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

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 ( http://www.plasmaproteomeprofiling.org) to assess overall sample‐related bias in clinical studies and to prevent costly miss‐assignment of biomarker candidates.

Plasma proteome profiling discovers novel proteins associated with non‐alcoholic fatty liver disease

“…We quantified on average 503 proteins per individual (684 in total, of which 3 by single peptide) (Fig C), with MS signals that spanned an abundance range of six orders of magnitude (Fig C and D). To investigate the quality of the study samples in terms of consistency of collection and handling, we used our recently developed quality marker panels for coagulation and erythrocyte contamination (Geyer et al , ; preprint: Geyer et al , ). No outliers of these marker indices were found based on global protein abundance profiles, indicating that the samples were of high quality and that changes in plasma proteins should be due to disease‐related pathological disturbances (Fig E).…”

“…It requires only one microliter of plasma and features high reproducibility and low variability. So far we have applied this technology to study the effects of sustained weight loss on the human plasma proteome and to rigorously assess the quality of plasma samples (Geyer et al , ; preprint: Geyer et al , ).…”

Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics

“…MS-based proteomics hence has the potential to become an ideal technology to be applied in situations when rapid responses are required. At present, MS-based proteomics workflows are well-established in research laboratories, where they are routinely used for biomarker discovery and profiling (Bruderer et al, 2019;Geyer et al, 2016aGeyer et al, , 2016bGeyer et al, , 2017Geyer et al, , 2019Liu et al, 2015;Niu et al, 2019;Wewer Albrechtsen et al, 2018) . Increasingly, MS-based proteomics is also entering regulated clinical and diagnostic environments (Crutchfield et al, 2016) .…”

Proteomic profiling analysis of postmenopausal osteoporosis and osteopenia identifies potential proteins associated with low bone mineral density

“…During the process of bone remodeling, biochemical products are produced and can be detected in the blood and/or urine, which are considered to be biomarkers. Plasma and serum are rich sources of information regarding an individual's health state, and protein tests inform medical decision making (Geyer et al, 2019;Lin et al, 2018). Biomedical substances that are involved in metabolic activities are tied to an individual's biological or metabolic status; thus, circulating proteins are considered sensitive and specific markers of certain pathological states, including abnormal bone metabolism (Brosseron et al, 2018;Shao et al, 2019).…”