Biological and methodical challenges of blood-based proteomics in the field of neurological research

A Framework for Quality Control in Quantitative Proteomics

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow, from planning to analysis. We share vignettes applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at the protein and peptide levels allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis (Skyline), longitudinal QC metrics (AutoQC), and server-based data deposition (PanoramaWeb). We propose that this integrated approach to QC is a useful starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible. Data are available on Panorama Public and ProteomeXchange under the identifier PXD051318.

A framework for quality control in quantitative proteomics

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share vignettes applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis (Skyline), longitudinal QC metrics (AutoQC), and server-based data deposition (PanoramaWeb). We propose that this integrated approach to QC is a useful starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible. Data are available on Panorama Public and on ProteomeXchange under the identifier PXD051318.

An optimized proteomics-based approach to estimate blood contamination and cellular heterogeneity of frozen placental tissue

INTRODUCTION

Archived human placental tissue specimens are vital for studying placenta pathophysiology and toxicology. Proteomics analysis of placental tissue provides mechanistic and translational information, but the highly perfused and heterogenous nature of the placenta creates confounding technical variability. In this study, we developed an optimized proteomics-based approach to address the technical variability of proteomics data by normalizing blood contamination and cellular heterogeneity of archived placenta samples.

METHODS

Placenta samples (n = 99) were homogenized, digested using trypsin, and analyzed by liquid chromatography mass-spectrometry. Label-free quantification (LFQ) intensities of the proteins were analyzed for their correlation with blood (albumin) and placenta (aromatase) markers. Proteins that positively correlated with albumin and negatively correlated with aromatase or vice versa were considered blood and placental proteins, respectively. Next, the cellular heterogeneity of individual placenta samples was evaluated by quantifying specific cellular markers of cytotrophoblasts, syncytiotrophoblasts, extravillous trophoblasts, fibroblasts, Hofbauer cells, and decidual cells.

RESULTS

We found that placental proteins were contaminated by 41 to 85% blood proteins. Analysis of cellular markers confirmed syncytiotrophoblasts as the major cell type in placenta (i.e., 41 ± 9% of all cell types). Two samples showed distinct cell compositions with higher levels of the extravillous trophoblasts and decidual cells.

DISCUSSION

In summary, the optimized proteomics-based approach to estimate blood contamination and cellular heterogeneity of placental tissues has the potential to address technical variability in placenta proteomics analysis, which can be extended to other highly perfused and heterogenous tissues.

Robust Preanalytical Performance of Soluble PD-1, PD-L1 and PD-L2 Assessed by Sensitive ELISAs in Blood

The interaction between programmed death-1 receptor PD-1 and its ligands PD-L1 and PD-L2 is involved in self-tolerance, immune escape of cancer, cardiovascular diseases, and COVID-19. As blood-based protein markers they bear great potential to improve oncoimmunology research and monitoring of anti-cancer immunotherapy. A variety of preanalytical conditions were tested to assure high quality plasma sample measurements: (i) different time intervals and storage temperatures before and after blood centrifugation; (ii) fresh samples and repeated freeze-thaw-cycles; (iii) different conditions of sample preparation before measurement. Concerning short-term stability, acceptable recoveries for PD-1 between 80 and 120% were obtained when samples were kept up to 24 h at 4 and 25 °C before and after blood centrifugation. Similarly, recoveries for PD-L2 were acceptable for 24 h at 4 °C and 6 h at 25 °C before blood centrifugation and up to 24 h at 4 and 25 °C after centrifugation. Variations for PD-L1 were somewhat higher, however, at very low signal levels. Sample concentrations (ng/mL) were neither affected by the freezing process nor by repeated freeze-thaw cycles with coefficients of variation for PD-1: 9.1%, PD-L1 6.8%, and PD-L2 4.8%. All three biomarkers showed good stability regarding preanalytic conditions of sample handling enabling reliable and reproducible quantification in oncoimmunology research and clinical settings of anti-cancer immunotherapy.

The Known Unknowns: An Overview of the State of Blood-Based Protein Biomarkers of Mild Traumatic Brain Injury

Blood-based protein biomarkers have revolutionized several fields of medicine by enabling molecular level diagnosis, as well as monitoring disease progression and treatment efficacy. Traumatic brain injury (TBI) so far has benefitted only moderately from using protein biomarkers to improve injury outcome. Because of its complexity and dynamic nature, TBI, especially its most prevalent mild form (mild TBI; mTBI), presents unique challenges toward protein biomarker discovery and validation given that blood is frequently obtained and processed outside of the clinical laboratory (e.g., athletic fields, battlefield) under variable conditions. As it stands, the field of mTBI blood biomarkers faces a number of outstanding questions. Do elevated blood levels of currently used biomarkers-ubiquitin carboxy-terminal hydrolase L1, glial fibrillary acidic protein, neurofilament light chain, and tau/p-tau-truly mirror the extent of parenchymal damage? Do these different proteins represent distinct injury mechanisms? Is the blood-brain barrier a "brick wall"? What is the relationship between intra- versus extracranial values? Does prolonged elevation of blood levels reflect de novo release or extended protein half-lives? Does biological sex affect the pathobiological responses after mTBI and thus blood levels of protein biomarkers? At the practical level, it is unknown how pre-analytical variables-sample collection, preparation, handling, and stability-affect the quality and reliability of biomarker data. The ever-increasing sensitivity of assay systems and lack of quality control of samples, combined with the almost complete reliance on antibody-based assay platforms, represent important unsolved issues given that false-negative results can lead to false clinical decision making and adverse outcomes. This article serves as a commentary on the state of mTBI biomarkers and the landscape of significant challenges. We highlight and discusses several biological and methodological "known unknowns" and close with some practical recommendations.

Proteomics as a reliable approach for discovery of blood-based Alzheimer's disease biomarkers: A systematic review and meta-analysis

In order to gauge the impact of proteomics in discovery of Alzheimer's disease (AD) blood-based biomarkers, this study had systematically reviewed articles published between 1984-2019. Articles that fulfilled the inclusion criteria were assessed for risk of bias. A meta-analysis was performed for replicable candidate biomarkers (CB). Of the 1651 articles that were identified, 17 case-control and two cohort studies, as well as three combined case-control and longitudinal designs were shortlisted. A total of 207 AD and mild cognitive impairment (MCI) CB were discovered, with 48 reported in >2 studies. This review highlights six CB, namely alpha-2-macroglobulin (α2M)_ps, pancreatic polypeptide (PP)_ps, apolipoprotein A-1 (ApoA-1)_ps, afamin_p, insulin growth factor binding protein-2 (IGFBP-2)_ps and fibrinogen-γ-chain_p, all of which exhibited consistent pattern of regulation in >three independent cohorts. They are involved in AD pathogenesis via amyloid-beta (Aβ), neurofibrillary tangles, diabetes and cardiovascular diseases (CVD). Meta-analysis indicated that ApoA-1_ps was significantly downregulated in AD (SMD = -1.52, 95% CI: -1.89, -1.16, p < 0.00001), with low inter-study heterogeneity (I² = 0%, p = 0.59). α2M_ps was significantly upregulated in AD (SMD = 0.83, 95% CI: 0.05, 1.62, p = 0.04), with moderate inter-study heterogeneity (I² = 41%, p = 0.19). Both CB are involved in Aβ formation. These findings provide important insights into blood-based AD biomarkers discovery via proteomics.

A multiple reaction monitoring method for determining peanut (Arachis hypogea) allergens in serum using quadrupole and time-of-flight mass spectrometry

Peanut is a major cause of severe IgE-mediated food allergic reactions, which can be exacerbated by factors, such as exercise, that may increase allergen uptake into the circulation. Enzyme-linked immunosorbent assays (ELISAs) have been used to determine allergen uptake into serum, but there are concerns over their specificity and a confirmatory method is required. Mass spectrometry (MS) methods have the potential to provide rigorous alternatives for allergen determination. A suite of peptide targets representing the major clinically relevant peanut allergens previously applied in food analysis were used to develop a targeted multiple reaction monitoring (MRM) method for determination of peanut in serum. Depletion of serum using affinity chromatography was found to be essential to allow detection of the peptide targets. A comparison of triple quadrupole and Q-TOF methods showed that one Ara h 2 peptide was only detected by the Q-TOF, the other peptide targets giving similar assay sensitivities with both MS platforms, although transitions for all the peptides were detected more consistently with the Q-TOF. The Q-TOF MRM assay detected peanut from spiked serum more effectively than the triple quadrupole assay, with Ara h 3 being detected down to 3 mg total peanut protein/L of serum, comparable with an Ara h 3-specific ELISA. The poor recoveries observed for both methods are likely due to loss of peanut immune complexes during the serum depletion process. Nevertheless, the Q-TOF MRM method has much promise to confirm the uptake of peanut proteins in serum samples providing immune complexes can be disrupted effectively prior to depletion. Graphical abstract.

Current state of Alzheimer's fluid biomarkers

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with a complex and heterogeneous pathophysiology. The number of people living with AD is predicted to increase; however, there are no disease-modifying therapies currently available and none have been successful in late-stage clinical trials. Fluid biomarkers measured in cerebrospinal fluid (CSF) or blood hold promise for enabling more effective drug development and establishing a more personalized medicine approach for AD diagnosis and treatment. Biomarkers used in drug development programmes should be qualified for a specific context of use (COU). These COUs include, but are not limited to, subject/patient selection, assessment of disease state and/or prognosis, assessment of mechanism of action, dose optimization, drug response monitoring, efficacy maximization, and toxicity/adverse reactions identification and minimization. The core AD CSF biomarkers Aβ42, t-tau, and p-tau are recognized by research guidelines for their diagnostic utility and are being considered for qualification for subject selection in clinical trials. However, there is a need to better understand their potential for other COUs, as well as identify additional fluid biomarkers reflecting other aspects of AD pathophysiology. Several novel fluid biomarkers have been proposed, but their role in AD pathology and their use as AD biomarkers have yet to be validated. In this review, we summarize some of the pathological mechanisms implicated in the sporadic AD and highlight the data for several established and novel fluid biomarkers (including BACE1, TREM2, YKL-40, IP-10, neurogranin, SNAP-25, synaptotagmin, α-synuclein, TDP-43, ferritin, VILIP-1, and NF-L) associated with each mechanism. We discuss the potential COUs for each biomarker.

Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic

Biomarker discovery and development for clinical research, diagnostics and therapy monitoring in clinical trials have advanced rapidly in key areas of medicine - most notably, oncology and cardiovascular diseases - allowing rapid early detection and supporting the evolution of biomarker-guided, precision-medicine-based targeted therapies. In Alzheimer disease (AD), breakthroughs in biomarker identification and validation include cerebrospinal fluid and PET markers of amyloid-β and tau proteins, which are highly accurate in detecting the presence of AD-associated pathophysiological and neuropathological changes. However, the high cost, insufficient accessibility and/or invasiveness of these assays limit their use as viable first-line tools for detecting patterns of pathophysiology. Therefore, a multistage, tiered approach is needed, prioritizing development of an initial screen to exclude from these tests the high numbers of people with cognitive deficits who do not demonstrate evidence of underlying AD pathophysiology. This Review summarizes the efforts of an international working group that aimed to survey the current landscape of blood-based AD biomarkers and outlines operational steps for an effective academic-industry co-development pathway from identification and assay development to validation for clinical use.

The effect of blood sampling and preanalytical processing on human N-glycome

Glycome modulations have been described in the onset and progression of many diseases. Thus, many studies have proposed glycans from blood glycoproteins as disease markers. Astonishingly, little effort has been given unraveling preanalytical conditions potentially influencing glycan analysis prior to blood biomarker studies. In this work, we evaluate for the first time the effect of hemolysis, storage and blood collection, but also influence of various times and temperatures between individual processing steps on the total N-glycome and on a glycan-biomarker score. Venous blood was collected from 10 healthy donors in 11 blood collection tubes with different additives, processed variously to obtain 16 preanalytical variables and N-glycans released from serum or plasma were analyzed by MALDI-TOF-MS and capillary electrophoresis coupled with fluorescence detection (CE-LIF) for the first time. Long time storage of deep frozen samples at -20°C or -80°C exerted only a minor influence on the glycome as demonstrated by CE-LIF. The N-glycome was very stable evidenced by MALDI-TOF when stored at 4°C for at least 48 hours and blood collected in tubes devoid of additives. The glycome was stable upon storage after centrifugation and aliquoting, which is an important information considering future diagnostic applications. Hemolysis, however, negatively correlated with an established glycan score for ovarian cancer, when evaluated by MALDI-TOF-MS measurement by affecting relative intensities of certain glycans, which could lead to false negative / positive results in glycan biomarker studies.

Direct Assessment of Plasma/Serum Sample Quality for Proteomics Biomarker Investigation

Blood proteome analysis for biomarker discovery represents one of the most challenging tasks to be achieved through clinical proteomics due to the sample complexity, such as the extreme heterogeneity of proteins in very dynamic concentrations, and to the observation of proper sampling and storage conditions. Quantitative and qualitative proteomics profiling of plasma and serum could be useful both for the early detection of diseases and for the evaluation of pathological status. Two main sources of variability can affect the precision and accuracy of the quantitative experiments designed for biomarker discovery and validation. These sources are divided into two categories, pre-analytical and analytical, and are often ignored; however, they can contribute to consistent errors and misunderstanding in biomarker research. In this chapter, we review critical pre-analytical and analytical variables that can influence quantitative proteomics. According to guidelines accepted by proteomics community, we propose some recommendations and strategies for a proper proteomics analysis addressed to biomarker studies.

Evolving Relevance of Neuroproteomics in Alzheimer's Disease

Substantial progress in the understanding of the biology of Alzheimer's disease (AD) has been achieved over the past decades. The early detection and diagnosis of AD and other age-related neurodegenerative diseases, however, remain a challenging scientific frontier. Therefore, the comprehensive discovery (relating to all individual, converging or diverging biochemical disease mechanisms), development, validation, and qualification of standardized biological markers with diagnostic and prognostic functions with a precise performance profile regarding specificity, sensitivity, and positive and negative predictive value are warranted.Methodological innovations in the area of exploratory high-throughput technologies, such as sequencing, microarrays, and mass spectrometry-based analyses of proteins/peptides, have led to the generation of large global molecular datasets from a multiplicity of biological systems, such as biological fluids, cells, tissues, and organs. Such methodological progress has shifted the attention to the execution of hypothesis-independent comprehensive exploratory analyses (opposed to the classical hypothesis-driven candidate approach), with the aim of fully understanding the biological systems in physiology and disease as a whole. The systems biology paradigm integrates experimental biology with accurate and rigorous computational modelling to describe and foresee the dynamic features of biological systems. The use of dynamically evolving technological platforms, including mass spectrometry, in the area of proteomics has enabled to rush the process of biomarker discovery and validation for refining significantly the diagnosis of AD. Currently, proteomics-which is part of the systems biology paradigm-is designated as one of the dominant matured sciences needed for the effective exploratory discovery of prospective biomarker candidates expected to play an effective role in aiding the early detection, diagnosis, prognosis, and therapy development in AD.

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

Plasma proteomics reveals coagulation, inflammation, and metabolic shifts in H-type hypertension patients with and without acute ischemic stroke

Systematic profiling of a larger portion of circulating plasma proteome provide opportunities for unbiased discovery of novel markers to improve diagnostic, therapeutic, or predictive accuracy. This study aimed to identify differentially expressed proteins (DEPs) in plasma that could provide overall insight into the molecular changes of both H- type hypertension (HH) and HH-related acute ischemic stroke (AIS). This study used an iTRAQ-based LC-MS/MS proteomics approach to screen for plasma DEPs in HH patients with and without AIS, and controls. After excluding highly abundant plasma proteins, more than 600 proteins, and their relative levels, were identified. Of these, 26 DEPs, each showing > 1.2-fold change, were identified in HH and HH-related AIS patients compared with controls. Bioinformatics analysis revealed that these DEPs were enriched in 21 functional gene ontology items; “blood coagulation” was the most predominant pathway showing enrichment. Of these, eight DEPs were located in the hub position of networks involved with protein-protein interactions. AT-3, CRP, ApoB, and AHSG were further validated in each group by enzyme-linked immune sorbent assays. Comparing HH-related AIS with HH, the areas under the curve for AT-3, CRP, ApoB, and AHSG were 0.698, 0.892, 0.626, and 0.847, respectively. This proteomic profiling study provided enhanced pathophysiological understanding of the regulatory processes involved in coagulation, inflammation, and metabolism, and identified a panel of novel biomarkers for detecting HH-related AIS during its pre-stroke stage.

Biological Markers in Nursing Research

INTRODUCTION

Biobehavioral research requires the ability to objectively measure the presence and/or severity of disease, symptoms and their burden, or to determine the effect of treatment on outcomes. Biomarker research has advanced care for patients across the lifespan. There have been significant advancements in biological marker use for nursing research in recent years. The purposes of this article are to define the characteristics of a valid biomarker; review common biological sources of genetic, hormonal, and proteomic biomarkers with attention to practical strengths, weaknesses, and challenges for specimen selection and quality; and discuss potential use of biomarkers in clinical and research settings.

METHODS

Authors draw on the literature and research experiences to address the issues relevant to incorporating biomarkers into nursing research.

RESULTS AND DISCUSSION

An overview of the practical aspects of incorporating biomarkers into nursing research, and the resultant actual and potential clinical applications, are discussed.

Biomarkers in Sporadic and Familial Alzheimer's Disease

Most forms of Alzheimer's disease (AD) are sporadic (sAD) or inherited in a non-Mendelian fashion, and less than 1% of cases are autosomal-dominant. Forms of sAD do not exhibit familial aggregation and are characterized by complex genetic and environmental interactions. Recently, the expansion of genomic methodologies, in association with substantially larger combined cohorts, has resulted in various genome-wide association studies that have identified several novel genetic associations of AD. Currently, the most effective methods for establishing the diagnosis of AD are defined by multi-modal pathways, starting with clinical and neuropsychological assessment, cerebrospinal fluid (CSF) analysis, and brain-imaging procedures, all of which have significant cost- and access-to-care barriers. Consequently, research efforts have focused on the development and validation of non-invasive and generalizable blood-based biomarkers. Among the modalities conceptualized by the systems biology paradigm and utilized in the "exploratory biomarker discovery arena", proteome analysis has received the most attention. However, metabolomics, lipidomics, transcriptomics, and epigenomics have recently become key modalities in the search for AD biomarkers. Interestingly, biomarker changes for familial AD (fAD), in many but not all cases, seem similar to those for sAD. The integration of neurogenetics with systems biology/physiology-based strategies and high-throughput technologies for molecular profiling is expected to help identify the causes, mechanisms, and biomarkers associated with the various forms of AD. Moreover, in order to hypothesize the dynamic trajectories of biomarkers through disease stages and elucidate the mechanisms of biomarker alterations, updated and more sophisticated theoretical models have been proposed for both sAD and fAD.

Comparing biological markers of Alzheimer's disease across blood fraction and platforms: Comparing apples to oranges

Introduction

This study investigated the comparability of potential Alzheimer's disease (AD) biomarkers across blood fractions and assay platforms.

Methods

Nonfasting serum and plasma samples from 300 participants (150 AD patients and 150 controls) were analyzed. Proteomic markers were obtained via electrochemiluminescence or Luminex technology. Comparisons were conducted via Pearson correlations. The relative importance of proteins within an AD diagnostic profile was examined using random forest importance plots.

Results

On the Meso Scale Discovery multiplex platform, 10 of the 21 markers shared >50% of the variance across blood fractions (serum amyloid A R² = 0.99, interleukin (IL)10 R² = 0.95, fatty acid-binding protein (FABP) R² = 0.94, I309 R² = 0.94, IL-5 R² = 0.94, IL-6 R² = 0.94, eotaxin3 R² = 0.91, IL-18 R² = 0.87, soluble tumor necrosis factor receptor 1 R² = 0.85, and pancreatic polypeptide R² = 0.81). When examining protein concentrations across platforms, only five markers shared >50% of the variance (beta 2 microglobulin R² = 0.92, IL-18 R² = 0.80, factor VII R² = 0.78, CRP R² = 0.74, and FABP R² = 0.70).

Discussion

The current findings highlight the importance of considering blood fractions and assay platforms when searching for AD relevant biomarkers.

Neuroproteomic profiling of human body fluids

Analysis of protein expression and abundance provides a possibility to extend the current knowledge on disease-associated processes and pathways. The human brain is a complex organ and dysfunction or damage can give rise to a variety of neurological diseases. Although many proteins potentially reflecting disease progress are originating from brain, the scarce availability of human tissue material has lead to utilization of body fluids such as cerebrospinal fluid and blood in disease-related research. Within the most common neurological disorders, much effort has been spent on studying the role of a few hallmark proteins in disease pathogenesis but despite extensive investigation, the signatures they provide seem insufficient to fully understand and predict disease progress. In order to expand the view the field of neuroproteomics has lately emerged alongside developing technologies, such as affinity proteomics and mass spectrometry, for multiplexed and high-throughput protein profiling. Here, we provide an overview of how such technologies have been applied to study neurological disease and we also discuss some important considerations concerning discovery of disease-associated profiles.

Systems vaccinology: a promise for the young and the poor

As a child, the risk of suffering and dying from infection is higher the younger you are; and higher, the less developed a region you are born in. Childhood vaccination programmes have greatly reduced mortality around the world, but least so for the very young among the very poor of the world. This appears partly owing to suboptimal vaccine effectiveness. Unfortunately, although most vaccines are administered to the newborn and very young infant (less than or equal to two months), we know the least about their host response to vaccination. We thus currently lack the knowledge to guide efforts aimed at improving vaccine effectiveness in this vulnerable population. Systems vaccinology, the study of molecular networks activated by immunization, has begun to provide unprecedented insights into mechanisms leading to vaccine-induced protection from infection or disease. However, all published reports of systems vaccinology have focused on either adults or at most children and older infants, not those most in need, i.e. newborns and very young infants. Given that the tools of systems vaccinology work perfectly well with very small sample volumes, it is time we deliver the promise that systems vaccinology holds for those most in need of vaccine-mediated protection from infection.

Neuroinflammation in Alzheimer's disease

Increasing evidence suggests that Alzheimer's disease pathogenesis is not restricted to the neuronal compartment, but includes strong interactions with immunological mechanisms in the brain. Misfolded and aggregated proteins bind to pattern recognition receptors on microglia and astroglia, and trigger an innate immune response characterised by release of inflammatory mediators, which contribute to disease progression and severity. Genome-wide analysis suggests that several genes that increase the risk for sporadic Alzheimer's disease encode factors that regulate glial clearance of misfolded proteins and the inflammatory reaction. External factors, including systemic inflammation and obesity, are likely to interfere with immunological processes of the brain and further promote disease progression. Modulation of risk factors and targeting of these immune mechanisms could lead to future therapeutic or preventive strategies for Alzheimer's disease.

Can proteomics-based diagnostics aid clinical psychiatry?

Despite major advances in infrastructure and instrumentation, proteomics-driven translational applications have not yet yielded the results that the scientific community has envisaged. In this viewpoint, the perspective of proteomics-based diagnostics in the field of clinical psychiatry is explored. The challenges that proteomics faces in the context of translational approaches are outlined and directions toward a successful clinical implementation are provided. Additional challenges that psychiatric disorders pose for clinical proteomics are highlighted and the potential of proteomics-based, blood tests for psychiatric disorders is being assessed. Proteomics offers a valuable toolkit for clinical translation that needs to be handled in a pragmatic manner and with realistic expectations.

Significance of surface charge and shell material of superparamagnetic iron oxide nanoparticle (SPION) based core/shell nanoparticles on the composition of the protein corona

We showed that protein corona is strongly dependent on the coating of the material.

Solid-phase extraction strategies to surmount body fluid sample complexity in high-throughput mass spectrometry-based proteomics

For large-scale and standardized applications in mass spectrometry- (MS-) based proteomics automation of each step is essential. Here we present high-throughput sample preparation solutions for balancing the speed of current MS-acquisitions and the time needed for analytical workup of body fluids. The discussed workflows reduce body fluid sample complexity and apply for both bottom-up proteomics experiments and top-down protein characterization approaches. Various sample preparation methods that involve solid-phase extraction (SPE) including affinity enrichment strategies have been automated. Obtained peptide and protein fractions can be mass analyzed by direct infusion into an electrospray ionization (ESI) source or by means of matrix-assisted laser desorption ionization (MALDI) without further need of time-consuming liquid chromatography (LC) separations.

Guidelines for the standardization of preanalytic variables for blood-based biomarker studies in Alzheimer's disease research

The lack of readily available biomarkers is a significant hindrance toward progressing to effective therapeutic and preventative strategies for Alzheimer's disease (AD). Blood-based biomarkers have potential to overcome access and cost barriers and greatly facilitate advanced neuroimaging and cerebrospinal fluid biomarker approaches. Despite the fact that preanalytical processing is the largest source of variability in laboratory testing, there are no currently available standardized preanalytical guidelines. The current international working group provides the initial starting point for such guidelines for standardized operating procedures (SOPs). It is anticipated that these guidelines will be updated as additional research findings become available. The statement provides (1) a synopsis of selected preanalytical methods utilized in many international AD cohort studies, (2) initial draft guidelines/SOPs for preanalytical methods, and (3) a list of required methodological information and protocols to be made available for publications in the field to foster cross-validation across cohorts and laboratories.

Alzheimer's and Parkinson's diseases: an environmental proteomic point of view

Alzheimer's and Parkinson's diseases are severe neurodegenerative conditions triggered by complex biochemical routes. Many groups are currently pursuing the search for valuable biomarkers to either perform early diagnostic or to follow the disease's progress. Several studies have reported relevant findings regarding environmental issues and the progression of such diseases. Here the etiology and mechanisms of these diseases are briefly reviewed. Approaches that might reveal candidate biomarkers and environmental stressors associated to the diseases were analyzed under a proteomic perspective. This article is part of a Special Issue entitled: Environmental and structural proteomics.

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers.

Combination of surface imprinting and immobilized template techniques for preparation of core-shell molecularly imprinted polymers based on directly amino-modified Fe3O4 nanoparticles for specific recognition of bovine hemoglobin

In this work, the core-shell bovine hemoglobin (BHb)-imprinted superparamagnetic nanoparticles (Fe₃O₄@BHb-MIPs) were synthesized by combining for the first time a surface imprinting technique and a two-step immobilized template strategy. Initially, amino-functionalized Fe₃O₄ nanoparticles (Fe₃O₄@NH₂) were synthesized directly through a facile one-pot hydrothermal method. Next, BHb was immobilized on the surface of Fe₃O₄@NH₂ through non-covalent interactions. Then, siloxane co-polymerization on the Fe₃O₄@NH₂-protein complex surface resulted in a polymeric network molded around BHb which then became further immobilized. Finally, a thin polymer layer with specific recognition cavities for BHb was formed on the surface of Fe₃O₄@NH₂ after the removal of the template protein. The morphology and structure property of the prepared magnetic nanoparticles were characterized by transmission electronic microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR), X-ray diffractometer (XRD), and vibrating sample magnetometer (VSM). To obtain the best selectivity and binding performance, the polymerization and adsorption conditions were investigated in detail. Under the optimized conditions, the Fe₃O₄@BHb-MIPs exhibited fast adsorption kinetics, large binding capacity, significant selectivity, and favorable reproducibility. The resultant Fe₃O₄@BHb-MIPs could not only specifically extract BHb from a mixed standard protein mixture, but also selectively enriched BHb from a real bovine blood sample. In addition, the synthetic process was quite simple and the stability and regeneration of the Fe₃O₄@BHb-MIPs were also satisfactory.

MRM for the verification of cancer biomarker proteins: recent applications to human plasma and serum

Accurate cancer biomarkers are needed for early detection, disease classification, prediction of therapeutic response and monitoring treatment. While there appears to be no shortage of candidate biomarker proteins, a major bottleneck in the biomarker pipeline continues to be their verification by enzyme linked immunosorbent assays. Multiple reaction monitoring (MRM), also known as selected reaction monitoring, is a targeted mass spectrometry approach to protein quantitation and is emerging to bridge the gap between biomarker discovery and clinical validation. Highly multiplexed MRM assays are readily configured and enable simultaneous verification of large numbers of candidates facilitating the development of biomarker panels which can increase specificity. This review focuses on recent applications of MRM to the analysis of plasma and serum from cancer patients for biomarker verification. The current status of this approach is discussed along with future directions for targeted mass spectrometry in clinical biomarker validation.

The future of blood-based biomarkers for Alzheimer's disease

Treatment of Alzheimer's disease (AD) is significantly hampered by the lack of easily accessible biomarkers that can detect disease presence and predict disease risk reliably. Fluid biomarkers of AD currently provide indications of disease stage; however, they are not robust predictors of disease progression or treatment response, and most are measured in cerebrospinal fluid, which limits their applicability. With these aspects in mind, the aim of this article is to underscore the concerted efforts of the Blood-Based Biomarker Interest Group, an international working group of experts in the field. The points addressed include: (1) the major challenges in the development of blood-based biomarkers of AD, including patient heterogeneity, inclusion of the "right" control population, and the blood-brain barrier; (2) the need for a clear definition of the purpose of the individual markers (e.g., prognostic, diagnostic, or monitoring therapeutic efficacy); (3) a critical evaluation of the ongoing biomarker approaches; and (4) highlighting the need for standardization of preanalytical variables and analytical methodologies used by the field.

Design and experimental approach to the construction of a human signal-molecule-profiling database

The human signal-molecule-profiling database (HSMPD) is designed as a prospective medical database for translational bioinformatics (TBI). To explore the feasibility of low-cost database construction, we studied the roadmap of HSMPD. A HSMPD-oriented tool, called “signal-molecule-profiling (SMP) chip” was developed for data acquisition, which can be employed in the routine blood tests in hospitals; the results will be stored in the HSMPD system automatically. HSMPD system can provide data services for the TBI community, which generates a stable income to support the data acquisition. The small-scale experimental test was performed in the hospital to verify SMP chips and the demo HSMPD software. One hundred and eighty nine complete SMP records were collected, and the demo HSMPD system was also evaluated in the survey study on patients and doctors. The function of SMP chip was verified, whereas the demo HSMPD software needed to be improved. The survey study showed that patients would only accept free tests of SMP chips when they originally needed blood examinations. The study indicated that the construction of HSMPD relies on the self-motivated cooperation of the TBI community and the traditional healthcare system. The proposed roadmap potentially provides an executable solution to build the HSMPD without high costs.

Perspective on future role of biological markers in clinical therapy trials of Alzheimer's disease: a long-range point of view beyond 2020

Recent advances in understanding the molecular mechanisms underlying various paths toward the pathogenesis of Alzheimer's disease (AD) has begun to provide new insight for interventions to modify disease progression. The evolving knowledge gained from multidisciplinary basic research has begun to identify new concepts for treatments and distinct classes of therapeutic targets; as well as putative disease-modifying compounds that are now being tested in clinical trials. There is a mounting consensus that such disease modifying compounds and/or interventions are more likely to be effectively administered as early as possible in the cascade of pathogenic processes preceding and underlying the clinical expression of AD. The budding sentiment is that "treatments" need to be applied before various molecular mechanisms converge into an irreversible pathway leading to morphological, metabolic and functional alterations that characterize the pathophysiology of AD. In light of this, biological indicators of pathophysiological mechanisms are desired to chart and detect AD throughout the asymptomatic early molecular stages into the prodromal and early dementia phase. A major conceptual development in the clinical AD research field was the recent proposal of new diagnostic criteria, which specifically incorporate the use of biomarkers as defining criteria for preclinical stages of AD. This paradigm shift in AD definition, conceptualization, operationalization, detection and diagnosis represents novel fundamental opportunities for the modification of interventional trial designs. This perspective summarizes not only present knowledge regarding biological markers but also unresolved questions on the status of surrogate indicators for detection of the disease in asymptomatic people and diagnosis of AD.

Pre-analytical and analytical variability in absolute quantitative MRM-based plasma proteomic studies

Quantitative plasma proteomics, through the use of targeted MRM-MS and isotopically labeled standards, is emerging as a popular technique to address biological- and biomedical-centered queries. High precision and accuracy are essential in such measurements, particularly in protein biomarker research where translation to the clinic is sought. Standardized procedures and routine performance evaluation of all stages of the workflow (both pre-analytical and analytical) are therefore imperative to satisfy these requisites and enable high inter-laboratory reproducibility and transferability. In this review, we first discuss the pre-analytical and analytical variables that can affect the precision and accuracy of ‘absolute’ quantitative plasma proteomic measurements. Proposed strategies to limit such variability will then be highlighted and unmet needs for future exploration will be noted. Although there is no way to conduct a truly comprehensive review on this broad, rapidly changing topic, we have highlighted key aspects and included references to review articles on various sub-topics.

Biomarkers for Alzheimer's disease in plasma, serum and blood - conceptual and practical problems

Substances produced throughout the body are detectable in the blood, which is the most common biological fluid used in clinical testing. Biomarkers for Alzheimer's disease (AD) have long been sought in the blood, but none has become an established or validated diagnostic test. Companion reviews in Alzheimer's Research & Therapy will review specific types of biomarkers or applications; in this overview, we cover key concepts related to AD blood biomarker studies in general. Reasons for the difficulty of detecting markers of a brain-specific disorder, such as AD, in the blood are outlined; these pose conceptual challenges for blood biomarker discovery and development. Applications of blood tests in AD go beyond screening and diagnostic testing; other potential uses are risk assessment, prognostication, and evaluation of treatment target engagement, toxicity, and outcome. Opportunities and questions that may surround these different uses are discussed. A systematic approach to biomarker discovery, detection, assay development and quality control, sample collection, handling and storage, and design and analysis of clinical studies needs to be implemented at every step of discovery and translation to identify an interpretable and useful biomarker.

Liposomes and nanotechnology in drug development: focus on neurological targets

Neurological diseases represent a medical, social, and economic problem of paramount importance in developed countries. Although their etiology is generally known, developing therapeutic interventions for the central nervous system is challenging due to the impermeability of the blood-brain barrier. Thus, the fight against neurological diseases usually struggles "at the gates" of the brain. Flooding the bloodstream with drugs, where only a minor fraction reaches its target therapeutic site, is an inefficient, expensive, and dangerous procedure, because of the risk of side effects at nontargeted sites. Currently, advances in the field of nanotechnology have enabled development of a generation of multifunctional molecular platforms that are capable of transporting drugs across the blood-brain barrier, targeting specific cell types or functional states within the brain, releasing drugs in a controlled manner, and enabling visualization of processes in vivo using conventional imaging systems. The marriage between drug delivery and molecular imaging disciplines has resulted in a relatively new discipline, known as theranostics, which represents the basis of the concept of personalized medicine. In this study, we review the concepts of the blood-brain barrier and the strategies used to traverse/bypass it, the role of nanotechnology in theranostics, the wide range of nanoparticles (with emphasis on liposomes) that can be used as stealth drug carriers, imaging probes and targeting devices for the treatment of neurological diseases, and the targets and targeting strategies envisaged in the treatment of different types of brain pathology.