Article pubs.acs.org/ac
A Systematic Approach to Obtain Validated Partial Least Square Models for Predicting Lipoprotein Subclasses from Serum NMR Spectra Velitchka V. Mihaleva,*,†,‡ Daniel̈ B. van Schalkwijk,§ Albert A. de Graaf,§ John van Duynhoven,‡,∥,⊥ Ferdinand A. van Dorsten,‡,∥ Jacques Vervoort,†,‡ Age Smilde,‡,@ Johan A. Westerhuis,‡,@ and Doris M. Jacobs‡,∥ †
Laboratory of Biochemistry, Wageningen University, Dreijenlaan 3, 6703 HA Wageningen, The Netherlands Netherlands Metabolomics Centre, Einsteinweg 55, 2333 CC Leiden, The Netherlands § TNO, Microbiology and Systems Biology, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands ∥ Unilever R&D, Olivier van Noortlaan 120, 3133 AT Vlaardingen, The Netherlands ⊥ Laboratory of Biophysics, Wageningen University, Dreijenlaan 3, 6703 HA Wageningen, The Netherlands @ Swammerdam Institute for Life Sciences, Universiteit van Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands ‡
S Supporting Information *
ABSTRACT: A systematic approach is described for building validated PLS models that predict cholesterol and triglyceride concentrations in lipoprotein subclasses in fasting serum from a normolipidemic, healthy population. The PLS models were built on diffusion-edited 1H NMR spectra and calibrated on HPLC-derived lipoprotein subclasses. The PLS models were validated using an independent test set. In addition to total VLDL, LDL, and HDL lipoproteins, statistically significant PLS models were obtained for 13 subclasses, including 5 VLDLs (particle size 64−31.3 nm), 4 LDLs (particle size 28.6−20.7 nm) and 4 HDLs (particle size 13.5−9.8 nm). The best models were obtained for triglycerides in VLDL (0.82 < Q2
