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Metabolic Fingerprinting of Covid-19: Benchtop Nmr Spectroscopy for Precision Diagnostics in Hospitals

Year: 2026

Type: article

Abstract: COVID-19 pandemic highlighted the need for diagnostics and track respiratory diseases, especially in Intensive Care Units (ICUs). Nuclear Magnetic Resonance (NMR)-based metabolomics offers unique metabolic fingerprinting for respiratory disease detection and characterization, but conventional NMR systems are limited by size and cost. Benchtop NMR (b-NMR) spectrometers have emerged as promising alternatives for clinical applications. The aim of this study is to assess the potential of b-NMR techniques as a valuable tool for clinical implementation, focusing on ICU applications. In this project, serum samples from Madrid hospitals during early COVID-19 pandemic were analyzed. Metabolomics analysis was conducted in 128 cases (83 mild, 15 moderate, 6 severe and 24 very severe) using both conventional (500 MHz Bruker AVIII) and benchtop (80 MHz Magritek Spinsolve Ultra) NMR spectrometers. NMR spectra were processed for multivariate statistical analyses. Our results demonstrated the ability to stratify patients by disease severity using both equipment, with an excellent group separation in Principal Component Analysis (PCA). Partial Least Squares Discriminant Analysis (PLS-DA) achieved perfect classification performance with near perfect accuracy (99.23% for the conventional and 85.93% for b-NMR) and robust cross-validation metrics. A stratification model accurately distinguished mild cases from hospitalized patients (moderate, severe and very severe cases), achieving an AUC-ROC value of 0.999 (CI95%: 0.994-1) with 100% sensitivity and 97.59% specificity using conventional instrument, and an AUC-ROC of 0.996 (CI95%: 0.984-1), 95.56% sensitivity and 96% specificity using b-NMR. Moreover, we identified 21 biomarkers associated with respiratory failure, revealing significant alterations in metabolic pathways. These studies demonstrate that b-NMR is a reliable and cost-effective tool for clinical metabolomics, especially for COVID-19 respiratory infection in hospital settings.

Source: Open Respiratory Archives

DOI: 10.1016/j.opresp.2026.100554