Almeida, Ingrid Marins de; https://orcid.org/0000-0002-4251-2448; http://lattes.cnpq.br/1663579852602347
Resumo:
Introduction: The COVID-19 pandemic, caused by the SARS-CoV-2 virus, was a global
crisis, with Brazil being one of the countries with the highest number of deaths due to COVID-19 in the world, 701,494 deaths. Many factors can determine the severity of COVID-19,
including viral load, genetic factors, presence of comorbidities, age, gender, and uncontrolled
inflammation. It is estimated that approximately 5% of cases develop severe acute respiratory
distress syndrome due to cytokine storm. A cell signaling pathway that may be involved in this
process is PI3K/AKT/MTOR. Studies demonstrate that AKT inhibition can potentially suppress
pathologic inflammation, cytokine storm, fibroproliferation, and platelet activation associated
with COVID-19. Objectives: To investigate the association between AKT1 gene variants and
the severity of COVID-19. Methods: Peripheral blood samples and sociodemographic data
were collected from 508 individuals with COVID-19, 216 mild cases and 292 severe cases,
from April 2020 to April 2021. Plasma cytokine concentrations were measured by ELISA.
Genotyping of the SNPs, rs1130214 and rs2494746, and AKT1 gene expression were performed
using Thermo Fisher kits and analyzed by qRT-PCR in the QuantStudio 12K (Applied
Biosystems). Results and Conclusions: The rs2494746-C allele was associated with severity,
ICU admission, and death from COVID-19. Meanwhile, the C allele of rs1130214 was
associated with elevated TNF-α and D-dimer levels. In addition, variants demonstrated a
cumulative risk associated with severity, criticality, and death from COVID-19. In the
predictive analysis, the rs2494746 obtained an accuracy of 71%, suggesting a high probability
of the test determining the severity of the disease. Therefore, the present study contributes to
understanding the influence of the AKT1 gene and its variants on immune damage in individuals
infected with SARS-CoV-2, which may be useful in the future to help predict a worse outcome
of COVID-19.