Discovery of novel serum biomarkers for prenatal Down syndrome screening by integrative data mining.

Abstract

BACKGROUND: To facilitate the experimental search for novel maternal serum biomarkers in prenatal Down Syndrome screening, we aimed to create a set of candidate biomarkers using a data mining approach. METHODOLOGY/PRINCIPAL FINDINGS: Because current screening markers are derived from either fetal liver or placental trophoblasts, we reasoned that new biomarkers can primarily be found to be derived from these two tissues. By applying a three-stage filtering strategy on publicly available data from different sources, we identified 49 potential blood-detectable protein biomarkers. Our set contains three biomarkers that are currently widely used in either first- or second-trimester screening (AFP, PAPP-A and fbeta-hCG), as well as ten other proteins that are or have been examined as prenatal serum markers. This supports the effectiveness of our strategy and indicates the set contains other markers potentially applicable for screening. CONCLUSIONS/SIGNIFICANCE: We anticipate the set will help support further experimental studies for the identification of new Down Syndrome screening markers in maternal blood.