Identification of VEGFA-centric temporal hypoxia-responsive dynamic cardiopulmonary network biomarkers.

AIMS: Hypoxia, a pathophysiological condition, is profound in several cardiopulmonary diseases (CPD). Every individual's lethality to a hypoxia state differs in terms of hypoxia exposure time, dosage units and dependent on the individual's genetic makeup. Most of the proposed markers for CPD were generally aim to distinguish disease samples from normal samples. Although, as per the 2018 GOLD guidelines, clinically useful biomarkers for several cardio pulmonary disease patients in stable condition have yet to be identified. We attempt to address these key issues through the identification of Dynamic Network Biomarkers (DNB) to detect hypoxia induced early warning signals of CPD before the catastrophic deterioration. MATERIALS AND METHODS: The human microvascular endothelial tissues microarray datasets (GSE11341) of lung and cardiac expose to hypoxia (1% O2) for 3, 24 and 48 h were retrieved from the public repository. The time dependent differentially expressed genes were subjected to tissue specificity and promoter analysis to filtrate the noise levels in the networks and to dissect the tissue specific hypoxia induced genes. These filtered out genes were used to construct the dynamic segmentation networks. The hypoxia induced dynamic differentially expressed genes were validated in the lung and heart tissues of male rats. These rats were exposed to hypobaric hypoxia (simulated altitude of 25,000 or PO2 - 282 mm of Hg) progressively for 3, 24 and 48 h. KEY FINDINGS: To identify the temporal key genes regulated in hypoxia, we ranked the dominant genes based on their consolidated topological features from tissue specific networks, time dependent networks and dynamic networks. Overall topological ranking described VEGFA as a single node dynamic hub and strongly communicated with tissue specific genes to carry forward their tissue specific information. We named this type of VEGFAcentric dynamic networks as "V-DNBs". As a proof of principle, our methodology helped us to identify the V-DNBs specific for lung and cardiac tissues namely V-DNBL and V-DNBC respectively. SIGNIFICANCE: Our experimental studies identified VEGFA, SLC2A3, ADM and ENO2 as the minimum and sufficient candidates of V-DNBL. The dynamic expression patterns could be readily exploited to capture the pre disease state of hypoxia induced pulmonary vascular remodelling. Whereas in V-DNBC the minimum and sufficient candidates are VEGFA, SCL2A3, ADM, NDRG1, ENO2 and BHLHE40. The time dependent single node expansion indicates V-DNBC could also be the pre disease state pathological hallmark for hypoxia-associated cardiovascular remodelling. The network cross-talk and expression pattern between V-DNBL and V-DNBC are completely distinct. On the other hand, the great clinical advantage of V-DNBs for pre disease predictions, a set of samples during the healthy condition should suffice. Future clinical studies might further shed light on the predictive power of V-DNBs as prognostic and diagnostic biomarkers for CPD.

The miRNA-gene regulatory circuits in nSARS-CoV-2 and their potential correlations with pulmonary and thrombotic disorders (preprint)

In view of the worldwide spread of the novel Severe Acute Respiratory Syndrome Coronavirus 2 (nSARS-CoV-2) infection pandemic situation, research to repurpose drugs, identify novel drug targets, vaccine candidates, diagnostic markers etc have created a new race to curb the disease. To uncover nSARS-CoV-2-related important biological features and understanding the molecular basis of this disease, network biology and miRNA-gene regulatory motif-based approach is used. 11 antiviral human-microRNAs (miRNAs) which can potentially target SARS-CoV-2 genes were collated; their direct miRNA interactors were identified and a comprehensive nSARS-CoV-2 responsive miRNA:Transcription Factor (TF):gene coregulatory network was built. 1385 miRNA:TF:gene tripartite, Feed-Forward Loops (FFLs) were identified from the network. The network topology was mapped into the biological space and the overrepresented pathways were identified. Four regulatory circuits: hsa-mir-9-5p-EP300-PLCB4, hsa-mir-324-3p-MYC-HLA-F, hsa-mir-1827-E2F1-CTSV and hsa-mir-1277-5p-SP1-CANX are identified. These miRNA-gene regulatory circuits are found to regulate signalling pathways like virus endocytosis, viral replication, inflammatory response, pulmonary vascularization, cell cycle control, virus spike protein stabilization, antigen presentation, etc. Some novel computational evidences for understanding nSARS-CoV-2 molecular mechanisms controlled by these regulatory circuits is put forth. The novel associations of miRNAs and genes identified with this infection are open for experimental validation. Further, these regulatory circuits also suggest potential correlations/similarity in the molecular mechanisms during nSARS-CoV-2 infection and pulmonary diseases and thromboembolic disorders. A detailed molecular snapshot of TGF-β signalling pathway as the common mechanism that could play an important role in controlling common pathophysiology i.e. systemic inflammation, increased pulmonary pressure, ground glass opacities, D-dimer overexpression is also put forth.

Identification of pulmonary comorbid diseases network based repurposing effective drugs for COVID-19 (preprint)

The number of hospitalization of COVID-19 patients with one or more comorbid diseases is highly alarming. Despite the lack of large clinical data and incomplete understanding of virus pathology, identification of the COVID-19 associated diseases with clinical precision are highly limited. In this regard, our text mining of 6238 PubMed abstracts (as on 23 April 2020) successfully identified broad spectrum of COVID-19 comorbid diseases/disorders (54), and their prevalence on the basis of the number of occurrence of disease terms in the abstracts. The disease ontology based semantic similarity network analysis revealed the six highly comorbid diseases of COVID-19 namely Viral Pneumonia, Pulmonary Fibrosis, Pulmonary Edema, Acute Respiratory Distress Syndrome (ARDS), Chronic Obstructive Pulmonary Disease (COPD) and Asthma. The disease gene bipartite network revealed 15 genes that were strongly associated with several viral pathways including the corona viruses may involve in the manifestation (mild to critical) of COVID-19. Our tripartite network- based repurposing of the approved drugs in the world market revealed six promising drugs namely resveratrol, dexamethasone, acetyl cysteine, Tretinoin, simvastatin and aspirin to treat comorbid symptoms of COVID-19 patients. Our animal studies in rats and literatures strongly supported that resveratrol is the most promising drug to possibly reduce several comorbid symptoms associated with COVID-19 including the severe hypoxemia induced vascular leakage. Overall, the anti-viral properties of resveratrol against corona virus could be readily exploited to effectively control the viral load at early stage of COVID-19 infection through nasal administration.