Discovery of novel serum biomarkers for prenatal Down syndrome screening by integrative data mining.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 19956656.
- Also identified by DOI 10.1371/journal.pone.0008010 and PMC identifier 2777317.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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.
Medical subject headings
- Biomarkers
- Computational Biology
- Data Mining
- Down Syndrome
- Prenatal Diagnosis