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Clinical population genetic analysis of variants in the SARS-CoV-2 receptor ACE2
Amin Ardeshirdavani; Pooya Zakeri; Amirhosein Mehrtash; Sayed Mostafa Hosseini; Guangdi Li; Hanifeh Mirtavoos-Mahyari; Mohamad javad Soltanpour; Mahmoud Tavallaie; Yves Moreau.
Affiliation
  • Amin Ardeshirdavani; Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium.
  • Pooya Zakeri; Centre for Brain and Disease Research, Flanders Institute for Biotechnology (VIB), Leuven, Belgium. Department of Neurosciences and Leuven Brain Institute, KU L
  • Amirhosein Mehrtash; Cimorgh Medical IT Solutions, Tehran, Iran
  • Sayed Mostafa Hosseini; Human Genetic Research Center, Baqiyatallah Medical Science University, Tehran, Iran
  • Guangdi Li; Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
  • Hanifeh Mirtavoos-Mahyari; Lung Transplantation Research Center (LTRC), National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Scien
  • Mohamad javad Soltanpour; DCLS, Clinical Laboratory Dep., Baqiyatallah Hospital, Tehran, Iran
  • Mahmoud Tavallaie; Human Genetic Research Center, Baqiyatallah Medical Science University, Tehran, Iran
  • Yves Moreau; Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
Preprint in English | medRxiv | ID: ppmedrxiv-20115071
ABSTRACT
PurposeSARS-CoV-2 infects cells via the human Angiotensin-converting enzyme 2 (ACE2) protein. The genetic variation of ACE2 function and expression across populations is still poorly understood. This study aims at better understanding the genetic basis of COVID-19 outcomes by studying association between genetic variation in ACE2 and disease severity in the Iranian population. MethodsWe analyzed two large Iranian cohorts and several publicly available human population variant databases to identify novel and previously known ACE2 exonic variants present in the Iranian population and considered those as candidate variants for association between genetic variation and disease severity. We genotyped these variants across three groups of COVID-19 patients with different clinical outcomes (mild disease, severe disease, and death) and evaluated this genetic variation with regard to clinical outcomes. ResultsWe identified 32 exonic variants present in Iranian cohorts or other public variant databases. Among those, 11 variants are novel and have thus not been described in other populations previously. Following genotyping of these 32 candidate variants, only the synonymous polymorphism (c.2247G>A) was detected across the three groups of COVID-19 patients. ConclusionGenetic variability of known and novel exonic variants was low among our COVID-19 patients. Our results do not provide support for the hypothesis that exonic variation in ACE2 has a sizeable impact on COVID-19 severity across the Iranian population.
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Full text: Available Collection: Preprints Database: medRxiv Type of study: Cohort_studies / Experimental_studies / Observational study / Prognostic study / Rct Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Cohort_studies / Experimental_studies / Observational study / Prognostic study / Rct Language: English Year: 2020 Document type: Preprint
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