Mass spectrometry: A platform for biomarker discovery and validation for Alzheimer's and Parkinson's diseases

ProPickML: Advancing Clinical Diagnostics with Automated Peak Picking in Label-Free Targeted Proteomics

In targeted proteomics utilizing Selected Reaction Monitoring (SRM), the precise detection of specific peptides within complex mixtures remains a significant challenge, particularly due to noise and interference in chromatograms. Existing methodologies, such as isotopic labeling and scoring algorithms, offer partial solutions but are constrained by high run times and elevated false discovery rates. To address these limitations, we have developed ProPickML a machine learning-based tool designed to accurately identify peptide peaks across diverse data sets, independent of the assumed presence of the peptide. This model was trained on a manually labeled data set and subsequently validated to assess its predictive accuracy. The results demonstrate that the model reliably identifies peptide peaks in the presence of noise, achieving a Matthews correlation coefficient (MCC) of 0.81 on an independent test data set, surpassing mProphet's MCC of 0.71. Implemented in R as ProPickML, this tool offers a competitive, cost-effective alternative to existing techniques, significantly reducing reliance on isotopic labeling and enhancing the accuracy of peptide identification in SRM workflows.

A Proteomics Pipeline for Generating Clinical Grade Biomarker Candidates from Data-Independent Acquisition Mass Spectrometry (DIA-MS) Discovery

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package that uses data-independent acquisition analysis from a discovery cohort to select precursors, peptides, and proteins that adhere to analytical criteria required for established targeted assays. TEAQ was applied to DIA-MS data from plasma samples acquired on a new high resolution accurate mass (HRAM) mass spectrometry platform where precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation based on 8- or 11-point loading curves at three throughputs. This data can be used as a general resource for developing other targeted assays. TEAQ analysis of data from a case and control cohort for inflammatory bowel disease (n=492) identified 1110 signature peptides for 326 quantifiable proteins from the 1179 identified proteins. Applying TEAQ analysis to discovery data will streamline targeted assay development and the transition to validation and clinical studies.

Application of multi-omics in the study of traditional Chinese medicine

Traditional Chinese medicine (TCM) is playing an increasingly important role in disease treatment due to the advantages of multi-target, multi-pathway mechanisms, low adverse reactions and cost-effectiveness. However, the complexity of TCM system poses challenges for research. In recent years, there has been a surge in the application of multi-omics integrated research to explore the active components and treatment mechanisms of TCM from various perspectives, which aids in advancing TCM's integration into clinical practice and holds immense importance in promoting modernization. In this review, we discuss the application of proteomics, metabolomics, and mass spectrometry imaging in the study of composition, quality evaluation, target identification, and mechanism of action of TCM based on existing literature. We focus on the workflows and applications of multi-omics based on mass spectrometry in the research of TCM. Additionally, potential research ideas for future exploration in TCM are outlined. Overall, we emphasize the advantages and prospects of multi-omics based on mass spectrometry in the study of the substance basis and mechanism of action of TCM. This synthesis of methodologies holds promise for enhancing our understanding of TCM and driving its further integration into contemporary medical practices.

Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package. This innovative tool uses the discovery cohort analysis to select precursors, peptides, and proteins that adhere to established targeted assay criteria. TEAQ was applied to Data-Independent Acquisition MS data from plasma samples acquired on an Orbitrap™ Astral™ MS. Identified precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation from 11-point loading curves under three throughputs, to develop a resource for clinical-grade targeted assays. From a clinical cohort of individuals with inflammatory bowel disease (n=492), TEAQ successfully identified 1116 signature peptides for 327 quantifiable proteins from 1180 identified proteins. Embedding stringent selection criteria adaptable to targeted assay development into the analysis of discovery data will streamline the transition to validation and clinical studies.

DNAzyme-based faithful probing and pulldown to identify candidate biomarkers of low abundance

Biomarker discovery is essential for the understanding, diagnosis, targeted therapy and prognosis assessment of malignant diseases. However, it remains a huge challenge due to the lack of sensitive methods to identify disease-specific rare molecules. Here we present MORAC, molecular recognition based on affinity and catalysis, which enables the effective identification of candidate biomarkers with low abundance. MORAC relies on a class of DNAzymes, each cleaving a sole RNA linkage embedded in their DNA chain upon specifically sensing a complex system with no prior knowledge of the system's molecular content. We show that signal amplification from catalysis ensures the DNAzymes high sensitivity (for target probing); meanwhile, a simple RNA-to-DNA mutation can shut down their RNA cleavage ability and turn them into a pure affinity tool (for target pulldown). Using MORAC, we identify previously unknown, low-abundance candidate biomarkers with clear clinical value, including apolipoprotein L6 in breast cancer and seryl-tRNA synthetase 1 in polyps preceding colon cancer.

Integrated metabolomics and proteomics analysis of plasma lipid metabolism in Parkinson's disease

INTRODUCTION

Metabolomics and proteomics are two growing fields of science which may shed light on the molecular mechanisms that contribute to neurodegenerative diseases. Studies focusing on these aspects can reveal specific metabolites and proteins that can halt or reverse the progressive neurodegenerative process leading to dopaminergic cell death in the brain.

AREAS COVERED

In this article, an overview of the current status of metabolomic and proteomic profiling in the neurodegenerative disease such as Parkinson's disease (PD) is presented. We discuss the importance of state-of-the-art metabolomics and proteomics using advanced analytical methodologies and their potential for discovering new biomarkers in PD. We critically review the research to date, highlighting how metabolomics and proteomics can have an important impact on early disease diagnosis, future therapy development and the identification of new biomarkers. Finally, we will discuss interactions between lipids and α-synuclein (SNCA) and also consider the role of SNCA in lipid metabolism.

EXPERT OPINION

Metabolomic and proteomic studies contribute to understanding the biological basis of PD pathogenesis, identifying potential biomarkers and introducing new therapeutic strategies. The complexity and multifactorial nature of this disease requires a comprehensive approach, which can be achieved by integrating just these two omic studies.

Systematic review and meta-analysis of human health-related protein markers for realizing real-time wastewater-based epidemiology

For effective implementation of the wastewater-based epidemiology (WBE) approach, real-time quantification of markers in wastewater is critical for data acquisition before data interpretation, dissemination, and decision-making. This can be achieved by using biosensor technology, but whether the quantification/detection limits of different types of biosensors comply with the concentration of WBE markers in wastewater is unclear. In the present study, we identified promising protein markers with relatively high concentrations in wastewater samples and analyzed biosensor technologies that are potentially available for real-time WBE. The concentrations of potential protein markers in stool and urine samples were obtained through systematic review and meta-analysis. We examined 231 peer-review papers to collect information regarding potential protein markers that can enable us to achieve real-time monitoring using biosensor technology. Fourteen markers in stool samples were identified at the ng/g level, presumably equivalent to ng/L of wastewater after dilution. Moreover, relatively high average concentrations of fecal inflammatory proteins were observed, e.g., fecal calprotectin, clusterin, and lactoferrin. Fecal calprotectin exhibited the highest average log concentration among the markers identified in stool samples with its mean value being 5.24 [95 % CI: 5.05, 5.42] ng/g. We identified 50 protein markers in urine samples at the ng/mL level. Uromodulin (4.48 [95 % CI: 4.20, 4.76] ng/mL) and plasmin (4.18 [95 % CI: 3.15, 5.21] ng/mL) had the top two highest log concentrations in urine samples. Furthermore, the quantification limit of some electrochemical- and optical-based biosensors was found to be around the femtogram/mL level, which is sufficiently low to detect protein markers in wastewater even after dilution in sewer pipes.

Proteomics identifies lipocalin-2 in neonatal inflammation associated with cerebrovascular alteration in mice and preterm infants

Staphylococcus (S.) epidermidis is the most common nosocomial coagulase-negative staphylococci infection in preterm infants. Clinical signs of infection are often unspecific and novel markers to complement diagnosis are needed. We investigated proteomic alterations in mouse brain after S. epidermidis infection and in preterm infant blood. We identified lipocalin-2 (LCN2) as a crucial protein associated with cerebrovascular changes and astrocyte reactivity in mice. We further proved that LCN2 protein expression was associated with endothelial cells but not astrocyte reactivity. By combining network analysis and differential expression approaches, we identified LCN2 linked to blood C-reactive protein levels in preterm infants born <28 weeks of gestation. Blood LCN2 levels were associated with similar alterations of cytokines and chemokines in both infected mice and human preterm infants with increased levels of C-reactive protein. This experimental and clinical study suggests that LCN2 may be a marker of preterm infection/inflammation associated with cerebrovascular changes and neuroinflammation.

A Quantitative LC-MS/MS Method for Distinguishing the Tau Protein Forms Phosphorylated and Nonphosphorylated at Serine-396

Hyperphosphorylated tau protein is well-known to be involved in the formation of neurofibrillary tangles and the progression of age-related neurodegenerative diseases (tauopathies), including Alzheimer's Disease (AD). Tau protein phosphorylated at serine-396 (pS396-tau) is often linked to disease progression, and we therefore developed an analytical method to measure pS396-tau in cerebrospinal fluid (CSF) in humans and animal models of AD. In the S396-region, multiple phosphorylation sites are present, causing structural complexity and sensitivity challenges for conventional bottom-up mass spectrometry approaches. Here, we present an indirect LC-MS/MS method for quantification of pS396-tau. We take advantage of the reproducible miscleavage caused by S396 being preceded by a lysine (K395) and the proteolytic enzyme trypsin not cleaving when the following amino acid is phosphorylated. Therefore, treatment with trypsin discriminates between the forms of tau with and without phosphorylation at S396 and pS396-tau can be quantified as the difference between total S396-tau and nonphosphorylated S396-tau. To qualify the method, it was successfully applied for quantification of pS396-tau in human CSF from healthy controls and patients with Mild Cognitive Impairment and AD. In addition, the method was applied for rTg4510 mice where a clear dose dependent decrease in pS396-tau was observed in CSF following intravenous administration of a monoclonal antibody (Lu AF87908, hC10.2) targeting the tau epitope containing pS396. Finally, a formal validation of the method was conducted. In conclusion, this sensitive LC-MS/MS-based method for measurement of pS396-tau in CSF allows for quantitative translational biomarker applications for tauopathies including investigations of potential drug induced effects.

Lipidomics and proteomics: An integrative approach for early diagnosis of dementia and Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder and considered to be responsible for majority of worldwide prevalent dementia cases. The number of patients suffering from dementia are estimated to increase up to 115.4 million cases worldwide in 2050. Hence, AD is contemplated to be one of the major healthcare challenge in current era. This disorder is characterized by impairment in various signaling molecules at cellular and nuclear level including aggregation of Aβ protein, tau hyper phosphorylation altered lipid metabolism, metabolites dysregulation, protein intensity alteration etc. Being heterogeneous and multifactorial in nature, the disease do not has any cure or any confirmed diagnosis before the onset of clinical manifestations. Hence, there is a requisite for early diagnosis of AD in order to downturn the progression/risk of the disorder and utilization of newer technologies developed in this field are aimed to provide an extraordinary assistance towards the same. The lipidomics and proteomics constitute large scale study of cellular lipids and proteomes in biological matrices at normal stage or any stage of a disease. The study involves high throughput quantification and detection techniques such as mass spectrometry, liquid chromatography, nuclear mass resonance spectroscopy, fluorescence spectroscopy etc. The early detection of altered levels of lipids and proteins in blood or any other biological matrices could aid in preventing the progression of AD and dementia. Therefore, the present review is designed to focus on the recent techniques and early diagnostic criteria for AD, revealing the role of lipids and proteins in this disease and their assessment through different techniques.

The Potential of ANK1 to Predict Parkinson's Disease

The main cause of Parkinson's disease (PD) remains unknown and the pathologic changes in the brain limit rapid diagnosis. Herein, differentially expressed genes (DEGs) in the Gene Expression Omnibus (GEO) database (GSE8397 and GSE22491) were assessed using linear models for microarray analysis (limma). Ankyrin 1 (ANK1) was the only common gene differentially down-regulated in lateral substantia nigra (LSN), medial substantia nigra (MSN) and blood. Additionally, DEGs between high ANK1 and low ANK1 in GSE99039 were picked out and then uploaded to the Database for Annotation, Visualization and Integrated Discovery (DAVID) for gene ontology (GO) functional annotation analysis. GO analysis displayed that these DEGs were mainly enriched in oxygen transport, myeloid cell development and gas transport (biological process (BP)); hemoglobin complex, haptoglobin-hemoglobin complex and cortical cytoskeleton (cellular component (CC)); and oxygen transporter activity, haptoglobin binding and oxygen binding (molecular function (MF)). Receiver operating characteristic (ROC) curve analysis showed ANK1 had good diagnostic accuracy and increased the area under the curve (AUC) value when combined with other biomarkers. Consistently, intraperitoneal injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropy-ridi-ne (MPTP) in C57BL/6J mice reduced ANK1 mRNA expression in both substantia nigra and blood compared to the control group. Thus, ANK1 may serve as a candidate biomarker for PD diagnosis.

Applications of spatially resolved omics in the field of endocrine tumors

Endocrine tumors derive from endocrine cells with high heterogeneity in function, structure and embryology, and are characteristic of a marked diversity and tissue heterogeneity. There are still challenges in analyzing the molecular alternations within the heterogeneous microenvironment for endocrine tumors. Recently, several proteomic, lipidomic and metabolomic platforms have been applied to the analysis of endocrine tumors to explore the cellular and molecular mechanisms of tumor genesis, progression and metastasis. In this review, we provide a comprehensive overview of spatially resolved proteomics, lipidomics and metabolomics guided by mass spectrometry imaging and spatially resolved microproteomics directed by microextraction and tandem mass spectrometry. In this regard, we will discuss different mass spectrometry imaging techniques, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization and desorption electrospray ionization. Additionally, we will highlight microextraction approaches such as laser capture microdissection and liquid microjunction extraction. With these methods, proteins can be extracted precisely from specific regions of the endocrine tumor. Finally, we compare applications of proteomic, lipidomic and metabolomic platforms in the field of endocrine tumors and outline their potentials in elucidating cellular and molecular processes involved in endocrine tumors.

Mechanistic insight into female predominance in Alzheimer's disease based on aberrant protein S-nitrosylation of C3

Protein S-nitros(yl)ation (SNO) is a posttranslational modification involved in diverse processes in health and disease and can contribute to synaptic damage in Alzheimer's disease (AD). To identify SNO proteins in AD brains, we used triaryl phosphine (SNOTRAP) combined with mass spectrometry (MS). We detected 1449 SNO proteins with 2809 SNO sites, representing a wide range of S-nitrosylated proteins in 40 postmortem AD and non-AD human brains from patients of both sexes. Integrative protein ranking revealed the top 10 increased SNO proteins, including complement component 3 (C3), p62 (SQSTM1), and phospholipase D3. Increased levels of S-nitrosylated C3 were present in female over male AD brains. Mechanistically, we show that formation of SNO-C3 is dependent on falling β-estradiol levels, leading to increased synaptic phagocytosis and thus synapse loss and consequent cognitive decline. Collectively, we demonstrate robust alterations in the S-nitrosoproteome that contribute to AD pathogenesis in a sex-dependent manner.

Global, in situ analysis of the structural proteome in individuals with Parkinson's disease to identify a new class of biomarker

Parkinson's disease (PD) is a prevalent neurodegenerative disease for which robust biomarkers are needed. Because protein structure reflects function, we tested whether global, in situ analysis of protein structural changes provides insight into PD pathophysiology and could inform a new concept of structural disease biomarkers. Using limited proteolysis-mass spectrometry (LiP-MS), we identified 76 structurally altered proteins in cerebrospinal fluid (CSF) of individuals with PD relative to healthy donors. These proteins were enriched in processes misregulated in PD, and some proteins also showed structural changes in PD brain samples. CSF protein structural information outperformed abundance information in discriminating between healthy participants and those with PD and improved the discriminatory performance of CSF measures of the hallmark PD protein α-synuclein. We also present the first analysis of inter-individual variability of a structural proteome in healthy individuals, identifying biophysical features of variable protein regions. Although independent validation is needed, our data suggest that global analyses of the human structural proteome will guide the development of novel structural biomarkers of disease and enable hypothesis generation about underlying disease processes.

Study on Ammonia Content and Distribution in the Microenvironment Based on Covalent Organic Framework Nanochannels

A crack-free micrometer-sized compact structure of 1,3,5-tris(4-aminophenyl)benzene-terephthaldehyde-covalent organic frameworks (TAPB-PDA-COFs) was constructed in situ at the tip of a theta micropipette (TMP). The COF-covered theta micropipette (CTP) then created a stable liquid-gas interface inside COF nanochannels, which was utilized to electrochemically analyze the content and distribution of ammonia gas in the microenvironments. The TMP-based electrochemical ammonia sensor (TEAS) shows a high sensing response, with current increasing linearly from 0 to 50,000 ppm ammonia, owing to the absorption of ammonia gas in the solvent meniscus that connects both barrels of the TEAS. The TEAS also exhibits a short response and recovery time of 5 ± 2 s and 6 ± 2 s, respectively. This response of the ammonia sensor is remarkably stable and repeatable, with a relative standard deviation of 6% for 500 ppm ammonia gas dispensing with humidity control. Due to its fast, reproducible, and stable response to ammonia gas, the TEAS was also utilized as a scanning electrochemical microscopy (SECM) probe for imaging the distribution of ammonia gas in a microspace. This study unlocks new possibilities for using a TMP in designing microscale probes for gas sensing and imaging.

Alzheimer's disease: a scoping review of biomarker research and development for effective disease diagnosis

INTRODUCTION

Alzheimer's disease (AD) is regarded as the foremost reason for neurodegeneration that prominently affects the geriatric population. Characterized by extracellular accumulation of amyloid-beta (Aβ), intracellular aggregation of hyperphosphorylated tau (p-tau), and neuronal degeneration that causes impairment of memory and cognition. Amyloid/tau/neurodegeneration (ATN) classification is utilized for research purposes and involves amyloid, tau, and neuronal injury staging through MRI, PET scanning, and CSF protein concentration estimations. CSF sampling is invasive, and MRI and PET scanning requires sophisticated radiological facilities which limit its widespread diagnostic use. ATN classification lacks effectiveness in preclinical AD.

AREAS COVERED

This publication intends to collate and review the existing biomarker profile and the current research and development of a new arsenal of biomarkers for AD pathology from different biological samples, microRNA (miRNA), proteomics, metabolomics, artificial intelligence, and machine learning for AD screening, diagnosis, prognosis, and monitoring of AD treatments.

EXPERT OPINION

It is an accepted observation that AD-related pathological changes occur over a long period of time before the first symptoms are observed providing ample opportunity for detection of biological alterations in various biological samples that can aid in early diagnosis and modify treatment outcomes.

Current Progress in Aptasensor for Ultra-Low Level Monitoring of Parkinson's Disease Biomarkers

In today's world, Parkinson's disease (PD) has been introduced as a long-term degenerative disorder of the central nervous system which mainly affects approximately more than ten million people worldwide. The vast majority of diagnostic methods for PD have operated based on conventional sensing platforms, while the traditional laboratory tests are not efficient for diagnosis of PD in the early stage due to symptoms of this common neurodegenerative syndrome starting slowly. The advent of the aptasensor has revolutionized the early-stage diagnosis of PD by measuring related biomarkers due to the myriad advantages of originating from aptamers which can be able to sensitive and selective capture various types of related biomarkers. The progress of numerous sensing platforms and methodologies in terms of biosensors based on aptamer application for PD diagnosis has revealed promising results. In this review, we present the latest developments in myriad types of aptasensors for the determination of related PD biomarkers. Working strategies, advantages and limitations of these sensing approaches are also mentioned, followed by prospects and challenges.

Identification of the target protein of the metastatic colorectal cancer-specific aptamer W3 as a biomarker by aptamer-based target cells sorting and functional characterization

Metastasis is a leading cause of cancer-related deaths. Hence, the discovery of more reliable metastasis-related biomarkers is crucial to improve the survival rate of cancer patients. W3 is an aptamer previously produced by the subtractive cell-SELEX using metastatic colorectal cancer cells as target cells and non-metastatic cells as negative cells. In this study, we aimed to evaluate whether the target molecule of W3 can potentially act as a metastatic biomarker. First, we obtained two cell subpopulations with different expression levels of the target molecule by W3-based cell sorting. Subsequently, we demonstrated that W3^high cells have a higher metastatic potential than W3^low cells both in vitro and in vivo. Further, immunohistochemical analysis revealed that W3 target expression is positively associated with metastasis and poor prognosis of CRC patients. Using mass spectrometry (MS) combined with pull-down, we identified that Ephrin type-A receptor 2 (EphA2) is the target of W3. EphA2's potential as a metastatic predictor was demonstrated by capturing W3-positive circulating tumor cells from CRC patients using a W3 probe. Based on these results, we put forward a stratagem for cell-SELEX-based biomarker discovery: selecting an aptamer through subtractive cell-SELEX towards the phenotype of interest; evaluating the functional phenotype of the target molecule by aptamer-based target cell sorting and analysis of clinical samples; and identifying the aptamer's target molecule using MS and aptamer-based target enrichment. This stratagem not only shortens the time for the clinical application of aptamers but also enables a more targeted and efficient discovery of biomarkers.

Analysis of human brain tissue derived from DBS surgery

Background

Transcriptomic and proteomic profiling of human brain tissue is hindered by the availability of fresh samples from living patients. Postmortem samples usually represent the advanced disease stage of the patient. Furthermore, the postmortem interval can affect the transcriptomic and proteomic profiles. Therefore, fresh brain tissue samples from living patients represent a valuable resource of metabolically intact tissue. Implantation of deep brain stimulation (DBS) electrodes into the human brain is a neurosurgical treatment for, e.g., movement disorders. Here, we describe an improved approach to collecting brain tissues from surgical instruments used in implantation of DBS device for transcriptomics and proteomics analyses.

Methods

Samples were extracted from guide tubes and recording electrodes used in routine DBS implantation procedure to treat patients with Parkinson’s disease, genetic dystonia and tremor. RNA sequencing was performed in tissues extracted from the recording microelectrodes and liquid chromatography-mass spectrometry (LC-MS) performed in tissues from guide tubes. To assess the performance of the current approach, the obtained datasets were compared with previously published datasets representing brain tissues.

Results

Altogether, 32,034 RNA transcripts representing the unique Ensembl gene identifiers were detected from eight samples representing both hemispheres of four patients. By using  LC-MS, we identified 734 unique proteins from 31 samples collected from 14 patients. The datasets are available in the BioStudies database (accession number S-BSST667). Our results indicate that surgical instruments used in DBS installation retain brain material sufficient for protein and gene expression studies. Comparison with previously published datasets obtained with similar approach proved the robustness and reproducibility of the protocol.

Conclusions

The instruments used during routine DBS surgery are a useful source for obtaining fresh brain tissues from living patients. This approach overcomes the issues that arise from using postmortem tissues, such as the effect of postmortem interval on transcriptomic and proteomic landscape of the brain, and can be used for studying molecular aspects of DBS-treatable diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40035-022-00297-y.

Applications of Tandem Mass Spectrometry (MS/MS) in Protein Analysis for Biomedical Research

Mass Spectrometry (MS) allows the analysis of proteins and peptides through a variety of methods, such as Electrospray Ionization-Mass Spectrometry (ESI-MS) or Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry (MALDI-MS). These methods allow identification of the mass of a protein or a peptide as intact molecules or the identification of a protein through peptide-mass fingerprinting generated upon enzymatic digestion. Tandem mass spectrometry (MS/MS) allows the fragmentation of proteins and peptides to determine the amino acid sequence of proteins (top-down and middle-down proteomics) and peptides (bottom-up proteomics). Furthermore, tandem mass spectrometry also allows the identification of post-translational modifications (PTMs) of proteins and peptides. Here, we discuss the application of MS/MS in biomedical research, indicating specific examples for the identification of proteins or peptides and their PTMs as relevant biomarkers for diagnostic and therapy.

Morphologically Flex Sm-MOF Based Electrochemical Immunosensor for Ultrasensitive Detection of a Colon Cancer Biomarker

Despite having the potential to synthesize stable metal-organic frameworks (MOFs), rare earth metal-based MOFs have not been exploited extensively. Owing to the high coordination numbers, the MOFs can generate a suitable coordination environment for various applications. Herein, samarium (Sm)-based MOFs were synthesized with three different organic linkers, namely, trimesic acid (TMA), meso-tetra(4-carboxyphenyl)porphine (TCPP), and 1,3,6,8-tetra(4-carboxylphenyl) pyrene(TBPy) by the solvothermal approach. The morphologies of Sm-TMA MOF, Sm-TCPP MOF, Sm-TBPy MOF were rod-shaped, cubic consisting of stacked 2D layers, and spherical made of small cubic structures, respectively. After the electrochemical properties of the synthesized MOFs were investigated, the MOFs were used to fabricate immunosensors for detection of carcinoembryonic antigen using a label-free signaling strategy. The immunosensors exhibited a wide linear detection range and a lower detection limit. The exhibited reproducibility and selectivity of the immunosensors were within the tolerable limits. The established label-free immunosensor has been successfully applied for detection of carcinoembryonic antigen in human serum samples, demonstrating that the rare earth metal-based MOFs are promising for construction of biosensors for medical diagnosis.

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.

Mass spectrometry-based methods for robust measurement of Alzheimer's disease biomarkers in biological fluids

Alzheimer's disease (AD) is the most common form of dementia affecting 60%-70% of people afflicted with this disease. Accurate antemortem diagnosis is urgently needed for early detection of AD to enable reliable estimation of prognosis, intervention, and monitoring of the disease. The National Institute on Aging/Alzheimer's Association sponsored the 'Research Framework: towards a biological definition of AD', which recommends using different biomarkers in living persons for a biomarker-based definition of AD regardless of clinical status. Fluid biomarkers represent one of key groups of them. Since cerebrospinal fluid (CSF) is in direct contact with brain and many proteins present in the brain can be detected in CSF, this fluid has been regarded as the best biofluid in which to measure AD biomarkers. Recently, technological advancements in protein detection made possible the effective study of plasma AD biomarkers despite their significantly lower concentrations versus to that in CSF. This and other challenges that face plasma-based biomarker measurements can be overcome by using mass spectrometry. In this review, we discuss AD biomarkers which can be reliably measured in CSF and plasma using targeted mass spectrometry coupled to liquid chromatography (LC/MS/MS). We describe progress in LC/MS/MS methods' development, emphasize the challenges, and summarize major findings. We also highlight the role of mass spectrometry and progress made in the process of global standardization of the measurement of Aβ42/Aβ40. Finally, we briefly describe exploratory proteomics which seek to identify new biomarkers that can contribute to detection of co-pathological processes that are common in sporadic AD.

Glycoproteins as diagnostic and prognostic biomarkers for neurodegenerative diseases: A glycoproteomic approach

Neurodegenerative diseases (NDs) are incurable and can develop progressively debilitating disorders, including dementia and ataxias. Alzheimer's disease and Parkinson's disease are the most common NDs that mainly affect the elderly people. There is an urgent need to develop new diagnostic tools so that patients can be accurately stratified at an early stage. As a common post-translational modification, protein glycosylation plays a key role in physiological and pathological processes. The abnormal changes in glycosylation are associated with the altered biological pathways in NDs. The pathogenesis-related proteins, like amyloid-β and microtubule-associated protein tau, have altered glycosylation. Importantly, specific glycosylation changes in cerebrospinal fluid, blood and urine are valuable for revealing neurodegeneration in the early stages. This review describes the emerging biomarkers based on glycoproteomics in NDs, highlighting the potential applications of glycoprotein biomarkers in the early detection of diseases, monitoring of the disease progression, and measurement of the therapeutic responses. The mass spectrometry-based strategies for characterizing glycoprotein biomarkers are also introduced.

Data-driven biomarker analysis using computational omics approaches to assess neurodegenerative disease progression

The complexity of biological systems suggests that current definitions of molecular dysfunctions are essential distinctions of a complex phenotype. This is well seen in neurodegenerative diseases (ND), such as Alzheimer's disease (AD) and Parkinson's disease (PD), multi-factorial pathologies characterized by high heterogeneity. These challenges make it necessary to understand the effectiveness of candidate biomarkers for early diagnosis, as well as to obtain a comprehensive mapping of how selective treatment alters the progression of the disorder. A large number of computational methods have been developed to explain network-based approaches by integrating individual components for modeling a complex system. In this review, high-throughput omics methodologies are presented for the identification of potent biomarkers associated with AD and PD pathogenesis as well as for monitoring the response of dysfunctional molecular pathways incorporating multilevel clinical information. In addition, principles for efficient data analysis pipelines are being discussed that can help address current limitations during the experimental process by increasing the reproducibility of benchmarking studies.

Cerebrospinal Fluid Biomarkers in Childhood Leukemias

Involvement of the central nervous system (CNS) in childhood leukemias remains a major cause of treatment failures. Analysis of the cerebrospinal fluid constitutes the most important diagnostic pillar in the detection of CNS leukemia and relies primarily on cytological and flow-cytometry studies. With increasing survival rates, it has become clear that treatments for pediatric leukemias pose a toll on the developing brain, as they may cause acute toxicities and persistent neurocognitive deficits. Preclinical research has demonstrated that established and newer therapies can injure and even destroy neuronal and glial cells in the brain. Both passive and active cell death forms can result from DNA damage, oxidative stress, cytokine release, and acceleration of cell aging. In addition, chemotherapy agents may impair neurogenesis as well as the function, formation, and plasticity of synapses. Clinical studies show that neurocognitive toxicity of chemotherapy is greatest in younger children. This raises concerns that, in addition to injury, chemotherapy may also disrupt crucial developmental events resulting in impairment of the formation and efficiency of neuronal networks. This review presents an overview of studies demonstrating that cerebrospinal fluid biomarkers can be utilized in tracing both CNS disease and neurotoxicity of administered treatments in childhood leukemias.

Systems-based proteomics to resolve the biology of Alzheimer's disease beyond amyloid and tau

The repeated failures of amyloid-targeting therapies have challenged our narrow understanding of Alzheimer's disease (AD) pathogenesis and inspired wide-ranging investigations into the underlying mechanisms of disease. Increasing evidence indicates that AD develops from an intricate web of biochemical and cellular processes that extend far beyond amyloid and tau accumulation. This growing recognition surrounding the diversity of AD pathophysiology underscores the need for holistic systems-based approaches to explore AD pathogenesis. Here we describe how network-based proteomics has emerged as a powerful tool and how its application to the AD brain has provided an informative framework for the complex protein pathophysiology underlying the disease. Furthermore, we outline how the AD brain network proteome can be leveraged to advance additional scientific and translational efforts, including the discovery of novel protein biomarkers of disease.

Novel biomarkers in Alzheimer's disease using high resolution proteomics and metabolomics: miRNAS, proteins and metabolites

Alzheimer's disease (AD) is the most common form of dementia. It affects approximately 6% of people over the age of 65 years. It is a clinicopathological, degenerative, chronical and progressive disease that exhibits a deterioration of memory, orientation, speech and other functions. Factors contributing to the pathogenesis of the disease are the presence of extracellular amyloid deposits, called neuritic senile plaques, and fibrillary protein deposits inside neurons, known as neurofibrillary bundles, that appear mainly in the frontal and temporal lobes. AD has a long preclinical latency and is difficult to diagnose and prevent at early stages. Despite the advent of novel high-throughput technologies, it is a great challenge to identify precise biomarkers to understand the progression of the disease and the development of new treatments. In this sense, important knowledge is emerging regarding novel molecular and biological candidates with diagnostic potential, including microRNAs that have a key role in gene repression. On the other hand, proteomic approaches offer a platform for the comprehensive analysis of the whole proteome in a certain physiological time. Proteomic technology investigates protein expression directly and reveals post-translational modifications known to be determinant for many human diseases. Clinically, there is growing evidence for the role of proteomic and metabolomic technologies in AD biomarker discovery. This review discusses the role of several miRNAs identified using genomic technologies, and the importance of novel proteomic and metabolomic approaches to identify new proteins and metabolites that may be useful as biomarkers for monitoring the progression and treatment of AD.

Analytical Chemistry in the 21st Century: Challenges, Solutions, and Future Perspectives of Complex Matrices Quantitative Analyses in Biological/Clinical Field

Nowadays, the challenges in analytical chemistry, and mostly in quantitative analysis, include the development and validation of new materials, strategies and procedures to meet the growing need for rapid, sensitive, selective and green methods. In this context, considering the constantly updated International Guidelines, constant innovation is mandatory both in the pre-treatment procedures and in the instrumental configurations to obtain reliable, true, and reproducible information. In this context, additionally to the classic plasma (or serum) matrices, biopsies, whole blood, and urine have seen an increase in the works that also consider non-conventional matrices. Obviously, all these studies have shown that there is a correlation between the blood levels and those found in the new matrix, in order to be able to correlate and compare the results in a robust way and reduce any bias problems. This review provides an update of the most recent developments currently in use in the sample pre-treatment and instrument configurations in the biological/clinical fields. Furthermore, the review concludes with a series of considerations regarding the role and future developments of Analytical Chemistry in light of the forthcoming challenges and new goals to be achieved.

Mitochondrial clearance and maturation of autophagosomes are compromised in LRRK2 G2019S familial Parkinson's disease patient fibroblasts

This study utilized human fibroblasts as a preclinical discovery and diagnostic platform for identification of cell biological signatures specific for the LRRK2 G2019S mutation producing Parkinson's disease (PD). Using live cell imaging with a pH-sensitive Rosella biosensor probe reflecting lysosomal breakdown of mitochondria, mitophagy rates were found to be decreased in fibroblasts carrying the LRRK2 G2019S mutation compared to cells isolated from healthy subject (HS) controls. The mutant LRRK2 increased kinase activity was reduced by pharmacological inhibition and targeted antisense oligonucleotide treatment, which normalized mitophagy rates in the G2019S cells and also increased mitophagy levels in HS cells. Detailed mechanistic analysis showed a reduction of mature autophagosomes in LRRK2 G2019S fibroblasts, which was rescued by LRRK2 specific kinase inhibition. These findings demonstrate an important role for LRRK2 protein in regulation of mitochondrial clearance by the lysosomes, which is hampered in PD with the G2019S mutation. The current results are relevant for cell phenotypic diagnostic approaches and potentially for stratification of PD patients for targeted therapy.

Perspectives in fluid biomarkers in neurodegeneration from the 2019 biomarkers in neurodegenerative diseases course-a joint PhD student course at University College London and University of Gothenburg

Until relatively recently, a diagnosis of probable Alzheimer's disease (AD) and other neurodegenerative disorders was principally based on clinical presentation, with post-mortem examination remaining a gold standard for disease confirmation. This is in sharp contrast to other areas of medicine, where fluid biomarkers, such as troponin levels in myocardial infarction, form an integral part of the diagnostic and treatment criteria. There is a pressing need for such quantifiable and easily accessible tools in neurodegenerative diseases.In this paper, based on lectures given at the 2019 Biomarkers in Neurodegenerative Diseases Course, we provide an overview of a range of cerebrospinal fluid (CSF) and blood biomarkers in neurodegenerative disorders, including the 'core' AD biomarkers amyloid β (Aβ) and tau, as well as other disease-specific and general markers of neuroaxonal injury. We then highlight the main challenges in the field, and how those could be overcome with the aid of new methodological advances, such as assay automation, mass spectrometry and ultrasensitive immunoassays.As we hopefully move towards an era of disease-modifying treatments, reliable biomarkers will be essential to increase diagnostic accuracy, allow for earlier diagnosis, better participant selection and disease activity and treatment effect monitoring.

Proteomics: techniques and applications in neuroscience

This Preface introduces the articles of the special issue on 'Proteomics' where we survey these powerful techniques specifically in the context of applications in neurosciences. Proteomics as used here is a catch-all term for approaches where a broad survey of all protein content of a cell or tissue is performed in parallel. In the special issue, various experts outline applications as diverse as finding disease biomarkers in human samples, including living participants or post-mortem brain, as well as application of protein technologies to model systems such as animals and cells. Collectively, these articles outline the utility of current technologies for proteome interrogation and identify enhancements that will shape applications to future studies. This is the Preface for the special issue "Proteomics". Cover Image for this issue: doi: 10.1111/jnc.14530.

Co-extraction for Metabolomics and Proteomics from a Single CSF Sample

In the field of neurodegeneration, it is important to identify biomarkers that enable early disease prediction, since these disorders start decades before clinical symptoms manifest. Cerebrospinal fluid (CSF) is considered an excellent source for biomarker discovery since it is in direct contact with the extracellular space of the brain and directly reflects disease-specific changes.While the liquor drainage is no major risk factor for patients, it is still not as easy and popular as simple blood sampling and less liquid can be collected. Especially when a variety of experiments for one cohort is planned, the volume of CSF can be a limiting factor. Therefore, it is essential that extraction and analytical methods are adapted to low amounts of liquor. If in follow-up studies, additional replicates to increase statistical significance or different extraction approaches are planned, the required amounts have to be minimized.With this extraction method, a combined proteomics and metabolomics approach is possible. This opportunity implies a variety of advantages. First, a classification matrix based on the comprehensive data set has a potentially higher accuracy even without a deeper understanding of the biological meaning of the different omics changes. If the proteome and metabolome differences can be linked to each other, this approach can conceivably open so far unknown doors regarding the cause or progression of different diseases like Alzheimer's or Parkinson's disease.