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We have developed a novel plasma protein analysis platform with optimized sample preparation, chromatography, and MS analysis protocols. The workflow, which utilizes chemical isobaric mass tag labeling for relative quantification of plasma proteins, achieves far greater depth of proteome detection and quantification while simultaneously having increased sample throughput than prior methods. We applied the new workflow to a time series of plasma samples from patients undergoing a therapeutic, “planned” myocardial infarction for hypertrophic cardiomyopathy, a unique human model in which each person serves as their own biologic control. Over 5300 proteins were confidently identified in our experiments with an average of 4600 proteins identified per sample (with two or more distinct peptides identified per protein) using iTRAQ four-plex labeling. Nearly 3400 proteins were quantified in common across all 16 patient samples. Compared with a previously published label-free approach, the new method quantified almost fivefold more proteins/sample and provided a six- to nine-fold increase in sample analysis throughput. Moreover, this study provides the largest high-confidence plasma proteome dataset available to date. The reliability of relative quantification was also greatly improved relative to the label-free approach, with measured iTRAQ ratios and temporal trends correlating well with results from a 23-plex immunoMRM (iMRM) assay containing a subset of the candidate proteins applied to the same patient samples. The functional importance of improved detection and quantification was reflected in a markedly expanded list of significantly regulated proteins that provided many new candidate biomarker proteins. Preliminary evaluation of plasma sample labeling with TMT six-plex and ten-plex reagents suggests that even further increases in multiplexing of plasma analysis are practically achievable without significant losses in depth of detection relative to iTRAQ four-plex. These results obtained with our novel platform provide clear demonstration of the value of using isobaric mass tag reagents in plasma-based biomarker discovery experiments. We have developed a novel plasma protein analysis platform with optimized sample preparation, chromatography, and MS analysis protocols. The workflow, which utilizes chemical isobaric mass tag labeling for relative quantification of plasma proteins, achieves far greater depth of proteome detection and quantification while simultaneously having increased sample throughput than prior methods. We applied the new workflow to a time series of plasma samples from patients undergoing a therapeutic, “planned” myocardial infarction for hypertrophic cardiomyopathy, a unique human model in which each person serves as their own biologic control. Over 5300 proteins were confidently identified in our experiments with an average of 4600 proteins identified per sample (with two or more distinct peptides identified per protein) using iTRAQ four-plex labeling. Nearly 3400 proteins were quantified in common across all 16 patient samples. Compared with a previously published label-free approach, the new method quantified almost fivefold more proteins/sample and provided a six- to nine-fold increase in sample analysis throughput. Moreover, this study provides the largest high-confidence plasma proteome dataset available to date. The reliability of relative quantification was also greatly improved relative to the label-free approach, with measured iTRAQ ratios and temporal trends correlating well with results from a 23-plex immunoMRM (iMRM) assay containing a subset of the candidate proteins applied to the same patient samples. The functional importance of improved detection and quantification was reflected in a markedly expanded list of significantly regulated proteins that provided many new candidate biomarker proteins. Preliminary evaluation of plasma sample labeling with TMT six-plex and ten-plex reagents suggests that even further increases in multiplexing of plasma analysis are practically achievable without significant losses in depth of detection relative to iTRAQ four-plex. These results obtained with our novel platform provide clear demonstration of the value of using isobaric mass tag reagents in plasma-based biomarker discovery experiments. The goal of biomarker discovery studies in plasma or other biological matrices is to identify proteins that are truly differential in abundance between a population of cases and suitable controls, or before and after a relevant perturbation. The approach has generally been to use label-free methods to analyze individual samples from each class or condition, often few in number, and to employ a differential cutoff to discriminate real differences from technical artifacts or biological noise. These cutoffs are frequently as the of measured peptides and the of samples in the the and of plasma with the that are to of plasma samples for biomarker discovery are often before MS to depth of detection in plasma of proteins and the protein or using that from the the mass chromatography, or the in plasma discovery experiments has been to increase the of confidently identified and the relative of abundance proteins, of methods for analysis of plasma with as a of methods for analysis of plasma approach with for of with for proteome of human of individual samples depth of the of increased and throughput. in increases the technical and the that measured between samples. an of the and of a have previously plasma-based biomarker discovery for myocardial using a label-free workflow of of the plasma proteins and of peptides prior to analysis that the discovery and of plasma protein candidate for of to proteins per sample time was and each using a markedly the of samples that and the to the 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We have human experiments in which each person serves as their own biologic across a series of time our to for differences from We that differences between biologic and also biomarker that from our discovery across of controls, using more throughput The mass and the for from using the this dataset from We of and of for of iTRAQ and for with mass for and relative mass myocardial discovery mass protein and and a protein
Keshishian et al. (Fri,) studied this question.