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, 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