Comparison of Common Plasma Proteomics Workflows Reveals Distinct Preanalytical Biases by Sample Preparation and Nanoparticle Enrichment

Human plasma proteomics is critical for biomedical research but challenged by an extraordinary dynamic range. We evaluated six mass spectrometry workflows, including bead-based enrichment (Proteograph XT, P2, Mag-Net), depletion of the 14 most abundant proteins, and neat plasma analysis. Enrichment methods achieved superior proteome coverage, identifying up to 4600 proteins, but exhibited acute susceptibility to preanalytical bias from cellular contaminants and vesicles in plasma. Increased centrifugation stringency before proteomics analysis drastically decreased protein identifications. Crucially, the abundance of the vast majority of secreted proteins was not significantly affected by centrifugation for all tested workflows, suggesting that their quantification is little influenced by contaminating cells or vesicles, whereas depleted proteins are enriched for cellular components like cytoskeleton organization and platelet activation. Our results underscore that nanoparticle-based methods allow robust and deep measurement of the secreted plasma proteome, providing additional insights by reporting the contributions of proteins of cellular origin when applying the common practice of 2000 × g centrifugation prior to analysis.