Targeted MS based multi-omic analysis of blood plasma from COVID-19 patients to predict survival
Richard VR, Gaither C, Popp R, Chaplygina D, Brzhozovskiy A, Kononikhin A, Mohammed Y, Zahedi RP, Nikolaev EN, Borchers CH. Early prediction of COVID-19 patient survival by targeted plasma multi-omics and machine learning. Mol Cell Proteomics. 2022 Aug 3:100277. doi: 10.1016/j.mcpro.2022.100277. Epub ahead of print. PMID: 35931319; PMCID: PMC9345792.
- Organism: Homo sapiens
- Instrument: 6495B Triple Quadrupole LC/MS
- SpikeIn:
Yes
- Keywords:
COVID-19, SARS COV 2, mass spectrometry, MRM, plasma, proteomics, internal standards
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Lab head: Christoph Borchers
Submitter: Claudia Gaither
Molecular signatures to discriminate patients based on risk of severe disease and mortality from COVID-19 infection are urgently required by the global medical community. Although non-targeted methods are useful for comprehensive ‘omic coverage, targeted MS-based approaches generally provide higher precision, and improved inter-laboratory reproducibility, allowing for more realistic materialization of true biomarkers via validation studies in independent cohorts.
We found a relatively small subset of molecular features that can be used to predict the chances of survival of hospitalized COVID-19 patients within the first day of admission, using a robust LC-MRM setup which is already available in many clinical laboratories.
Created on 8/16/21, 8:08 PM