Published November 1, 2022
| Version v2
Dataset
Open
A patient-centric modelling framework captures recovery from SARS-CoV-2 infection
Creators
- Hélène Ruffieux1
- Aimee L. Hanson2
- Samantha Lodge3
- Nathan G. Lawler3
- Luke Whiley4
- Nicola Gray3
- Tui H. Nolan1
- Laura Bergamaschi2
- Federica Mescia2
- Lorinda Turner2
- Aloka de Sa2
- Victoria S. Pelly2
- The Cambridge Institute of Therapeutic Immunology and Infectious Disease-National Institute of Health Research (CITIID-NIHR) BioResource COVID-19 Collaboration
- Prasanti Kotagiri2
- Nathalie Kingston5
- John R. Bradley6
- Elaine Holmes7
- Julien Wist8
- Jeremy K. Nicholson9
- Paul A. Lyons2
- Kenneth G.C. Smith2
- Sylvia Richardson1
- Glenn R. Bantug10
- Christoph Hess11
- 1. MRC Biostatistics Unit, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SR, UK
- 2. Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge CB2 0AW, UK, Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
- 3. Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia, Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia
- 4. Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia, Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia, Perron Institute for Neurological and Translational Science, Nedlands, WA 6009, Australia
- 5. Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK, NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
- 6. Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK, NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
- 7. Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia, Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK
- 8. Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia, Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia, Chemistry Department, Universidad del Valle, 76001 Cali, Colombia
- 9. Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia, Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia, Institute of Global Health Innovation, Imperial College London, London SW7 2AZ, UK
- 10. Department of Biomedicine, University and University Hospital Basel, 4031 Basel, Switzerland, Botnar Research Centre for Child Health (BRCCH) University Basel & ETH Zurich, 4058 Basel, Switzerland
- 11. Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge CB2 0AW, UK, Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK, Department of Biomedicine, University and University Hospital Basel, 4031 Basel, Switzerland, Botnar Research Centre for Child Health (BRCCH) University Basel & ETH Zurich, 4058 Basel, Switzerland
Description
The biology driving individual patient responses to SARS-CoV-2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data and covering a year post-disease onset, from 215 SARS-CoV-2 infected subjects with differing disease severities. Our analyses revealed distinct “systemic recovery” profiles, with specific progression and resolution of the inflammatory, immune cell, metabolic and clinical responses. In particular, we found a strong inter- and intra-patient temporal covariation of innate immune cell numbers, kynurenine metabolites and lipid metabolites, which highlighted candidate immunologic and metabolic pathways influencing the restoration of homeostasis, the risk of death and that of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery at the patient level, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-19-systemic-recovery-prediction-app, designed to test our findings prospectively.
Notes
We thank NIHR BioResource volunteers for their participation, and gratefully acknowledge NIHR BioResource centres, NHS Trusts and staff for their contribution. We thank the National Institute for Health and Care Research, NHS Blood and Transplant, and Health Data Research UK as part of the Digital Innovation Hub Programme. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.
We are also grateful for the generous support of CVC Capital Partners, the Evelyn Trust (20/75), UKRI COVID Immunology Consortium, Addenbrooke's Charitable Trust (12/20A), the UKRI/NIHR through the UK Coronavirus Immunology Consortium (UK-CIC), the COVID-19 Rapid Response DCF (RG93172/HESS/40558) and the Botnar Research Centre for Child Health (BRCCH) for their financial support. H.R. would like to thank the Lopez–Loreta Foundation for their support. J.N., J.W. and E.H. would like to acknowledge the Australian Federal Government's Medical Research Future Fund (MRFF-ARAPC ARG76435), the Western Australian Department of Health, the Spinnaker Health Research Foundation and the McCusker Charitable Foundation for their support and contributions to this research program. K.G.C.S. acknowledges support from Wellcome Investigator and Collaborative Awards (200871/Z/16/ Z; 219506/Z/19/Z) and a Medical Research Council Programme Grant (MR/L019027). We would also like to thank the NIHR Cambridge Clinic Research Facility outreach team for enrollment of patients; and the NIHR Cambridge Biomedical Research Centre Cell Phenotyping Hub and the CRUK Cambridge Institute flow cytometry core facility for their support with flow and mass cytometry.