tetano
Editor, Senior Moderator
Nat Immunol
. 2023 Jan 30.
doi: 10.1038/s41590-022-01380-2. Online ahead of print.
A patient-centric modeling framework captures recovery from SARS-CoV-2 infection
Hélène Ruffieux[SUP] 1 [/SUP], Aimee L Hanson[SUP] 2 3 [/SUP], Samantha Lodge[SUP] 4 5 [/SUP], Nathan G Lawler[SUP] 4 5 [/SUP], Luke Whiley[SUP] 4 5 6 [/SUP], Nicola Gray[SUP] 4 5 [/SUP], Tui H Nolan[SUP] 7 [/SUP], Laura Bergamaschi[SUP] 2 3 [/SUP], Federica Mescia[SUP] 2 3 [/SUP], Lorinda Turner[SUP] 2 3 [/SUP], Aloka de Sa[SUP] 2 3 [/SUP], Victoria S Pelly[SUP] 2 3 [/SUP]; Cambridge Institute of Therapeutic Immunology and Infectious Disease-National Institute of Health Research (CITIID-NIHR) BioResource COVID-19 Collaboration; Prasanti Kotagiri[SUP] 2 3 [/SUP], Nathalie Kingston[SUP] 8 9 [/SUP], John R Bradley[SUP] 3 9 [/SUP], Elaine Holmes[SUP] 4 5 10 [/SUP], Julien Wist[SUP] 4 5 11 [/SUP], Jeremy K Nicholson[SUP] 4 5 12 [/SUP], Paul A Lyons[SUP] 2 3 [/SUP], Kenneth G C Smith[SUP] 2 3 [/SUP], Sylvia Richardson[SUP] 7 [/SUP], Glenn R Bantug[SUP] 13 14 [/SUP], Christoph Hess[SUP] 15 16 17 18 [/SUP]
Affiliations
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.
. 2023 Jan 30.
doi: 10.1038/s41590-022-01380-2. Online ahead of print.
A patient-centric modeling framework captures recovery from SARS-CoV-2 infection
Hélène Ruffieux[SUP] 1 [/SUP], Aimee L Hanson[SUP] 2 3 [/SUP], Samantha Lodge[SUP] 4 5 [/SUP], Nathan G Lawler[SUP] 4 5 [/SUP], Luke Whiley[SUP] 4 5 6 [/SUP], Nicola Gray[SUP] 4 5 [/SUP], Tui H Nolan[SUP] 7 [/SUP], Laura Bergamaschi[SUP] 2 3 [/SUP], Federica Mescia[SUP] 2 3 [/SUP], Lorinda Turner[SUP] 2 3 [/SUP], Aloka de Sa[SUP] 2 3 [/SUP], Victoria S Pelly[SUP] 2 3 [/SUP]; Cambridge Institute of Therapeutic Immunology and Infectious Disease-National Institute of Health Research (CITIID-NIHR) BioResource COVID-19 Collaboration; Prasanti Kotagiri[SUP] 2 3 [/SUP], Nathalie Kingston[SUP] 8 9 [/SUP], John R Bradley[SUP] 3 9 [/SUP], Elaine Holmes[SUP] 4 5 10 [/SUP], Julien Wist[SUP] 4 5 11 [/SUP], Jeremy K Nicholson[SUP] 4 5 12 [/SUP], Paul A Lyons[SUP] 2 3 [/SUP], Kenneth G C Smith[SUP] 2 3 [/SUP], Sylvia Richardson[SUP] 7 [/SUP], Glenn R Bantug[SUP] 13 14 [/SUP], Christoph Hess[SUP] 15 16 17 18 [/SUP]
Affiliations
- PMID: 36717723
- DOI: 10.1038/s41590-022-01380-2
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.