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Association of clade-G SARS-CoV-2 viruses and age with increased mortality rates across 57 countries and India

Several reports have highlighted the contributions of host factors such as age, gender and co-morbidities such as diabetes, hypertension and coronary heart disease in determining COVID-19 disease severity. However, inspite of initial efforts at understanding the contributions of SARS-CoV-2 variants,...

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Autores principales: Pandit, Bhaswati, Bhattacharjee, Samsiddhi, Bhattacharjee, Bornali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7839510/
https://www.ncbi.nlm.nih.gov/pubmed/33508515
http://dx.doi.org/10.1016/j.meegid.2021.104734
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author Pandit, Bhaswati
Bhattacharjee, Samsiddhi
Bhattacharjee, Bornali
author_facet Pandit, Bhaswati
Bhattacharjee, Samsiddhi
Bhattacharjee, Bornali
author_sort Pandit, Bhaswati
collection PubMed
description Several reports have highlighted the contributions of host factors such as age, gender and co-morbidities such as diabetes, hypertension and coronary heart disease in determining COVID-19 disease severity. However, inspite of initial efforts at understanding the contributions of SARS-CoV-2 variants, most were unable to delineate causality. Hence, in this study we re-visited the contributions of different clades of viruses (G, GR and GH) along with other attributes in explaining the disparity in mortality rates among countries. A total of 26,642 high quality SARS-CoV-2 sequences were included and the A23,403G (S:D614G) variant was found to be in linkage disequilibrium with C14,408 U (RdRp: P323L). Linear regression analyses revealed increase in age [Odds ratio: 1.055 (p-value 0.000358)] and higher frequency of clade-G viruses [Odds ratio: 1.029(p-value 0.000135)] could explain 37.43% of the differences in mortality rates across the 58 countries (Multiple R-squared: 0.3743). Next, Machine-Learning algorithms LogitBoost and AdaboostM1 were applied to determine whether countries belonging to high/low mortality groups could be classified using the same attributes and accurate classification was achieved in 70.69% and 62.07% of the countries, respectively. Further, evolutionary analyses of the Indian viral population (n = 662) were carried out. Allele frequency spectrum, nucleotide diversity (π) values and negative Tajima's D values across ORFs were indicative of population expansion. Network analysis revealed the presence of two major clusters of viral haplotypes, namely, clade-G and a variant of clade L [L(v)] having the RdRp:A97V amino acid change. Clade-G genomes were found to be evolving more rapidly and were also found in higher proportions in three states with highest mortality rates namely, Gujarat, Madhya Pradesh and West Bengal. Thus, the findings of this study and results from in vitro studies highlighting the role of these variants in increasing transmissibility and altering response to antivirals reflect the role of viral factors in disease prognosis.
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spelling pubmed-78395102021-01-28 Association of clade-G SARS-CoV-2 viruses and age with increased mortality rates across 57 countries and India Pandit, Bhaswati Bhattacharjee, Samsiddhi Bhattacharjee, Bornali Infect Genet Evol Research Paper Several reports have highlighted the contributions of host factors such as age, gender and co-morbidities such as diabetes, hypertension and coronary heart disease in determining COVID-19 disease severity. However, inspite of initial efforts at understanding the contributions of SARS-CoV-2 variants, most were unable to delineate causality. Hence, in this study we re-visited the contributions of different clades of viruses (G, GR and GH) along with other attributes in explaining the disparity in mortality rates among countries. A total of 26,642 high quality SARS-CoV-2 sequences were included and the A23,403G (S:D614G) variant was found to be in linkage disequilibrium with C14,408 U (RdRp: P323L). Linear regression analyses revealed increase in age [Odds ratio: 1.055 (p-value 0.000358)] and higher frequency of clade-G viruses [Odds ratio: 1.029(p-value 0.000135)] could explain 37.43% of the differences in mortality rates across the 58 countries (Multiple R-squared: 0.3743). Next, Machine-Learning algorithms LogitBoost and AdaboostM1 were applied to determine whether countries belonging to high/low mortality groups could be classified using the same attributes and accurate classification was achieved in 70.69% and 62.07% of the countries, respectively. Further, evolutionary analyses of the Indian viral population (n = 662) were carried out. Allele frequency spectrum, nucleotide diversity (π) values and negative Tajima's D values across ORFs were indicative of population expansion. Network analysis revealed the presence of two major clusters of viral haplotypes, namely, clade-G and a variant of clade L [L(v)] having the RdRp:A97V amino acid change. Clade-G genomes were found to be evolving more rapidly and were also found in higher proportions in three states with highest mortality rates namely, Gujarat, Madhya Pradesh and West Bengal. Thus, the findings of this study and results from in vitro studies highlighting the role of these variants in increasing transmissibility and altering response to antivirals reflect the role of viral factors in disease prognosis. Elsevier B.V. 2021-06 2021-01-27 /pmc/articles/PMC7839510/ /pubmed/33508515 http://dx.doi.org/10.1016/j.meegid.2021.104734 Text en © 2021 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Research Paper
Pandit, Bhaswati
Bhattacharjee, Samsiddhi
Bhattacharjee, Bornali
Association of clade-G SARS-CoV-2 viruses and age with increased mortality rates across 57 countries and India
title Association of clade-G SARS-CoV-2 viruses and age with increased mortality rates across 57 countries and India
title_full Association of clade-G SARS-CoV-2 viruses and age with increased mortality rates across 57 countries and India
title_fullStr Association of clade-G SARS-CoV-2 viruses and age with increased mortality rates across 57 countries and India
title_full_unstemmed Association of clade-G SARS-CoV-2 viruses and age with increased mortality rates across 57 countries and India
title_short Association of clade-G SARS-CoV-2 viruses and age with increased mortality rates across 57 countries and India
title_sort association of clade-g sars-cov-2 viruses and age with increased mortality rates across 57 countries and india
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7839510/
https://www.ncbi.nlm.nih.gov/pubmed/33508515
http://dx.doi.org/10.1016/j.meegid.2021.104734
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