TY - JOUR
T1 - Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction
AU - Lodge, Samantha
AU - Lawler, Nathan G.
AU - Gray, Nicola
AU - Masuda, Reika
AU - Nitschke, Philipp
AU - Whiley, Luke
AU - Bong, Sze How
AU - Yeap, Bu B.
AU - Dwivedi, Girish
AU - Spraul, Manfred
AU - Schaefer, Hartmut
AU - Gil-Redondo, Rubén
AU - Embade, Nieves
AU - Millet, Oscar
AU - Holmes, Elaine
AU - Wist, Julien
AU - Nicholson, Jeremy K.
PY - 2023/7
Y1 - 2023/7
N2 - An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff’s delta 0.91–0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff’s delta = −0.98 and PE.P 16:0/18:1, Cliff’s delta = −0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these “high risk” patients in the early disease stages.
AB - An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff’s delta 0.91–0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff’s delta = −0.98 and PE.P 16:0/18:1, Cliff’s delta = −0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these “high risk” patients in the early disease stages.
KW - COVID-19
KW - diagnostic modelling
KW - lipidomics
KW - lipids
KW - lipoproteins
KW - mass spectrometry
KW - metabolic phenotyping
KW - metabolomics
KW - mortality prediction
KW - NMR spectroscopy
KW - patient stratification
KW - plasma IVDr
KW - SARS-CoV-2
UR - http://www.scopus.com/inward/record.url?scp=85165975739&partnerID=8YFLogxK
U2 - 10.3390/ijms241411614
DO - 10.3390/ijms241411614
M3 - Article
C2 - 37511373
AN - SCOPUS:85165975739
SN - 1661-6596
VL - 24
JO - International Journal of Molecular Sciences
JF - International Journal of Molecular Sciences
IS - 14
M1 - 11614
ER -