Prediction of PPAR-alpha ligand-mediated physiological changes using gene expression profiles

J Lipid Res. 2004 Mar;45(3):592-601. doi: 10.1194/jlr.M300239-JLR200.

Abstract

Peroxisome proliferator-activated receptor (PPAR)-alpha controls the transcription of a variety of genes involved in lipid metabolism and is the target receptor for the hypolipidemic drug class of fibrates. In the present study, the molecular and physiological effects of seven different PPAR-activating drugs have been examined in a rodent model of dyslipidemia. The drugs examined were selected to display varying potencies and efficacies toward PPAR-alpha. To help elucidate the link between the gene regulation elicited by PPAR-alpha ligands and the concomitant physiological changes, we have used cDNA microarray analysis to identify smaller gene sets that are predictive of the function of these ligands. A number of genes showed strong correlations to the relative PPAR-alpha efficacy of the drugs. Furthermore, using multivariate analysis, a strong relationship between the drug-induced triglyceride lowering and the transcriptional profiles of the different drugs could be found.

MeSH terms

  • Animals
  • Apolipoproteins C / blood
  • Biomarkers
  • Cell Line
  • Cholesterol, Dietary / pharmacology
  • Disease Models, Animal
  • Drug Evaluation, Preclinical / methods*
  • Gene Expression Profiling*
  • Humans
  • Hyperlipidemias / blood
  • Hyperlipidemias / chemically induced
  • Hyperlipidemias / genetics
  • Ligands
  • Male
  • Molecular Structure
  • Oligonucleotide Array Sequence Analysis
  • Predictive Value of Tests
  • RNA, Messenger / analysis
  • RNA, Messenger / genetics
  • Rats
  • Rats, Sprague-Dawley
  • Receptors, Cytoplasmic and Nuclear / agonists*
  • Receptors, Cytoplasmic and Nuclear / genetics
  • Receptors, Cytoplasmic and Nuclear / metabolism*
  • Transcription Factors / agonists*
  • Transcription Factors / genetics
  • Transcription Factors / metabolism*
  • Triglycerides / blood

Substances

  • Apolipoproteins C
  • Biomarkers
  • Cholesterol, Dietary
  • Ligands
  • RNA, Messenger
  • Receptors, Cytoplasmic and Nuclear
  • Transcription Factors
  • Triglycerides