title: Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.
abstract: BACKGROUND
  Preeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3-5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify "PE-specific" genes have yielded inconsistent results. We therefore hypothesize that preeclampsia is a multifactorial disease encompassing several pathology subclasses, and that large cohort placental gene expression analysis will reveal these groups.
  
  
  RESULTS
  To address our hypothesis, we utilized known bioinformatic methods to aggregate 7 microarray data sets across multiple platforms in order to generate a large data set of 173 patient samples, including 77 with preeclampsia. Unsupervised clustering of these patient samples revealed three distinct molecular subclasses of PE. This included a "canonical" PE subclass demonstrating elevated expression of known PE markers and genes associated with poor oxygenation and increased secretion, as well as two other subclasses potentially representing a poor maternal response to pregnancy and an immunological presentation of preeclampsia.
  
  
  CONCLUSIONS
  Our analysis sheds new light on the heterogeneity of PE patients, and offers up additional avenues for future investigation. Hopefully, our subclassification of preeclampsia based on molecular diversity will finally lead to the development of robust diagnostics and patient-based treatments for this disorder.
authors: Department of Physiology, University of Toronto, Toronto, Ontario, Canada.
authors: Katherine
authors: K
authors: Leavey
authors: Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada.
authors: Shannon A
authors: SA
authors: Bainbridge
authors: Department of Physiology, University of Toronto, Toronto, Ontario, Canada.
authors: Brian J
authors: BJ
authors: Cox
mesh_terms: D015415:Biomarkers / Q000378:metabolism; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D005260:Female; D006801:Humans; D046228:Microarray Analysis; D011225:Pre-Eclampsia / Q000145:classification* / Q000235:genetics*; D011247:Pregnancy
chemical_list: D015415:Biomarkers