| Literature DB >> 34251833 |
Reika Masuda1,2, Samantha Lodge1,2, Philipp Nitschke1, Manfred Spraul3, Hartmut Schaefer3, Sze-How Bong1, Torben Kimhofer1,2, Drew Hall1, Ruey Leng Loo1,2, Maider Bizkarguenaga4, Chiara Bruzzone4, Rubén Gil-Redondo4, Nieves Embade4, José M Mato4, Elaine Holmes1,2,5, Julien Wist1,2,6, Oscar Millet4, Jeremy K Nicholson1,2,7.
Abstract
Quantitative plasma lipoprotein and metabolite profiles were measured on an autonomous community of the Basque Country (Spain) cohort consisting of hospitalized COVID-19 patients (n = 72) and a matched control group (n = 75) and a Western Australian (WA) cohort consisting of (n = 17) SARS-CoV-2 positives and (n = 20) healthy controls using 600 MHz 1H nuclear magnetic resonance (NMR) spectroscopy. Spanish samples were measured in two laboratories using one-dimensional (1D) solvent-suppressed and T2-filtered methods with in vitro diagnostic quantification of lipoproteins and metabolites. SARS-CoV-2 positive patients and healthy controls from both populations were modeled and cross-projected to estimate the biological similarities and validate biomarkers. Using the top 15 most discriminatory variables enabled construction of a cross-predictive model with 100% sensitivity and specificity (within populations) and 100% sensitivity and 82% specificity (between populations). Minor differences were observed between the control metabolic variables in the two cohorts, but the lipoproteins were virtually indistinguishable. We observed highly significant infection-related reductions in high-density lipoprotein (HDL) subfraction 4 phospholipids, apolipoproteins A1 and A2,that have previously been associated with negative regulation of blood coagulation and fibrinolysis. The Spanish and Australian diagnostic SARS-CoV-2 biomarkers were mathematically and biologically equivalent, demonstrating that NMR-based technologies are suitable for the study of the comparative pathology of COVID-19 via plasma phenotyping.Entities:
Keywords: COVID-19; NMR spectroscopy; SARS-CoV-2; diagnostic modeling; lipoproteins; metabolic phenotyping; phenoconversion; plasma IVDr; population cross-validation
Year: 2021 PMID: 34251833 DOI: 10.1021/acs.jproteome.1c00458
Source DB: PubMed Journal: J Proteome Res ISSN: 1535-3893 Impact factor: 4.466