Emerging Affinity-Based Proteomic Technologies for Large-Scale Plasma Profiling in Cardiovascular Disease

Abstract

Plasma biomarkers that reflect molecular states of the cardiovascular system are central for clinical decision making. Routinely used plasma biomarkers include troponins, natriuretic peptides, and lipoprotein particles, yet interrogate only a modest subset of pathways relevant to cardiovascular disease. Systematic profiling of a larger portion of circulating plasma proteins (the plasma proteome) will provide opportunities for unbiased discovery of novel markers to improve diagnostic or predictive accuracy. In addition, proteomic profiling may inform pathophysiological understanding and point to novel therapeutic targets. Obstacles for comprehensive proteomic profiling include the immense size and structural heterogeneity of the proteome, and the broad range of abundance levels, as well. Proteome-wide, untargeted profiling can be performed in tissues and cells with tandem mass spectrometry. However, applications to plasma are limited by the need for complex preanalytical sample preparation stages limiting sample throughput. Multiplexing of targeted methods based on capture and detection of specific proteins are therefore receiving increasing attention in plasma proteomics. Immunoaffinity assays are the workhorse for measuring individual proteins but have been limited for proteomic applications by long development times, cross-reactivity preventing multiplexing, specificity issues, and incomplete sensitivity to detect proteins in the lower range of the abundance spectrum (below picograms per milliliter). Emerging technologies to address these issues include nucleotide-labeled immunoassays and aptamer reagents that can be automated for efficient multiplexing of thousands of proteins at high sample throughput, coupling of affinity capture methods to mass spectrometry for improved specificity, and ultrasensitive detection systems to measure low-abundance proteins. In addition, proteomics can now be integrated with modern genomics tools to comprehensively relate proteomic profiles to genetic variants, which may both influence binding of affinity reagents and serve to validate the target specificity of affinity assays. The application of deep quantitative proteomic profiling to large cohorts has thus become increasingly feasible with emerging affinity methods. The aims of this article are to provide the broad readership of Circulation with a timely overview of emerging methods for affinity proteomics and recent progress in cardiovascular medicine based on such methods.

Keywords: biomarkers; cardiovascular diseases; epidemiology; plasma; proteomics.

Figure 1. Dynamic range of the human plasma proteome and current detection methods

Dynamic ranges for classical plasma proteins (high-medium abundance) and selected clinically relevant proteins. Intervals refer to published 95% reference ranges, or quartiles or ranges where reference intervals were unavailable. Lower ends of reference intervals have not been established for a few proteins (arrowhead). Affinity-based methods essentially capture proteins across the entire abundance spectrum but may be offset by specificity, whereas mass spectrometry (MS) has excellent specificity but is limited to proteins with high and medium abundance. Newer MS methods such as multiple reaction monitoring (MRM), immuno-MRM (iMRM) and isobaric tags (iTRAQ) may detect lower-abundance proteins and with additional separation steps reach as low as affinity methods. Ultrasensitive single molecule detection (SMD) assays are necessary to detect proteins at very low abundance, down to fg/ml. 2DE, 2-dimensional gel electrophoresis. LC-MS, liquid chromatography MS.

Figure 2. Schematic workflow for emerging affinity proteomic tools

Abbreviations: DNA, deoxyribonucleic acid. m/z, mass to charge ratio. qPCR, quantitative polymerase chain reaction.