Human Blood Lipoprotein Predictions from 1 H NMR Spectra: Protocol, Model Performances, and Cage of Covariance

• Published in: Analytical chemistry (Washington) Vol. 94; no. 2; pp. 628 - 636
• Main Authors: Khakimov, Bekzod, Hoefsloot, Huub C. J., Mobaraki, Nabiollah, Aru, Violetta, Kristensen, Mette, Lind, Mads V., Holm, Lars, Castro-Mejía, Josué L., Nielsen, Dennis S., Jacobs, Doris M., Smilde, Age K., Engelsen, Søren Balling
• Format: Journal Article
• Language: English
• Published: United States 18.01.2022
• Subjects: Humans; Lipoproteins; Lipoproteins, LDL; Magnetic Resonance Spectroscopy - methods; Proton Magnetic Resonance Spectroscopy; Sweden; Sweden
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/acs.analchem.1c01654

Lipoprotein subfractions are biomarkers for the early diagnosis of cardiovascular diseases. The reference method, ultracentrifugation, for measuring lipoproteins is time-consuming, and there is a need to develop a rapid method for cohort screenings. This study presents partial least-squares regression models developed using H nuclear magnetic resonance (NMR) spectra and concentrations of lipoproteins as measured by ultracentrifugation on 316 healthy Danes. This study explores, for the first time, different regions of the H NMR spectrum representing signals of molecules in lipoprotein particles and different lipid species to develop parsimonious, reliable, and optimal prediction models. A total of 65 lipoprotein main and subfractions were predictable with high accuracy, of >0.6, using an optimal spectral region (1.4-0.6 ppm) containing methylene and methyl signals from lipids. The models were subsequently tested on an independent cohort of 290 healthy Swedes with predicted and reference values matching by up to 85-95%. In addition, an open software tool was developed to predict lipoproteins concentrations in human blood from standardized H NMR spectral recordings.