Evaluation of residual protein on unprocessed and decontaminated dental extraction forceps

Research into protein contamination of surgical instruments has received increasing attention and has focused on a quantitative analysis, without subsequent identification of these proteins. This study aimed to validate methods for the isolation and identification of instrument protein contamination using extraction forceps as a model. The working ends of used, unclean and decontaminated forceps were boiled in 1% (v/v) SDS and samples precipitated using StrataClean? resin and Amicon? filtration. Proteins were visualised using SDS-PAGE and identified by mass spectrometry and Western blot. A total of 17 proteins were identified from used, unclean forceps, including blood and bacterial proteins and 2 protein bands from decontaminated forceps samples which could not be accurately identified. The methods described, when used in conjunction with quantitative and surface analysis of instruments, can aid development of cleaning processes by identifying contaminants on used devices that have been removed following cleaning.     

Protein precipitation of diluted samples in SDS‐containing buffer with acetone leads to higher protein recovery and reproducibility in comparison with TCA/acetone approach

Proteomic approaches are extremely valuable in many fields of research, where mass spectrometry methods have gained an increasing interest, especially because of the ability to perform quantitative analysis. Nonetheless, sample preparation prior to mass spectrometry analysis is of the utmost importance. In this work, two protein precipitation approaches, widely used for cleaning and concentrating protein samples, were tested and compared in very diluted samples solubilized in a strong buffer (containing SDS). The amount of protein recovered after acetone and TCA/acetone precipitation was assessed, as well as the protein identification and relative quantification by SWATH‐MS yields were compared with the results from the same sample without precipitation. From this study, it was possible to conclude that in the case of diluted samples in denaturing buffers, the use of cold acetone as precipitation protocol is more favourable than the use of TCA/acetone in terms of reproducibility in protein recovery and number of identified and quantified proteins. Furthermore, the reproducibility in relative quantification of the proteins is even higher in samples precipitated with acetone compared with the original sample.     

基于头发蛋白质组学区分个人特质的方法学探究

目的 头发是一类重要的皮肤附属物,主要由角蛋白和角蛋白相关蛋白等组成。不同种族及性别样本的头发蛋白质组成和占比存在差异,且目前缺乏高效率提取头发蛋白的方法。本文探究基于定量头发蛋白质组学方法,旨在探索该方法区分不同个体的可能性。方法 以3例头发样本,对样品处理方法和裂解缓冲液进行探究,发展一种名为PLEE (PTM lab for protein extraction from hair with high efficiency)的稳定、高效的头发蛋白质提取方法,对7例人发样本,以PLEE法进行提取,结合胶内消化方法进行蛋白质组学实验,产出蛋白质组学数据,分析个体间的头发蛋白质组成及占比。结果 共鉴定274种蛋白质,共有的蛋白质107种,非共有蛋白质种类在57～119,部分样本存在独特鉴定蛋白。使用共鉴定107种蛋白质进行定量蛋白质组分析,通过聚类和主成分分析,可将各样本进行区分,且技术重复样本可聚在一起,表明流程的稳定性。另外,筛选出10个关键蛋白（KRT33A、KRTAP9-6、KRT83、KRTAP7-1、KRT32、BLMH、KRT38、KRTAP11-1、NPAS1、KRTA...     

Doped diamond-like carbon coatings for surgical instruments reduce protein and prion-amyloid biofouling and improve subsequent cleaning

Doped diamond-like carbon (DLC) coatings offer potential antifouling surfaces against microbial and protein attachment. In particular, stainless steel surgical instruments are subject to tissue protein and resilient prion protein attachment, making decontamination methods used in sterile service departments ineffective, potentially increasing the risk of iatrogenic Creutzfeldt-Jakob disease during surgical procedures. This study examined the adsorption of proteins and prion-associated amyloid to doped DLC surfaces and the efficacy of commercial cleaning chemistries applied to these spiked surfaces, compared to titanium nitride coating and stainless steel. Surfaces inoculated with ME7-infected brain homogenate were visualised using SYPRO Ruby/Thioflavin T staining and modified epi-fluorescence microscopy before and after cleaning. Reduced protein and prion amyloid contamination was observed on the modified surfaces and subsequent decontamination efficacy improved. This highlights the potential for a new generation of coatings for surgical instruments to reduce the risk of iatrogenic CJD infection.     

Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells

Proteomics strategies based on nanoflow (nano-) LC-MS/MS allow the identification of hundreds to thousands of proteins in complex mixtures. When combined with protein isotopic labeling, quantitative comparison of the proteome from different samples can be achieved using these approaches. However, bioinformatics analysis of the data remains a bottleneck in large scale quantitative proteomics studies. Here we present a new software named Mascot File Parsing and Quantification (MFPaQ) that easily processes the results of the Mascot search engine and performs protein quantification in the case of isotopic labeling experiments using either the ICAT or SILAC (stable isotope labeling with amino acids in cell culture) method. This new tool provides a convenient interface to retrieve Mascot protein lists; sort them according to Mascot scoring or to user-defined criteria based on the number, the score, and the rank of identified peptides; and to validate the results. Moreover the software extracts quantitative data from raw files obtained by nano-LC-MS/MS, calculates peptide ratios, and generates a non-redundant list of proteins identified in a multisearch experiment with their calculated averaged and normalized ratio. Here we apply this software to the proteomics analysis of membrane proteins from primary human endothelial cells (ECs), a cell type involved in many physiological and pathological processes including chronic inflammatory diseases such as rheumatoid arthritis. We analyzed the EC membrane proteome and set up methods for quantitative analysis of this proteome by ICAT labeling. EC microsomal proteins were fractionated and analyzed by nano-LC-MS/MS, and database searches were performed with Mascot. Data validation and clustering of proteins were performed with MFPaQ, which allowed identification of more than 600 unique proteins. The software was also successfully used in a quantitative differential proteomics analysis of the EC membrane proteome after stimulation with a combination of proinflammatory mediators (tumor necrosis factor-alpha, interferon-gamma, and lymphotoxin alpha/beta) that resulted in the identification of a full spectrum of EC membrane proteins regulated by inflammation.     

Characterization of the rat liver membrane proteome using peptide immobilized pH gradient isoelectric focusing

Membrane proteins are of particular interest in proteomics because of their potential therapeutic utility. Past proteomic approaches used to investigate membrane proteins have only been partially successful at providing a comprehensive analysis due to the inherently hydrophobic nature and low abundance for some of these proteins. Recently, these difficulties have been improved by analyzing membrane protein enriched samples using shotgun proteomics. In addition, the recent application of methanol-assisted trypsin digestion of membrane proteins has been shown to be a method to improve membrane protein identifications. In this study, a comparison of different concentrations of methanol was assessed for assisting membrane protein digestion with trypsin prior to analysis using a gel-based shotgun proteomics approach called peptide immobilized pH gradient isoelectric focusing (IPG-IEF). We demonstrate the use of peptide IEF on pH 3-10 IPG strips as the first dimension of two-dimensional shotgun proteomics for protein identifications from the membrane fraction of rat liver. Tryptic digestion of proteins was carried out in varying concentrations of methanol in 10 mM ammonium bicarbonate: 0% (v/v), 40% (v/v), and 60% (v/v). A total of 800 proteins were identified from 60% (v/v) methanol, which increased the protein identifications by 17% and 14% compared to 0% (v/v) methanol and 40% (v/v) methanol assisted digestion, respectively. In total, 1549 nonredundant proteins were identified from all three concentrations of methanol including 690 (42%) integral membrane proteins of which 626 of these proteins contained at least one transmembrane domain. Peptide IPG-IEF separation of peptides was successful as the peptides were separated into discrete pI regions with high resolution. The results from this study prove utility of 60% (v/v) methanol assisted digestion in conjunction with peptide IPG-IEF as an optimal shotgun proteomics technique for the separation and identification of previously unreported membrane proteins.     

Multistep mass tagging coupled with 2D LC-MS--an approach to increasing the number of identified proteins.

Identification of large numbers of proteins from complex biological samples is a continuing challenge in the area of quantitative proteomics. We introduce here a simple and reliable multistep mass tagging technique using our recently developed solid phase mass tagging reagents. When coupled with two-dimensional liquid chromatography/nano-electrospray ionization ion trap mass spectrometry (2D-LC/nano-ESI-MS), this method allows enhanced protein identification when tested on samples from prokaryotic and eukaryotic sources. The proteome of Escherichia coli D21 grown to either mid-exponential or stationary phase, and the membrane proteome from established breast cancer cell lines BT474 and MCF7 were used as model systems in these experiments. In both experiments, the numbers of total identified proteins are at least twice the numbers identified from a single tagging cycle. The sample complexity can be effectively reduced with corresponding increases in protein identification using the multistep method. The strategy described here represents a potentially powerful technique for large-scale qualitative and quantitative proteome research.     

In-depth analysis of the human CSF proteome using protein prefractionation

The identification of disease markers in human body fluids requires an extensive and thorough analysis of its protein constituents. In the present study, we have extended our analysis of the human cerebrospinal fluid (CSF) proteome using protein prefractional followed by shotgun mass spectrometry. After the removal of abundant protein components from the mixture with the help of immunodepletion affinity chromatography, we used either anion exchange chromatography or sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to further subfractionate the proteins present in CSFs. Each protein subfraction was enzyme digested and analyzed by tandem mass spectrometry and the resulting data evaluated using the Spectrum Mill software. Different subfractionation methods resulted in the identification of a grant total of 259 proteins in CSF from a patient with normal pressure hydrocephalus. The greatest number of protein, 240 in total, were identified after prefractionating the CSF proteins by immunodepletion and SDS-PAGE. Immuno-depletion combined with anion exchange fractionation resulted in 112 proteins and 74 proteins were found when only immunodepletion of the CSF samples was carried out. All methods used showed a significant increase in the number of identified proteins as compared with nondepleted and unfractionated CSF sample analysis, which yielded only 38 protein identifications. The present work establishes a platform for future studies aimed at a detailed comparative proteome analysis of CSFs from different groups of patients suffering from various psychiatric and neurological disorders.     

Label-free quantitative analysis of one-dimensional PAGE LC/MS/MS proteome: application on angiotensin II-stimulated smooth muscle cells secretome

A widely used method for protein identification couples prefractionation of protein samples by one-dimensional (1D) PAGE with LC/MS/MS. We developed a new label-free quantitative algorithm by combining measurements of spectral counting, ion intensity, and peak area on 1D PAGE-based proteomics. This algorithm has several improvements over other label-free quantitative algorithms: (i) Errors in peak detection are reduced because the retention time is based on each LC/MS/MS run and actual precursor m/z. (ii) Detection sensitivity is increased because protein quantification is based on the combination of peptide count, ion intensity, and peak area. (iii) Peak intensity and peak area are calculated in each LC/MS/MS run for all slices from 1D PAGE for every single identified protein and visualized as a Western blot image. The sensitivity and accuracy of this algorithm were demonstrated by using standard curves (17.4 fmol to 8.7 pmol), complex protein mixtures (30 fmol to 1.16 pmol) of known composition, and spiked protein (34.8 fmol to 17.4 pmol) in complex proteins. We studied the feasibility of this approach using the secretome of angiotensin II (Ang II)-stimulated vascular smooth muscle cells (VSMCs). From the VSMC-conditioned medium, 629 proteins were identified including 212 putative secreted proteins. 26 proteins were differently expressed in control and Ang II-stimulated VSMCs, including 18 proteins not previously reported. Proteins related to cell growth (CYR61, protein NOV, and clusterin) were increased, whereas growth arrest-specific 6 (GAS6) and growth/differentiation factor 6 were decreased by Ang II stimulation. Ang II-stimulated changes of plasminogen activator inhibitor-1, GAS6, cathepsin B, and periostin were validated by Western blot. In conclusion, a novel label-free quantitative analysis of 1D PAGE-LC/MS/MS-based proteomics has been successfully applied to the identification of new potential mediators of Ang II action and may provide an alternative to traditional protein staining methods.     

Computational methods for the comparative quantification of proteins in label-free LCn-MS experiments

Liquid chromatography (LC) coupled to electrospray mass spectrometry (MS) is well established in high-throughput proteomics. The technology enables rapid identification of large numbers of proteins in a relatively short time. Comparative quantification of identified proteins from different samples is often regarded as the next step in proteomics experiments enabling the comparison of protein expression in different proteomes. Differential labeling of samples using stable isotope incorporation or conjugation is commonly used to compare protein levels between samples but these procedures are difficult to carry out in the laboratory and for large numbers of samples. Recently, comparative quantification of label-free LC(n)-MS proteomics data has emerged as an alternative approach. In this review, we discuss different computational approaches for extracting comparative quantitative information from label-free LC(n)-MS proteomics data. The procedure for computationally recovering the quantitative information is described. Furthermore, statistical tests used to evaluate the relevance of results will also be discussed.     

适用于双向电泳分析的水稻悬浮细胞外分泌蛋白提取方法

目的:建立适用于双向电泳分析的水稻悬浮细胞外分泌蛋白提取方法。方法:采用酚抽提结合甲醇醋酸铵沉淀法、三氯乙酸-丙酮沉淀法和硫酸铵沉淀等3种方法制备水稻悬浮细胞外分泌蛋白,并进行双向电泳分析;利用Western印迹对候选方法提取的外分泌蛋白进行纯度检测。另外,还利用质谱技术对从双向电泳胶上随机挑选的9个蛋白点进行测定,并用SignalP 3.0 Server对测定的蛋白点进行信号肽预测。结果:酚抽提结合甲醇醋酸铵沉淀法提取的外分泌蛋白得率最高,且双向电泳图谱清晰,并能检测到最多的蛋白点;Western印迹表明利用该法所提取的外分泌蛋白未被细胞内蛋白质污染。利用质谱技术鉴定了随机挑选的9个蛋白点,SignalP 3.0 Server分析表明其中6个蛋白含有信号肽。结论:酚抽提结合甲醇醋酸铵沉淀法是一种适用于双向电泳分析的水稻悬浮细胞外分泌蛋白提取方法。     

The impact of blood contamination on the proteome of cerebrospinal fluid

Human cerebrospinal fluid (CSF) is in direct contact with the brain extracellular space. Beside the secretion of CSF by the choroid plexus the fluid also derives directly from the brain by the ependymal lining of the ventricular system and the glial membrane and from blood vessels in the arachnoid. Therefore, biochemical change in the brain may be reflected in the CSF. CSF is a potential source of protein molecular indices of central nervous system function and pathology. However, various amounts of blood contamination in CSF may arise during sample acquisition. The concentration of protein in the CSF is only 0.2 to 0.5% that of blood. Minor contamination of CSF with blood during collection of the fluid may dramatically alter the protein profile confounding the identification of potential biomarkers. We have analyzed CSF and CSF spiked with increasing amounts of whole blood using proteomic techniques. We detected at least four blood specific highly abundant proteins: hemoglobin, catalase, peroxiredoxin and carbonic anhydrase I. These proteins can be used as blood contamination markers for proteomic analysis of CSF. Proteins in blood contaminated CSF samples were less stable compared to neat CSF at 37 degrees C suggesting that blood borne protease may induce protein degradation in CSF during sample acquisition. This analysis was aimed at identification of proteins found primarily in CSF, those found primarily in blood and assessment of the impact of blood contamination on those proteins found in both fluids.     

Quantitative proteomics using 16O/18O labeling and linear ion trap mass spectrometry

Quantitative proteomics using stable isotopic 16O/18O labeling has emerged as a very powerful tool, since it has a number of advantages over other methods, including the simplicity of chemistry, the constant mass tag at the C termini and its general applicability. However, due to the small mass difference between labeled and unlabeled peptide species, this approach has usually been restricted to high-resolution mass spectrometers. In this study we explored whether the high-resolution scanning mode, together with the extremely high scanning speed of the linear IT allows the 16O/18O-labeling method to be used for accurate, large-scale quantitative analysis of proteomes. A protocol, including digestion, desalting, labeling, MS and quantitative analysis was developed and tested using protein standards and whole proteome extracts. Using this method we were able to identify and quantify 140 proteins from only 10 mug of a proteome extract from mesenchymal stem cells. Relative expression changes larger than twofold can be identified with this method at the 95% confidence level. Our results demonstrate that accurate quantitative analysis using 16O/18O labeling can be performed in the practice using linear IT MS, without compromising large-scale peptide identification efficiency.     

Extending the dynamic range of label-free mass spectrometric quantification of affinity purifications

Affinity purification (AP) of protein complexes combined with LC-MS/MS analysis is the current method of choice for identification of protein-protein interactions. Their interpretation with respect to significance, specificity, and selectivity requires quantification methods coping with enrichment factors of more than 1000-fold, variable amounts of total protein, and low abundant, unlabeled samples. We used standardized samples (0.1-1000 fmol) measured on high resolution hybrid linear ion trap instruments (LTQ-FT/Orbitrap) to characterize and improve linearity and dynamic range of label-free approaches. Quantification based on spectral counts was limited by saturation and ion suppression effects with samples exceeding 100 ng of protein, depending on the instrument setup. In contrast, signal intensities of peptides (peak volumes) selected by a novel correlation-based method (TopCorr-PV) were linear over at least 4 orders of magnitude and allowed for accurate relative quantification of standard proteins spiked into a complex protein background. Application of this procedure to APs of the voltage-gated potassium channel Kv1.1 as a model membrane protein complex unambiguously identified the whole set of known interaction partners together with novel candidates. In addition to discriminating these proteins from background, we could determine efficiency, cross-reactivities, and selection biases of the used purification antibodies. The enhanced dynamic range of the developed quantification procedure appears well suited for sensitive identification of specific protein-protein interactions, detection of antibody-related artifacts, and optimization of AP conditions.     

An approach to identify cold-induced low-abundant proteins in rice leaf

A proteomic approach has been adopted to investigate the low-abundant proteins in rice leaf in response to cold stress. Rice seedlings were exposed to different temperatures, such as 5 or 10 degrees C, and samples were collected after different time course. To eliminate the high-abundant proteins in leaf tissues such as ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco), proteins were fractionated by polyethylene glycol (PEG). The elimination of Rubisco from the protein samples was confirmed by Western blot analysis. The PEG fractionated protein samples were separated by 2-DE and visualized by silver or CBB staining. A total 12 up-regulated protein spots were identified using the analysis of MALDI-TOF mass spectrometry or ESI MS/MS. We identified some novel proteins such as cysteine proteinase, thioredoxin peroxidase, a RING zinc finger protein-like, drought-inducible late embryogenesis abundant, and a fibrillin-like protein that had not yet been reported in the earlier reports on cold proteomic analysis. The identification of some novel low-abundant proteins in response to cold stress may provide a new homeostasis to develop enhanced cold tolerance transgenic plants. Thus, we propose that a PEG fractionation system can be used as an influential protein extraction method from the leaf samples, which can lead to knowledge of the expression pattern of low-abundant proteins in response to various biotic or abiotic stresses.     

Evaluation of prefractionation methods as a preparatory step for multidimensional based chromatography of serum proteins

Prefractionations of proteins prior to their proteolysis, chromatography, and MS/MS analyses help reduce complexity and increase the yield of protein identifications. A number of methods were evaluated here for prefractionating serum samples distributed to the participating laboratories as part of the human Plasma Proteome Project. These methods include strong cation exchange (SCX) chromatography, slicing of SDS-PAGE gel bands, and liquid-phase IEF of the proteins. The fractionated proteins were trypsinized and the resulting peptides were resolved and analyzed by multidimensional protein identification technology coupled to IT MS/MS. The MS/MS spectra were clustered, combined, and searched against the IPI protein databank using Pep-Miner. The identification results were evaluated for the efficacy of the different prefractionation methodologies to identify larger numbers of proteins at higher confidence and to achieve the best coverage of the proteins with the identified peptides. Prefractionation based on SCX resulted in the largest number of identified proteins, followed by gel slices and then the liquid-phase IEF. An important observation was that each of the methods revealed a set of unique proteins, some identified with high confidence. Therefore, for comprehensive identification of the serum proteins, several different prefractionation approaches should be used in parallel.     

Evaluation of two-dimensional differential gel electrophoresis for proteomic expression analysis of a model breast cancer cell system

The technique of fluorescent two-dimensional (2D) difference gel electrophoresis for differential protein expression analysis has been evaluated using a model breast cancer cell system of ErbB-2 overexpression. Labeling of paired cell lysate samples with N-hydroxy succinimidyl ester-derivatives of fluorescent Cy3 and Cy5 dyes for separation on the same 2D gel enabled quantitative, sensitive, and reproducible differential expression analysis of the cell lines. SyproRuby staining was shown to be a highly sensitive and 2D difference gel electrophoresis-compatible method for post-electrophoretic visualization of proteins, which could then be picked and identified by matrix-assisted laser-desorption ionization mass spectroscopy. Indeed, from these experiments, we have identified multiple proteins that are likely to be involved in ErbB-2-mediated transformation. A triple dye labeling methodology was used to identify proteins differentially expressed in the cell system over a time course of growth factor stimulation. A Cy2-labeled pool of samples was used as a standard with all Cy3- and Cy5-labeled sample pairs to facilitate cross-gel quantitative analysis. DeCyder (Amersham Biosciences, Inc.) software was used to distinguish clear statistical differences in protein expression over time and between the cell lines.     

Modification of a commercial cell sorter to support efficient and reliable preparation of ALDH-bright cells for clinical use

BACKGROUND: Cell populations manufactured by conventional commercial cell sorters have been safely infused into patients, but reliably sterilizing these instruments remains challenging. We are developing clinical protocols involving use of ALDH bright cells manufactured by cell sorting in patients. However, we encountered problems when we attempted to reliably sterilize the FACSAria cell sorter using standard methods. RESULTS: We have identified and modified potential sources of microbial contamination in several FACSAria systems. We added new filter systems to the sheath and sample air lines, to the wet cart fluid supply, and to the sample line. Sheath was provided from an external sterile, disposable bag through sterile disposable tubing sets. The plenum reservoirs were modified in several ways to allow efficient decontamination of internal surfaces. A new bubble filter assembly was added and one valve was eliminated from the sample pathway to improve flow cell sterilization. A new cleaning and sterilization protocol was developed and validated. All cell products manufactured using the modified instrument and validated cleaning protocol have met lot release criteria for prevention of microbial contamination and safe clinical use. DISCUSSION: The instrument modification and cleaning protocol described enable reliable manufacture of ALDH bright cell populations that are suitable for clinical trials. We have manufactured nineteen consecutive samples that meet all clinical release criteria in an on-going Phase 1 human trial.     

High throughput peptide mass fingerprinting and protein macroarray analysis using chemical printing strategies

We describe a chemical printer that uses piezoelectric pulsing for rapid, accurate, and non-contact microdispensing of fluid for proteomic analysis of immobilized protein macroarrays. We demonstrate protein digestion and peptide mass fingerprinting analysis of human plasma and platelet proteins direct from a membrane surface subsequent to defined microdispensing of trypsin and matrix solutions, hence bypassing multiple liquid-handling steps. Detection of low abundance, alkaline proteins from whole human platelet extracts has been highlighted. Membrane immobilization of protein permits archiving of samples pre-/post-analysis and provides a means for subanalysis using multiple chemistries. This study highlights the ability to increase sequence coverage for protein identification using multiple enzymes and to characterize N-glycosylation modifications using a combination of PNGase F and trypsin. We also demonstrate microdispensing of multiple serum samples in a quantitative microenzyme-linked immunosorbent assay format to rapidly screen protein macroarrays for pathogen-derived antigens. We anticipate the chemical printer will be a major component of proteomic platforms for high throughput protein identification and characterization with widespread applications in biomedical and diagnostic discovery.     

Low abundance protein enrichment for discovery of candidate plasma protein biomarkers for early detection of breast cancer

Molecular biomarkers of early stage breast cancer may improve the sensitivity and specificity of diagnosis. Plasma biomarkers have additional value in that they can be monitored with minimal invasiveness. Plasma biomarker discovery by genome-wide proteomic methods is impeded by the wide dynamic range of protein abundance and the heterogeneity of protein expression in healthy and disease populations which requires the analysis of a large number of samples. We addressed these issues through the development of a novel protocol that couples a combinatorial peptide ligand library protein enrichment strategy with isobaric label-based 2D LC-MS/MS for the identification of candidate biomarkers in high throughput. Plasma was collected from patients with stage I breast cancer or benign breast lesions. Low abundance proteins were enriched using a bead-based combinatorial library of hexapeptides. This resulted in the identification of 397 proteins, 22% of which are novel plasma proteins. Twenty-three differentially expressed plasma proteins were identified, demonstrating the effectiveness of the described protocol and defining a set of candidate biomarkers to be validated in independent samples. This work can be used as the basis for the design of properly powered investigations of plasma protein expression for biomarker discovery in larger cohorts of patients with complex disease.