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Approved Research

CARdiovascular GENetic risk score in patients positive for SARS-CoV-2 infection Risk Stratification (CARGENCORS): validation of the significant single nucleotide polymorphisms.

Principal Investigator: Professor Irene Degano
Approved Research ID: 84905
Approval date: August 10th 2022

Lay summary

We will analyze the association between genetic variants and severe coronavirus disease (COVID-19). The genetic variants under study are changes of one letter in the genome. These changes can be associated with diseases such as COVID-19.

We will select COVID-19 patients who had a severe/fatal course of the disease as well as patients who had only mild/moderate symptoms. We will examine 86 genetic variants and the clinical history of these patients to analyze whether there is an association between each of the genetic variants and having severe COVID-19. The 86 genetic variants are present in or near to genes linked with cardiovascular diseases, inflammation and response to infections. We selected these variants because COVID-19 patients with cardiovascular diseases have a worse disease course, and because inflammation is a key clinical manifestation of severe COVID-19. We will include factors that are known to worsen the prognosis of COVID-19 such as presence of hypertension, obesity, diabetes, chronic kidney disease, and cardiovascular disease.

We have already identified 19 genetic variants that are associated with severe COVID-19 in a discovery study. But to be confident on these results we must redo the analysis in a different population. And this is what we plan to do with the UK Biobank data.

The COVID-19 pandemic has already affected more than 270 million people and more than 5 million have died. While the vaccination has reduced the mortality due to COVID-19, severe cases continue to occur.

Our aim is to validate some of the genetic variants we identified in the discovery study to be associated with COVID-19 severity. Then, we will develop a calculation to predict the expected COVID-19 severity of the patients based on their genetic variants and risk factors. We plan to fulfill these objectives in 6 months.

The results from this project will be validated genetic variants as well as novel variants associated with COVID-19. Another output will be a calculation to obtain the severity risk of COVID-19 patients based on genetic variants and risk factors. With the knowledge from this project it will be possible to design a genetic test to know in advance the severity risk of COVID-19 patients. This information will allow a more personalized treatment of these patients. In addition, the identification of validated and novel genetic variants will open new research lines to design drugs to treat severe COVID-19 and to reuse drugs currently employed to treat other diseases.