Label-free quantitative comparison of cerebrospinal fluid glycoproteins and endogenous peptides in subjects with Alzheimer's disease, mild cognitive impairment, and healthy individuals

Carotenoid Supplementation for Alleviating the Symptoms of Alzheimer's Disease

Alzheimer's disease (AD) is characterized by, among other things, dementia and a decline in cognitive performance. In AD, dementia has neurodegenerative features and starts with mild cognitive impairment (MCI). Research indicates that apoptosis and neuronal loss occur in AD, in which oxidative stress plays an important role. Therefore, reducing oxidative stress with antioxidants is a natural strategy to prevent and slow down the progression of AD. Carotenoids are natural pigments commonly found in fruits and vegetables. They include lipophilic carotenes, such as lycopene, α- and β-carotenes, and more polar xanthophylls, for example, lutein, zeaxanthin, canthaxanthin, and β-cryptoxanthin. Carotenoids can cross the blood-brain barrier (BBB) and scavenge free radicals, especially singlet oxygen, which helps prevent the peroxidation of lipids abundant in the brain. As a result, carotenoids have neuroprotective potential. Numerous in vivo and in vitro studies, as well as randomized controlled trials, have mostly confirmed that carotenoids can help prevent neurodegeneration and alleviate cognitive impairment in AD. While carotenoids have not been officially approved as an AD therapy, they are indicated in the diet recommended for AD, including the consumption of products rich in carotenoids. This review summarizes the latest research findings supporting the potential use of carotenoids in preventing and alleviating AD symptoms. A literature review suggests that a diet rich in carotenoids should be promoted to avoid cognitive decline in AD. One of the goals of the food industry should be to encourage the enrichment of food products with functional substances, such as carotenoids, which may reduce the risk of neurodegenerative diseases.

Profiling Human Cerebrospinal Fluid (CSF) Endogenous Peptidome in Alzheimer's Disease

Human cerebrospinal fluid (CSF) is a rich source for central nervous system (CNS)-related disease biomarker discovery due to its direct interchange with the extracellular fluid of the CNS. Though extensive proteome-level profiling has been conducted for CSF, studies targeting at its endogenous peptidome is still limited. It is more difficult to include the post-translational modifications (PTMs) characterization of the peptidome in the mass spectrometry (MS) analysis because of their low abundance and the challenge of data interpretation. In this chapter, we present a peptidomic workflow that combines molecular weight cut-off (MWCO) separation, electron-transfer and higher-energy collision dissociation (EThcD) fragmentation, and a three-step database searching strategy for comprehensive PTM analysis of endogenous peptides including both N-glycosylation and O-glycosylation and other common peptide PTMs. The method has been successfully adopted to analyze CSF samples from healthy donors, mild cognitive impairment (MCI), and Alzheimer's disease (AD) patients to provide a landscape of peptidome in different disease states.

Integrating intracellular and extracellular proteomic profiling for in-depth investigations of cellular communication in a model of prostate cancer

Cellular communication is essential for cell-cell interactions, maintaining homeostasis and progression of certain disease states. While many studies examine extracellular proteins, the holistic extracellular proteome is often left uncaptured, leaving gaps in our understanding of how all extracellular proteins may impact communication and interaction. We used a cellular-based proteomics approach to more holistically profile both the intracellular and extracellular proteome of prostate cancer. Our workflow was generated in such a manner that multiple experimental conditions can be observed with the opportunity for high throughput integration. Additionally, this workflow is not limited to a proteomic aspect, as metabolomic and lipidomic studies can be integrated for a multi-omics workflow. Our analysis showed coverage of over 8000 proteins while also garnering insights into cellular communication in the context of prostate cancer development and progression. Identified proteins covered a variety of cellular processes and pathways, allowing for the investigation of multiple aspects into cellular biology. This workflow demonstrates advantages for integrating intra- and extracellular proteomic analyses as well as potential for multi-omics researchers. This approach possesses great value for future investigations into the systems biology aspects of disease development and progression.

Re-remembering the influence of randomized β-carotene on cognitive decline

The wave of individuals impacted by dementia continues to rise rapidly as worldwide lifespan increases. Dietary strategies to slow cognitive decline and prolong time to clinical dementia remain understudied, but with potentially powerful public health consequences. Indeed, previously conducted large, randomized, placebo-controlled trials of micronutrients remain an under-leveraged resource to study changes in cognitive performance. As a motivating example, we highlight an ancillary report from the Physicians' Health Study, where subjects randomized to β-carotene (a provitamin A carotenoid) had a more attenuated change in longitudinal global cognitive performance and verbal memory, as compared to subjects randomized to placebo. Despite mechanistic evidence from cell and animal studies supporting a vitamin A-mediated role in the biology associated with cognition, limited follow-up work has been conducted. We argue that dietary factors (including provitamin A) deserve a second look, leveraging multi-omic approaches, to elucidate how they may mitigate cognitive decline and dementia risk.

Meta-analysis of published cerebrospinal fluid proteomics data identifies and validates metabolic enzyme panel as Alzheimer's disease biomarkers

To develop therapies for Alzheimer's disease, we need accurate in vivo diagnostics. Multiple proteomic studies mapping biomarker candidates in cerebrospinal fluid (CSF) resulted in little overlap. To overcome this shortcoming, we apply the rarely used concept of proteomics meta-analysis to identify an effective biomarker panel. We combine ten independent datasets for biomarker identification: seven datasets from 150 patients/controls for discovery, one dataset with 20 patients/controls for down-selection, and two datasets with 494 patients/controls for validation. The discovery results in 21 biomarker candidates and down-selection in three, to be validated in the two additional large-scale proteomics datasets with 228 diseased and 266 control samples. This resulting 3-protein biomarker panel differentiates Alzheimer's disease (AD) from controls in the two validation cohorts with areas under the receiver operating characteristic curve (AUROCs) of 0.83 and 0.87, respectively. This study highlights the value of systematically re-analyzing previously published proteomics data and the need for more stringent data deposition.

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.

In-Depth Site-Specific O-Glycosylation Analysis of Glycoproteins and Endogenous Peptides in Cerebrospinal Fluid (CSF) from Healthy Individuals, Mild Cognitive Impairment (MCI), and Alzheimer's Disease (AD) Patients

Site-specific O-glycoproteome mapping in complex biological systems provides a molecular basis for understanding the structure-function relationships of glycoproteins and their roles in physiological and pathological processes. Previous O-glycoproteome analysis in cerebrospinal fluid (CSF) focused on sialylated glycoforms, while missing information on other glycosylation types. In order to achieve an unbiased O-glycosylation profile, we developed an integrated strategy combining universal boronic acid enrichment, high-pH fractionation, and electron-transfer and higher-energy collision dissociation (EThcD) for enhanced intact O-glycopeptide analysis. We applied this strategy to analyze the O-glycoproteome in CSF, resulting in the identification of 308 O-glycopeptides from 110 O-glycoproteins, covering both sialylated and nonsialylated glycoforms. To our knowledge, this is the largest data set of O-glycoproteins and O-glycosites reported for CSF to date. We also developed a peptidomics workflow that utilized the EThcD and a three-step database searching strategy for comprehensive PTM analysis of endogenous peptides, including N-glycosylation, O-glycosylation, and other common peptide PTMs. Interestingly, among the 1411 endogenous peptides identified, 89 were O-glycosylated, and only one N-glycosylated peptide was found, indicating that CSF endogenous peptides were predominantly O-glycosylated. Analyses of the O-glycoproteome and endogenous peptidome PTMs were also conducted in the CSF of MCI and AD patients to provide a landscape of glycosylation patterns in different disease states. Our results showed a decreasing trend in fucosylation and an increasing trend of endogenous peptide O-glycosylation, which may play an important role in AD progression.

Peptidomic Approaches and Observations in Neurodegenerative Diseases

Mass spectrometry (MS), with its immense technological developments over the last two decades, has emerged as an unavoidable technique in analyzing biomolecules such as proteins and peptides. Its multiplexing capability and explorative approach make it a valuable tool for analyzing complex clinical samples concerning biomarker research and investigating pathophysiological mechanisms. Peptides regulate various biological processes, and several of them play a critical role in many disease-related pathological conditions. One important example in neurodegenerative diseases is the accumulation of amyloid-beta peptides (Aβ) in the brain of Alzheimer’s disease (AD) patients. When investigating brain function and brain-related pathologies, such as neurodegenerative diseases, cerebrospinal fluid (CSF) represents the most suitable sample because of its direct contact with the brain. In this review, we evaluate publications applying peptidomics analysis to CSF samples, focusing on neurodegenerative diseases. We describe the methodology of peptidomics analysis and give an overview of the achievements of CSF peptidomics over the years. Finally, publications reporting peptides regulated in AD are discussed.

Sequestration of TDP-43216-414 Aggregates by Cytoplasmic Expression of the proSAAS Chaperone

As neurons age, protein homeostasis becomes less efficient, resulting in misfolding and aggregation. Chaperone proteins perform vital functions in the maintenance of cellular proteostasis, and chaperone-based therapies that promote sequestration of toxic aggregates may prove useful in blocking the development of neurodegenerative disease. We previously demonstrated that proSAAS, a small secreted neuronal protein, exhibits potent chaperone activity against protein aggregation in vitro and blocks the cytotoxic effects of amyloid and synuclein oligomers in cell culture systems. We now examine whether cytoplasmic expression of proSAAS results in interactions with protein aggregates in this cellular compartment. We report that expression of proSAAS within the cytoplasm generates dense, membraneless 2 μm proSAAS spheres which progressively fuse to form larger spheres, suggesting liquid droplet-like properties. ProSAAS spheres selectively accumulate a C-terminally truncated fluorescently tagged form of TDP-43, initiating its cellular redistribution; these TDP-43-containing spheres also exhibit dynamic fusion. Efficient encapsulation of TDP-43 into proSAAS spheres is driven by its C-terminal prion-like domain; spheres must be formed for sequestration to occur. Three proSAAS sequences, a predicted coiled-coil, a conserved region (residues 158-169), and the positively charged sequence 181-185, are all required for proSAAS to form spheres able to encapsulate TDP-43 aggregates. Substitution of lysines for arginines in the 181-185 sequence results in nuclear translocation of proSAAS and encapsulation of nuclear-localized TDP-43216-414. As a functional output, we demonstrate that proSAAS expression results in cytoprotection against full-length TDP-43 toxicity in yeast. We conclude that proSAAS can act as a functional holdase for TDP-43 via this phase-separation property, representing a cytoprotectant whose unusual biochemical properties can potentially be exploited in the design of therapeutic molecules.

A CD10-OGP Membrane Peptolytic Signaling Axis in Fibroblasts Regulates Lipid Metabolism of Cancer Stem Cells via SCD1

Carcinoma-associated fibroblasts (CAFs) consist of heterogeneous subpopulations that play a critical role in the dynamics of the tumor microenvironment. The extracellular signals of CAFs have been attributed to the extracellular matrix, cytokines, cell surface checkpoints, and exosomes. In the present study, it is demonstrated that the CD10 transmembrane hydrolase expressed on a subset of CAFs supports tumor stemness and induces chemoresistance. Mechanistically, CD10 degenerates an antitumoral peptide termed osteogenic growth peptide (OGP). OGP restrains the expression of rate-limiting desaturase SCD1 and inhibits lipid desaturation, which is required for cancer stem cells (CSCs). Targeting CD10 significantly improves the efficacy of chemotherapy in vivo. Clinically, CD10-OGP signals are associated with the response to neoadjuvant chemotherapy in patients with breast cancer. The collective data suggest that a nexus between the niche and lipid metabolism in CSCs is a promising therapeutic target for breast cancer.

Biological Significance of the Protein Changes Occurring in the Cerebrospinal Fluid of Alzheimer's Disease Patients: Getting Clues from Proteomic Studies

The fact that cerebrospinal fluid (CSF) deeply irrigates the brain together with the relative simplicity of sample extraction from patients make this biological fluid the best target for biomarker discovery in neurodegenerative diseases. During the last decade, biomarker discovery has been especially fruitful for the identification new proteins that appear in the CSF of Alzheimer's disease (AD) patients together with amyloid-β (Aβ42), total tau (T-tau), and phosphorylated tau (P-tau). Thus, several proteins have been already stablished as important biomarkers, due to an increase (i.e., CHI3L1) or a decrease (i.e., VGF) in AD patients' CSF. Notwithstanding this, only a deep analysis of a database generated with all the changes observed in CSF across multiple proteomic studies, and especially those using state-of-the-art methodologies, may expose those components or metabolic pathways disrupted at different levels in AD. Deep comparative analysis of all the up- and down-regulated proteins across these studies revealed that 66% of the most consistent protein changes in CSF correspond to intracellular proteins. Interestingly, processes such as those associated to glucose metabolism or RXR signaling appeared inversely represented in CSF from AD patients in a significant manner. Herein, we discuss whether certain cellular processes constitute accurate indicators of AD progression by examining CSF. Furthermore, we uncover new CSF AD markers, such as ITAM, PTPRZ or CXL16, identified by this study.

Different Inflammatory Signatures in Alzheimer's Disease and Frontotemporal Dementia Cerebrospinal Fluid

Background:

Neuroinflammatory processes are common in neurodegenerative diseases such as Alzheimer’s disease (AD) and frontotemporal dementia (FTD), but current knowledge is limited as to whether cerebrospinal fluid (CSF) levels of neuroinflammatory proteins are altered in these diseases.

Objective:

To identify and characterize neuroinflammatory signatures in CSF from patients with AD, mild cognitive impairment (MCI), and FTD.

Methods:

We used proximity extension assay and ANOVA to measure and compare levels of 92 inflammatory proteins in CSF from 42 patients with AD, 29 with MCI due to AD (MCI/AD), 22 with stable MCI, 42 with FTD, and 49 control subjects, correcting for age, gender, collection unit, and multiple testing.

Results:

Levels of matrix metalloproteinase-10 (MMP-10) were increased in AD, MCI/AD, and FTD compared with controls (AD: fold change [FC] = 1.32, 95% confidence interval [CI] 1.14–1.53, q = 0.018; MCI/AD: FC = 1.53, 95% CI 1.20–1.94, q = 0.045; and FTD: FC = 1.42, 95% CI 1.10–1.83, q = 0.020). MMP-10 and eleven additional proteins were increased in MCI/AD, compared with MCI (q < 0.05). In FTD, 36 proteins were decreased, while none was decreased in AD or MCI/AD, compared with controls (q < 0.05).

Conclusion:

In this cross-sectional multi-center study, we found distinct patterns of CSF inflammatory marker levels in FTD and in both early and established AD, suggesting differing neuroinflammatory processes in the two disorders.

PEN Receptor GPR83 in Anxiety-Like Behaviors: Differential Regulation in Global vs Amygdalar Knockdown

Anxiety disorders are prevalent across the United States and result in a large personal and societal burden. Currently, numerous therapeutic and pharmaceutical treatment options exist. However, drugs to classical receptor targets have shown limited efficacy and often come with unpleasant side effects, highlighting the need to identify novel targets involved in the etiology and treatment of anxiety disorders. GPR83, a recently deorphanized receptor activated by the abundant neuropeptide PEN, has also been identified as a glucocorticoid regulated receptor (and named GIR) suggesting that this receptor may be involved in stress-responses that underlie anxiety. Consistent with this, GPR83 null mice have been found to be resistant to stress-induced anxiety. However, studies examining the role of GPR83 within specific brain regions or potential sex differences have been lacking. In this study, we investigate anxiety-related behaviors in male and female mice with global knockout and following local GPR83 knockdown in female mice. We find that a global knockdown of GPR83 has minimal impact on anxiety-like behaviors in female mice and a decrease in anxiety-related behaviors in male mice. In contrast, a local GPR83 knockdown in the basolateral amygdala leads to more anxiety-related behaviors in female mice. Local GPR83 knockdown in the central amygdala or nucleus accumbens (NAc) showed no significant effect on anxiety-related behaviors. Finally, dexamethasone administration leads to a significant decrease in receptor expression in the amygdala and NAc of female mice. Together, our studies uncover a significant, but divergent role for GPR83 in different brain regions in the regulation of anxiety-related behaviors, which is furthermore dependent on sex.

Exploring the Potential of Neuroproteomics in Alzheimer's Disease

Alzheimer's disease (AD) is progressive brain amyloidosis that damages brain regions associated with memory, thinking, behavioral and social skills. Neuropathologically, AD is characterized by intraneuronal hyperphosphorylated tau inclusions as neurofibrillary tangles (NFTs), and buildup of extracellular amyloid-beta (Aβ) peptide as senile plaques. Several biomarker tests capturing these pathologies have been developed. However, for the full clinical expression of the neurodegenerative events of AD, there exist other central molecular pathways. In terms of understanding the unidentified underlying processes for the progression and development of AD, a complete comprehension of the structure and composition of atypical aggregation of proteins is essential. Presently, to aid the prognosis, diagnosis, detection, and development of drug targets in AD, neuroproteomics is elected as one of the leading essential tools for the efficient exploratory discovery of prospective biomarker candidates estimated to play a crucial role. Therefore, the aim of this review is to present the role of neuroproteomics to analyze the complexity of AD.

In-depth Site-specific Analysis of N-glycoproteome in Human Cerebrospinal Fluid and Glycosylation Landscape Changes in Alzheimer's Disease

As the body fluid that directly interchanges with the extracellular fluid of the central nervous system (CNS), cerebrospinal fluid (CSF) serves as a rich source for CNS-related disease biomarker discovery. Extensive proteome profiling has been conducted for CSF, but studies aimed at unraveling site-specific CSF N-glycoproteome are lacking. Initial efforts into site-specific N-glycoproteomics study in CSF yield limited coverage, hindering further experimental design of glycosylation-based disease biomarker discovery in CSF. In the present study, we have developed an N-glycoproteomic approach that combines enhanced N-glycopeptide sequential enrichment by hydrophilic interaction chromatography (HILIC) and boronic acid enrichment with electron transfer and higher-energy collision dissociation (EThcD) for large-scale intact N-glycopeptide analysis. The application of the developed approach to the analyses of human CSF samples enabled identifications of a total of 2893 intact N-glycopeptides from 511 N-glycosites and 285 N-glycoproteins. To our knowledge, this is the largest site-specific N-glycoproteome dataset reported for CSF to date. Such dataset provides molecular basis for a better understanding of the structure-function relationships of glycoproteins and their roles in CNS-related physiological and pathological processes. As accumulating evidence suggests that defects in glycosylation are involved in Alzheimer's disease (AD) pathogenesis, in the present study, a comparative in-depth N-glycoproteomic analysis was conducted for CSF samples from healthy control and AD patients, which yielded a comparable N-glycoproteome coverage but a distinct expression pattern for different categories of glycoforms, such as decreased fucosylation in AD CSF samples. Altered glycosylation patterns were detected for a number of N-glycoproteins including alpha-1-antichymotrypsin, ephrin-A3 and carnosinase CN1 etc., which serve as potentially interesting targets for further glycosylation-based AD study and may eventually lead to molecular elucidation of the role of glycosylation in AD progression.

Proteomics Landscape of Alzheimer's Disease

Alzheimer’s disease (AD) is the most prevalent form of dementia, and the numbers of AD patients are expected to increase as human life expectancy improves. Deposition of β-amyloid protein (Aβ) in the extracellular matrix and intracellular neurofibrillary tangles are molecular hallmarks of the disease. Since the precise pathophysiology of AD has not been elucidated yet, effective treatment is not available. Thus, understanding the disease pathology, as well as identification and development of valid biomarkers, is imperative for early diagnosis as well as for monitoring disease progression and therapeutic responses. Keeping this goal in mind several studies using quantitative proteomics platform have been carried out on both clinical specimens including the brain, cerebrospinal fluid (CSF), plasma and on animal models of AD. In this review, we summarize the mass spectrometry (MS)-based proteomics studies on AD and discuss the discovery as well as validation stages in brief to identify candidate biomarkers.

Increased expression and retention of the secretory chaperone proSAAS following cell stress

The secretory pathway of neurons and endocrine cells contains a variety of mechanisms designed to combat cellular stress. These include not only the unfolded protein response pathways but also diverse chaperone proteins that collectively work to ensure proteostatic control of secreted and membrane-bound molecules. One of the least studied of these chaperones is the neural- and endocrine-specific molecule known as proSAAS. This small chaperone protein acts as a potent anti-aggregant both in vitro and in cellulo and also represents a cerebrospinal fluid biomarker in Alzheimer's disease. In the present study, we have examined the idea that proSAAS, like other secretory chaperones, might represent a stress-responsive protein. We find that exposure of neural and endocrine cells to the cell stressors tunicamycin and thapsigargin increases cellular proSAAS mRNA and protein in Neuro2A cells. Paradoxically, proSAAS secretion is inhibited by these same drugs. Exposure of Neuro2A cells to low concentrations of the hypoxic stress inducer cobalt chloride, or to sodium arsenite, an oxidative stressor, also increases cellular proSAAS content and reduces its secretion. We conclude that the cellular levels of the small secretory chaperone proSAAS are positively modulated by cell stress.

Mass Defect-Based DiLeu Tagging for Multiplexed Data-Independent Acquisition

The unbiased selection of peptide precursors makes data-independent acquisition (DIA) an advantageous alternative to data-dependent acquisition (DDA) for discovery proteomics, but traditional multiplexed quantification approaches employing mass difference labeling or isobaric tagging are incompatible with DIA. Here, we describe a strategy that permits multiplexed quantification by DIA using mass defect-based N,N-dimethyl leucine (mdDiLeu) tags and high-resolution tandem mass spectrometry (MS2) analysis. Millidalton mass differences between mdDiLeu isotopologues produce fragment ion multiplet peaks separated in mass by as little as 5.8 mDa, enabling up to 4-plex quantification in DIA MS2 spectra. Quantitative analysis of yeast samples displayed comparable accuracy and precision for MS2-based DIA and MS1-based DDA methods. Multiplexed DIA analysis of cerebrospinal fluid revealed the dynamic proteome changes in Alzheimer's disease, demonstrating its utility for discovery of potential clinical biomarkers. We show that the mdDiLeu tagging approach for multiplexed DIA is a viable methodology for investigating proteome changes, particularly for low-abundance proteins, in different biological matrices.

A comprehensive systematic review of CSF proteins and peptides that define Alzheimer's disease

BACKGROUND

During the last two decades, over 100 proteomics studies have identified a variety of potential biomarkers in CSF of Alzheimer's (AD) patients. Although several reviews have proposed specific biomarkers, to date, the statistical relevance of these proteins has not been investigated and no peptidomic analyses have been generated on the basis of specific up- or down- regulation. Herein, we perform an analysis of all unbiased explorative proteomics studies of CSF biomarkers in AD to critically evaluate whether proteins and peptides identified in each study are consistent in distribution; direction change; and significance, which would strengthen their potential use in studies of AD pathology and progression.

METHODS

We generated a database containing all CSF proteins whose levels are known to be significantly altered in human AD from 47 independent, validated, proteomics studies. Using this database, which contains 2022 AD and 2562 control human samples, we examined whether each protein is consistently present on the basis of reliable statistical studies; and if so, whether it is over- or under-represented in AD. Additionally, we performed a direct analysis of available mass spectrometric data of these proteins to generate an AD CSF peptide database with 3221 peptides for further analysis.

RESULTS

Of the 162 proteins that were identified in 2 or more studies, we investigated their enrichment or depletion in AD CSF. This allowed us to identify 23 proteins which were increased and 50 proteins which were decreased in AD, some of which have never been revealed as consistent AD biomarkers (i.e. SPRC or MUC18). Regarding the analysis of the tryptic peptide database, we identified 87 peptides corresponding to 13 proteins as the most highly consistently altered peptides in AD. Analysis of tryptic peptide fingerprinting revealed specific peptides encoded by CH3L1, VGF, SCG2, PCSK1N, FBLN3 and APOC2 with the highest probability of detection in AD.

CONCLUSIONS

Our study reveals a panel of 27 proteins and 21 peptides highly altered in AD with consistent statistical significance; this panel constitutes a potent tool for the classification and diagnosis of AD.

Cerebrospinal fluid proteomics and biological heterogeneity in Alzheimer's disease: A literature review

Alzheimer's disease (AD) is the most common cause of dementia and is characterized by aggregation of amyloid and tau proteins in the brain. Results from genetic studies suggest that the pathophysiology underlying AD is complex, but studying this complexity in patients remains difficult. The cerebrospinal fluid (CSF) proteome contains a large number of proteins that can reflect ongoing biological processes. Proteomics techniques can be used to measure many proteins simultaneously in individual patients and may therefore provide an opportunity to study AD disease mechanisms. Here, we review the CSF proteomics literature to identify proteins consistently associated with AD, and perform pathway analyses on these proteins to study which biological processes may be involved in the disease.We performed a literature search of studies that investigated CSF proteomic alterations related to AD. We included original research articles when they measured at least 10 proteins in (antemortem) CSF in at least 10 individuals with AD, mild cognitive impairment (MCI) or controls. We examined if proteins were consistently related to AD, defined as consistent increase or decrease in AD vs. controls across studies. Next, we used the proteins identified as input to pathway analyses using Reactome to investigate which biological processes were enriched.In total, 29 studies were included that investigated AD-related changes to the CSF proteome, including a total of 1434 individuals with AD (of whom 47.1% had a CSF biomarker profile and 9.6% a postmortem examination consistent with AD) and 1380 controls. The studies reported 1 to 138 proteins associated with AD, of which 97 proteins were reported by two or more studies. Among proteins that were measured in more than one study, 27 (27.8%) showed consistent increases, 15 (15.5%) consistent decreases and 55 (56.7%) had contrasting results. Pathway analyses showed that AD-related proteins were enriched for hemostasis, lipoprotein and extracellular matrix pathways.These results indicate that proteomic alterations in CSF associated with AD reflect involvement of various biological pathways. The frequent occurrence of inconsistent protein level changes reported by different studies suggests that additional biological and/or (pre)analytical factors may influence the CSF proteome in AD, which should be further investigated in order to improve understanding of the biological complexity underlying AD.

Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. Over the last decade, large-scale profiling of N-linked glycoproteins and glycosylation sites from biological and clinical samples has been achieved through mass spectrometry-based glycoproteomic approaches. In this paper, we reviewed the human glycoproteomic profiles that have been reported in more than 80 individual studies, and mainly focused on the N-glycoproteins and glycosylation sites identified through their deglycosylated forms of glycosite-containing peptides. According to our analyses, more than 30,000 glycosite-containing peptides and 7,000 human glycoproteins have been identified from five different body fluids, twelve human tissues (or related cell lines), and four special cell types. As the glycoproteomic data is still missing for many organs and tissues, a systematical glycoproteomic analysis of various human tissues and body fluids using a uniform platform is still needed for an integrated map of human N-glycoproteomes.

Mass spectrometry is a multifaceted weapon to be used in the battle against Alzheimer's disease: Amyloid beta peptides and beyond

Amyloid-β peptide (Aβ) accumulation and aggregation have been considered for many years the main cause of Alzheimer's disease (AD), and therefore have been the principal target of investigation as well as of the proposed therapeutic approaches (Grasso [2011] Mass Spectrom Rev. 30: 347-365). However, the amyloid cascade hypothesis, which considers Aβ accumulation the only causative agent of the disease, has proven to be incomplete if not wrong. In recent years, actors such as metal ions, oxidative stress, and other cofactors have been proposed as possible co-agents or, in some cases, main causative factors of AD. In this scenario, MS investigation has proven to be fundamental to design possible diagnostic strategies of this elusive disease, as well as to understand the biomolecular mechanisms involved, in the attempt to find a possible therapeutic solution. We review the current applications of MS in the search for possible Aβ biomarkers of AD to help the diagnosis of the disease. Recent examples of the important contributions that MS has given to prove or build theories on the molecular pathways involved with such terrible disease are also reviewed.

Mass Spectrometry Approaches to Glycomic and Glycoproteomic Analyses

Glycomic and glycoproteomic analyses involve the characterization of oligosaccharides (glycans) conjugated to proteins. Glycans are produced through a complicated nontemplate driven process involving the competition of enzymes that extend the nascent chain. The large diversity of structures, the variations in polarity of the individual saccharide residues, and the poor ionization efficiencies of glycans all conspire to make the analysis arguably much more difficult than any other biopolymer. Furthermore, the large number of glycoforms associated with a specific protein site makes it more difficult to characterize than any post-translational modification. Nonetheless, there have been significant progress, and advanced separation and mass spectrometry methods have been at its center and the main reason for the progress. While glycomic and glycoproteomic analyses are still typically available only through highly specialized laboratories, new software and workflow is making it more accessible. This review focuses on the role of mass spectrometry and separation methods in advancing glycomic and glycoproteomic analyses. It describes the current state of the field and progress toward making it more available to the larger scientific community.

Proteomic Approaches for the Discovery of Biofluid Biomarkers of Neurodegenerative Dementias

Neurodegenerative dementias are highly complex disorders driven by vicious cycles of intersecting pathophysiologies. While most can be definitively diagnosed by the presence of disease-specific pathology in the brain at postmortem examination, clinical disease presentations often involve substantially overlapping cognitive, behavioral, and functional impairment profiles that hamper accurate diagnosis of the specific disease. As global demographics shift towards an aging population in developed countries, clinicians need more sensitive and specific diagnostic tools to appropriately diagnose, monitor, and treat neurodegenerative conditions. This review is intended as an overview of how modern proteomic techniques (liquid chromatography mass spectrometry (LC-MS/MS) and advanced capture-based technologies) may contribute to the discovery and establishment of better biofluid biomarkers for neurodegenerative disease, and the limitations of these techniques. The review highlights some of the more interesting technical innovations and common themes in the field but is not intended to be an exhaustive systematic review of studies to date. Finally, we discuss clear reporting principles that should be integrated into all studies going forward to ensure data is presented in sufficient detail to allow meaningful comparisons across studies.

Retinol-Binding Protein Interferes with Transthyretin-Mediated β-Amyloid Aggregation Inhibition

β-Amyloid (Aβ) aggregation is causally linked to Alzheimer's disease. On the basis of in vitro and transgenic animal studies, transthyretin (TTR) is hypothesized to provide neuroprotection against Aβ toxicity by binding to Aβ and inhibiting its aggregation. TTR is a homotetrameric protein that circulates in blood and cerebrospinal fluid; its normal physiological role is as a carrier for thyroxine and retinol-binding protein (RBP). RBP forms a complex with retinol, and the holoprotein (hRBP) binds with high affinity to TTR. In this study, the role of TTR ligands in TTR-mediated inhibition of Aβ aggregation was investigated. hRBP strongly reduced the ability of TTR to inhibit Aβ aggregation. The effect was not due to competition between Aβ and hRBP for binding to TTR, as Aβ bound equally well to TTR-hRBP complexes and TTR. hRBP is known to stabilize the TTR tetrameric structure. We show that Aβ partially destabilizes TTR and that hRBP counteracts this destabilization. Taken together, our results support a mechanism wherein TTR-mediated inhibition of Aβ aggregation requires not only TTR-Aβ binding but also destabilization of TTR quaternary structure.

Comparative Evaluation of MS-based Metabolomics Software and Its Application to Preclinical Alzheimer's Disease

Mass spectrometry-based metabolomics has undergone significant progresses in the past decade, with a variety of software packages being developed for data analysis. However, systematic comparison of different metabolomics software tools has rarely been conducted. In this study, several representative software packages were comparatively evaluated throughout the entire pipeline of metabolomics data analysis, including data processing, statistical analysis, feature selection, metabolite identification, pathway analysis, and classification model construction. LC-MS-based metabolomics was applied to preclinical Alzheimer's disease (AD) using a small cohort of human cerebrospinal fluid (CSF) samples (N = 30). All three software packages, XCMS Online, SIEVE, and Compound Discoverer, provided consistent and reproducible data processing results. A hybrid method combining statistical test and support vector machine feature selection was employed to screen key metabolites, achieving a complementary selection of candidate biomarkers from three software packages. Machine learning classification using candidate biomarkers generated highly accurate and predictive models to classify patients into preclinical AD or control category. Overall, our study demonstrated a systematic evaluation of different MS-based metabolomics software packages for the entire data analysis pipeline which was applied to the candidate biomarker discovery of preclinical AD.

Quantitative Proteomics of Cerebrospinal Fluid in Paediatric Pneumococcal Meningitis

Streptococcus pneumoniae is responsible for diseases causing major global public health problems, including meningitis, pneumonia and septicaemia. Despite recent advances in antimicrobial therapy, pneumococcal meningitis remains a life-threatening disease. Furthermore, long-term sequelae are a major concern for survivors. Hence, a better understanding of the processes occurring in the central nervous system is crucial to the development of more effective management strategies. We used mass spectrometry based quantitative proteomics to identify protein changes in cerebrospinal fluid from children with Streptococcus pneumoniae infection, compared with children admitted to hospital with bacterial meningitis symptoms but negative diagnosis. Samples were analysed, by label free proteomics, in two independent cohorts (cohort 1: cases (n = 8) and hospital controls (n = 4); cohort 2: cases (n = 8), hospital controls (n = 8)). Over 200 human proteins were differentially expressed in each cohort, of which 65% were common to both. Proteins involved in the immune response and exosome signalling were significantly enriched in the infected samples. For a subset of proteins derived from the proteome analysis, we corroborated the proteomics data in a third cohort (hospital controls (n = 15), healthy controls (n = 5), cases (n = 20)) by automated quantitative western blotting, with excellent agreement with our proteomics findings. Proteomics data are available via ProteomeXchange with identifier PXD004219.

Metaproteomic strategies and applications for gut microbial research

The human intestine hosts various complex microbial communities that are closely associated with multiple health and disease processes. Determining the composition and function of these microbial communities is critical to unveil disease mechanisms and promote human health. Recently, meta-omic strategies have been developed that use high-throughput techniques to provide a wealth of information, thus accelerating the study of gut microbes. Metaproteomics is a newly emerged analytical approach that aims to identify proteins on a large scale in complex environmental microbial communities (e.g., the gut microbiota). This review introduces the recent analytical strategies and applications of metaproteomics, with a focus on advances in gut microbiota research, including a discussion of the limitations and challenges of these approaches.