Journal article
Diagnostic potential of the plasma lipidome in infectious disease: Application to acute SARS-CoV-2 infection
Metabolites, Vol.11(7), 467
2021
Abstract
Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography–mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive; 37 healthy controls; 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive; 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal–Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive individuals from SARS-CoV-2-negative individuals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management.
Details
- Title
- Diagnostic potential of the plasma lipidome in infectious disease: Application to acute SARS-CoV-2 infection
- Authors/Creators
- N. Gray (Author/Creator) - Murdoch UniversityN. Lawler (Author/Creator) - Murdoch UniversityA. Zeng (Author/Creator) - Murdoch UniversityM. Ryan (Author/Creator) - Murdoch University, Australian National Phenome CentreS-H Bong (Author/Creator) - Murdoch UniversityB. Boughton (Author/Creator) - Murdoch UniversityM. Bizkarguenaga (Author/Creator) - CIC bioGUNEC. Bruzzone (Author/Creator) - CIC bioGUNEN. Embade (Author/Creator) - CIC bioGUNEJ. Wist (Author/Creator) - Murdoch UniversityE. Holmes (Author/Creator) - Murdoch UniversityO. Millet (Author/Creator) - CIC bioGUNEJ. Nicholson (Author/Creator) - Murdoch UniversityL. Whiley (Author/Creator) - Murdoch University
- Publication Details
- Metabolites, Vol.11(7), 467
- Publisher
- MDPI
- Identifiers
- 991005543064907891
- Copyright
- © 2021 by the authors
- Murdoch Affiliation
- Australian National Phenome Centre; Centre for Computational and Systems Medicine; Health Futures Institute
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International collaboration
- Citation topics
- 2 Chemistry
- 2.211 Mass Spectrometry
- 2.211.990 Metabolomics
- Web Of Science research areas
- Biochemistry & Molecular Biology
- ESI research areas
- Biology & Biochemistry