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10.1007/s12041-020-01217-7

http://scihub22266oqcxt.onion/10.1007/s12041-020-01217-7
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suck abstract from ncbi


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pmid32661206      J+Genet 2020 ; 99 (1): ä
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  • Assessment of risk conferred by coding and regulatory variations of TMPRSS2 and CD26 in susceptibility to SARS-CoV-2 infection in human #MMPMID32661206
  • Senapati S; Kumar S; Singh AK; Banerjee P; Bhagavatula S
  • J Genet 2020[]; 99 (1): ä PMID32661206show ga
  • At present, more than 200 countries and territories are directly affected by the coronavirus disease-19 (COVID-19) pandemic. Incidence and case fatality rate are significantly higher among elderly individuals (age>60 years), type 2 diabetes and hypertension patients. Cellular receptor ACE2, serine protease TMPRSS2 and exopeptidase CD26 (also known as DPP4) are the three membrane bound proteins potentially implicated in SARS-CoV-2 infection. We hypothesised that common variants from TMPRSS2 and CD26 may play critical role in infection susceptibility of predisposed population or group of individuals. Coding (missense) and regulatory variants from TMPRSS2 and CD26 were studied across 26 global populations. Two missense and five regulatory SNPs were identified to have differential allelic frequency. Significant linkage disequilibrium (LD) signature was observed in different populations. Modelled protein-protein interaction (PPI) predicted strong molecular interaction between these two receptors and SARS-CoV-2 spike protein (S1 domain). However, two missense SNPs, rs12329760 (TMPRSS2) and rs1129599 (CD26), were not found to be involved physically in the said interaction. Four regulatory variants (rs112657409, rs11910678, rs77675406 and rs713400) from TMPRSS2 were found to influence the expression of TMPRSS2 and pathologically relevant MX1. rs13015258 a 50 UTR variant from CD26 have significant role in regulation of expression of key regulatory genes that could be involved in SARS-CoV-2 internalization. Overexpression of CD26 through epigenetic modification at rs13015258-C allele was found critical and could explain the higher SARS-CoV-2 infected fatality rate among type 2 diabetes.
  • |Betacoronavirus/*physiology[MESH]
  • |COVID-19[MESH]
  • |Coronavirus Infections/*genetics/metabolism/virology[MESH]
  • |Dipeptidyl Peptidase 4/*genetics/metabolism[MESH]
  • |Epigenomics[MESH]
  • |Genetic Predisposition to Disease[MESH]
  • |Genetic Variation[MESH]
  • |Humans[MESH]
  • |Linkage Disequilibrium[MESH]
  • |Molecular Docking Simulation[MESH]
  • |Pandemics[MESH]
  • |Pneumonia, Viral/*genetics/metabolism/virology[MESH]
  • |Polymorphism, Single Nucleotide[MESH]
  • |Protein Interaction Domains and Motifs[MESH]
  • |SARS-CoV-2[MESH]
  • |Serine Endopeptidases/*genetics/metabolism[MESH]
  • |Spike Glycoprotein, Coronavirus/metabolism[MESH]


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