Challenges in translating plasma proteomics from bench to bedside: update from the NHLBI Clinical Proteomics Programs

Robert E Gerszten, Frank Accurso, Gordon R Bernard, Richard M Caprioli, Eric W Klee, George G Klee, Iftikhar Kullo, Theresa A Laguna, Frederick P Roth, Marc Sabatine, Pothur Srinivas, Thomas J Wang, Lorraine B Ware, Robert E Gerszten, Frank Accurso, Gordon R Bernard, Richard M Caprioli, Eric W Klee, George G Klee, Iftikhar Kullo, Theresa A Laguna, Frederick P Roth, Marc Sabatine, Pothur Srinivas, Thomas J Wang, Lorraine B Ware

Abstract

The emerging scientific field of proteomics encompasses the identification, characterization, and quantification of the protein content or proteome of whole cells, tissues, or body fluids. The potential for proteomic technologies to identify and quantify novel proteins in the plasma that can function as biomarkers of the presence or severity of clinical disease states holds great promise for clinical use. However, there are many challenges in translating plasma proteomics from bench to bedside, and relatively few plasma biomarkers have successfully transitioned from proteomic discovery to routine clinical use. Key barriers to this translation include the need for "orthogonal" biomarkers (i.e., uncorrelated with existing markers), the complexity of the proteome in biological samples, the presence of high abundance proteins such as albumin in biological samples that hinder detection of low abundance proteins, false positive associations that occur with analysis of high dimensional datasets, and the limited understanding of the effects of growth, development, and age on the normal plasma proteome. Strategies to overcome these challenges are discussed.

Figures

Fig. 1.
Fig. 1.
Receiver-operating-characteristic curves for death during 5-yr follow-up. For each end point, curves are based on models of the prediction of risk with the use of conventional risk factors with or without biomarkers (multimarker score). Biomarkers for death were B-type natriuretic peptide, C-reactive protein, the urinary albumin-to-creatinine ratio, homocysteine, and renin. [From Wang et al. (46).]
Fig. 2.
Fig. 2.
Flow diagram illustrating mass spectrometry measurement of biomarkers utilizing prior enzyme digestion and immuno-affinity extraction of peptide fragments.
Fig. 3.
Fig. 3.
Matrix-assisted laser desorption ionization time-of-flight mass spectroscopy (MALDI-TOF MS) of reverse phase purified plasma samples. Light blue line shows the spectrum from an archival EDTA plasma sample from a patient with acute lung injury (ALI/ARDS) enrolled in a clinical trial. The other spectra (black, red, green, dark blue) are from a single EDTA plasma sample drawn from a healthy volunteer that was spun and frozen immediately, thawed, and either reverse phase purified immediately (black line) or allowed to remain on ice for 7–8 h before reverse phase purification and spotting for MALDI-TOF MS. Note that control samples that were kept on ice for 7–8 h developed new peaks in the low mass-to-charge range (m/z) that were not visualized in the freshly thawed control plasma sample. The archival acute lung injury plasma sample also had numerous peaks in the low m/z range.

Source: PubMed

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