title: Integrative data mining to identify novel candidate serum biomarkers for pre-eclampsia screening.
abstract: OBJECTIVE
  Pre-eclampsia (PE) is a serious complication that affects approximately 2% of pregnant women worldwide. At present, there is no sufficiently reliable test for early detection of PE in a screening setting that would allow timely intervention. To help future experimental identification of serum biomarkers for early onset PE, we applied a data mining approach to create a set of candidate biomarkers.
  
  
  METHODS
  We started from the disease etiology, which involves impaired trophoblast invasion into the spiral arteries. On the basis of this, we used a three-stage filtering strategy consisting of selection of tissue-specific genes, textmining for further gene prioritization, and identifying blood-detectable markers.
  
  
  RESULTS
  This approach resulted in 38 candidate biomarkers. These include the best three first-trimester serum biomarkers for PE found to date LGALS13 (placental protein 13, PP13), PAPPA (pregnancy-associated plasma protein-A, PAPP-A), and PGF (placental growth factor, PlGF), as well as five proteins previously identified as biomarker after the first-trimester or disease onset. This substantiates the effectiveness of our approach and provides an important indication that the list will contain several new biomarkers for PE.
  
  
  CONCLUSIONS
  We anticipate this list can serve in prioritization of future experimental studies on serum biomarkers for early onset PE.
authors.affiliation: Laboratory for Health Protection Research, National Institute for Public Health and the Environment, Bilthoven, The Netherlands. Jeroen.Pennings@rivm.nl
authors.forename: Jeroen L A
authors.initials: JL
authors.lastname: Pennings
authors.forename: Sylwia
authors.initials: S
authors.lastname: Kuc
authors.forename: Wendy
authors.initials: W
authors.lastname: Rodenburg
authors.forename: Maria P H
authors.initials: MP
authors.lastname: Koster
authors.forename: Peter C J I
authors.initials: PC
authors.lastname: Schielen
authors.forename: Annemieke
authors.initials: A
authors.lastname: de Vries
mesh_terms: D015415:Biomarkers / Q000097:blood*; D057225:Data Mining; D005260:Female; D006801:Humans; D008403:Mass Screening; D011225:Pre-Eclampsia / Q000097:blood / Q000175:diagnosis* / Q000235:genetics; D011247:Pregnancy
chemical_list: D015415:Biomarkers