Pre-analytical drivers of bias in bead-enriched plasma proteomics

Bead-based enrichment is a promising strategy to improve depth in plasma proteomics by overcoming the dynamic range barrier. However, its robustness against pre-analytical variation has not been sufficiently characterized. Here, we systematically evaluate five plasma proteomics workflows, including three bead-based methods, a neat workflow, and a precipitation protocol using spike-ins of low-abundance proteins and defined cellular contaminants. We find that bead-based approaches enhance detection of low-abundance proteins but can be highly susceptible to systematic bias from platelet and PBMC contamination. This can inflate results by thousands of proteins, potentially explaining some of the high literature-reported numbers. A perchloric acid-based workflow shows resistance to erythrocyte and platelet-derived contamination. We investigate how centrifugation conditions, anticoagulant choice, and buffer-bead combinations modulate contamination profiles and demonstrate that bias can be mitigated by optimized sample handling. Altogether, we identify more than 13,000 different protein groups, including cellular components from the circulating proteome. Our results provide a quantitative framework for assessing workflow performance under variable sample quality and offer guidance for both biomarker discovery and quality control in clinical proteomics studies.