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Strong association between angiotensin-converting enzyme gene InDel polymorphism and COVID-19 diseases. | LitMetric

Strong association between angiotensin-converting enzyme gene InDel polymorphism and COVID-19 diseases.

Med Clin (Barc)

Department of Cardiovascular Surgery, Faculty of Medicine, Near East University, Nicosia, Cyprus; Department of Medical Genetics, Faculty of Medicine, Near East University, Nicosia, Cyprus. Electronic address:

Published: June 2023

AI Article Synopsis

Article Abstract

Background And Objectives: The COVID-19 pandemic that emerged in China in late 2019 and spread rapidly around the world. There is evidence that COVID-19 infection can be influenced by genetic variations in the host. The aim of this study was to investigate the association between ACE InDel polymorphism and COVID-19 in Northern Cyprus.

Patients And Methods: This study included 250 patients diagnosed with COVID-19 and 371 healthy controls. Genotyping for the ACE InDel gene polymorphism was performed by polymerase chain reaction.

Results: The frequency of ACE DD homozygotes was significantly increased in COVID-19 patients compared to the control group (p=0.022). The difference in the presence of the D allele between the patient and control groups was statistically significant (57.2% and 50.67%, respectively, p<0.05). Individuals with the genotype II were found to have a higher risk of symptomatic COVID-19 (p=0.011). In addition, chest radiographic findings were observed more frequently in individuals with the genotype DD compared to individuals with the genotypes ID and II (p=0.005). A statistically significant difference was found when the time of onset of symptoms for COVID-19 and duration of treatment were compared with participants' genotypes (p=0.016 and p=0.014, respectively). The time of onset of COVID-19 was shorter in individuals with the genotype DD than in individuals with the genotype II, while the duration of treatment was longer.

Conclusion: In conclusion, the ACE I/D polymorphism has the potential to predict the severity of COVID-19.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9868356PMC
http://dx.doi.org/10.1016/j.medcli.2022.11.023DOI Listing

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