Proteomic Approaches for the Discovery of Biofluid Biomarkers of Neurodegenerative Dementias

A multilayer network analysis of Alzheimer's disease pathogenesis: Roles for p-tau, synaptic peptides, and physical activity

INTRODUCTION

In the aging brain, cognitive abilities emerge from the coordination of complex pathways arising from a balance between protective lifestyle and environmental factors and accumulation of neuropathologies.

METHODS

As part of the Rush Memory and Aging Project (n = 440), we measured accelerometer-based actigraphy, cognitive performance, and after brain autopsy, selected reaction monitoring mass spectrometry. Multilevel network analysis was used to examine the relationships among the molecular machinery of vesicular neurotransmission, Alzheimer's disease (AD) neuropathology, cognition, and late-life physical activity.

RESULTS

Synaptic peptides involved in neuronal secretory function were the most influential contributors to the multilayer network, reflecting the complex interdependencies among AD pathology, synaptic processes, and late-life cognition. Older adults with lower physical activity evidenced stronger adverse relationships among phosphorylated tau peptides, markers of synaptic integrity, and tangle pathology.

DISCUSSION

Network-based approaches simultaneously model interdependent biological processes and advance understanding of the role of physical activity in age-associated cognitive impairment.

HIGHLIGHTS

Network-based approaches simultaneously model interdependent biological processes. Secretory synaptic peptides were influential contributors to the multilayer network. Older adults with lower physical activity had adverse relationships among pathology. There was interdependence among phosphorylated tau, synaptic integrity, and tangles. Network methods elucidate the role of physical activity in cognitive impairment.

Interrogation of the human cortical peptidome uncovers cell-type specific signatures of cognitive resilience against Alzheimer's disease

Alzheimer's disease (AD) is characterised by age-related cognitive decline. Brain accumulation of amyloid-β plaques and tau tangles is required for a neuropathological AD diagnosis, yet up to one-third of AD-pathology positive community-dwelling elderly adults experience no symptoms of cognitive decline during life. Conversely, some exhibit chronic cognitive impairment in absence of measurable neuropathology, prompting interest into cognitive resilience-retained cognition despite significant neuropathology-and cognitive frailty-impaired cognition despite low neuropathology. Synapse loss is widespread within the AD-dementia, but not AD-resilient, brain. Recent evidence points towards critical roles for synaptic proteins, such as neurosecretory VGF, in cognitive resilience. However, VGF and related proteins often signal as peptide derivatives. Here, nontryptic peptidomic mass spectrometry was performed on 102 post-mortem cortical samples from individuals across cognitive and neuropathological spectra. Neuropeptide signalling proteoforms derived from VGF, somatostatin (SST) and protachykinin-1 (TAC1) showed higher abundance in AD-resilient than AD-dementia brain, whereas signalling proteoforms of cholecystokinin (CCK) and chromogranin (CHG) A/B and multiple cytoskeletal molecules were enriched in frail vs control brain. Integrating our data with publicly available single nuclear RNA sequencing (snRNA-seq) showed enrichment of cognition-related genes in defined cell-types with established links to cognitive resilience, including SST interneurons and excitatory intratelencephalic cells.

Induced-pluripotent stem cells and neuroproteomics as tools for studying neurodegeneration

The investigation of neurodegenerative diseases advanced significantly with the advent of cell-reprogramming technology, leading to the creation of new models of human illness. These models, derived from induced pluripotent stem cells (iPSCs), facilitate the study of sporadic as well as hereditary diseases and provide a comprehensive understanding of the molecular mechanisms involved with neurodegeneration. Through proteomics, a quantitative tool capable of identifying thousands of proteins from small sample volumes, researchers have attempted to identify disease mechanisms by detecting differentially expressed proteins and proteoforms in disease models, biofluids, and postmortem brain tissue. The integration of these two technologies allows for the identification of novel pathological targets within the realm of neurodegenerative diseases. Here, we highlight studies from the past 5 years on the contributions of iPSCs within neuroproteomic investigations, which uncover the molecular mechanisms behind these illnesses.

Data-independent acquisition proteomics of cerebrospinal fluid implicates endoplasmic reticulum and inflammatory mechanisms in amyotrophic lateral sclerosis

While unbiased proteomics of human cerebrospinal fluid (CSF) has been used successfully to identify biomarkers of amyotrophic lateral sclerosis (ALS), high-abundance proteins mask the presence of lower abundance proteins that may have diagnostic and prognostic value. However, developments in mass spectrometry (MS) proteomic data acquisition methods offer improved protein depth. In this study, MS with library-free data-independent acquisition (DIA) was used to compare the CSF proteome of people with ALS (n = 40), healthy (n = 15) and disease (n = 8) controls. Quantified protein groups were subsequently correlated with clinical variables. Univariate analysis identified 7 proteins, all significantly upregulated in ALS versus healthy controls, and 9 with altered abundance in ALS versus disease controls (FDR < 0.1). Elevated chitotriosidase-1 (CHIT1) was common to both comparisons and was proportional to ALS disability progression rate (Pearson r = 0.41, FDR-adjusted p = 0.035) but not overall survival. Ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1; upregulated in ALS versus healthy controls) was proportional to disability progression rate (Pearson r = 0.53, FDR-adjusted p = 0.003) and survival (Kaplan Meier log-rank p = 0.013) but not independently in multivariate proportional hazards models. Weighted correlation network analysis was used to identify functionally relevant modules of proteins. One module, enriched for inflammatory functions, was associated with age at symptom onset (Pearson r = 0.58, FDR-adjusted p = 0.005) and survival (Hazard Ratio = 1.78, FDR = 0.065), and a second module, enriched for endoplasmic reticulum proteins, was negatively correlated with disability progression rate (r = -0.42, FDR-adjusted p = 0.109). DIA acquisition methodology therefore strengthened the biomarker candidacy of CHIT1 and UCHL1 in ALS, while additionally highlighted inflammatory and endoplasmic reticulum proteins as novel sources of prognostic biomarkers.

Identifying Sex-Specific Serum Patterns of Alzheimer's Mice through Deep TMT Profiling and a Concentration-Dependent Concatenation Strategy

Alzheimer's disease (AD) is the most prevalent form of dementia, disproportionately affecting women in disease prevalence and progression. Comprehensive analysis of the serum proteome in a common AD mouse model offers potential in identifying possible AD pathology- and gender-associated biomarkers. Here, we introduce a multiplexed, nondepleted mouse serum proteome profiling via tandem mass-tag (TMTpro) labeling. The labeled sample was separated into 475 fractions using basic reversed-phase liquid chromatography (RPLC), which were categorized into low-, medium-, and high-concentration fractions for concatenation. This concentration-dependent concatenation strategy resulted in 128 fractions for acidic RPLC-tandem mass spectrometry (MS/MS) analysis, collecting ∼5 million MS/MS scans and identifying 3972 unique proteins (3413 genes) that cover a dynamic range spanning at least 6 orders of magnitude. The differential expression analysis between wild type and the commonly used AD model (5xFAD) mice exhibited minimal significant protein alterations. However, we detected 60 statistically significant (FDR < 0.05), sex-specific proteins, including complement components, serpins, carboxylesterases, major urinary proteins, cysteine-rich secretory protein 1, pregnancy-associated murine protein 1, prolactin, amyloid P component, epidermal growth factor receptor, fibrinogen-like protein 1, and hepcidin. The results suggest that our platform possesses the sensitivity and reproducibility required to detect sex-specific differentially expressed proteins in mouse serum samples.

Cerebrospinal and Blood Biomarkers in Alzheimer's Disease: Did Mild Cognitive Impairment Definition Affect Their Clinical Usefulness?

Despite Alzheimer's Disease (AD) being known from the times of Alois Alzheimer, who lived more than one century ago, many aspects of the disease are still obscure, including the pathogenesis, the clinical spectrum definition, and the therapeutic approach. Well-established biomarkers for AD come from the histopathological hallmarks of the disease, which are Aβ and phosphorylated Tau protein aggregates. Consistently, cerebrospinal fluid (CSF) Amyloid β (Aβ) and phosphorylated Tau level measurements are currently used to detect AD presence. However, two central biases affect these biomarkers. Firstly, incomplete knowledge of the pathogenesis of diseases legitimates the search for novel molecules that, reasonably, could be expressed by neurons and microglia and could be detected in blood simpler and earlier than the classical markers and in a higher amount. Further, studies have been performed to evaluate whether CSF biomarkers can predict AD onset in Mild Cognitive Impairment (MCI) patients. However, the MCI definition has changed over time. Hence, the studies on MCI patients seem to be biased at the beginning due to the imprecise enrollment and heterogeneous composition of the miscellaneous MCI subgroup. Plasma biomarkers and novel candidate molecules, such as microglia biomarkers, have been tentatively investigated and could represent valuable targets for diagnosing and monitoring AD. Also, novel AD markers are urgently needed to identify molecular targets for treatment strategies. This review article summarizes the main CSF and blood AD biomarkers, underpins their advantages and flaws, and mentions novel molecules that can be used as potential biomarkers for AD.

Research progress on the role of extracellular vesicles in neurodegenerative diseases

Neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease, affect millions of people worldwide. Tremendous efforts have been put into disease-related research, but few breakthroughs have been made in diagnostic and therapeutic approaches. Extracellular vesicles (EVs) are heterogeneous cell-derived membrane structures that arise from the endosomal system or are directly separated from the plasma membrane. EVs contain many biomolecules, including proteins, nucleic acids, and lipids, which can be transferred between different cells, tissues, or organs, thereby regulating cross-organ communication between cells during normal and pathological processes. Recently, EVs have been shown to participate in various aspects of neurodegenerative diseases. Abnormal secretion and levels of EVs are closely related to the pathogenesis of neurodegenerative diseases and contribute to disease progression. Numerous studies have proposed EVs as therapeutic targets or biomarkers for neurodegenerative diseases. In this review, we summarize and discuss the advanced research progress on EVs in the pathological processes of several neurodegenerative diseases. Moreover, we outline the latest research on the roles of EVs in neurodegenerative diseases and their therapeutic potential for the diseases.

Large-scale proximity extension assay reveals CSF midkine and DOPA decarboxylase as supportive diagnostic biomarkers for Parkinson's disease

BACKGROUND

There is a need for biomarkers to support an accurate diagnosis of Parkinson's disease (PD). Cerebrospinal fluid (CSF) has been a successful biofluid for finding neurodegenerative biomarkers, and modern highly sensitive multiplexing methods offer the possibility to perform discovery studies. Using a large-scale multiplex proximity extension assay (PEA) approach, we aimed to discover novel diagnostic protein biomarkers allowing accurate discrimination of PD from both controls and atypical Parkinsonian disorders (APD).

METHODS

CSF from patients with PD, corticobasal syndrome (CBS), progressive supranuclear palsy (PSP), multiple system atrophy and controls, were analysed with Olink PEA panels. Three cohorts were used in this study, comprising 192, 88 and 36 cases, respectively. All samples were run on the Cardiovascular II, Oncology II and Metabolism PEA panels.

RESULTS

Our analysis revealed that 26 and 39 proteins were differentially expressed in the CSF of test and validation PD cohorts, respectively, compared to controls. Among them, 6 proteins were changed in both cohorts. Midkine (MK) was increased in PD with the strongest effect size and results were validated with ELISA. Another most increased protein in PD, DOPA decarboxylase (DDC), which catalyses the decarboxylation of DOPA (L-3,4-dihydroxyphenylalanine) to dopamine, was strongly correlated with dopaminergic treatment. Moreover, Kallikrein 10 was specifically changed in APD compared with both PD and controls, but unchanged between PD and controls. Wnt inhibitory factor 1 was consistently downregulated in CBS and PSP patients in two independent cohorts.

CONCLUSIONS

Using the large-scale PEA approach, we have identified potential novel PD diagnostic biomarkers, most notably MK and DDC, in the CSF of PD patients.

Plasma levels of neurology-related proteins are associated with cognitive performance in an older population with overweight/obesity and metabolic syndrome

Cognitive impairment is present in a broad spectrum of medical conditions and in aging. Here, we aimed to identify plasma proteins related to cognitive function in a sample of older adults with overweight/obesity and metabolic syndrome. A total of 129 subjects (mean age 64.7 years; 36% females) were grouped according to low (l-GCF, N=65) or high (h-GCF, N=64) global cognitive function and matched according to education, sex, age, and body mass index. Cognitive performance was assessed using neuropsychological tests. Plasma levels of 92 neurology-related proteins were assessed using a proximity extension assay. An elastic net regression analysis was used to identify proteins more associated with cognitive performance. Additionally, the protein expression levels were compared between the two groups by means of a t-test with false discovery rate correction. Pearson correlations were used to assess associations between the protein levels and scores from the neurocognitive tests. Six proteins (alpha-2-MRAP, HAGH, Siglec-9, MDGA1, IL12, and EDA2R) were identified as potential contributors to cognitive performance, remaining significantly increased in l-GCF compared to h-GCF participants after correction for multiple testing. Negative correlations (r= -0.23 to -0.18, i.e., lower protein levels, higher cognitive function) were found between global cognitive function and Siglec-9, NMNAT1, HAGH, LXN, gal-8, alpha-2-MRAP, IL12, PDGF-R-alpha, NAAA, EDA2R, CLEC1B, and LAT. Mini-mental state examination z scores showed the strongest correlations with protein levels, specifically negative correlations with CLEC1b, LXN, LAT, PLXNB3, NMNAT1, gal-8, HAGH, NAAA, CTSS, EZR, KYNU, MANF (r=-0.38 to -0.26) and a positive correlation with ADAM23 (r= 0.26). In summary, we identified several plasma proteins that were significantly associated with cognitive performance in older adults with obesity and metabolic syndrome, although further research is needed to replicate the results in larger samples and to include a predictive perspective.

Cross-Platform Synaptic Network Analysis of Human Entorhinal Cortex Identifies TWF2 as a Modulator of Dendritic Spine Length

Proteomic studies using postmortem human brain tissue samples have yielded robust assessments of the aging and neurodegenerative disease(s) proteomes. While these analyses provide lists of molecular alterations in human conditions, like Alzheimer's disease (AD), identifying individual proteins that affect biological processes remains a challenge. To complicate matters, protein targets may be highly understudied and have limited information on their function. To address these hurdles, we sought to establish a blueprint to aid selection and functional validation of targets from proteomic datasets. A cross-platform pipeline was engineered to focus on synaptic processes in the entorhinal cortex (EC) of human patients, including controls, preclinical AD, and AD cases. Label-free quantification mass spectrometry (MS) data (n = 2260 proteins) was generated on synaptosome fractionated tissue from Brodmann area 28 (BA28; n = 58 samples). In parallel, dendritic spine density and morphology was measured in the same individuals. Weighted gene co-expression network analysis was used to construct a network of protein co-expression modules that were correlated with dendritic spine metrics. Module-trait correlations were used to guide unbiased selection of Twinfilin-2 (TWF2), which was the top hub protein of a module that positively correlated with thin spine length. Using CRISPR-dCas9 activation strategies, we demonstrated that boosting endogenous TWF2 protein levels in primary hippocampal neurons increased thin spine length, thus providing experimental validation for the human network analysis. Collectively, this study describes alterations in dendritic spine density and morphology as well as synaptic proteins and phosphorylated tau from the entorhinal cortex of preclinical and advanced stage AD patients.SIGNIFICANCE STATEMENT Proteomic studies can yield vast lists of molecules that are altered under various experimental or disease conditions. Here, we provide a blueprint to facilitate mechanistic validation of protein targets from human brain proteomic datasets. We conducted a proteomic analysis of human entorhinal cortex (EC) samples spanning cognitively normal and Alzheimer's disease (AD) cases with a comparison of dendritic spine morphology in the same samples. Network integration of proteomics with dendritic spine measurements allowed for unbiased discovery of Twinfilin-2 (TWF2) as a regulator of dendritic spine length. A proof-of-concept experiment in cultured neurons demonstrated that altering Twinfilin-2 protein level induced corresponding changes in dendritic spine length, thus providing experimental validation for the computational framework.

Variant biomarker discovery using mass spectrometry-based proteogenomics

Genomic diversity plays critical roles in risk of disease pathogenesis and diagnosis. While genomic variants-including single nucleotide variants, frameshift variants, and mis-splicing isoforms-are commonly detected at the DNA or RNA level, their translated variant protein or polypeptide products are ultimately the functional units of the associated disease. These products are often released in biofluids and could be leveraged for clinical diagnosis and patient stratification. Recent emergence of integrated analysis of genomics with mass spectrometry-based proteomics for biomarker discovery, also known as proteogenomics, have significantly advanced the understanding disease risk variants, precise medicine, and biomarker discovery. In this review, we discuss variant proteins in the context of cancers and neurodegenerative diseases, outline current and emerging proteogenomic approaches for biomarker discovery, and provide a comprehensive proteogenomic strategy for detection of putative biomarker candidates in human biospecimens. This strategy can be implemented for proteogenomic studies in any field of enquiry. Our review timely addresses the need of biomarkers for aging related diseases.

A Standardized Protocol for Assuring the Validity of Proteomics Results from Liquid Chromatography-High-Resolution Mass Spectrometry

Significant advances in the technological development of mass spectrometry in the field of proteomics and the generation of extremely large amounts of data require a very critical approach to assure the validity of results. Commonly used procedures involved liquid chromatography followed by high-resolution mass spectrometry measurements. Proteomics analysis is used in many fields including the investigation of the metabolism of biologically active substances in organisms. Thus, there is a need to care about the validity of the obtained results. In this work, we proposed a standardized protocol for proteomic analysis using liquid chromatography-high-resolution mass spectrometry, which covers all of these analytical steps to ensure the validity of the results. For this purpose, we explored the requirements of the ISO/IEC 17025:2017 standard as a reference document for quality control in biochemistry research-based mass spectrometry.

Recent advances in top-down proteome sample processing ahead of MS analysis

Top-down proteomics is emerging as a preferred approach to investigate biological systems, with objectives ranging from the detailed assessment of a single protein therapeutic, to the complete characterization of every possible protein including their modifications, which define the human proteoform. Given the controlling influence of protein modifications on their biological function, understanding how gene products manifest or respond to disease is most precisely achieved by characterization at the intact protein level. Top-down mass spectrometry (MS) analysis of proteins entails unique challenges associated with processing whole proteins while maintaining their integrity throughout the processes of extraction, enrichment, purification, and fractionation. Recent advances in each of these critical front-end preparation processes, including minimalistic workflows, have greatly expanded the capacity of MS for top-down proteome analysis. Acknowledging the many contributions in MS technology and sample processing, the present review aims to highlight the diverse strategies that have forged a pathway for top-down proteomics. We comprehensively discuss the evolution of front-end workflows that today facilitate optimal characterization of proteoform-driven biology, including a brief description of the clinical applications that have motivated these impactful contributions.

Structural Proteomic Profiling of Cerebrospinal Fluids to Reveal Novel Conformational Biomarkers for Alzheimer's Disease

Alzheimer's disease (AD) is the most common representation of dementia, with brain pathological hallmarks of protein abnormal aggregation, such as with amyloid beta and tau protein. It is well established that posttranslational modifications on tau protein, particularly phosphorylation, increase the likelihood of its aggregation and subsequent formation of neurofibrillary tangles, another hallmark of AD. As additional misfolded proteins presumably exist distinctly in AD disease states, which would serve as potential source of AD biomarkers, we used limited proteolysis-coupled with mass spectrometry (LiP-MS) to probe protein structural changes. After optimizing the LiP-MS conditions, we further applied this method to human cerebrospinal fluid specimens collected from healthy control, mild cognitive impairment (MCI), and AD subject groups to characterize proteome-wide misfolding tendencies as a result of disease progression. The fully tryptic peptides embedding LiP sites were compared with the half-tryptic peptides generated from internal cleavage of the same region to determine any structural unfolding or misfolding. We discovered hundreds of significantly up- and down-regulated peptides associated with MCI and AD indicating their potential structural changes in AD progression. Moreover, we detected 53 structurally changed regions in 12 proteins with high confidence between the healthy control and disease groups, illustrating the functional relevance of these proteins with AD progression. These newly discovered conformational biomarker candidates establish valuable future directions for exploring the molecular mechanism of designing therapeutic targets for AD.

Unraveling protein dynamics to understand the brain - the next molecular frontier

The technological revolution to measure global gene expression at the single-cell level is currently transforming our knowledge of the brain and neurological diseases, leading from a basic understanding of genetic regulators and risk factors to one of more complex gene interactions and biological pathways. Looking ahead, our next challenge will be the reliable measurement and understanding of proteins. We describe in this review how to apply new, powerful methods of protein labeling, tracking, and detection. Recent developments of these methods now enable researchers to uncover protein mechanisms in vivo that may previously have only been hypothesized. These methods are also useful for discovering new biology because how proteins regulate systemic interactions is not well understood in most cases, such as how they travel through the bloodstream to distal targets or cross the blood–brain barrier. Genetic sequencing of DNA and RNA have enabled many great discoveries in the past 20 years, and now, the protein methods described here are creating a more complete picture of how cells to whole organisms function. It is likely that these developments will generate another transformation in biomedical research and our understanding of the brain and will ultimately allow for patient-specific medicine on a protein level.

Technical Performance Evaluation of Olink Proximity Extension Assay for Blood-Based Biomarker Discovery in Longitudinal Studies of Alzheimer's Disease

The core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers; amyloid-β (Aß), total tau (t-tau), and phosphorylated tau (p-tau181), are strong indicators of the presence of AD pathology, but do not correlate well with disease progression, and can be difficult to implement in longitudinal studies where repeat biofluid sampling is required. As a result, blood-based biomarkers are increasingly being sought as alternatives. In this study, we aimed to evaluate a promising blood biomarker discovery technology, Olink Proximity Extension Assays for technical reproducibility characteristics in order to highlight the advantages and disadvantages of using this technology in biomarker discovery in AD. We evaluated the performance of five Olink Proteomic multiplex proximity extension assays (PEA) in plasma samples. Three technical control samples included on each plate allowed calculation of technical variability. Biotemporal stability was measured in three sequential annual samples from 54 individuals with and without AD. Coefficients of variation (CVs), analysis of variance (ANOVA), and variance component analyses were used to quantify technical and individual variation over time. We show that overall, Olink assays are technically robust, with the largest experimental variation stemming from biological differences between individuals for most analytes. As a powerful illustration of one of the potential pitfalls of using a multi-plexed technology for discovery, we performed power calculations using the baseline samples to demonstrate the size of study required to overcome the need for multiple test correction with this technology. We show that the power of moderate effect size proteins was strongly reduced, and as a result investigators should strongly consider pooling resources to perform larger studies using this multiplexed technique where possible.

Mass Spectrometry Based Protein Biomarkers and Drug Target Discovery and Clinical Diagnosis in Age-Related Progressing Neurodegenerative Diseases

Neurodegenerative diseases correspond to overly complex health disorders that are driven by intersecting pathophysiology that are often trapped in vicious cycles of degeneration and cognitive decline. The usual diagnostic route of these diseases is based on postmortem examination that involves identifying pathology that is specific to the disease in the brain. However, in such cases, accurate diagnosis of the specific disease is limited because clinical disease presentations are often complex that do not easily allow to discriminate patient's cognitive, behavioral, and functional impairment profiles. Additionally, an early identification and therapeutic intervention of these diseases is pivotal to slow the progression of neurodegeneration and extend healthy life span. Mass spectrometry-based techniques have proven to be hugely promising in biological sample analysis and discovery of biomarkers including protein and peptide biomarkers for potential drug target discovery. Recent studies on these biomarkers have demonstrated their potential for applications in early diagnostics and identifying therapeutic targets to battle against neurodegenerative diseases. In this review, we have presented principles of mass spectrometry (MS) and the associated workflows in analyzing and imaging biological samples for discovery of biomarkers. We have especially focused on age- related progressing neurodegenerative diseases such as Alzheimer's (AD) and Parkinson's disease (PD), Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal dementia (FTD) and the related MS-based biomarkers developments for these diseases. Finally, we present a future perspective discussing the potential research directions ahead.

Online μSEC2-nRPLC-MS for Improved Sensitivity of Intact Protein Detection of IEF-Separated Nonhuman Primate Cerebrospinal Fluid Proteins

Proteoform-resolved information, obtained by top-down (TD) "intact protein" proteomics, is expected to contribute substantially to the understanding of molecular pathogenic mechanisms and, in turn, identify novel therapeutic and diagnostic targets. However, the robustness of mass spectrometry (MS) analysis of intact proteins in complex biological samples is hindered by the high dynamic range in protein concentration and mass, protein instability, and buffer complexity. Here, we describe an evolutionary step for intact protein investigations through the online implementation of tandem microflow size-exclusion chromatography with nanoflow reversed-phase liquid chromatography and MS (μSEC2-nRPLC-MS). Online serial high-/low-pass SEC filtration overcomes the aforementioned hurdles to intact proteomic analysis through automated sample desalting/cleanup and enrichment of target mass ranges (5-155 kDa) prior to nRPLC-MS. The coupling of μSEC to nRPLC is achieved through a novel injection volume control (IVC) strategy of inserting protein trap columns, pre- and post-μSEC columns, to enable injection of dilute samples in high volumes without loss of sensitivity or resolution. Critical characteristics of the approach are tested via rigorous investigations on samples of varied complexity and chemical background. Application of the platform to cerebrospinal fluid (CSF) prefractionated by OFFGEL isoelectric focusing drastically increases the number of intact mass tags (IMTs) detected within the target mass range (5-30 kDa) in comparison to one-dimensional nRPLC-MS with approximately 100× less CSF than previous OFFGEL studies. Furthermore, the modular design of the μSEC2-nRPLC-MS platform is robust and promises significant flexibility for large-scale TDMS analysis of diverse samples either directly or in concert with other multidimensional fractionation steps.

Comparison of proteomic methods in evaluating biomarker-AKI associations in cardiac surgery patients

Although immunoassays are the most widely used protein measurement method, aptamer-based methods such as the SomaScan platform can quantify up to 7000 proteins per biosample, creating new opportunities for unbiased discovery. However, there is limited research comparing the consistency of biomarker-disease associations between immunoassay and aptamer-based platforms. In a substudy of the TRIBE-AKI cohort, preoperative and postoperative plasma samples from 294 patients with previous immunoassay measurements were analyzed using the SomaScan platform. Inter-platform Spearman correlations (r_s) and biomarker-AKI associations were compared across 30 preoperative and 34 postoperative immunoassay-aptamer pairs. Possible factors contributing to inter-platform differences were examined including target protein characteristics, immunoassay, and SomaScan coefficients of variation, other assay characteristics, and sample storage time. The median r_s was 0.54 (interquartile range [IQR] 0.34-0.83) in postoperative samples and 0.41 (IQR 0.21-0.69) in preoperative samples. We observed a trend of greater r_s in biomarkers with greater concentrations; the Spearman correlation between the concentration of protein and the inter-platform correlation was 0.64 in preoperative pairs and 0.53 in postoperative pairs. Of proteins measured by immunoassays, we observed significant biomarker-AKI associations for 13 proteins preop and 24 postop; of all corresponding aptamers, 8 proteins preop and 12 postop. All proteins significantly associated with AKI as measured by SomaScan were also significantly associated with AKI as measured by immunoassay. All biomarker-AKI odds ratios were significantly different (P < 0.05) between platforms in 14% of aptamer-immunoassay pairs, none of which had high (r_s > 0.50) inter-platform correlations. Although similar biomarker-disease associations were observed overall, biomarkers with high physiological concentrations tended to have the highest-confidence inter-platform operability in correlations and biomarker-disease associations. Aptamer assays provide excellent precision and an unprecedented coverage and promise for disease associations but interpretation of results should keep in mind a broad range of correlations with immunoassays.

Advancing mechanistic understanding and biomarker development in amyotrophic lateral sclerosis

INTRODUCTION

Proteomic analysis has contributed significantly to the study of the neurodegenerative disease amyotrophic lateral sclerosis (ALS). It has helped to define the pathological change common to nearly all cases, namely intracellular aggregates of phosphorylated TDP-43, shifting the focus of pathogenesis in ALS toward RNA biology. Proteomics has also uniquely underpinned the delineation of disease mechanisms in model systems and has been central to recent advances in human ALS biomarker development.

AREAS COVERED

The contribution of proteomics to understanding the cellular pathological changes, disease mechanisms, and biomarker development in ALS are covered.

EXPERT OPINION

Proteomics has delivered unique insights into the pathogenesis of ALS and advanced the goal of objective measurements of disease activity to improve therapeutic trials. Further developments in sensitivity and quantification are expected, with application to the presymptomatic phase of human disease offering the hope of prevention strategies.

Molecular Pathways Involved in Frontotemporal Lobar Degeneration with TDP-43 Proteinopathy: What Can We Learn from Proteomics?

Frontotemporal lobar degeneration (FTLD) is a neurodegenerative disorder clinically characterized by behavioral, language, and motor symptoms, with major impact on the lives of patients and their families. TDP-43 proteinopathy is the underlying neuropathological substrate in the majority of cases, referred to as FTLD-TDP. Several genetic causes have been identified, which have revealed some components of its pathophysiology. However, the exact mechanisms driving FTLD-TDP remain largely unknown, forestalling the development of therapies. Proteomic approaches, in particular high-throughput mass spectrometry, hold promise to help elucidate the pathogenic molecular and cellular alterations. In this review, we describe the main findings of the proteomic profiling studies performed on human FTLD-TDP brain tissue. Subsequently, we address the major biological pathways implicated in FTLD-TDP, by reviewing these data together with knowledge derived from genomic and transcriptomic literature. We illustrate that an integrated perspective, encompassing both proteomic, genetic, and transcriptomic discoveries, is vital to unravel core disease processes, and to enable the identification of disease biomarkers and therapeutic targets for this devastating disorder.

Evaluation of the Sensitivity and Reproducibility of Targeted Proteomic Analysis Using Data-Independent Acquisition for Serum and Cerebrospinal Fluid Proteins

There is a need for targeted analysis of biological fluids for diagnosis, prognosis, or monitoring the progression of diseases. Cerebrospinal fluid (CSF) and serum have been widely used for the development of protein analysis for neurodegenerative diseases and other diseases, respectively. Recently, data-independent acquisition (DIA) mass spectrometry (MS) has been developed to increase the throughput over data-dependent acquisition (DDA) on screening of a large number of samples and discovery of candidate targets. When it comes to target validation, the analytical performance of targeted analysis is critical. However, the inter- and intralaboratory analytical performances of the DIA-MS for targeted proteomic analysis of CSF and serum samples have not yet been investigated. In this study, we showed that the DIA-MS approach allowed us to identify and quantify 1732 CSF and 424 serum proteins, with 90% of proteins identified and quantified in at least 50% of DIA-MS runs. To evaluate the sensitivity, linearity, and dynamic range of the DIA approach, we included the stable isotope-labeled (SI) peptides into CSF and serum samples with serial dilutions. The lower limit of quantification (LLOQ) of peptides was 0.1-0.5 fmol, and the dynamic range was over 3.53 orders of magnitude, with excellent linearity (r2 < 0.978) in CSF and serum samples. Finally, the reproducibility of the DIA-MS approach was evaluated using entire proteins identified in CSF and serum samples. The intralaboratory three replicate results showed reliable reproducibility with 12.5 and 17.3% of the median coefficient of variation (CV) in both CSF and serum matrices, whereas the median CVs of interlaboratory three replicates were 23.8 and 32.0% in CSF and serum samples, respectively. The comparison of the quantitative result between replicates showed close similarity at intra- and interlaboratories with a median Pearson correlation value of >0.98 in CSF and serum, respectively. In conclusion, we demonstrate the capability of the DIA approach as a targeted proteomic analysis for candidate proteins from CSF and serum samples.

Developing the ATX(N) classification for use across the Alzheimer disease continuum

Breakthroughs in the development of highly accurate fluid and neuroimaging biomarkers have catalysed the conceptual transformation of Alzheimer disease (AD) from the traditional clinical symptom-based definition to a clinical-biological construct along a temporal continuum. The AT(N) system is a symptom-agnostic classification scheme that categorizes individuals using biomarkers that chart core AD pathophysiological features, namely the amyloid-β (Aβ) pathway (A), tau-mediated pathophysiology (T) and neurodegeneration (N). This biomarker matrix is now expanding towards an ATX(N) system, where X represents novel candidate biomarkers for additional pathophysiological mechanisms such as neuroimmune dysregulation, synaptic dysfunction and blood-brain barrier alterations. In this Perspective, we describe the conceptual framework and clinical importance of the existing AT(N) system and the evolving ATX(N) system. We provide a state-of-the-art summary of the potential contexts of use of these systems in AD clinical trials and future clinical practice. We also discuss current challenges related to the validation, standardization and qualification process and provide an outlook on the real-world application of the AT(N) system.

Synaptic proteins associated with cognitive performance and neuropathology in older humans revealed by multiplexed fractionated proteomics

Alzheimer's disease (AD) is defined by the presence of abundant amyloid-β (Aβ) and tau neuropathology. While this neuropathology is necessary for AD diagnosis, it is not sufficient for causing cognitive impairment. Up to one third of community dwelling older adults harbor intermediate to high levels of AD neuropathology at death yet demonstrate no significant cognitive impairment. Conversely, there are individuals who exhibit dementia with no gross explanatory neuropathology. In prior studies, synapse loss correlated with cognitive impairment. To understand how synaptic composition changes in relation to neuropathology and cognition, multiplexed liquid chromatography mass-spectrometry was used to quantify enriched synaptic proteins from the parietal association cortex of 100 subjects with contrasting levels of AD pathology and cognitive performance. 123 unique proteins were significantly associated with diagnostic category. Functional analysis showed enrichment of serotonin release and oxidative phosphorylation categories in normal (cognitively unimpaired, low neuropathology) and "resilient" (unimpaired despite AD pathology) individuals. In contrast, frail individuals, (low pathology, impaired cognition) showed a metabolic shift towards glycolysis and increased presence of proteasome subunits.

Proteomic landscape of Alzheimer's Disease: novel insights into pathogenesis and biomarker discovery

Mass spectrometry-based proteomics empowers deep profiling of proteome and protein posttranslational modifications (PTMs) in Alzheimer's disease (AD). Here we review the advances and limitations in historic and recent AD proteomic research. Complementary to genetic mapping, proteomic studies not only validate canonical amyloid and tau pathways, but also uncover novel components in broad protein networks, such as RNA splicing, development, immunity, membrane transport, lipid metabolism, synaptic function, and mitochondrial activity. Meta-analysis of seven deep datasets reveals 2,698 differentially expressed (DE) proteins in the landscape of AD brain proteome (n = 12,017 proteins/genes), covering 35 reported AD genes and risk loci. The DE proteins contain cellular markers enriched in neurons, microglia, astrocytes, oligodendrocytes, and epithelial cells, supporting the involvement of diverse cell types in AD pathology. We discuss the hypothesized protective or detrimental roles of selected DE proteins, emphasizing top proteins in "amyloidome" (all biomolecules in amyloid plaques) and disease progression. Comprehensive PTM analysis represents another layer of molecular events in AD. In particular, tau PTMs are correlated with disease stages and indicate the heterogeneity of individual AD patients. Moreover, the unprecedented proteomic coverage of biofluids, such as cerebrospinal fluid and serum, procures novel putative AD biomarkers through meta-analysis. Thus, proteomics-driven systems biology presents a new frontier to link genotype, proteotype, and phenotype, accelerating the development of improved AD models and treatment strategies.

LC-MS/MS analysis of lesional and normally looking psoriatic skin reveals significant changes in protein metabolism and RNA processing

Background

Plaque psoriasis is a chronic autoimmune disorder characterized by the development of red scaly plaques. To date psoriasis lesional skin transcriptome has been extensively studied, whereas only few proteomic studies of psoriatic skin are available.

Aim

The aim of this study was to compare protein expression patterns of lesional and normally looking skin of psoriasis patients with skin of the healthy volunteers, reveal differentially expressed proteins and identify changes in cell metabolism caused by the disease.

Methods

Skin samples of normally looking and lesional skin donated by psoriasis patients (n = 5) and samples of healthy skin donated by volunteers (n = 5) were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). After protein identification and data processing, the set of differentially expressed proteins was subjected to protein ontology analysis to characterize changes in biological processes, cell components and molecular functions in the patients’ skin compared to skin of the healthy volunteers. The expression of selected differentially expressed proteins was validated by ELISA and immunohistochemistry.

Results

The performed analysis identified 405 and 59 differentially expressed proteins in lesional and normally looking psoriatic skin compared to healthy control. In normally looking skin of the patients, we discovered decreased expression of KNG1, APOE, HRG, THBS1 and PLG. Presumably, these changes were needed to protect the epidermis from spontaneous activation of kallikrein-kinin system and delay the following development of inflammatory response. In lesional skin, we identified several large groups of proteins with coordinated expression. Mainly, these proteins were involved in different aspects of protein and RNA metabolism, namely ATP synthesis and consumption; intracellular trafficking of membrane-bound vesicles, pre-RNA processing, translation, chaperoning and degradation in proteasomes/immunoproteasomes.

Conclusion

Our findings explain the molecular basis of metabolic changes caused by disease in skin lesions, such as faster cell turnover and higher metabolic rate. They also indicate on downregulation of kallikrein-kinin system in normally looking skin of the patients that would be needed to delay exacerbation of the disease. Data are available via ProteomeXchange with identifier PXD021673.

The synapse in traumatic brain injury

Traumatic brain injury (TBI) is a leading cause of death and disability worldwide and is a risk factor for dementia later in life. Research into the pathophysiology of TBI has focused on the impact of injury on the neuron. However, recent advances have shown that TBI has a major impact on synapse structure and function through a combination of the immediate mechanical insult and the ensuing secondary injury processes, leading to synapse loss. In this review, we highlight the role of the synapse in TBI pathophysiology with a focus on the confluence of multiple secondary injury processes including excitotoxicity, inflammation and oxidative stress. The primary insult triggers a cascade of events in each of these secondary processes and we discuss the complex interplay that occurs at the synapse. We also examine how the synapse is impacted by traumatic axonal injury and the role it may play in the spread of tau after TBI. We propose that astrocytes play a crucial role by mediating both synapse loss and recovery. Finally, we highlight recent developments in the field including synapse molecular imaging, fluid biomarkers and therapeutics. In particular, we discuss advances in our understanding of synapse diversity and suggest that the new technology of synaptome mapping may prove useful in identifying synapses that are vulnerable or resistant to TBI.

The Evolving Landscape of Exosomes in Neurodegenerative Diseases: Exosomes Characteristics and a Promising Role in Early Diagnosis

Neurodegenerative diseases (ND) remains to be one of the biggest burdens on healthcare systems and serves as a leading cause of disability and death. Alzheimer's disease (AD) is among the most common of such disorders, followed by Parkinson's disease (PD). The basic molecular details of disease initiation and pathology are still under research. Only recently, the role of exosomes has been linked to the initiation and progression of these neurodegenerative diseases. Exosomes are small bilipid layer enclosed extracellular vesicles, which were once considered as a cellular waste and functionless. These nano-vesicles of 30-150 nm in diameter carry specific proteins, lipids, functional mRNAs, and high amounts of non-coding RNAs (miRNAs, lncRNAs, and circRNAs). As the exosomes content is known to vary as per their originating and recipient cells, these vesicles can be utilized as a diagnostic biomarker for early disease detection. Here we review exosomes, their biogenesis, composition, and role in neurodegenerative diseases. We have also provided details for their characterization through an array of available techniques. Their updated role in neurodegenerative disease pathology is also discussed. Finally, we have shed light on a novel field of salivary exosomes as a potential candidate for early diagnosis in neurodegenerative diseases and compared the biomarkers of salivary exosomes with other blood/cerebrospinal fluid (CSF) based exosomes within these neurological ailments.

Host-Based Biomarkers in Saliva for the Diagnosis of Pulmonary Tuberculosis in Children: A Mini-Review

The diagnosis of pulmonary tuberculosis (TB) in children remains a significant challenge due to its paucibacillary nature, non-specificity of symptoms and suboptimal sensitivity of available diagnostic methods. In young children particularly, it is difficult to obtain high-quality sputum specimens for testing, with this group the least likely to be diagnosed, while most at risk of severe disease. The World Health Organization (WHO) has prioritized research into rapid biomarker-based tests for TB using easily obtainable non-sputum samples, such as saliva. However, the role of biomarkers in saliva for diagnosing TB in children has not been fully explored. In this mini-review, we discuss the value of saliva as a diagnostic specimen in children given its ready availability and non-invasive nature of collection, and review the literature on the use of host-based biomarkers in saliva for diagnosing active pulmonary TB in adults and children. Based on available data from adult studies, we highlight that combinations of cytokines and other proteins show promise in reaching WHO-endorsed target product profiles for new TB triage tests. Given the lack of pediatric research on host biomarkers in saliva and the differing immune response to TB infection between children and adults, we recommend that pediatric studies are now performed to discover and validate salivary host biosignatures for diagnosing pulmonary TB in children. Future directions for pediatric saliva studies are discussed, with suggestions for technologies that can be applied for salivary biomarker discovery and point-of-care test development.

Proteomics of Muscle Microdialysates Identifies Potential Circulating Biomarkers in Facioscapulohumeral Muscular Dystrophy

Facioscapulohumeral muscular dystrophy (FSHD) is caused by a complex epigenetic mechanism finally leading to the misexpression of DUX4 in skeletal muscle. Detecting DUX4 and quantifying disease progression in FSHD is extremely challenging, thus increasing the need for surrogate biomarkers. We applied a shotgun proteomic approach with two different setups to analyze the protein repertoire of interstitial fluids obtained from 20 muscles in different disease stages classified by magnetic resonance imaging (MRI) and serum samples from 10 FSHD patients. A total of 1156 proteins were identified in the microdialysates by data independent acquisition, 130 of which only found in muscles in active disease stage. Proteomic profiles were able to distinguish FSHD patients from controls. Two innate immunity mediators (S100-A8 and A9) and Dermcidin were upregulated in muscles with active disease and selectively present in the sera of FSHD patients. Structural muscle and plasminogen pathway proteins were downregulated. Together with the upstream inhibition of myogenic factors, this suggests defective muscle regeneration and increased fibrosis in early/active FSHD. Our MRI targeted exploratory approach confirmed that inflammatory response has a prominent role, together with impaired muscle regeneration, before clear muscle wasting occurs. We also identified three proteins as tissue and possibly circulating biomarkers in FSHD.

Urinary Biomarkers for Neurodegenerative Diseases

Global incidence of neurodegenerative diseases (NDDs) such as Alzheimer's disease (AD) and Parkinson's disease (PD) is rapidly increasing, but the diagnosis of these diseases at their early stage is challenging. Therefore, the availability of reproducible and reliable biomarkers to diagnose such diseases is more critical than ever. In addition, biomarkers could be used not only to diagnose diseases but also to monitor the development of disease therapeutics. Urine is an excellent biofluid that can be utilized as a source of biomarker to diagnose not only several renal diseases but also other diseases because of its abundance in invasive sampling. However, urine was conventionally regarded as inappropriate as a source of biomarker for neurodegenerative diseases because it is anatomically distant from the central nervous system (CNS), a major pathologic site of NDD, in comparison to other biofluids such as cerebrospinal fluid (CSF) and plasma. However, recent studies have suggested that urine could be utilized as a source of NDD biomarker if an appropriate marker is predetermined by metabolomic and proteomic approaches in urine and other samples. In this review, we summarize such studies related to NDD.

Comparative Analysis of Multiplex Platforms for Detecting Vitreous Biomarkers in Diabetic Retinopathy

Purpose

To evaluate the feasibility of using the Proximity Extension Assay (PEA) platform to detect biomarkers in vitreous and to compare the findings with results obtained with an electrochemiluminescent (ECL) sandwich immunoassay.

Methods

Vitreous samples from patients with proliferative diabetic retinopathy (PDR) and non-diabetic controls were tested using two different proteomics platforms. Forty-one assays were completed with the ECL platform and 459 with the PEA platform. Spearman's rank correlation coefficient (r_s) was used to determine the direction and strength of the relationship between protein levels detected by both platforms.

Results

Three hundred sixty-six PEA assays detected the tested protein in at least 25% of samples, and the difference in protein abundance between PDR and controls was statistically significant for 262 assays. Seventeen ECL assays yielded a detection rate ≥ 25%, and the difference in protein concentration between PDR and controls was statistically significant for 13 proteins. There was a subset of proteins that were detected by both platforms, and for those the Spearman's correlation coefficient was higher than 0.8.

Conclusions

PEA is suitable for the analysis of vitreous samples, showing a strong correlation with the ECL platform. The detection rate of PEA panels was higher than the panels tested with ECL. The levels of several proinflammatory and angiogenic cytokines were significantly higher in PDR vitreous compared to controls.

Translational Relevance

This study provides new information on the yields of small-volume assays that can detect proteins of interest in ocular specimens, and it identifies patterns of cytokine dysregulation in PDR.

Identification of novel cerebrospinal fluid biomarker candidates for dementia with Lewy bodies: a proteomic approach

BACKGROUND

Diagnosis of dementia with Lewy bodies (DLB) is challenging, largely due to a lack of diagnostic tools. Cerebrospinal fluid (CSF) biomarkers have been proven useful in Alzheimer's disease (AD) diagnosis. Here, we aimed to identify novel CSF biomarkers for DLB using a high-throughput proteomic approach.

METHODS

We applied liquid chromatography/tandem mass spectrometry with label-free quantification to identify biomarker candidates to individual CSF samples from a well-characterized cohort comprising patients with DLB (n = 20) and controls (n = 20). Validation was performed using (1) the identical proteomic workflow in an independent cohort (n = 30), (2) proteomic data from patients with related neurodegenerative diseases (n = 149) and (3) orthogonal techniques in an extended cohort consisting of DLB patients and controls (n = 76). Additionally, we utilized random forest analysis to identify the subset of candidate markers that best distinguished DLB from all other groups.

RESULTS

In total, we identified 1995 proteins. In the discovery cohort, 69 proteins were differentially expressed in DLB compared to controls (p < 0.05). Independent cohort replication confirmed VGF, SCG2, NPTX2, NPTXR, PDYN and PCSK1N as candidate biomarkers for DLB. The downregulation of the candidate biomarkers was somewhat more pronounced in DLB in comparison with related neurodegenerative diseases. Using random forest analysis, we identified a panel of VGF, SCG2 and PDYN to best differentiate between DLB and other clinical groups (accuracy: 0.82 (95%CI: 0.75-0.89)). Moreover, we confirmed the decrease of VGF and NPTX2 in DLB by ELISA and SRM methods. Low CSF levels of all biomarker candidates, except PCSK1N, were associated with more pronounced cognitive decline (0.37 < r < 0.56, all p < 0.01).

CONCLUSION

We identified and validated six novel CSF biomarkers for DLB. These biomarkers, particularly when used as a panel, show promise to improve diagnostic accuracy and strengthen the importance of synaptic dysfunction in the pathophysiology of DLB.

Methods for the Determination of the Purity of Exosomes

BACKGROUND

Exosomes open exciting new opportunities for advanced drug transport and targeted release. Furthermore, exosomes may be used for vaccination, immunosuppression or wound healing. To fully utilize their potential as drug carriers or immune-modulatory agents, the optimal purity of exosome preparations is of crucial importance.

METHODS

Articles describing the isolation and purification of exosomes were retrieved from the PubMed database.

RESULTS

Exosomes are often separated from biological fluids containing high concentrations of proteins, lipids and other molecules that keep vesicle purification challenging. A great number of purification protocols have been published, however, their outcome is difficult to compare because the assessment of purity has not been standardized. In this review, we first give an overview of the generation and composition of exosomes, as well as their multifaceted biological functions that stimulated various medical applications. Finally, we describe various methods that have been used to purify small vesicles and to assess the purity of exosome preparations and critically compare the quality of these evaluation protocols.

CONCLUSION

Combinations of various techniques have to be applied to reach the required purity and quality control of exosome preparations.

Utility of Animal Models to Understand Human Alzheimer's Disease, Using the Mastermind Research Approach to Avoid Unnecessary Further Sacrifices of Animals

To diagnose and treat early-stage (preclinical) Alzheimer’s disease (AD) patients, we need body-fluid-based biomarkers that reflect the processes that occur in this stage, but current knowledge on associated processes is lacking. As human studies on (possible) onset and early-stage AD would be extremely expensive and time-consuming, we investigate the potential value of animal AD models to help to fill this knowledge gap. We provide a comprehensive overview of processes associated with AD pathogenesis and biomarkers, current knowledge on AD-related biomarkers derived from on human and animal brains and body fluids, comparisons of biomarkers obtained in human AD and frequently used animal AD models, and emerging body-fluid-based biomarkers. In human studies, amyloid beta (Aβ), hyperphosphorylated tau (P-tau), total tau (T-tau), neurogranin, SNAP-25, glial fibrillary acidic protein (GFAP), YKL-40, and especially neurofilament light (NfL) are frequently measured. In animal studies, the emphasis has been mostly on Aβ. Although a direct comparison between human (familial and sporadic) AD and (mostly genetic) animal AD models cannot be made, still, in brain, cerebrospinal fluid (CSF), and blood, a majority of similar trends are observed for human AD stage and animal AD model life stage. This indicates the potential value of animal AD models in understanding of the onset and early stage of AD. Moreover, animal studies can be smartly designed to provide mechanistic information on the interrelationships between the different AD processes in a longitudinal fashion and may also include the combinations of different conditions that may reflect comorbidities in human AD, according to the Mastermind Research approach.

Discovery of Potential Plasma Biomarkers for Tuberculosis in HIV-Infected Patients by Data-Independent Acquisition-Based Quantitative Proteomics

Purpose

Tuberculosis (TB) is the leading cause of mortality in individuals infected with human immunodeficiency virus (HIV), yet the methods for detecting Mycobacterium tuberculosis at an early stage remain insensitive or ineffective. This study aimed to discover plasma biomarkers for distinguishing HIV-TB coinfected individuals from HIV individuals without TB (HIV-nonTB).

Patients and Methods

A total of 200 Chinese HIV-positive patients were recruited, 100 each for HIV-nonTB group and HIV-TB group. Plasma proteomic profiles were analyzed for 50 patients each in both groups, using data-independent acquisition (DIA)-mass spectrometry-based proteomics. Differently expressed proteins were revealed with ridge regression analysis. Enzyme-linked immunosorbent assay (ELISA) analyses were performed for further validation in other 100 patients.

Results

DIA-mass spectrometry revealed 13 upregulated and 33 downregulated proteins in the HIV-TB group. AMACR (α-methylacyl-CoA racemase), LDHB (L-lactate dehydrogenase B chain), and RAP1B (Ras-related protein Rap-1b) were selected for building a diagnostic model, for which the receiver operation characteristic curve had under areas of 0.99 and 0.89 testing with proteomics data (sensitivity = 92%, specificity = 100%) and ELISA data (sensitivity = 76%, specificity = 92%), respectively.

Conclusion

The combination of AMACR, LDHB, and RAP1B proteins may serve as a potential marker of TB in HIV-infected patients.

Protein–protein interaction network with machine learning models and multiomics data reveal potential neurodegenerative disease-related proteins

Research of protein–protein interaction in several model organisms is accumulating since the development of high-throughput experimental technologies and computational methods. The protein–protein interaction network (PPIN) is able to examine biological processes in a systematic manner and has already been used to predict potential disease-related proteins or drug targets. Based on the topological characteristics of the PPIN, we investigated the application of the random forest classification algorithm to predict proteins that may cause neurodegenerative disease, a set of pathological changes featured by protein malfunction. By integrating multiomics data, we further showed the validity of our machine learning model and narrowed down the prediction results to several hub proteins that play essential roles in the PPIN. The novel insights into neurodegeneration pathogenesis brought by this computational study can indicate promising directions for future experimental research.

Neurology-related protein biomarkers are associated with cognitive ability and brain volume in older age

Identifying biological correlates of late life cognitive function is important if we are to ascertain biomarkers for, and develop treatments to help reduce, age-related cognitive decline. Here, we investigated the associations between plasma levels of 90 neurology-related proteins (Olink® Proteomics) and general fluid cognitive ability in the Lothian Birth Cohort 1936 (LBC1936, N = 798), Lothian Birth Cohort 1921 (LBC1921, N = 165), and the INTERVAL BioResource (N = 4451). In the LBC1936, 22 of the proteins were significantly associated with general fluid cognitive ability (β between -0.11 and -0.17). MRI-assessed total brain volume partially mediated the association between 10 of these proteins and general fluid cognitive ability. In an age-matched subsample of INTERVAL, effect sizes for the 22 proteins, although smaller, were all in the same direction as in LBC1936. Plasma levels of a number of neurology-related proteins are associated with general fluid cognitive ability in later life, mediated by brain volume in some cases.

Isolation of Secretome with Enhanced Antifibrotic Properties from miR-214-Transfected Adipose-Derived Stem Cells

BACKGROUND

Secretome refers to the total set of molecules secreted or surface-shed by stem cells. The limitations of stem cell research have led numerous investigators to turn their attention to the use of secretome instead of stem cells. In this study, we intended to reinforce antifibrotic properties of the secretome released from adipose-derived stem cells (ASCs) transfected with miR-214.

METHODS

We generated miR-214-transfected ASCs, and extracted the secretome (miR214-secretome) from conditioned media of the transfected ASCs through a series of ultrafiltrations. Subsequently, we intravenously injected the miR-214-secretome into mice with liver fibrosis, and determined the effects of miR-214-secretome on liver fibrosis.

RESULTS

Compared with that by naïve secretome, liver fibrosis was ameliorated by intravenous infusion of miR-214-secretome into mice with liver fibrosis, which was demonstrated by significantly lower expression of fibrosis-related markers (alpha-smooth muscle actin, transforming growth factor-β, and metalloproteinases-2) in the livers as well as lower fibrotic scores in the special stained livers compared with naïve secretome. The infusion of miR-214-secretome also led to lesser local and systemic inflammation, higher expression of an antioxidant enzyme (superoxide dismutase), and higher liver proliferative and synthetic function.

CONCLUSION

MicroRNA-214 transfection stimulates ASCs to release the secretome with higher antifibrotic and anti-inflammatory properties. miR-214-secretome is thus expected to be one of the prominent ways of overcoming liver fibrosis, if further studies consistently validate its safety and efficiency.

Detection of amyloid beta peptides in body fluids for the diagnosis of alzheimer's disease: Where do we stand?

Alzheimer's disease (AD) is an incurable neurodegenerative disease characterized by progressive decline of cognitive abilities. Amyloid beta peptides (Aβ), Tau proteins and the phosphorylated form of the Tau protein, p-Tau, are the core pathological biomarkers of the disease, and their detection for the diagnosis of patients is progressively being implemented. However, to date, their quantification is mostly performed on cerebrospinal fluid (CSF), the collection of which requires an invasive lumbar puncture. Early diagnosis has been shown to be important for disease-modifying treatment, which is currently in development, to limit the progression of the disease. Nevertheless, the diagnosis is often delayed to the point where the disease has already progressed, and the tools currently available do not allow for a systematic follow-up of patients. Thus, the search for a molecular signature of AD in a body fluid such as blood or saliva that can be collected in a minimally invasive way offers hope. A number of methods have been developed for the quantification of core biomarkers, especially in easily accessible fluids such as the blood, that improve their accuracy, specificity and sensitivity. This review summarizes and compares these approaches, focusing in particular on their use for Aβ detection, the earliest biomarker to be modified in the course of AD. The review also discusses biomarker quantification in CSF, blood and saliva and their clinical applications.

Antioxidant action of hypoxic conditioned media from adipose-derived stem cells in the hepatic injury of expressing higher reactive oxygen species

Purpose

Almost all liver diseases are known to be accompanied by increased levels of reactive oxygen species (ROS), regardless of the cause of the liver disorder. However, little is known about the role of hypoxic conditioned media (HCM) in the view of pro-oxidative/antioxidative balance.

Methods

Normoxic conditioned media (NCM) and HCM were obtained after culturing adipose-derived stem cells in 20% O₂ or 1% O₂ for 24 hours, respectively. Their effects on the expression of various markers reflecting pro-oxidative/antioxidative balance were investigated in both in vitro (thioacetamide-treated AML12 cells) and in vivo (partially hepatectomized mice) models of liver injury, respectively.

Results

HCM treatment induced the higher expression of antioxidant enzymes, such as superoxide dismutase, glutathione peroxidase, and catalase than did NCM in the in vitro model of liver injury. We also found that HCM increased the expression of nuclear factor erythroid 2-related factor (NRF2). The in vivo models of liver injury consistently validated the phenomenon of upregulated expression of antioxidant enzymes by HCM.

Conclusion

We thus could conclude that HCM provides protection against ROS-related toxicity by increasing the expression of antioxidant enzymes, in part by releasing NRF2 in the injured liver.

Editorial for Special Issue: Neuroproteomics

Recent advances in mass spectrometry (MS) instrumentation [...].

Determination of Cerebrospinal Fluid Proteome Variations by Isobaric Labeling Coupled with Strong Cation-Exchange Chromatography and Tandem Mass Spectrometry

Cerebrospinal fluid (CSF) is in direct contact with the brain and represents a valuable source of mediators that reflect metabolic processes occurring in the central nervous system (CNS). In this sense, mass spectrometry (MS) methods have proven to be sensitive in quantifying the proteomic profiles of CSF, therefore being able to detect biomarker candidates for neurological disorders. In particular, a key development has been the use of multiplexing technologies to easily identify and quantify complex protein mixtures. This chapter describes a workflow suitable for the analysis of CSF proteome using isobaric labeling coupled to strong cation-exchange chromatography fractionation for its potential use as a biomarker discovery platform. In this case, the isobaric tags for relative and absolute quantitation (iTRAQ) label all proteins in a sample via free amines at the N-terminus and on the side chain of lysine residues. Then, the labeled samples are pooled and chromatographically fractionated. These fractions with the pooled samples are afterward analyzed by tandem mass spectrometry (MS/MS), and proteins are quantified by the relative intensities of the reporter ions in the MS/MS spectra, simultaneously obtaining the amino acid sequence. This method complements the neuroproteomic toolbox to identify new protein biomarkers not only for the early clinical diagnosis and disease staging of CNS-related disorders but also to elucidate the molecular mechanisms related to the pathophysiology of these symptoms.

Guidelines for CSF Processing and Biobanking: Impact on the Identification and Development of Optimal CSF Protein Biomarkers

The field of neurological diseases strongly needs biomarkers for early diagnosis and optimal stratification of patients in clinical trials or to monitor disease progression. Cerebrospinal fluid (CSF) is one of the main sources for the identification of novel protein biomarkers for neurological diseases. Despite the enormous efforts employed to identify novel CSF biomarkers, the high variability observed across different studies has hampered their validation and implementation in clinical practice. Such variability is partly caused by the effect of different pre-analytical confounding factors on protein stability, highlighting the importance to develop and comply with standardized operating procedures. In this chapter, we describe the international consensus pre-analytical guidelines for CSF processing and biobanking that have been established during the last decade, with a special focus on the influence of pre-analytical confounders on the global CSF proteome. In addition, we provide novel results on the influence of different delayed storage and freeze/thaw conditions on the CSF proteome using two novel large multiplex protein arrays (SOMAscan and Olink). Compliance to consensus guidelines will likely facilitate the successful development and implementation of CSF protein biomarkers in both research and clinical settings, ultimately facilitating the successful development of disease-modifying therapies.