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

V.V. Mihaleva, D.B. van Schalkwijk, A.A. de Graaf, J.P.M. van Duynhoven, F.A. van Dorsten, J.J.M. Vervoort, A.K. Smilde, J.A. Westerhuis, D.M. Jacobs

Research output: Contribution to journalArticleAcademicpeer-review

30 Citations (Scopus)

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)
Original languageEnglish
Pages (from-to)543-550
JournalAnalytical Chemistry
Volume86
Issue number1
DOIs
Publication statusPublished - 2014

Keywords

  • nuclear-magnetic-resonance
  • low-density lipoprotein
  • plasma-lipoproteins
  • insulin-resistance
  • regression-models
  • spectroscopy
  • quantification
  • chromatography
  • abnormalities
  • chemometrics

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