Infection Genetics and EvolutionGeneticsPeer-reviewed journal article
Genetic association of TMPRSS2 rs2070788 polymorphism with COVID-19 Case Fatality Rate among Indian populations
Rudra Kumar PandeyiD, Anshika Srivastava, Prajjval Pratap SinghiD, Gyaneshwer ChaubeyiD
Abstract
SARS-CoV2, the causative agent for COVID-19, an ongoing pandemic, engages the ACE2 receptor to enter the host cell through S protein priming by a serine protease, TMPRSS2. Variation in the TMPRSS2 gene may account for the difference in population disease susceptibility. The haplotype-based genetic sharing and structure of TMPRSS2 among global populations have not been studied so far. Therefore, in the present work, we used this approach with a focus on South Asia to study the haplotypes and their sharing among various populations worldwide. We have used next-generation sequencing data of 393 individuals and analysed the TMPRSS2 gene. Our analysis of genetic relatedness for this gene showed a closer affinity of South Asians with the West Eurasian populations therefore, host disease susceptibility and severity particularly in the context of TMPRSS2 will be more akin to West Eurasian instead of East Eurasian. This is in contrast to our prior study on ACE2 gene which shows South Asian haplotypes have a strong affinity towards West Eurasians. Thus ACE2 and TMPRSS2 have an antagonistic genetic relatedness among South Asians. We have also tested the SNPs frequencies of this gene among various Indian state populations with respect to the case fatality rate. Interestingly, we found a significant positive association between the rs2070788 SNP (G Allele) and the case fatality rate in India. It has been shown that the GG genotype of rs2070788 allele tends to have a higher expression of TMPRSS2 in the lung compared to the AG and AA genotypes, thus it might play a vital part in determining differential disease vulnerability. We trust that this information will be useful in underscoring the role of the TMPRSS2 variant in COVID-19 susceptibility and using it as a biomarker may help to predict populations at risk.
- organism: human
- assay: whole-genome sequencing
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 37
- FWCI
- 4.97
- Field percentile
- top 3%
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