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Cross-platform Clinical Proteomics using the Charité Open Standard for Plasma Proteomics (OSPP)

Technological & Instrument advances in MS

Abstract #4 Posted on7 February 20259 May 2025 9 May 2025 18h33

Abstract

Human plasma is a valuable resource for clinical research due to its minimally invasive collection and rich physiological data. LC-MS-based plasma proteomics holds promise for disease characterization and biomarker discovery, but improvements in accuracy, reproducibility, and cost effectiveness are needed for clinical adoption.
We developed the Charité Open Peptide Standard for Plasma Proteomics (OSPP), a panel of 211 stable-isotope labeled peptides from 131 consistently quantified plasma proteins, designed for high-throughput targeted and untargeted proteomics in large clinical cohorts. Using MRM, MRM-HR, and discovery proteomics across multiple LC-MS platforms, we validated the panel’s performance. The OSPP demonstrated robust disease classification, outcome prediction, and cross-platform consistency in over 10,000 plasma samples. In a COVID-19 cohort, it enabled patient classification, biomarker identification, and cross-platform quantitative alignment.
Costing less than 1€ addition per sample, OSPP was successfully applied to over 15,000 samples, highlighting its scalability and utility in translational medicine. OSPP offers high consistency, cost-effectiveness, and versatility, advancing high-throughput plasma proteomics for clinical research.

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Human plasma is a valuable resource for clinical research due to its minimally invasive collection and rich physiological data. LC-MS-based plasma proteomics holds promise for disease characterization and biomarker discovery, but improvements in accuracy, reproducibility, and cost effectiveness are needed for clinical adoption. 
We developed the Charité Open Peptide Standard for Plasma Proteomics (OSPP), a panel of 211 stable-isotope labeled peptides from 131 consistently quantified plasma proteins, designed for high-throughput targeted and untargeted proteomics in large clinical cohorts. Using MRM, MRM-HR, and discovery proteomics across multiple LC-MS platforms, we validated the panel’s performance. The OSPP demonstrated robust disease classification, outcome prediction, and cross-platform consistency in over 10,000 plasma samples. In a COVID-19 cohort, it enabled patient classification, biomarker identification, and cross-platform quantitative alignment. 
Costing less than 1€ addition per sample, OSPP was successfully applied to over 15,000 samples, highlighting its scalability and utility in translational medicine. OSPP offers high consistency, cost-effectiveness, and versatility, advancing high-throughput plasma proteomics for clinical research.

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