BioResource volunteers support research to help develop online tool for predicting COVID-19 recovery

Patients from our COVID-19 BioResource participated in the international collaboration, led by University of Cambridge researchers, to help pave the way for a better understanding of the molecular mechanisms underpinning long COVID.

Initial research on SARS-CoV-2 focussed on the immune response to the virus in order to address how it is linked to the severity of the acute illness. Now that hospitalization rates have dropped, the focus of research has shifted towards questions around incomplete recovery and long-term effects of the virus.

A new, first-of-its-kind patient-centric study, trying to understand recovery from COVID-19 from an organismal, systemic sense, has now published in the journal Nature Immunology. Through analysis of existing and new data drawn from a large patient cohort, researchers set out to exploit a tailored statistical framework to disentangle the heterogeneity of patient’s response to infection and characterise the long-term recovery profiles at the patient level.

Immunophenotypes, molecular measurements and patient questionnaires addressing long-term symptoms were obtained in 215 patients with different clinical severities of infection.

Patients had consented to join our COVID-19 BioResource cohort, set up in response to the outbreak of the pandemic in March 2020. Currently more than 8,000 volunteers are part of this research resource and available for participation in studies. We are no longer actively recruiting new COVID patients, but anyone can join the NIHR BioResource and contribute to research efforts into a wide range of common and rare diseases.

Senior author Prof Christoph Hess from Cambridge Institute for Therapeutic Immunology & Infectious Disease (CITIID) commenting on the role of the BioResource and our volunteers said:

"Our work provides a basis for monitoring changes in patient recovery profiles and understand the drivers of these changes. In addition, our statistical framework can be re-deployed on other cohorts which permits systematic comparisons towards actionable strategies for personalized intervention.”

"The BioResource is a wonderful resource without which this work would not have been possible. We would therefore like to wholeheartedly thank all participants enrolled in our study and the entire, huge BioResource team that made this happen, despite incredibly stressful times. We hope that with our work we may, in one way or another, give something back to our patients one day."

The study identified composite signatures predictive of incomplete recovery using a joint model on cellular and molecular parameters measured soon after disease onset. These signatures can be inspected and predictions for new patients can be obtained using the online tool: Integrative prediction of systemic recovery from COVID-19.

The next step for the researchers is to validate the model in an independent cohort.

Lead author of the study, Dr Hélène Ruffieux, Senior Research Associate at the MRC Biostatistics Unit said:

"The cellular, inflammatory and metabolic dynamics driving incomplete recovery from SARS-CoV-2 are complex and subject to strong inter-patient variability. We performed longitudinal latent modelling analyses to characterise the individual patient disease trajectories, taking full advantage of detailed clinical and biological data collected over a year post disease onset.”

We would like to extend our thanks to the whole research team for this important and encouraging development. Thanks also to our volunteers for agreeing to take part and the large BioResource team involved in identifying participants, arranging appointments and collecting hundreds of blood samples.

The work was supported by the Cambridge Institute of Therapeutic Immunology and Infectious Disease-National Institute for Health and Care Research (CITIID-NIHR) COVID-19 BioResource Collaboration, NIHR BioResource, Cambridge University Hospitals NHS Foundation Trust, MRC Biostatistics Unit and Department of Medicine, University of Cambridge, Addenbrooke’s Hospital.

Read full paper: A patient-centric modeling framework captures recovery from SARS-CoV-2 infection | Nature Immunology

Original article published 31st January 2023 via University of Cambridge, Department of Medicine News feed.

If you are interested in working with the NIHR BioResource to support your research, as the research team did in this story, please get in touch. 

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