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Cross-immunity between respiratory coronaviruses may limit COVID-19 fatalities.

ABSTRACT: Of the seven coronaviruses associated with disease in humans, SARS-CoV, MERS-CoV and SARS-CoV-2 cause considerable mortality but also share significant sequence homology, and potentially antigenic epitopes capable of inducing an immune response. The degree of similarity is such that perhaps prior exposure to one virus could confer partial immunity to another. Indeed, data suggests a considerable amount of cross-reactivity and recognition by the hosts immune response between different coronavirus infections. While the ongoing COVID-19 outbreak rapidly overwhelmed medical facilities of particularly Europe and North America, accounting for 78% of global deaths, only 8% of deaths have occurred in Asia where the outbreak originated. Interestingly, Asia and the Middle East have previously experienced multiple rounds of coronavirus infections, perhaps suggesting buildup of acquired immunity to the causative SARS-CoV-2 that underlies COVID-19. This article hypothesizes that a causative factor underlying such low morbidity in these regions is perhaps (at least in part) due to acquired immunity from multiple rounds of coronavirus infections and discusses the mechanisms and recent evidence to support such assertions. Further investigations of such phenomenon would allow us to examine strategies to confer protective immunity, perhaps aiding vaccine development.

SUBMITTER: Yaqinuddin A

PROVIDER: S-EPMC7326438 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Cross-immunity between respiratory coronaviruses may limit COVID-19 fatalities.

Yaqinuddin Ahmed A

Medical hypotheses 20200630

Of the seven coronaviruses associated with disease in humans, SARS-CoV, MERS-CoV and SARS-CoV-2 cause considerable mortality but also share significant sequence homology, and potentially antigenic epitopes capable of inducing an immune response. The degree of similarity is such that perhaps prior exposure to one virus could confer partial immunity to another. Indeed, data suggests a considerable amount of cross-reactivity and recognition by the hosts immune response between different coronavirus ...[more]

PMID: 32758887

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Project description:Coronavirus disease 2019 (COVID-19) has caused thousands of deaths worldwide and has become an urgent public health concern. The extraordinary interhuman transmission of this disease has urged scientists to examine the various facets of its pathogenic agent, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, based on publicly available genomic data, we analyzed the codon usage co-adaptation profiles of SARS-CoV-2 and other respiratory coronaviruses (CoVs) with their human host, identified CoV-responsive human genes and their functional roles on the basis of both the relative synonymous codon usage (RSCU)-based correlation of viral genes with human genes and differential gene expression analysis, and predicted potential drugs for COVID-19 treatment based on these genes. The relatively high codon adaptation index (CAI) values (>0.70) signposted the gene expressivity efficiency of CoVs in human. The ENc-GC3 plot indicated that SARS-CoV-2 genome was under strict selection pressure while SARS-CoV and MERS-CoV were under selection and mutational pressures. The RSCU-based correlation analysis indicated that the viral genomes shared similar codons with a panoply of human genes. The merging of RSCU-based correlation data and SARS-CoV-2-responsive differentially expressed genes allowed the identification of human genes potentially affected by SARS-CoV-2 infection. Functional enrichment analysis indicated that these genes were enriched in biological processes and pathways related to host response to viral infection and immune response. Using the drug-gene interaction database, we screened a list of drugs that could target these genes as potential COVID-19 therapeutics. Our findings not only will contribute in vaccine development but also provide a useful set of drugs that could guide practitioners in strategical monitoring of COVID-19. We recommend practitioners to scrupulously screen this list of predicted drugs in order to authenticate those qualified for treating COVID-19 symptoms.

Dataset Information

Cross-immunity between respiratory coronaviruses may limit COVID-19 fatalities.

Publications

Cross-immunity between respiratory coronaviruses may limit COVID-19 fatalities.

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