Imperials' REACT study expanded to help better understand Long COVID
- Health & Social Care Research, Big Data & Digital Health, Blood & Immune System, Heart & circulation, Infectious diseases, Inflammation, Multiple Conditions
A team of Imperial College London researchers has been awarded £5.5 million from the Government to study Long COVID.
Carried out in partnership with Queen Mary University of London, the Francis Crick Institute, Leiden University, Birmingham University and Newcastle University, the study will involve more than 120,000 people to better understand why some people who are infected with the coronavirus have symptoms for several weeks or even months – a condition called Long COVID – while others don’t.
The team will work closely with people who have Long COVID to understand their varied symptoms and experiences. The researchers will also look at how people’s biological makeup, their environment and social factors affect their likelihood of experiencing this illness, and the relationship between these. A number of people will also be asked to take part in a further study to document and analyse their experiences in depth.
In doing so the research hopes to find new ways to diagnose, support and effectively treat Long COVID, which may affect up to a quarter of people who have had the virus. The project is one of four studies to be jointly funded by the National Institute for Health Research (NIHR) and UK Research and Innovation to help understand and address the longer-term effects of COVID-19 on physical and mental health.
The research forms part of the Imperial-led REACT programme, which is using home testing on hundreds of thousands of volunteers each month to track England’s epidemic, involving more than 1.5 million people to date.
Long COVID: a poorly understood illness
Although there are several well-known symptoms of COVID-19, such as a loss of sense of taste or smell, the disease can affect people in very different ways. Some people experience a short illness and others don’t have any symptoms at all, while some individuals can have symptoms that persist for a long time.
People experiencing Long COVID have reported a range of symptoms affecting different parts of the body, from breathlessness to skin rash and brain fog, although these have been poorly defined to date. Little is also understood about the factors that can contribute to this condition, and who is most at risk.
Through involving and engaging patients and members of the public, the researchers will work to improve understanding of people’s experiences of the illness and help to better define it. A further study of survey data from 120,000 people recruited onto the REACT programme – 30,000 who tested positive and 90,000 negative – will explore social and environmental factors that could be linked with long COVID.
Professor Helen Ward, one of the investigators and Director of Imperial’s Patient Experience Research Centre, said:
“It is critical that we work closely with patients to ensure that we are asking the right questions about this new and as yet poorly understood condition. We will use innovative approaches to patient and public involvement, working with existing patient groups and VOICE-Global at Newcastle University. Because of the large scale of our study, we will also be able to explore social determinants and inequalities in outcomes.”
The study will also link up with another arm of the REACT programme called REACT GE, a genomic extension study being carried out by Imperial, Genomics England and Edinburgh University.
REACT GE is looking for biological ‘signatures’, such as molecules in the blood or variations in people’s genes, that could help explain why some infected individuals experience serious illness while others don’t.
This research will now be expanded to look for biological factors that could be linked with developing Long COVID. 8,000 people – half of whom report long-term symptoms following COVID – will have their DNA code read, alongside a variety of other tests looking at the brain and immune system. The researchers will then use statistical analysis and machine learning to find markers that give people a higher risk of Long COVID, which could highlight new treatment and diagnostic avenues.
Article text (excluding photos or graphics) © Imperial College London.