Multicenter evaluation of label-free quantification in human plasma on a high dynamic range benchmark set

Area of Science:

• Proteomics
• Biomarker Discovery
• Clinical Mass Spectrometry

Background:

• Human plasma is a vital source for diagnostic and stratification biomarkers.
• High protein dynamic range in plasma challenges Liquid Chromatography-Mass Spectrometry (LC-MS) analysis.
• Standardized benchmarking is needed for reliable plasma proteome quantification.

Purpose of the Study:

• To evaluate and benchmark quantitative performance of LC-MS for neat plasma analysis.
• To compare Data-Dependent Acquisition (DDA) and Data-Independent Acquisition (DIA) methods.
• To establish a reproducible workflow for clinical plasma proteome analysis.

Main Methods:

• Development of a multispecies tryptic digest sample set (PYE) with controlled spike-ins.
• Analysis across twelve sites using state-of-the-art LC-MS platforms.
• Comparison of DDA and DIA acquisition modes on 1116 individual runs.

Main Results:

• DIA methods significantly outperformed DDA in protein identifications, data completeness, accuracy, and precision.
• DIA demonstrated excellent technical reproducibility with protein-level CVs from 3.3% to 9.8%.
• Accurate and precise quantitative measurements were feasible across multiple sites in complex plasma matrix.

Conclusions:

• DIA is the preferred method for robust plasma proteome analysis and biomarker discovery.
• The PYE sample set and presented strategy enhance LC-MS accuracy and reproducibility.
• This work provides a valuable resource for optimizing clinical proteomic workflows.