In the face of several challenges, mass spectrometry (MS)-based proteomics is now starting to live up to its initial promise as a generic technology for the discovery and quantification of proteins that reflect an individual´s health or disease state. We dramatically streamlined the labor-intensive proteomic workflow by novel sample preparation strategies and robotic automation, resulting in a rapid, robust and highly reproducible pipeline called ‘Plasma Proteome Profiling’. The pipeline reduces the analysis time to less than 3 hours and standard operating procedures combined with robotics strongly improve the robustness. Such an analysis covers at least 50 known biomarkers that were approved by the U.S. Food and Drug Administration (FDA), while simultaneously quantifying hundreds of less described proteins with the potential to become biomarkers. Moreover, the implementation of novel chromatography concepts such as pre-formed gradients in the Evosep liquid chromatography system, will further move plasma proteomics to the fast lane and will ultimately enable clinical applications.
The development of Plasma Proteome Profiling and its optimization for high-throughput screening allowed us to develop new concepts within the field of biomarker discovery. After we repeatedly observed proteins that tended to emerge as groups of statistically significant outliers independent of a particular study, we developed contamination marker panels for the quality assessment of individual samples and entire studies. We successfully applied these contamination marker panels to several studies, provided sample preparation guidelines and an online resource (www.plasmaproteomeprofiling.org) to assess sample-related bias. Moreover, we calculated in a longitudinal dataset that the majority of all protein levels (69%) are individual-specific. A consequence for biomarker discovery studies is that longitudinal studies are preferable. However, if not available, large-scale cohorts should be considered, in a `rectangular strategy` of biomarker discovery. So far, we have applied our pipeline to follow life-style intervention in the case of a weight loss study, the effect of surgery and extreme weight loss on the human plasma proteome, discovered new biomarkers for liver diseases and also adapted it to define Alzheimer’s biomarkers in CSF.