Your browser doesn't support javascript.
A patient-centric modeling framework captures recovery from SARS-CoV-2 infection.
Ruffieux, Hélène; Hanson, Aimee L; Lodge, Samantha; Lawler, Nathan G; Whiley, Luke; Gray, Nicola; Nolan, Tui H; Bergamaschi, Laura; Mescia, Federica; Turner, Lorinda; de Sa, Aloka; Pelly, Victoria S; Kotagiri, Prasanti; Kingston, Nathalie; Bradley, John R; Holmes, Elaine; Wist, Julien; Nicholson, Jeremy K; Lyons, Paul A; Smith, Kenneth G C; Richardson, Sylvia; Bantug, Glenn R; Hess, Christoph.
  • Ruffieux H; MRC Biostatistics Unit, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK. helene.ruffieux@mrc-bsu.cam.ac.uk.
  • Hanson AL; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.
  • Lodge S; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
  • Lawler NG; Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia.
  • Whiley L; Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia.
  • Gray N; Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia.
  • Nolan TH; Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia.
  • Bergamaschi L; Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia.
  • Mescia F; Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia.
  • Turner L; Perron Institute for Neurological and Translational Science, Nedlands, Western Australia, Australia.
  • de Sa A; Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia.
  • Pelly VS; Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia.
  • Kotagiri P; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.
  • Kingston N; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
  • Bradley JR; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.
  • Holmes E; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
  • Wist J; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.
  • Nicholson JK; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
  • Lyons PA; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.
  • Smith KGC; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
  • Richardson S; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.
  • Bantug GR; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
Nat Immunol ; 24(2): 349-358, 2023 02.
Article in English | MEDLINE | ID: covidwho-2221843
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.
Subject(s)
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Prognostic study Topics: Long Covid Limits: Humans Language: English Journal: Nat Immunol Journal subject: Allergy and Immunology Year: 2023 Document Type: Article Affiliation country: S41590-022-01380-2

Similar

MEDLINE
LILACS
LIS
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Prognostic study Topics: Long Covid Limits: Humans Language: English Journal: Nat Immunol Journal subject: Allergy and Immunology Year: 2023 Document Type: Article Affiliation country: S41590-022-01380-2