Journal
FRONTIERS IN GENETICS
Volume 12, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2021.714185
Keywords
COVID-19; Indian population; polygenic risk score; genetics; suscepibility; genetic risk prediction
Categories
Funding
- IITDs intramural seed grant
- Department of Biotechnology (DBT), Govt. of India
- CSIR [GAP0206]
- Delhi Cluster-Delhi Research Implementation and Innovation (DRIIV) Project by the Principal Scientific Advisor Office, Prn.SA/Delhi/ Hub/2018(C)
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Host genetic variants play a role in susceptibility to COVID-19 infection and severity. A study on diverse Indian sub-populations revealed that genetic risk scores can predict differences in COVID-19 outcomes. Combining genetic risk scores with other risk factors may improve prediction models for identifying high COVID-19 risk groups and optimizing public health resource allocation.
Host genetic variants can determine their susceptibility to COVID-19 infection and severity as noted in a recent Genome-wide Association Study (GWAS). Given the prominent genetic differences in Indian sub-populations as well as differential prevalence of COVID-19, here, we compute genetic risk scores in diverse Indian sub-populations that may predict differences in the severity of COVID-19 outcomes. We utilized the top 100 most significantly associated single-nucleotide polymorphisms (SNPs) from a GWAS by Pairo-Castineira et al. determining the genetic susceptibility to severe COVID-19 infection, to compute population-wise polygenic risk scores (PRS) for populations represented in the Indian Genome Variation Consortium (IGVC) database. Using a generalized linear model accounting for confounding variables, we found that median PRS was significantly associated (p < 2 x 10(-16)) with COVID-19 mortality in each district corresponding to the population studied and had the largest effect on mortality (regression coefficient = 10.25). As a control we repeated our analysis on randomly selected 100 non-associated SNPs several times and did not find significant association. Therefore, we conclude that genetic susceptibility may play a major role in determining the differences in COVID-19 outcomes and mortality across the Indian sub-continent. We suggest that combining PRS with other observed risk-factors in a Bayesian framework may provide a better prediction model for ascertaining high COVID-19 risk groups and to design more effective public health resource allocation and vaccine distribution schemes.
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