A label-free selected reaction monitoring workflow identifies a subset of pregnancy specific glycoproteins as potential predictive markers of early-onset pre-eclampsia.

ABSTRACT

Pre-eclampsia (PE) is a serious complication of pregnancy with potentially life threatening consequences for both mother and baby. Presently there is no test with the required performance to predict which healthy first-time mothers will go on to develop PE. The high specificity, sensitivity, and multiplexed nature of selected reaction monitoring holds great potential as a tool for the verification and validation of putative candidate biomarkersfor disease states. Realization of this potential involves establishing a high throughput, cost effective, reproducible sample preparation workflow. We have developed a semi-automated HPLC-based sample preparation workflow before a label-free selected reaction monitoring approach. This workflow has been applied to the search for novel predictive biomarkers for PE. To discover novel candidate biomarkers for PE, we used isobaric tagging to identify several potential biomarker proteins in plasma obtained at 15 weeks gestation from nulliparous women who later developed PE compared with pregnant women who remained healthy. Such a study generates a number of "candidate" biomarkers that require further testing in larger patient cohorts. As proof-of-principle, two of these proteins were taken forward for verification in a 100 women (58 PE, 42 controls) using label-free SRM. We obtained reproducible protein quantitation across the 100 samples and demonstrated significant changes in protein levels, even with as little as 20% change in protein concentration. The SRM data correlated with a commercial ELISA, suggesting that this is a robust workflow suitable for rapid, affordable, label-free verification of which candidate biomarkers should be taken forward for thorough investigation. A subset of pregnancy-specific glycoproteins (PSGs) had value as novel predictive markers for PE.