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

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.

[1]  Matthias Mann,et al.  Plasma Proteome Profiling Reveals Dynamics of Inflammatory and Lipid Homeostasis Markers after Roux-En-Y Gastric Bypass Surgery. , 2018, Cell systems.

[2]  W. Rathmann,et al.  A Systemic Inflammatory Signature Reflecting Cross Talk Between Innate and Adaptive Immunity Is Associated With Incident Polyneuropathy: KORA F4/FF4 Study , 2018, Diabetes.

[3]  Stephen Burgess,et al.  Genomic atlas of the human plasma proteome , 2018, Nature.

[4]  Matthias Mann,et al.  BoxCar acquisition method enables single-shot proteomics at a depth of 10,000 proteins in 100 minutes , 2018, Nature Methods.

[5]  Qibin Zhang,et al.  Temporal expression profiling of plasma proteins reveals oxidative stress in early stages of Type 1 Diabetes progression. , 2018, Journal of Proteomics.

[6]  R. Aebersold,et al.  The Human Plasma Proteome Draft of 2017: Building on the Human Plasma PeptideAtlas from Mass Spectrometry and Complementary Assays. , 2017, Journal of proteome research.

[7]  Matthias Mann,et al.  Revisiting biomarker discovery by plasma proteomics , 2017, Molecular systems biology.

[8]  Matthias Mann,et al.  Loss-less Nano-fractionator for High Sensitivity, High Coverage Proteomics * , 2017, Molecular & Cellular Proteomics.

[9]  Matthias Mann,et al.  Proteomics reveals the effects of sustained weight loss on the human plasma proteome , 2016, Molecular systems biology.

[10]  Ruedi Aebersold,et al.  Mass-spectrometric exploration of proteome structure and function , 2016, Nature.

[11]  Marco Y. Hein,et al.  The Perseus computational platform for comprehensive analysis of (prote)omics data , 2016, Nature Methods.

[12]  Mark R Segal,et al.  Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients With Stable Coronary Heart Disease. , 2016, JAMA.

[13]  Matthias Mann,et al.  Plasma Proteome Profiling to Assess Human Health and Disease. , 2016, Cell systems.

[14]  Jeffrey R. Whiteaker,et al.  Recommendations for the Generation, Quantification, Storage, and Handling of Peptides Used for Mass Spectrometry-Based Assays. , 2016, Clinical chemistry.

[15]  S. Fisher,et al.  Evaluating the effects of preanalytical variables on the stability of the human plasma proteome. , 2015, Analytical biochemistry.

[16]  Albert J. R. Heck,et al.  From the human genome to the human proteome. , 2014, Angewandte Chemie.

[17]  Marco Y. Hein,et al.  Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ * , 2014, Molecular & Cellular Proteomics.

[18]  J. Stenvang,et al.  Homogenous 96-Plex PEA Immunoassay Exhibiting High Sensitivity, Specificity, and Excellent Scalability , 2014, PloS one.

[19]  M. Mann,et al.  Minimal, encapsulated proteomic-sample processing applied to copy-number estimation in eukaryotic cells , 2014, Nature Methods.

[20]  Mathias Uhlen,et al.  Profiling post-centrifugation delay of serum and plasma with antibody bead arrays. , 2013, Journal of proteomics.

[21]  Joshua LaBaer,et al.  Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies. , 2013, Journal of proteome research.

[22]  David Wild,et al.  The immunoassay handbook : theory and applications of ligand binding, ELISA and related techniques , 2013 .

[23]  N. Anderson,et al.  The riddle of protein diagnostics: future bleak or bright? , 2013, Clinical chemistry.

[24]  Matthias Mann,et al.  SprayQc: a real-time LC-MS/MS quality monitoring system to maximize uptime using off the shelf components. , 2012, Journal of proteome research.

[25]  M. Mann,et al.  System-wide Perturbation Analysis with Nearly Complete Coverage of the Yeast Proteome by Single-shot Ultra HPLC Runs on a Bench Top Orbitrap* , 2011, Molecular & Cellular Proteomics.

[26]  M. Mann,et al.  Andromeda: a peptide search engine integrated into the MaxQuant environment. , 2011, Journal of proteome research.

[27]  Ruedi Aebersold,et al.  On the development of plasma protein biomarkers. , 2011, Journal of proteome research.

[28]  M. Girolami,et al.  Recommendations for Biomarker Identification and Qualification in Clinical Proteomics , 2010, Science Translational Medicine.

[29]  Tracy R. Keeney,et al.  Aptamer-based multiplexed proteomic technology for biomarker discovery , 2010, Nature Precedings.

[30]  M. Mann,et al.  MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification , 2008, Nature Biotechnology.

[31]  Nils Brünner,et al.  Banking of Biological Fluids for Studies of Disease-associated Protein Biomarkers* , 2008, Molecular & Cellular Proteomics.

[32]  Zhiyuan Luo,et al.  Preanalytic influence of sample handling on SELDI-TOF serum protein profiles. , 2007, Clinical chemistry.

[33]  Graham B. I. Scott,et al.  HUPO Plasma Proteome Project specimen collection and handling: Towards the standardization of parameters for plasma proteome samples , 2005, Proteomics.

[34]  Eugene A. Kapp,et al.  Overview of the HUPO Plasma Proteome Project: Results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly‐available database , 2005, Proteomics.

[35]  R. Aebersold,et al.  Mass spectrometry-based proteomics , 2003, Nature.

[36]  the original work is properly cited. , 2022 .