Molecular modeling of C1-inhibitor as SARS-CoV-2 target identified from the immune signatures of multiple tissues: An integrated bioinformatics study.

The expeditious transmission of the severe acute respiratory coronavirus 2 (SARS-CoV-2), a strain of COVID-19, crumbled the global economic strength and caused a veritable collapse in health infrastructure. The molecular modeling of the novel coronavirus research sounds promising and equips more evidence about the pragmatic therapeutic options. This article proposes a machine-learning framework for identifying potential COVID-19 transcriptomic signatures. The transcriptomics data contains immune-related genes collected from multiple tissues (blood, nasal, and buccal) with accession number: GSE183071. Extensive bioinformatics work was carried out to identify the potential candidate markers, including differential expression analysis, protein interactions, gene ontology, and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment studies. The overlapping investigation found SERPING1, the gene that encodes a glycosylated plasma protein C1-INH, in all three datasets. Furthermore, the immuno-informatics study was conducted on the C1-INH protein. 5DU3, the protein identifier of C1-INH, was fetched to identify the antigenicity, major histocompatibility (MHC) Class I and II binding epitopes, allergenicity, toxicity, and immunogenicity. The screening of peptides satisfying the vaccine-design criteria based on the metrics mentioned above is performed. The drug-gene interaction study reported that Rhucin is strongly associated with SERPING1. HSIC-Lasso (Hilbert-Schmidt independence criterion-least absolute shrinkage and selection operator), a model-free biomarker selection technique, was employed to identify the genes having a nonlinear relationship with the target class. The gene subset is trained with supervised machine learning models by a leave-one-out cross-validation method. Explainable artificial intelligence techniques perform the model interpretation analysis.

COVID-19 and hereditary angioedema: Incidence, outcomes, and mechanistic implications.

Background: Patients with hereditary angioedema (HAE) have been postulated to be at increased risk for coronavirus disease 2019 (COVID-19) infection due to inherent dysregulation of the plasma kallikrein-kinin system. Only limited data have been available to explore this hypothesis. Objective: To assess the interrelationship(s) between COVID-19 and HAE. Methods: Self-reported COVID-19 infection, complications, morbidity, and mortality were surveyed by using an online questionnaire. The participants included subjects with HAE with C1 inhibitor (C1INH) deficiency (HAE-C1INH) and subjects with HAE with normal C1-inhibitor (HAE-nl-C1INH), and household controls (normal controls). The impact of HAE medications was examined. Results: A total of 1162 participants who completed the survey were analyzed, including: 695 subjects with HAE-C1INH, 175 subjects with HAE-nl-C1INH, and 292 normal controls. The incidence of reported COVID-19 was not significantly different between the normal controls (9%) and the subjects with HAE-C1INH (11%) but was greater in the subjects with HAE-nl-C1INH (19%; p = 0.006). Obesity was positively correlated with COVID-19 across the overall population (p = 0.012), with a similar but nonsignificant trend in the subjects with HAE-C1INH. Comorbid autoimmune disease was a risk factor for COVID-19 in the subjects with HAE-C1INH (p = 0.047). COVID-19 severity and complications were similar in all the groups. Reported COVID-19 was reduced in the subjects with HAE-C1INH who received prophylactic subcutaneous C1INH (5.6%; p = 0.0371) or on-demand icatibant (7.8%; p = 0.0016). The subjects with HAE-C1INH and not on any HAE medications had an increased risk of COVID-19 compared with the normal controls (24.5%; p = 0.006). Conclusion: The subjects with HAE-C1INH who were not taking HAE medications had a significantly higher rate of reported COVID-19 infection. Subcutaneous C1INH and icatibant use were associated with a significantly reduced rate of reported COVID-19. The results implicated potential roles for the complement cascade and tissue kallikrein-kinin pathways in the pathogenesis of COVID-19 in patients with HAE-C1INH.

Gene variants of coagulation related proteins that interact with SARS-CoV-2.

Thrombosis is a recognized complication of Coronavirus disease of 2019 (COVID-19) and is often associated with poor prognosis. There is a well-recognized link between coagulation and inflammation, however, the extent of thrombotic events associated with COVID-19 warrants further investigation. Poly(A) Binding Protein Cytoplasmic 4 (PABPC4), Serine/Cysteine Proteinase Inhibitor Clade G Member 1 (SERPING1) and Vitamin K epOxide Reductase Complex subunit 1 (VKORC1), which are all proteins linked to coagulation, have been shown to interact with SARS proteins. We computationally examined the interaction of these with SARS-CoV-2 proteins and, in the case of VKORC1, we describe its binding to ORF7a in detail. We examined the occurrence of variants of each of these proteins across populations and interrogated their potential contribution to COVID-19 severity. Potential mechanisms, by which some of these variants may contribute to disease, are proposed. Some of these variants are prevalent in minority groups that are disproportionally affected by severe COVID-19. Therefore, we are proposing that further investigation around these variants may lead to better understanding of disease pathogenesis in minority groups and more informed therapeutic approaches.