Genetic Risk Prediction of COVID-19 Susceptibility and Severity in the Indian Population

Abstract

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.

Molecular signature of postmortem lung tissue from COVID-19 patients suggests distinct trajectories driving mortality

“…Our study bridges the gap of diversity in sampling various populations across the world that are affected by the pandemic. This is particularly of interest as in our recent work we demonstrate a significant contribution of genetics towards mortality in severe COVID-19 ( Prakrithi et al, 2021 ). Therefore, we conclude by hypothesizing that the heterogeneity in the molecular signature of severe COVID-19 patients might be driven by patient genetics and can be used for candidate gene prioritization.…”

Covid-19: virology, variants, and vaccines

“…34 The use of polygenetic risk scores might be useful in determining an individual's risk for developing severe disease caused by covid-19. 35 A polygenetic risk score infers a person's risk of susceptibility to, or development of, a certain disease based on the total number of genomic variations they possess. Determining polygenetic risk scores with the inclusion of comorbidities, such as chronic obstructive pulmonary disease, 36 or other aspects such as coagulation factors, 37 could improve the usefulness of these scores in determining a person's risk of severe covid-19.…”

African Genetic Representation in the Context of SARS-CoV-2 Infection and COVID-19 Severity

“…( Grolmusz et al, 2021 ; Velavan et al, 2021 ). A study by Prakrithi et al calculated the PRS of previously identified COVID-19 associated single nucleotide polymorphisms (SNPs) in different Indian sub-populations, which allowed them to identify populations at higher risk of COVID-19-related deaths, and thereby provide support for vaccination prioritization in those specific populations ( Prakrithi et al, 2021 ). In addition, a group from Australia designed a model to predict an individual’s COVID-19 severity risk, showing that including genetic and clinical risk factors, as opposed to only using age and sex, increases the accuracy for risk discrimination by 111%.…”

“…( Dite et al, 2021 ). Predictive scores and models do have some limitations, including being population specific as the allele frequencies and linkage disequilibrium (LD) patterns used in these calculations could differ significantly across and within populations ( Sirugo et al, 2019 ; Grolmusz et al, 2021 ; Prakrithi et al, 2021 ).…”