Blood Test Predicts Risk of Pregnancy Complications

Proteins identified in the blood could be used to predict whether a woman in her first pregnancy is at increased risk of developing pre-eclampsia.

The high specificity, sensitivity, and multiplexed nature of selected reaction monitoring (SRM) has great potential as a tool for verification and validation of putative biomarkers for diseases.

An international team of scientists at the University of Manchester (UK) analyzed early pregnancy plasma samples from a prospective cohort of nulliparous women. The developed a semiautomated high-performance liquid chromatography (HPLC)-based preparation workflow prior to a label free SRM approach. They used isobaric tagging to identify several potential biomarkers for pre-eclampsia (PE). Two of the proteins found were verified in 58 PE women and 42 controls.

SRM is a method in which an ion of a particular mass is selected in the first stage of a tandem mass spectrometer and an ion product of a fragmentation reaction of the precursor ion is selected in the second mass spectrometer stage for detection. The SRM data was correlated with a commercial enzyme linked immunosorbent assay (RayBiotech; Norcross, GA, USA). Two proteins, which have not previously been linked to pre-eclampsia risk, were shown to be at least as good a predictor of disease risk as the current best marker, placental growth factor. These two new potential markers are called pregnancy specific glycoprotein 5 and 9 (PSG5 and PSG9).

Richard D. Unwin , PhD, from the Center for Advanced Discovery and Experimental Therapeutics at the Manchester Biomedical Research Center and a lead author of the study, said, “What we have also done here is to develop a suite of laboratory methods which can identify and begin to validate real disease markers from patient blood samples, even before symptoms have developed, and we are hoping to continue applying these methods to other major diseases, such as diabetes, Alzheimer's disease or stroke." The study was published on July 20, 2013, in the journal Molecular and Cellular Proteomics.

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