ACE (Fig. 6iiE). The interaction of most common TC-genes to GABR# is mainly through DRD2 or SLC6A4 (Fig. 6iiA and 6iiB). The sub-section extracts and constructs networks among common TC-genes from the top hit diseases (HTN, BIN, CNS_DA, and IC diseases).
3.5 Proposed model connecting Covid-19 and comorbidity. The network of selective common TC-genes interplay, extracted in the previous sub-section led to propose the mechanism of how SARS-CoV-2 infection guides the severe condition of the comorbid patients: SARS-CoV-2 enters human cells by binding to ACE2. The network of the first neighbours of ACE2 is represented in Fig. 5B. ACE2 helps modulate the activities of angiotensin II (Ang II). The later can increase inflammation and death of alveoli cells, which are critical for delivering oxygen into the body. ACE2 counters the activity of ACE by reducing the amount of Ang-II and increasing Ang(1-7) (Fig. 7). Ang-II binds to AGTR1 causing an increase of vasoconstriction. The ACE2 expression in hypertensive and cardiovascular disease patients is reported to be higher[38]. However, occupied ACE2 cannot participate in the function leading to enhance blood pressure (Fig. 7). Simultaneously, the infection leads to an increase in TNF-α level as immune cells activation, facilitating its cleavage into a soluble form (sACE2) (Fig. 7). The sACE2 is unable to counter-act the AGTR1 to reduce blood pressure.
Disruption of ACE2 drastically reduces the expression of endothelial nitric oxide synthase (eNOS), therefore, a significant reduction in nitric oxide (NO), a vasodilator. NO production is further effected by dysfunctional VEGFA, a homodimer glycoprotein’s signalling through PI3K (Phosphatidylinositol 4,5-bisphosphate 3-kinase)/Akt pathway[39]. Deletion of ACE2 function modulates oxidative stress through reactive oxygen species (ROS). ROS imbalance creates oxidative stress that leads to inflammation. Simultaneously, invasion of a pathogen causes nearby inflammation that attracts innate immune cells to act. For example, CXCL8 upregulates during inflammatory conditions and mediates recruitment of neutrophil as a role in innate response[40]. Transcription of certain cytokines/chemokines enhances the adaptive response of the immune system. VEGF dysfunction contributes to inflammation and immune response leading to leukocyte adhesion to endothelial cells; therefore, prevent platelet aggregation and leukocyte rolling, an important step in inflammation initiating immune response[41]. NO also limits the expression of IL-1 induced expression of adhesion molecules, thus affect leukocyte rolling and pro-inflammatory cytokines[42]. Cytokines in the serum are enhanced tremendously, especially IL-1, IL-6, tumour necrosis factor (TNF)-α, and interferon γ. DPP4, a cell surface glycoprotein receptor co-express with ACE2 and is reported to be essential for T-cell activation. T cells play a critical role in antiviral immunity, but their levels are dramatically reduced in Covid-19 patients[43].
Initiating immune response enhances the expression of GABA that mediates neuronal inhibition. Therefore, GABR#, ligand-gated chloride channels are activated by GABA, an inhibitory neurotransmitter[44]. Bhat et al[45] suggest its role in autoimmune inflammation. The network partners of GABR# are shown in Fig. 6ii suggesting their interaction with DRD2, OPRM1 and SLC6A4. Similar to GABA, the former’s depletion increases the inflammatory factors and cytokines/chemokines. Zhang et al[46] suggest that inflammation is the primary impact of decreased DRD2 function and its disruption is associated with increased reactive oxygen species (ROS)[47]. ROS induce oxidative stress which can activate the transcription of some TC-genes involved in inflammatory pathways[48]. CCR5 (C-C chemokine receptor type 5) is a receptor for several inflammatory CC chemokines. Complementing to our findings, IL-6 levels, an indicator of a cytokines storm and inflammation, is elevated in SARS-CoV-2 infected patients[49]. Similar to IL-6, elevated levels of C-reactive protein (CRP), D-dimer and ferritin also suggest the role of the immune system in the Covid-19 [16, 50, 51]. Most of the stated receptors also express on the nerve cells and are involved in signalling, therefore, are complementing with the GO analyses. The sub-section indicates that the TC-genes may be part of another pathway, but are associated to accomplish one or more broad functions. The cooperative actions of these selective TC-genes increase the oxidative stress causing inflammation that may damage the comorbid system leading to mortality. The findings of work are supported by a few of the experimental observations [52, 53], however, is carried out simultaneously and independently.
Interpretation of the interaction among the TC-genes is challenging due to the complexity of the interactome. The vast research data is characterizing the targets in isolation or reporting the clinical readings, that in general fails to provide an overall mechanism of action. However, we attempted linking the human targets collectively in a simplified yet effective way through the TC-genes. The approach is novel for disease-disease relationships as it considers the common pathways and reports the selective 85 TC-genes. Interpreting the network from limited 85 TC-genes is equally difficult, therefore, the top 9 of them were focused to infer the connection and the mechanism is interpreted. However, the study only considers the TC-genes, but non-coding DNA sequences, post-translational modifications, diet, age or environment could be a few of the factors that may affect the comorbid Covid-19 patient’s chances of death.