Integrative data mining to identify novel candidate serum biomarkers for pre-eclampsia screening

Authors

  • Jeroen L. A. Pennings,

    Corresponding author
    • Laboratory for Health Protection Research (GBO), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
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  • Sylwia Kuc,

    1. Laboratory for Infectious Diseases and Perinatal Screening (LIS), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
    2. Department of Obstetrics, Wilhelmina Children's Hospital, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
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  • Wendy Rodenburg,

    1. Laboratory for Health Protection Research (GBO), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
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  • Maria P. H. Koster,

    1. Laboratory for Infectious Diseases and Perinatal Screening (LIS), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
    2. Department of Obstetrics, Wilhelmina Children's Hospital, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
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  • Peter C. J. I. Schielen,

    1. Laboratory for Infectious Diseases and Perinatal Screening (LIS), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
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  • Annemieke de Vries

    1. Laboratory for Health Protection Research (GBO), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
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Jeroen L. A. Pennings, Laboratory for Health Protection Research (GBO), National Institute for Public Health and the Environment (RIVM), P.O. Box 1, NL-3720BA Bilthoven, The Netherlands.

E-mail: Jeroen.Pennings@rivm.nl

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. Copyright © 2011 John Wiley & Sons, Ltd.

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