Plasma Proteome Profiling to detect and avoid sample-related biases in biomarker studies.

Philipp E Geyer,Matthias Mann,Sophia Doll,Jakob M Bader,Peter V Treit,Marie‐Luise Buchholtz,Lesca M Holdt,Lili Niu,Eugenia Voytik,Daniel Teupser,Johannes B Müller,Alisa Kleinhempel

doi:10.15252/emmm.201910427

Abstract

Plasma and serum are rich sources of information regarding an individual's health state, and protein tests inform medical decision making. Despite major investments, few new biomarkers have reached the clinic. Mass spectrometry (MS)‐based proteomics now allows highly specific and quantitative readout of the plasma proteome. Here, we employ Plasma Proteome Profiling to define quality marker panels to assess plasma samples and the likelihood that suggested biomarkers are instead artifacts related to sample handling and processing. We acquire deep reference proteomes of erythrocytes, platelets, plasma, and whole blood of 20 individuals (> 6,000 proteins), and compare serum and plasma proteomes. Based on spike‐in experiments, we determine sample quality‐associated proteins, many of which have been reported as biomarker candidates as revealed by a comprehensive literature survey. We provide sample preparation guidelines and an online resource ( www.plasmaproteomeprofiling.org) to assess overall sample‐related bias in clinical studies and to prevent costly miss‐assignment of biomarker candidates.

Highlights

Protein levels determined in blood-based laboratory tests can be useful proxies of diseases
All five blood fractions were separately prepared for each individual by our automated proteomic sample preparation pipeline, followed by liquid chromatography coupled to high-resolution mass spectrometry (LC-Mass spectrometry (MS)/MS)
Protein levels in plasma can readily be affected by cellular contamination or handling-related issues, and in clinical practice, this is partially addressed by simple tests such as those for hemoglobin contamination

Summary

Introduction

Protein levels determined in blood-based laboratory tests can be useful proxies of diseases. These biomarkers assess normal physiological status, pathogenic processes, or a response to an exposure or intervention (FDA-NIH:Biomarker-Working-Group, 2016). Proteins and enzymes constitute the largest proportion of laboratory tests, reflecting the importance of the plasma proteome in clinical diagnostics (Geyer et al, 2017). Typical protein biomarkers such as the enzymes aspartate aminotransferase (ASAT) and alanine aminotransferase (ALAT) for the diagnosis of liver diseases or cardiac troponins indicating myocardial necrosis are used routinely in clinical decision making. There is a critical need to make the biomarker discovery process more efficient

Methods

Results

Conclusion