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Journal article
A patient-centric modeling framework captures recovery from SARS-CoV-2 infection
Nature immunology, Vol.24(2), pp.349-358
2023
PMID: 36717723
Abstract
The biology driving individual patient responses to severe acute respiratory syndrome coronavirus 2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data and covering a year after disease onset, from 215 infected individuals 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-patient 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, 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.
Details
- Title
- A patient-centric modeling framework captures recovery from SARS-CoV-2 infection
- Authors/Creators
- Hélène Ruffieux - MRC Biostatistics UnitAimee L Hanson - MRC Epidemiology UnitSamantha Lodge - Murdoch UniversityNathan G Lawler - Murdoch UniversityLuke Whiley - Murdoch UniversityNicola Gray - Murdoch UniversityTui H Nolan - MRC Biostatistics UnitLaura Bergamaschi - MRC Epidemiology UnitFederica Mescia - MRC Epidemiology UnitLorinda Turner - MRC Epidemiology UnitAloka de Sa - MRC Epidemiology UnitVictoria S Pelly - MRC Epidemiology UnitPrasanti Kotagiri - MRC Epidemiology UnitNathalie Kingston - University of CambridgeJohn R Bradley - Addenbrooke's HospitalElaine Holmes - Murdoch UniversityJulien Wist - Murdoch UniversityJeremy K Nicholson - Murdoch UniversityPaul A Lyons - MRC Epidemiology UnitKenneth G C Smith - MRC Epidemiology UnitSylvia Richardson - MRC Biostatistics UnitGlenn R Bantug - University Hospital of BaselChristoph Hess - MRC Epidemiology UnitCambridge Institute of Therapeutic Immunology and Infectious Disease-National Institute of Health Research (CITIID-NIHR) BioResource COVID-19 Collaboration
- Publication Details
- Nature immunology, Vol.24(2), pp.349-358
- Publisher
- Springer Nature
- Grant note
- 200871/Z/16/ Z / Wellcome Trust MR/W018861/1 / Medical Research Council 219506/Z/19/Z / Wellcome Trust MR/L019027/1 / Medical Research Council 200871 / Wellcome Trust 200871/Z/16/Z / Wellcome Trust MR/L019027 / Medical Research Council
- Identifiers
- 991005586607607891
- Copyright
- © The Author(s) 2023
- Murdoch Affiliation
- Health Futures Institute; Centre for Computational and Systems Medicine
- Language
- English
- Resource Type
- Journal article
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