Data scientists have used an AI enabled precision medicine platform to identify high risk genes for COVID-19, along with drug candidates for increasing survival rates.

The scientists from UK-headquartered AI precision medicine company, PrecisionLife, have used the platform to identify 13 high risk genes for COVID-19, and 59 repurposing drug candidates that could be used to develop new therapeutic strategies to increase the survival rate of patients who develop sepsis while suffering from severe COVID-19.

Sepsis is observed in 60% of severe COVID-19 patients and is a life-threatening condition with a mortality rate of approximately 20%.

The study, released on Biorxiv, sought to identify genetic risk factors for sepsis especially in the context of COVID-19, and to use these insights to identify existing drugs that might be used to treat life-threatening late-stage disease.

Analysis of sepsis patients

The team identified mutations in 70 sepsis risk genes, 61% of which were also present specifically in severe COVID-19 patients. Several of the disease associated genetic signatures found in both sepsis and severe COVID-19 patients have previously been linked to cancer, immune response, endothelial and vascular inflammation, and neuronal signalling.

PrecisionLife analysed patient datasets compiled by UK Biobank to identify genes associated with sepsis, which are also found in severe COVID-19 patients, finding 70 sepsis risk genes

Several of the disease associated genetic signatures found in both sepsis and severe COVID-19 patients have previously been linked to cancer, immune response, endothelial and vascular inflammation and neuronal signalling.

Dr Steve Gardner, CEO of PrecisionLife, said: “Ours is the first study looking at host genomics and opportunities to treat later stage severe disease where host immune processes take over.”

Potential therapies

By providing deeper insights, this study identifies novel approaches and hope for new therapies.

A total of 13 of the sepsis risk genes are able to be targeted by active chemical compounds used to treat other diseases, representing the potential for drug repurposing opportunities.

A further 59 compounds and drugs that are known to be active against these 13 targets were identified which could form the basis for future drug trials and repurposing projects, as well as COVID-19 high risk biomarkers.

Dr Gardner added: “Our high-resolution genomic analysis tools have allowed us to develop new insights into two serious and complex diseases for which new therapeutic options are urgently required.

“We hope that these will lead to better understanding of what drives sepsis in COVID-19 patients and result in new ways to treat seriously ill patients.”


Original source: https://www.healtheuropa.eu/ai-precision-medicine-mining-finds-13-human-covid-19-risk-genes/99851/