A systematic approach to obtain validated partial least square models for predicting lipoprotein subclasses from serum NMR spectra.
 

A systematic approach to obtain validated partial least square models for predicting lipoprotein subclasses from serum NMR spectra.

http://www.bionmr.com//www.ncbi.nlm....ed-acspubs.jpg Related Articles A systematic approach to obtain validated partial least square models for predicting lipoprotein subclasses from serum NMR spectra.

Anal Chem. 2014 Jan 7;86(1):543-50

Authors: Mihaleva VV, van Schalkwijk DB, de Graaf AA, van Duynhoven J, van Dorsten FA, Vervoort J, Smilde A, Westerhuis JA, Jacobs DM


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 (1)H 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 < Q(2)