Abstract
With the growing evidence on the variable human susceptibility against COVID-19, it is evident that some genetic loci modulate the severity of the infection. Recent studies have identified several loci associated with greater severity. More recently, a study has identified a 50 kb genomic segment introgressed from Neanderthal adding a risk for COVID-19, and this genomic segment is present among 16% and 50% people of European and South Asian descent, respectively. Our studies on ACE2 identified a haplotype present among 20% and 60% of European and South Asian populations, respectively, which appears to be responsible for the low case fatality rate among South Asian populations. This result was also consistent with the real-time infection rate and case fatality rate among various states of India. We readdressed this issue using both of the contrasting datasets and compared them with the real-time infection rates and case fatality rate in India. We found that the polymorphism present in the 50 kb introgressed genomic segment (rs10490770) did not show any significant correlation with the infection and case fatality rate in India.
Highlights
With the growing evidence on the variable human susceptibility against COVID-19, it is evident that some genetic loci modulate the severity of the infection
Recent genome wide association study has identified a gene cluster at chromosome 3 as well as the ABO gene at chromosome 9 associated with the severe risk factor for COVID-19 among E uropeans[6]
The worldwide meta-analysis of the COVID-19 Host Genetics Initiative has identified 13 genetic loci associated with higher susceptibility or higher severity[8]
Summary
With the growing evidence on the variable human susceptibility against COVID-19, it is evident that some genetic loci modulate the severity of the infection. To resolve this discrepancy between the two sets of findings and the associated claims, we have extracted a SNP (rs10490770) reported to be associated with the high risk for COVID-199, from our published and unpublished genome wide datasets (Supplementary Table S1), and looked for existing association with the state-wise COVID19 data of India. The frequency data for both of the SNPs from various Indian populations were extracted using Plink 1.914, from 1000 genome project data phase 3 15, data published by the Estonian Biocentre[16,17,18,19] and our newly genotyped samples for various Indian states and Bangladesh (Supplementary Table S1).
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
