Immune Senescence in COVID-19
Researchers examined how patients’ responses to infection with SARS-CoV-2 lead to different acute or prolonged disease outcomes and patients’ underlying biological differences underpinning different disease courses. Using a statistical modelling approach, the trajectories of different people’s experiences of COVID-19 were reconstructed. A model was then built which is capable of using data about specific biological markers soon after disease onset to predict an individual’s prognosis.
The Variation in COVID-19 Severity
The severity of symptoms experienced and the prognosis for individuals who contract COVID-19 varies markedly, as with other diseases. While some people develop very severe illness which requires inpatient care, others who test positive experience very mild, or even no symptoms at all. The long-term effects of the disease for those who recover from the acute stage of the infection also differ from person to person with some recovering fully and others experiencing a variety of chronic symptoms collectively referred to as ‘long COVID.’
The reasons for these differences in people’s responses to infection with the SARS-CoV-2 virus are ill-understood. However, it was apparent early in the pandemic that a disproportionate number of those manifesting severe COVID-19 were over 60 years old and had comorbidities that are associated with immune dysfunction, such as cardiovascular disease and obesity. This exemplifies a phenomenon termed ‘immune senescence’ whereby biologic ageing of the immune system (due to either advancing years or illness and disease) leads to a progressive decline in the competence of the immune system through metabolic changes affecting the functioning of immune cells. This decline leads in turn to an increased susceptibility to infection.
Identifying the Causes of Different Disease Outcomes
In this project, the team of researchers, led by Prof Christoph Hess examined how patients’ responses to infection with SARS-CoV-2 lead to different acute or prolonged disease outcomes and the underlying biological differences between patients that underpin these different disease courses. They followed 215 people infected with COVID-19 for 16 months between 2020 and 2021. This group represented a wide spectrum of disease severity from people who were hospitalised and ventilated through to those who experienced very mild or no symptoms at all. A control group of uninfected healthy individuals were also included in the study.
The impact of SARS-CoV-2 infection on multiple related clinical, metabolic and cellular parameters was examined. A person’s systemic inflammatory status is a measure of their immune response to a pathogen. It was determined that those infected with COVID-19 could be split into three groups based on the degree of inflammation that they experienced. The first group experienced mild inflammation or no inflammation at all. The second group experienced inflammation early, during the acute phase of the disease which then resolved. For the third group, the inflammation persisted. This consortium was successful in identifying distinct metabolic and senescent features of the immune cells in each of these three groups.
A Predictive Model of Prognosis
Using a statistical modelling approach, the researchers reconstructed the trajectories of different people’s experiences of COVID-19. They were then able to build a predictive model, which is capable of using data about specific biological markers soon after the onset of disease, to predict an individual’s prognosis. The online tool is free to access and utilises an easy-to-use interface.
The research carried out by this consortium provided scientific knowledge which was crucial to understanding patients’ long-term responses to infection and how these responses are associated with the inflammatory response experienced during the acute infection phase. The group has subsequently built upon this research to investigate potential therapeutic routes to moderate immune cell function.
Banner image above: S. Roffeis examining cells in the cell culture laboratory. Photograph: C. Berger.
