Proteomics of Human Milk: Definition of a Discovery Workflow for Clinical Research Studies.

Milk is a complex biological fluid composed mainly of water, carbohydrates, lipids, proteins, and diverse bioactive factors. Human milk represents a unique tailored source of nutrients that adapts during lactation to the specific needs of the developing infant. Proteins in milk have been studied for decades, and proteomics, peptidomics, and glycoproteomics are the main approaches previously deployed to decipher the proteome of human milk. In the present work, we aimed at implementing a highly automated pipeline for the proteomic analysis of human milk with liquid chromatography mass spectrometry (MS). Commercial human milk samples were used to evaluate and optimize workflows. Centrifugation for defatting milk samples was assessed before and after reduction, alkylation, and enzymatic digestion of proteins, without and with presence of surfactants. Skimmed milk samples were analyzed using isobaric labeling-based quantitative MS on an Orbitrap Tribrid mass spectrometer. Sample fractionation using isoelectric focusing was also evaluated to more deeply profile the human milk proteome. Finally, the most appropriate workflow was transferred to a liquid handling workstation for automated sample preparation. In conclusion, we have defined and describe herein an efficient highly automated proteomic workflow for human milk sample analysis. It is compatible with clinical research, possibly allowing the analysis of sufficiently large cohorts of samples.

Identification of Missing Proteins in Normal Human Cerebrospinal Fluid.

The cerebrospinal fluid (CSF) proteome data set presented herein was obtained after immunodepletion of abundant proteins and off-gel electrophoresis fractionation of a commercial pool of normal human CSF; liquid chromatography tandem mass spectrometry analysis was performed with a linear ion trap-Orbitrap Elite. We report the identification of 12 344 peptides mapping on 2281 proteins. In the context of the Chromosome-centric Human Proteome Project (C-HPP), the existence of seven missing proteins is proposed to be validated. This data set is available to the ProteomeXchange Consortium ( http://www.proteomexchange.org/ ) with the data set identifier PXD008029.

Deep Dive on the Proteome of Human Cerebrospinal Fluid: A Valuable Data Resource for Biomarker Discovery and Missing Protein Identification.

Cerebrospinal fluid (CSF) is a body fluid of choice for biomarker studies of brain disorders but remains relatively under-studied compared with other biological fluids such as plasma, partly due to the more invasive means of its sample collection. The present study establishes an in-depth CSF proteome through the analysis of a unique CSF sample from a pool of donors. After immunoaffinity depletion, the CSF sample was fractionated using off-gel electrophoresis and analyzed with liquid chromatography tandem mass spectrometry (MS) using the latest generation of hybrid Orbitrap mass spectrometers. The shotgun proteomic analysis allowed the identification of 20 689 peptides mapping on 3379 proteins. To the best of our knowledge, the obtained data set constitutes the largest CSF proteome published so far. Among the CSF proteins identified, 34% correspond to genes whose transcripts are highly expressed in brain according to the Human Protein Atlas. The principal Alzheimer's disease biomarkers (e.g., tau protein, amyloid-ß, apolipoprotein E, and neurogranin) were detected. Importantly, our data set significantly contributes to the Chromosome-centric Human Proteome Project (C-HPP), and 12 proteins considered as missing are proposed for validation in accordance with the HPP guidelines. Of these 12 proteins, 8 proteins are based on 2 to 6 uniquely mapping peptides from this CSF analysis, and 4 match a new peptide with a "stranded" single peptide in PeptideAtlas from previous CSF studies. The MS proteomic data are available to the ProteomeXchange Consortium ( http://www.proteomexchange.org/ ) with the data set identifier PXD009646.

Systematic Evaluation of the Use of Human Plasma and Serum for Mass-Spectrometry-Based Shotgun Proteomics.

Over the last two decades, EDTA-plasma has been used as the preferred sample matrix for human blood proteomic profiling. Serum has also been employed widely. Only a few studies have assessed the difference and relevance of the proteome profiles obtained from plasma samples, such as EDTA-plasma or lithium-heparin-plasma, and serum. A more complete evaluation of the use of EDTA-plasma, heparin-plasma, and serum would greatly expand the comprehensiveness of shotgun proteomics of blood samples. In this study, we evaluated the use of heparin-plasma with respect to EDTA-plasma and serum to profile blood proteomes using a scalable automated proteomic pipeline (ASAP2). The use of plasma and serum for mass-spectrometry-based shotgun proteomics was first tested with commercial pooled samples. The proteome coverage consistency and the quantitative performance were compared. Furthermore, protein measurements in EDTA-plasma and heparin-plasma samples were comparatively studied using matched sample pairs from 20 individuals from the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study. We identified 442 proteins in common between EDTA-plasma and heparin-plasma samples. Overall agreement of the relative protein quantification between the sample pairs demonstrated that shotgun proteomics using workflows such as the ASAP2 is suitable in analyzing heparin-plasma and that such sample type may be considered in large-scale clinical research studies. Moreover, the partial proteome coverage overlaps (e.g., ∼70%) showed that measures from heparin-plasma could be complementary to those obtained from EDTA-plasma.

An Adaptive Pipeline To Maximize Isobaric Tagging Data in Large-Scale MS-Based Proteomics.

Isobaric tagging is the method of choice in mass-spectrometry-based proteomics for comparing several conditions at a time. Despite its multiplexing capabilities, some drawbacks appear when multiple experiments are merged for comparison in large sample-size studies due to the presence of missing values, which result from the stochastic nature of the data-dependent acquisition mode. Another indirect cause of data incompleteness might derive from the proteomic-typical data-processing workflow that first identifies proteins in individual experiments and then only quantifies those identified proteins, leaving a large number of unmatched spectra with quantitative information unexploited. Inspired by untargeted metabolomic and label-free proteomic workflows, we developed a quantification-driven bioinformatic pipeline (Quantify then Identify (QtI)) that optimizes the processing of isobaric tandem mass tag (TMT) data from large-scale studies. This pipeline includes innovative features, such as peak filtering with a self-adaptive preprocessing pipeline optimization method, Peptide Match Rescue, and Optimized Post-Translational Modification. QtI outperforms a classical benchmark workflow in terms of quantification and identification rates, significantly reducing missing data while preserving unmatched features for quantitative comparison. The number of unexploited tandem mass spectra was reduced by 77 and 62% for two human cerebrospinal fluid and plasma data sets, respectively.

Coordinated activation of mitochondrial respiration and exocytosis mediated by PKC signaling in pancreatic ß cells.

Mitochondria play a central role in pancreatic ß-cell nutrient sensing by coupling their metabolism to plasma membrane excitability and insulin granule exocytosis. Whether non-nutrient secretagogues stimulate mitochondria as part of the molecular mechanism to promote insulin secretion is not known. Here, we show that PKC signaling, which is employed by many non-nutrient secretagogues, augments mitochondrial respiration in INS-1E (rat insulinoma cell line clone 1E) and human pancreatic ß cells. The phorbol ester, phorbol 12-myristate 13-acetate, accelerates mitochondrial respiration at both resting and stimulatory glucose concentrations. A range of inhibitors of novel PKC isoforms prevent phorbol ester-induced respiration. Respiratory response was blocked by oligomycin that demonstrated PKC-dependent acceleration of mitochondrial ATP synthesis. Enhanced respiration was observed even when glycolysis was bypassed or fatty acid transport was blocked, which suggested that PKC regulates mitochondrial processes rather than upstream catabolic fluxes. A phosphoproteome study of phorbol ester-stimulated INS-1E cells maintained under resting (2.5 mM) glucose revealed a large number of phosphorylation sites that were altered during short-term activation of PKC signaling. The data set was enriched for proteins that are involved in gene expression, cytoskeleton remodeling, secretory vesicle transport, and exocytosis. Interactome analysis identified PKC, C-Raf, and ERK1/2 as the central phosphointeraction cluster. Prevention of ERK1/2 signaling by using a MEK1 inhibitor caused a marked decreased in phorbol 12-myristate 13-acetate-induced mitochondrial respiration. ERK1/2 signaling module therefore links PKC activation to downstream mitochondrial activation. We conclude that non-nutrient secretagogues act, in part, via PKC and downstream ERK1/2 signaling to stimulate mitochondrial energy production to compensate for energy expenditure that is linked to ß-cell activation.-Santo-Domingo, J., Chareyron, I., Dayon, L., Galindo, A. N., Cominetti, O., Giménez, M. P. G., De Marchi, U., Canto, C., Kussmann, M., Wiederkehr, A. Coordinated activation of mitochondrial respiration and exocytosis mediated by PKC signaling in pancreatic ß cells.

Proteomic Biomarker Discovery in 1000 Human Plasma Samples with Mass Spectrometry.

The overall impact of proteomics on clinical research and its translation has lagged behind expectations. One recognized caveat is the limited size (subject numbers) of (pre)clinical studies performed at the discovery stage, the findings of which fail to be replicated in larger verification/validation trials. Compromised study designs and insufficient statistical power are consequences of the to-date still limited capacity of mass spectrometry (MS)-based workflows to handle large numbers of samples in a realistic time frame, while delivering comprehensive proteome coverages. We developed a highly automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked the quality of the MS data and provided descriptive statistics. The data set was interrogated for proteins with most stable expression levels in that set of plasma samples. We evaluated standard clinical variables that typically impact forthcoming results and assessed body mass index-associated and gender-specific proteins at two time points. We demonstrate that analyzing a large number of human plasma samples for biomarker discovery with MS using isobaric tagging is feasible, providing robust and consistent biological results.

Proteomics of Cerebrospinal Fluid: Throughput and Robustness Using a Scalable Automated Analysis Pipeline for Biomarker Discovery.

Cerebrospinal fluid (CSF) is a body fluid of high clinical relevance and an important source of potential biomarkers for brain-associated damages, such as traumatic brain injury and stroke, and for brain diseases, such as Alzheimer's and Parkinson's. Herein, we have implemented, evaluated, and validated a scalable automated proteomic pipeline (ASAP(2)) for the sample preparation and proteomic analysis of CSF, enabling increased throughput and robustness for biomarker discovery. Human CSF samples were depleted from abundant proteins and subjected to automated reduction, alkylation, protein digestion, tandem mass tag (TMT) 6-plex labeling, pooling, and sample cleanup in a 96-well-plate format before reversed-phase liquid chromatography tandem mass spectrometry (RP-LC MS/MS). We showed the impact on the CSF proteome coverage of applying the depletion of abundant proteins, which is usually performed on blood plasma or serum samples. Using ASAP(2) to analyze 96 identical CSF samples, we determined the analytical figures of merit of our shotgun proteomic approach regarding proteome coverage consistency (i.e., 387 proteins), quantitative accuracy, and individual protein variability. We demonstrated that, as for human plasma samples, ASAP(2) is efficient in analyzing large numbers of human CSF samples and is a valuable tool for biomarker discovery. The data has been deposited to the ProteomeXchange with identifier PXD003024.

Comprehensive and Scalable Highly Automated MS-Based Proteomic Workflow for Clinical Biomarker Discovery in Human Plasma.

Over the past decade, mass spectrometric performance has greatly improved in terms of sensitivity, dynamic range, and speed. By contrast, only limited progress has been accomplished with regard to automation, throughput, and robustness of the proteomic sample preparation process upstream of mass spectrometry. The present work delivers an optimized analysis of human plasma samples in both small preclinical and large clinical studies, enabled by the development of a highly automated quantitative proteomic workflow. Several iterative evaluation and validation steps were performed before process "design freeze" and development completion. A robotic liquid handling workflow and platform (including reduction, alkylation, digestion, TMT labeling, pooling, and purification) were shown to provide better quantitative trueness and precision than manual operation at the bench. Depletion of the most abundant human plasma proteins and subsequent buffer exchange were also developed and integrated. Finally, 96 identical pooled human plasma samples were prepared in a 96-well plate format, and each sample was individually subjected to our developed workflow. This test revealed increased throughput and robustness compared with to-date published manual or less automated workflows. Our workflow is ready-to-use for future (pre-) clinical studies. We expect our work to facilitate, accelerate, and improve clinical proteomic discovery in human blood plasma.

Detection of gluten peptides in human duodenal fluids with immuno-liquid chromatography-mass spectrometry.

Gluten proteins are storage proteins in wheat that exhibit a certain resistance to gastrointestinal digestion. To explore solutions to cope with accidental ingestion of gluten in individuals suffering from gluten-related disorders, it is essential to monitor the fate of gluten peptides in biological samples, i.e., gastrointestinal juices, blood plasma or urine. In this work, we aimed at developing a mass spectrometry (MS)-based method for measuring gluten peptides in human duodenal fluids. Seven gluten peptides, including the well-documented 33-mer gluten peptide (LQLQPFPQPQLPYPQPQLPYPQPQLPYPQPQPF), were selected after a literature review and characterization of a gluten-containing product. Isotopically labelled peptides were used as references and a targeted liquid chromatography (LC) MS assay based on high resolution parallel reaction monitoring (PRM) was designed. Despite iterative and fine tuning of the LC-PRM-MS method, the low level of endogenous gluten peptides in human duodenal fluid samples precluded their direct detection. Thus, an initial immunoprecipitation (IP) step was included. Several antibodies were tested, and one proved reliable for the enrichment of the 33-mer gluten peptide as well as a few additional gluten peptides. Figures-of-merits of the immuno-LC-PRM-MS assay were assessed with a focus on quantification trueness and precision. We have developed an MS-based method for measuring the 33-mer gluten peptide in human duodenal fluids. Based on isotopic dilution, the method relies on the combination of IP and LC-PRM-MS analysis. Measurements were shown to be sensitive, quantitative, and reproducible.

Proteomics reveals unique plasma signatures in constitutional thinness.

PURPOSE: Studying the plasma proteome of control versus constitutionally thin (CT) individuals, exposed to overfeeding, may give insights into weight-gain management, providing relevant information to the clinical entity of weight-gain resistant CT, and discovering new markers for the condition. EXPERIMENTAL DESIGN: Untargeted protein relative quantification of 63 CT and normal-weight individuals was obtained in blood plasma at baseline, during and after an overfeeding challenge using mass spectrometry-based proteomics. RESULTS: The plasma proteome of CT subjects presented limited specificity with respect to controls at baseline. Yet, CT showed lower levels of inflammatory C-reactive protein and larger levels of protective insulin-like growth factor-binding protein 2. Differences were more marked during and after overfeeding. CT plasma proteome showed larger magnitude and significance in response, suggesting enhanced "resilience" and more rapid adaptation to changes. Four proteins behaved similarly between CT and controls, while five were regulated in opposite fashion. Ten proteins were differential during overfeeding in CT only (including increased fatty acid-binding protein and glyceraldehyde-3-phosphate dehydrogenase, and decreased apolipoprotein C-II and transferrin receptor protein 1). CONCLUSIONS AND CLINICAL RELEVANCE: This first proteomic profiling of a CT cohort reveals different plasma proteomes between CT subjects and controls in a longitudinal clinical trial. Our molecular observations further support that the resistance to weight gain in CT subjects appears predominantly biological. CLINICALTRIALS: gov Identifier: NCT02004821.

Crosstalk between Drp1 phosphorylation sites during mitochondrial remodeling and their impact on metabolic adaptation.

Mitochondria constantly undergo fusion and fission events, referred as mitochondrial dynamics, which determine mitochondrial architecture and bioenergetics. Cultured cell studies demonstrate that mitochondrial dynamics are acutely regulated by phosphorylation of the mitochondrial fission orchestrator dynamin-related protein 1 (Drp1) at S579 or S600. However, the physiological impact and crosstalk of these phosphorylation sites is poorly understood. Here, we describe the functional interrelation between S579 and S600 phosphorylation sites in vivo and their role on mitochondrial remodeling. Mice carrying a homozygous Drp1 S600A knockin (Drp1 KI) mutation display larger mitochondria and enhanced lipid oxidation and respiratory capacities, granting improved glucose tolerance and thermogenic response upon high-fat feeding. Housing mice at thermoneutrality blunts these differences, suggesting a role for the brown adipose tissue in the protection of Drp1 KI mice against metabolic damage. Overall, we demonstrate crosstalk between Drp1 phosphorylation sites and provide evidence that their modulation could be used in the treatment and prevention of metabolic diseases.

Exploration of human cerebrospinal fluid: A large proteome dataset revealed by trapped ion mobility time-of-flight mass spectrometry.

Cerebrospinal fluid (CSF) is a biofluid in direct contact with the brain and as such constitutes a sample of choice in neurological disorder research, including neurodegenerative diseases such as Alzheimer or Parkinson. Human CSF has still been less studied using proteomic technologies compared to other biological fluids such as blood plasma or serum. In this work, a pool of "normal" human CSF samples was analysed using a shotgun proteomic workflow that combined removal of highly abundant proteins by immunoaffinity depletion and isoelectric focussing fractionation of tryptic peptides to alleviate the complexity of the biofluid. The resulting 24 fractions were analysed using liquid chromatography coupled to a high-resolution and high-accuracy timsTOF Pro mass spectrometer. This state-of-the-art mass spectrometry-based proteomic workflow allowed the identification of 3'174 proteins in CSF. The dataset reported herein completes the pool of the most comprehensive human CSF proteomes obtained so far. An overview of the identified proteins is provided based on gene ontology annotation. Mass and tandem mass spectra are made available as a possible starting point for further studies exploring the human CSF proteome.

Analyzing Cerebrospinal Fluid Proteomes to Characterize Central Nervous System Disorders: A Highly Automated Mass Spectrometry-Based Pipeline for Biomarker Discovery.

Over the past decade, liquid chromatography tandem mass spectrometry (LC MS/MS)-based workflows become standard for biomarker discovery in proteomics. These medium- to high-throughput (in terms of protein content) profiling approaches have been applied to clinical research. As a result, human proteomes have been characterized to a greater extent than ever before. However, proteomics in clinical research and biomarker discovery studies has generally been performed with small cohorts of subjects (or pooled samples from larger cohorts). This is problematic, as when aiming to identify novel biomarkers, small studies suffer from inherent and important limitations, as a result of the reduced biological diversity and representativity of human populations. Consequently, larger-scale proteomics will be key to delivering robust biomarker candidates and enabling translation to clinical practice.Cerebrospinal fluid (CSF) is a highly clinically relevant body fluid, and an important source of potential biomarkers for brain-associated damage, such as that induced by traumatic brain injury and stroke, and brain diseases, such as Alzheimer's disease and Parkinson's disease. We have developed a scalable automated proteomic pipeline (ASAP2) for biomarker discovery. This workflow is compatible with larger clinical research studies in terms of sample size, while still allowing several hundred proteins to be measured in CSF by MS. In this chapter, we describe the whole proteomic workflow to analyze human CSF. We further illustrate our protocol with some examples from an analysis of hundreds of human CSF samples, in the specific context of biomarker discovery to characterize central nervous system disorders.

A Versatile Workflow for Cerebrospinal Fluid Proteomic Analysis with Mass Spectrometry: A Matter of Choice between Deep Coverage and Sample Throughput.

Human cerebrospinal fluid (CSF) is a sample of choice in the study of brain disorders. This biological fluid circulates in the brain and the spinal cord and contains tissue-specific proteins, indicative of health and disease conditions. Despite its potential as a valid source of biological markers, CSF remains largely understudied as compared to blood, in particular due to its more invasive way of sampling.Challenges remain when performing proteomic analysis in clinical research studies. State-of-the-art mass spectrometry (MS) enables deep characterization of the human proteome. But some technical limitations are cardinal to be addressed, such as the capacity to routinely analyze large cohorts of samples. Importantly, a trade-off still needs to be made between the proteome coverage depth and the number of measured samples. In this context, we developed a scalable automated proteomic pipeline for the analysis of CSF. Because of its versatility, this workflow can be adapted to accommodate proteome coverage and/or sample throughput. It allows us to prepare and quantitatively analyze hundreds to thousands of CSF samples; it can also allow identification of more than 3000 proteins in a CSF sample when coupled with isoelectric focusing fractionation.In this chapter, we describe an end-to-end pipeline for the proteomic analysis of CSF. The main steps of the sample preparation comprise spiking of a standard, protein digestion, isobaric labeling, and purification; these are performed in a 96-well plate format enabling automation. Depending on the targeted depth of the CSF proteome, optional analytical steps can be included, such as the removal of abundant proteins and sample pre-fractionation. Liquid chromatography tandem MS as well as data processing and analysis complete the pipeline.

Regulation of inositol 1,4,5-trisphosphate-induced Ca2+ release from the endoplasmic reticulum by AMP-activated kinase modulators.

The 5' AMP-activated protein kinase (AMPK) is a nutrient-sensitive kinase that plays a key role in the control of cellular energy metabolism. We have explored here the relationship between AMPK and Ca2+ signaling by looking at the effect of an AMPK activator (A769662) and an AMPK inhibitor (dorsomorphin) on histamine-induced Ca2+-release from the endoplasmic reticulum (ER) in HeLa cells. Our data show that incubation with A769662 (EC50 = 29 µM) inhibited histamine-induced Ca2+-release from the ER in intact cells, as well as inositol-1,4,5-trisphosphate (IP3)-induced Ca2+ release in permeabilized cells. On the contrary, dorsomorphin (EC50 = 0.4 µM) activated both histamine and IP3-induced Ca2+-release and reversed the effect of A769662. These results suggest a direct effect of AMPK regulation on IP3 receptor (IP3R) function. A phosphoproteomic study did not reveal changes in IP3R phosphorylation, but showed significant changes in phosphorylation of proteins placed upstream in the IP3R interactome and in several proteins related with Ca2+ metabolism, which could be candidates to mediate the effects observed. In conclusion, our data suggest that AMPK negatively regulates IP3R. This effect constitutes a novel and very important link between Ca2+ signaling and the AMPK pathway.

Persistent low body weight in humans is associated with higher mitochondrial activity in white adipose tissue.

BACKGROUND: Constitutional thinness (CT) is a state of low but stable body weight (BMI ≤18 kg/m2). CT subjects have normal-range hormonal profiles and food intake but exhibit resistance to weight gain despite living in the modern world's obesogenic environment. OBJECTIVE: The goal of this study is to identify molecular mechanisms underlying this protective phenotype against weight gain. METHODS: We conducted a clinical overfeeding study on 30 CT subjects and 30 controls (BMI 20-25 kg/m2) matched for age and sex. We performed clinical and integrative molecular and transcriptomic analyses on white adipose and muscle tissues. RESULTS: Our results demonstrate that adipocytes were markedly smaller in CT individuals (mean ± SEM: 2174 ± 142 µm 2) compared with controls (3586 ± 216 µm2) (P < 0.01). The mitochondrial respiratory capacity was higher in CT adipose tissue, particularly at the level of complex II of the electron transport chain (2.2-fold increase; P < 0.01). This higher activity was paralleled by an increase in mitochondrial number (CT compared with control: 784 ± 27 compared with 675 ± 30 mitochondrial DNA molecules per cell; P < 0.05). No evidence for uncoupled respiration or "browning" of the white adipose tissue was found. In accordance with the mitochondrial differences, CT subjects had a distinct adipose transcriptomic profile [62 differentially expressed genes (false discovery rate of 0.1 and log fold change >0.75)], with many differentially expressed genes associating with positive metabolic outcomes. Pathway analyses revealed an increase in fatty acid oxidation ( P = 3 × 10-04) but also triglyceride biosynthesis (P = 3.6 × 10-04). No differential response to the overfeeding was observed in the 2 groups. CONCLUSIONS: The distinct molecular signature of the adipose tissue in CT individuals suggests the presence of augm ented futile lipid cycling, rather than mitochondrial uncoupling, as a way to increase energy expenditure in CT individuals. We propose that increased mitochondrial function in adipose tissue is an important mediator in sustaining the low body weight in CT individuals. This knowledge could ultimately allow more targeted approaches for weight management treatment strategies. This trial was registered at clinicaltrials.gov as NCT02004821.

Obesity shows preserved plasma proteome in large independent clinical cohorts.

Holistic human proteome maps are expected to complement comprehensive profile assessment of health and disease phenotypes. However, methodologies to analyze proteomes in human tissue or body fluid samples at relevant scale and performance are still limited in clinical research. Their deployment and demonstration in large enough human populations are even sparser. In the present study, we have characterized and compared the plasma proteomes of two large independent cohorts of obese and overweight individuals using shotgun mass spectrometry (MS)-based proteomics. Herein, we showed, in both populations from different continents of about 500 individuals each, the concordance of plasma protein MS measurements in terms of variability, gender-specificity, and age-relationship. Additionally, we replicated several known and new associations between proteins, clinical and molecular variables, such as insulin and glucose concentrations. In conclusion, our MS-based analyses of plasma samples from independent human cohorts proved the practical feasibility and efficiency of a large and unified discovery/replication approach in proteomics, which was also recently coined "rectangular" design.

Alzheimer disease pathology and the cerebrospinal fluid proteome.

BACKGROUND: Altered proteome profiles have been reported in both postmortem brain tissues and body fluids of subjects with Alzheimer disease (AD), but their broad relationships with AD pathology, amyloid pathology, and tau-related neurodegeneration have not yet been fully explored. Using a robust automated MS-based proteomic biomarker discovery workflow, we measured cerebrospinal fluid (CSF) proteomes to explore their association with well-established markers of core AD pathology. METHODS: Cross-sectional analysis was performed on CSF collected from 120 older community-dwelling adults with normal (n = 48) or impaired cognition (n = 72). LC-MS quantified hundreds of proteins in the CSF. CSF concentrations of ß-amyloid 1-42 (Aß1-42), tau, and tau phosphorylated at threonine 181 (P-tau181) were determined with immunoassays. First, we explored proteins relevant to biomarker-defined AD. Then, correlation analysis of CSF proteins with CSF markers of amyloid pathology, neuronal injury, and tau hyperphosphorylation (i.e., Aß1-42, tau, P-tau181) was performed using Pearson's correlation coefficient and Bonferroni correction for multiple comparisons. RESULTS: We quantified 790 proteins in CSF samples with MS. Four CSF proteins showed an association with CSF Aß1-42 levels (p value ≤ 0.05 with correlation coefficient (R) ≥ 0.38). We identified 50 additional CSF proteins associated with CSF tau and 46 proteins associated with CSF P-tau181 (p value ≤ 0.05 with R ≥ 0.37). The majority of those proteins that showed such associations were brain-enriched proteins. Gene Ontology annotation revealed an enrichment for synaptic proteins and proteins originating from reelin-producing cells and the myelin sheath. CONCLUSIONS: We used an MS-based proteomic workflow to profile the CSF proteome in relation to cerebral AD pathology. We report strong evidence of previously reported CSF proteins and several novel CSF proteins specifically associated with amyloid pathology or neuronal injury and tau hyperphosphorylation.

The differential plasma proteome of obese and overweight individuals undergoing a nutritional weight loss and maintenance intervention.

PURPOSE: The nutritional intervention program "DiOGenes" focuses on how obesity can be prevented and treated from a dietary perspective. We generated differential plasma proteome profiles in the DiOGenes cohort to identify proteins associated with weight loss and maintenance and explore their relation to body mass index, fat mass, insulin resistance, and sensitivity. EXPERIMENTAL DESIGN: Relative protein quantification was obtained at baseline and after combined weight loss/maintenance phases using isobaric tagging and MS/MS. A Welch t-test determined proteins differentially present after intervention. Protein relationships with clinical variables were explored using univariate linear models, considering collection center, gender and age as confounding factors. RESULTS: Four hundred and seventy three subjects were measured at baseline and end of the intervention; 39 proteins were longitudinally differential. Proteins with largest changes were sex hormone-binding globulin, adiponectin, C-reactive protein, calprotectin, serum amyloid A, and proteoglycan 4 (PRG4), whose association with obesity and weight loss is known. We identified new putative biomarkers for weight loss/maintenance. Correlation between PRG4 and proline-rich acidic protein 1 variation and Matsuda insulin sensitivity increment was showed. CONCLUSION AND CLINICAL RELEVANCE: MS-based proteomic analysis of a large cohort of non-diabetic overweight and obese individuals concomitantly identified known and novel proteins associated with weight loss and maintenance.