A Computationally Lightweight Algorithm for Deriving Reliable Metabolite Panel Measurements from 1D 1H NMR

Small Molecule Enhancement SpectroscopY (SMol-ESY) was employed to develop a unique and fully automated computational solution for the assignment and integration of H-1 nuclear magnetic resonance (NMR) signals from metabolites in challenging matrices containing macromolecules (herein blood products). Sensitive and reliable quantitation is provided by instant signal deconvolution and straightforward integration bolstered by spectral resolution enhancement and macromolecular signal suppression. The approach is highly efficient, requiring only standard one-dimensional H-1 NMR spectra and avoiding the need for sample preprocessing, complex deconvolution, and spectral baseline fitting. The performance of the algorithm, developed using >4000 NMR serum and plasma spectra, was evaluated using an additional >8800 spectra, yielding an assignment accuracy greater than 99.5% for all 22 metabolites targeted. Further validation of its quantitation capabilities illustrated a reliable performance among challenging phenotypes. The simplicity and complete automation of the approach support the application of NMR-based metabolite panel measurements in clinical and population screening applications.

Automated summary

The SMol-ESY technology offers a unique and fully automated computational solution for the assignment and integration of H-1 nuclear magnetic resonance signals from metabolites in challenging matrices containing macromolecules. The approach provides sensitive and reliable quantitation through instant signal deconvolution and straightforward integration, with spectral resolution enhancement and macromolecular signal suppression. The algorithm's performance was evaluated using a large number of NMR serum and plasma spectra, demonstrating high assignment accuracy and reliable quantitation capabilities for targeted metabolites.