A Label-free Selected Reaction Monitoring Workflow Identifies a Subset of Pregnancy Specific Glycoproteins as Potential Predictive Markers of Early-onset Pre-eclampsia

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.The identification of clinically relevant plasma biomarkers with diagnostic and/or predictive value continues to challenge the proteomics field. Whereas once the biomarker pipeline was described as a two part discovery and validation process, there is increasing consensus that an intermediate step is required in which the proteins identified in the discovery phase are technically verified in 50 to 200 samples. This verification step identifies false positives from the discovery phase and allows prioritization of proteins to be taken into large-scale clinical validation studies (1). Although commercial ELISA kits may be used in this phase, these are unavailable for many proteins, are expensive, and may lack specificity. In addition, sample requirements may be too high to perform ELISA on all candidates, especially if many proteins are identified as potential markers by low powered, high penetration discovery workflows.Selected reaction monitoring (SRM)¹ mass spectrometry has great potential as an alternative verification method (2–6) as it can be multiplexed, customized, and is highly specific. This potential has not been exploited to date, largely because of technical issues developing a low-cost, reproducible workflow encompassing plasma and serum preparation and LC/MS analysis with the capability to measure protein levels reproducible in hundreds of samples. With traditional stable isotope dilution SRM (SID-SRM), the high cost of accurately quantified, purified stable isotope encoded peptides or proteins may be prohibitive for the verification of multiple peptides from many proteins. Label-free relatively quantitative methods are increasingly popular in discovery proteomics but to a much lesser extent in targeted SRM studies (7, 8).For any SRM method, sample preparation workflows must balance the extent of enrichment and fractionation to enable quantification of lower abundance proteins, against increased technical variability (which is influenced by the number of sample handling steps) and reduced multiplexed potential as a consequence of fractionating peptides from the protein of interest into several distinct fractions. It is also essential that the true technical variation in the workflow is quantitatively evaluated from freezer to MS analysis, rather than just the variation within the LC-SRM part of the experiment. As a paradigm for a label-free SRM assay, we developed our workflow and applied it to the verification of candidate biomarkers that indicate the risk of pre-eclampsia (PE).PE affects 2–8% of pregnancies, and is characterized by hypertension and proteinuria, which may progress to severe maternal complications or death (9). Because delivery of the infant is the only effective intervention, a third of babies are born premature and fetal or newborn mortality is increased three- to 10-fold (10). Its complex etiology involves abnormal placentation, an altered immune response and a sensitized maternal vascular endothelium (11). Prediction of the condition in early pregnancy would allow prevention strategies, such as low dose aspirin, to be targeted to high risk women. In first-time pregnant women, a group particularly at risk, biomarkers continue to fall short of a test that would be useful or cost effective in clinical practice (12–14). Better-performing novel biomarkers are required.The aim of this study was to identify candidate predictive biomarkers for PE and then develop a verification assay using mass spectrometry to determine whether these should be taken forward into more extensive and expensive validation studies. Initial discovery experiments were employed using a pooled sample iTRAQ approach using two different MS platforms to increase plasma proteome coverage. Among the set of proteins discovered, we then developed a label-free SRM assay for relative quantification of CXCL7 (Platelet basic protein; PBP) and members of the Pregnancy specific glycoprotein (PSG) family in a 100-sample set from the international SCreeningfOr Pregnancy Endpoints (SCOPE) study (www.scopestudy.net). Our workflow allowed the specificity and linearity of response for each peptide to be determined, along with true technical variability. Although absolute concentration and LOD/LOQ cannot be calculated using this approach, we aimed to test the hypothesis that a label-free SRM approach could provide a rapid, robust, and efficient screen of candidate plasma biomarkers.