Development and Validation of Apolipoprotein AI-Associated Lipoprotein Proteome Panel for the Prediction of Cholesterol Efflux Capacity and Coronary Artery Disease

Clin Chem. 2019 Feb;65(2):282-290. doi: 10.1373/clinchem.2018.291922. Epub 2018 Nov 21.


Background: Cholesterol efflux capacity (CEC) is a measure of HDL function that, in cell-based studies, has demonstrated an inverse association with cardiovascular disease. The cell-based measure of CEC is complex and low-throughput. We hypothesized that assessment of the lipoprotein proteome would allow for precise, high-throughput CEC prediction.

Methods: After isolating lipoprotein particles from serum, we used LC-MS/MS to quantify 21 lipoprotein-associated proteins. A bioinformatic pipeline was used to identify proteins with univariate correlation to cell-based CEC measurements and generate a multivariate algorithm for CEC prediction (pCE). Using logistic regression, protein coefficients in the pCE model were reweighted to yield a new algorithm predicting coronary artery disease (pCAD).

Results: Discovery using targeted LC-MS/MS analysis of 105 training and test samples yielded a pCE model comprising 5 proteins (Spearman r = 0.86). Evaluation of pCE in a case-control study of 231 specimens from healthy individuals and patients with coronary artery disease revealed lower pCE in cases (P = 0.03). Derived within this same study, the pCAD model significantly improved classification (P < 0.0001). Following analytical validation of the multiplexed proteomic method, we conducted a case-control study of myocardial infarction in 137 postmenopausal women that confirmed significant separation of specimen cohorts in both the pCE (P = 0.015) and pCAD (P = 0.001) models.

Conclusions: Development of a proteomic pCE provides a reproducible high-throughput alternative to traditional cell-based CEC assays. The pCAD model improves stratification of case and control cohorts and, with further studies to establish clinical validity, presents a new opportunity for the assessment of cardiovascular health.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Apolipoprotein A-I / blood*
  • Area Under Curve
  • Case-Control Studies
  • Cholesterol / metabolism*
  • Chromatography, High Pressure Liquid
  • Coronary Artery Disease / blood
  • Coronary Artery Disease / pathology*
  • Female
  • Humans
  • Limit of Detection
  • Lipoproteins / blood*
  • Male
  • Middle Aged
  • Myocardial Infarction / blood
  • Myocardial Infarction / pathology
  • Proteome / analysis*
  • ROC Curve
  • Tandem Mass Spectrometry / methods*
  • Validation Studies as Topic


  • Apolipoprotein A-I
  • Lipoproteins
  • Proteome
  • Cholesterol