Genetically predicted COVID-19 linked to blood clots, thrombophlebitis and circulatory diseases

Research led by Queen Mary University of London associates genetically determined COVID-19 susceptibility with increased blood clot events in leg and lungs, thrombophlebitis and circulatory diseases.

The study used a Phenome-wide (PheWAS) analysis in up to 400,000 European ancestry individuals, derived from the UK Biobank, researchers aimed to identify traits and diseases associated with COVID-19 susceptibility and severity. PheWAS analysis allowed the team to construct the predictive COVID-19 genetic score, using the sum of COVID-19 risk alleles for each individual in the UK Biobank. This score was examined against all available traits and diseases in UK Biobank, adjusted for confounders, in a hypothesis-free manner.

The study found that genetically predicted COVID-19 is significantly associated with an 11% increased risk of phlebitis and thrombophlebitis, a 10% increased risk of blood clots in the leg and a 12 per cent increased risk of blood clots in the lung.

This PheWAS was conducted to determine if genetically predicted COVID-19 susceptibility and severity is associated with other diseases and traits, examining all of them in a hypothesis-free way. For COVID-19 susceptibility, we identified an increased risk of phlebitis and thrombophlebitis. In addition to that, we found that general COVID-19 susceptibility was associated with an increased risk of blood clots in leg and lung; factors involved in COVID-19 mortality.

The results from our study add valuable information for the identification and stratification of individuals at increased COVID-19 risk and other complications after infection. Our study identifies significant associations of genetically predicted COVID-19 susceptibility with increased blood clot events in the leg and lungs, thrombophlebitis and circulatory diseases. Our findings could have further significance for individual with long-covid complications."

Dr Eirini Marouli, Study Lead and Lecturer in Computational Biology, Queen Mary University of London

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Phase 2 study evaluates safety and efficacy of asunercept in COVID-19 patients