Quantitative proteomics for investigating psychiatric disorders

Dahuang Danshen Decoction Inhibits Pancreatic Fibrosis by Regulating Oxidative Stress and Endoplasmic Reticulum Stress

Background

In Traditional Chinese Medicine (TCM), Dahuang Danshen decoction (DD) is used to treat pancreatic fibrosis. Pancreatic fibrosis is a typical manifestation of chronic pancreatitis (CP), which affects the digestive system. The therapeutic mechanisms of DD in pancreatic fibrosis are unclear.

Aim

This study aimed to investigate the regulatory mechanisms of DD on oxidative stress and endoplasmic reticulum stress in CP.

Materials and Methods

Experimental rats were intraperitoneally injected with 500 mg/kg BW of diethyldithiocarbamate (DDC) twice a week for six weeks to induce CP. At the same time, DD was administered orally at daily doses of 1.37 g/kg BW, 2.74 g/kg BW, and 5.48 g/kg BW to evaluate its treatment effects on CP. After all treatments, pancreatic tissues were harvested and subjected to H&E staining. Transmission electron microscopy (TEM) was also performed to show the endoplasmic reticulum structure in the pancreatic tissues. Immunohistochemistry was used to detect the α-SMA expression level in the pancreatic tissues. Metabolomics analysis of the serum and proteomics analysis of the pancreatic tissues were performed to reveal the changes of endogenous metabolites and proteins, respectively. Concentrations of GSH, MDA, SOD, ROS, col-1, and col-3 were determined using corresponding kits. The western blotting method was used to determine the protein levels of Keap-1, HO-1, NQO1, Nrf2, GRP, JNK, and caspase 12. The pancreatic mRNA levels of NQO1, GPX1, HO-1, GST-π, GRP, JNK, and caspase 12 were also determined by quantitative PCR. The interactions between TCM components and Keap-1 were investigated by molecular docking modeling.

Results

The pathohistological results demonstrated that DD could ameliorate DDC-induced CP in vivo, indicated by reduction of α-SMA, col-1, col-3, TNF-α, and IL-6. DD increased serum levels of GSH and SOD but reduced pancreatic ROS. DD decreased cytoplasmic Keap-1 and increased Nrf2 nuclear localization. Correspondingly, DD increased the expression levels of Nrf2 downstream antioxidant genes NQO1, GPX1, HO-1, and GST-π. DD also decreased ERS hallmarks caspase 12 cleavage and GRP expression. Eventually, DD inhibited PSC activation by reducing JNK phosphorylation and MMK-3/p38 expression. Molecular docking analysis showed that salvianolic acid B and emodin had a good binding affinity toward Keap-1.

Conclusions

These results demonstrated that DD could ameliorate the oxidative and endoplasmic reticulum stress through releasing Nrf2 from Keap-1 binding and inducing the downstream antioxidant enzymes. As a result, DD could thwart pancreatic fibrosis by inhibiting PSCs activation, which was induced by OS and ERS through JNK and MMK3/p38 pathways.

Exploring the crosstalk of glycolysis and mitochondrial metabolism in psychiatric disorders and brain tumours

Dysfunction of metabolic pathways characterises a plethora of common pathologies and has emerged as an underlying hallmark of disease phenotypes. Here, we focus on psychiatric disorders and brain tumours and explore changes in the interplay between glycolysis and mitochondrial energy metabolism in the brain. We discuss alterations in glycolysis versus core mitochondrial metabolic pathways, such as the tricarboxylic acid cycle and oxidative phosphorylation, in major psychiatric disorders and brain tumours. We investigate potential common patterns of altered mitochondrial metabolism in different brain regions and sample types and explore how changes in mitochondrial number, shape and morphology affect disease-related manifestations. We also highlight the potential of pharmacologically targeting mitochondria to achieve therapeutic effects.

Downregulation of apolipoprotein A-IV in plasma & impaired reverse cholesterol transport in individuals with recent acts of deliberate self-harm

Background & objectives:

The major limiting factor in the prevention of suicide is the limited knowledge on molecular insights in individuals at risk. Identification of peripheral protein markers which can classify individuals at high-risk of suicide might aid in early diagnosis and effective medical intervention. The aim of the present study was, therefore, to analyze the differential regulation of plasma proteins in individuals with deliberate self-harm compared to controls.

Methods:

Using two-dimensional gel electrophoresis coupled with matrix-assisted laser desorption-ionization mass spectrometry, differentially expressed plasma proteins were identified in study participants with deliberate self-harm compared to age- and gender-matched controls. The finding was validated using mass spectrometry-based isotope-labelled relative quantification and Western blot analysis in a new set of individuals with deliberate self-harm and controls.

Results:

The plasma proteomic analysis showed that apolipoprotein A-IV (Apo A-IV) was downregulated by 2.63-fold (confidence interval: 1.52-4.54) in individuals with deliberate self-harm (n=10) compared to matched controls, which was consistent in mass spectrometry-based relative quantification and Western blot analysis performed in an independent set of individuals with deliberate self-harm (n=18). In addition, plasma levels of total cholesterol, esterified cholesterol and high-density lipoprotein (HDL) were observed to be significantly lower individuals with deliberate self-harm compared to controls.

Interpretation & conclusions:

Apo A-IV, which plays a crucial role in the esterification of free cholesterol, was found to be downregulated with concomitantly decreased levels of HDL, esterified cholesterol and total cholesterol in individuals with deliberate self-harm compared to matched controls. The present findings might provide a link between the differential regulation of plasma proteins and the previously reported results on altered cholesterol levels in individuals with deliberate self-harm.

Proteomics in the Diagnosis of Inborn Encephalopathies of Unknown Origin: A Myth or Reality

Synaptopathy underlies a great variety of neurological or neurodevelopmental disorders, including neurodegenerative diseases and the highly complex neuropsychiatric syndromes. Standard diagnostic assays in the majority of synaptopathies are insufficient to make an appropriate and fast diagnosis, which has spurred a search for more accurate diagnostic methods using recent technological advances. As synaptopathy phenotypes strictly depend on genetics and environmental factors, the best way to approach these diseases is the investigation of entire sets of protein characteristics. Thus, proteomics has emerged as a mainstay in the studies on synaptopathies, with mass spectrometry as a technology of choice. This review is an update on the proteomic methods and achievements in the understanding, diagnostics, and novel biomarkers of synaptopathies. The article also provides a critical point of view and future perspectives on the application of neuroproteomics in clinical practice.

Synaptosomal Proteome of the Orbitofrontal Cortex from Schizophrenia Patients Using Quantitative Label-Free and iTRAQ-Based Shotgun Proteomics

Schizophrenia is a chronic and incurable neuropsychiatric disorder that affects about one percent of the world population. The proteomic characterization of the synaptosome fraction of the orbitofrontal cortex is useful for providing valuable information about the molecular mechanisms of synaptic functions in these patients. Quantitative analyses of synaptic proteins were made with eight paranoid schizophrenia patients and a pool of eight healthy controls free of mental diseases. Label-free and iTRAQ labeling identified a total of 2018 protein groups. Statistical analyses revealed 12 and 55 significantly dysregulated proteins by iTRAQ and label-free, respectively. Quantitative proteome analyses showed an imbalance in the calcium signaling pathway and proteins such as reticulon-1 and cytochrome c, related to endoplasmic reticulum stress and programmed cell death. Also, it was found that there is a significant increase in limbic-system-associated membrane protein and α-calcium/calmodulin-dependent protein kinase II, associated with the regulation of human behavior. Our data contribute to a better understanding about apoptosis as a possible pathophysiological mechanism of this disease as well as neural systems supporting social behavior in schizophrenia. This study also is a joint effort of the Chr 15 C-HPP team and the Human Brain Proteome Project of B/D-HPP. All MS proteomics data are deposited in the ProteomeXchange Repository under PXD006798.

The Energy Metabolism Dysfunction in Psychiatric Disorders Postmortem Brains: Focus on Proteomic Evidence

Psychiatric disorders represent a great medical and social challenge and people suffering from these conditions face many impairments regarding personal and professional life. In addition, a mental disorder will manifest itself in approximately one quarter of the world's population at some period of their life. Dysfunction in energy metabolism is one of the most consistent scientific findings associated with these disorders. With this is mind, this review compiled data on disturbances in energy metabolism found by proteomic analyses of postmortem brains collected from patients affected by the most prevalent psychiatric disorders: schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD). We searched in the PubMed database to gather the studies and compiled all the differentially expressed proteins reported in each work. SCZ studies revealed 92 differentially expressed proteins related to energy metabolism, while 95 proteins were discovered in BPD, and 41 proteins in MDD. With the compiled data, it was possible to determine which proteins related to energy metabolism were found to be altered in all the disorders as well as which ones were altered exclusively in one of them. In conclusion, the information gathered in this work could contribute to a better understanding of the impaired metabolic mechanisms and hopefully bring insights into the underlying neuropathology of psychiatric disorders.

Serum Proteomic Profiling of Obsessive-Compulsive Disorder, Washing Subtype: A Preliminary Study

Introduction:

Obsessive-Compulsive Disorder (OCD) is a disabling mental condition that its proteomic profiling is not yet investigated. Proteomics is a valuable tool to discover biomarker approaches. It can be helpful to detect protein expression changes in complex disorders such as OCD.

Methods:

Here, by the application of 2D gel electrophoresis (2DE), a pilot study of serum proteome profile of females with washing subtype of OCD was performed. Serum samples were obtained from females with washing subtype of OCD. Following the protein extraction from the serum with acetone perception, the samples were subjected to 2DE for separation based on pI and molecular weight (MW) with triple replications. Finally, the protein spots were visualized using Coomassie blue staining method and analyzed by Progenesis SameSpots software. Furthermore, protein-protein interaction (PPI) network analysis was handled by the application of Cytoscape software.

Results:

The results suggested that 41 matched spots demonstrated significant expression alterations among which 5 proteins including immunoglobulin heavy constant alpha-1 (IGHA1), apolipoprotein A-4 (APOA4), haptoglobin (HP), protein α-1-antitrypsin (SERPINA1), and component 3 (C3) were identified by database query. Additionally, PPI network analysis indicated the central role of SERPINA1 and C3 in the network integrity. However, albumin (ALB), amyloid precursor protein (APP), and protein α-1-antitrypsin (APOA1) proteins were important in OCD PPI network as well. The identified proteins were related to 3 processes: acute-phase response, hydrogen peroxide catabolic process, and regulation of triglyceride metabolic process.

Conclusion:

It was concluded that these proteins may have a fundamental role in OCD pathogenesis. Moreover, the dysregulation of inflammatory and antioxidant systems in OCD risk was suggested by the current study. However, evaluation of bigger sample sizes and application of mass spectrometry are essential requirements to confirm this preliminary evaluation.

Recent advances in applying mass spectrometry and systems biology to determine brain dynamics

INTRODUCTION

Neurological disorders encompass various pathologies which disrupt normal brain physiology and function. Poor understanding of their underlying molecular mechanisms and their societal burden argues for the necessity of novel prevention strategies, early diagnostic techniques and alternative treatment options to reduce the scale of their expected increase. Areas covered: This review scrutinizes mass spectrometry based approaches used to investigate brain dynamics in various conditions, including neurodegenerative and neuropsychiatric disorders. Different proteomics workflows for isolation/enrichment of specific cell populations or brain regions, sample processing; mass spectrometry technologies, for differential proteome quantitation, analysis of post-translational modifications and imaging approaches in the brain are critically deliberated. Future directions, including analysis of cellular sub-compartments, targeted MS platforms (selected/parallel reaction monitoring) and use of mass cytometry are also discussed. Expert commentary: Here, we summarize and evaluate current mass spectrometry based approaches for determining brain dynamics in health and diseases states, with a focus on neurological disorders. Furthermore, we provide insight on current trends and new MS technologies with potential to improve this analysis.

Psychiatric disorders biochemical pathways unraveled by human brain proteomics

Approximately 25 % of the world population is affected by a mental disorder at some point in their life. Yet, only in the mid-twentieth century a biological cause has been proposed for these diseases. Since then, several studies have been conducted toward a better comprehension of those disorders, and although a strong genetic influence was revealed, the role of these genes in disease mechanism is still unclear. This led most recent studies to focus on the molecular basis of mental disorders. One line of investigation that has risen in the post-genomic era is proteomics, due to its power of revealing proteins and biochemical pathways associated with biological systems. Therefore, this review compiled and analyzed data of differentially expressed proteins, which were found in postmortem brain studies of the three most prevalent psychiatric diseases: schizophrenia, bipolar disorder and major depressive disorders. Overviewing both the proteomic methods used in postmortem brain studies, the most consistent metabolic pathways found altered in these diseases. We have unraveled those disorders share about 21 % of proteins affected, and though most are related to energy metabolism pathways deregulation, the main differences found are 14-3-3-mediated signaling in schizophrenia, mitochondrial dysfunction in bipolar disorder and oxidative phosphorylation in depression.

Using 15N-Metabolic Labeling for Quantitative Proteomic Analyses

Quantitative proteomics has benefited from the application of stable isotope labeling-based approaches. Using stable isotopically labeled material as an internal standard in proteomic comparisons allows an unbiased and accurate quantification of protein expression level changes. Here, we describe the use of in vivo ¹⁵N metabolic labeling to generate labeled protein standards from mice. We then present a protocol including sample preparation, mass spectrometry, and data analysis workflows using these standards to compare unlabeled proteomes. We focus on mouse brain tissue and plasma samples, although this conceptual framework can be applied to most organisms.

Stable isotope metabolic labeling suggests differential turnover of the DPYSL protein family

PURPOSE

In this work, we discuss how in vivo ¹⁵ N metabolic labeling in combination with MS simultaneously provides information on protein expression and protein turnover.

EXPERIMENTAL DESIGN

We metabolically labeled mice with the stable nitrogen isotope ¹⁵ N using a ¹⁵ N-enriched diet and analyzed unlabeled (¹⁴ N) versus ¹⁵ N-labeled brain tissue with LC-MS/MS. We then compared the ¹⁴ N versus ¹⁵ N peptide isotopologue clusters of ¹⁴ N and ¹⁵ N-labeled dihydropyrimidinase-related (DPYSL) proteins.

RESULTS

We present a workflow assessing protein expression and turnover at different time points of mouse brain development. Our data demonstrate distinct protein turnover patterns of DPYSL3 and DPYSL5 compared to other quantified proteins. We report the presence of two DPYSL3 and DPYSL5 populations with different ¹⁵ N incorporation rates, indicating altered protein turnover during development.

CONCLUSIONS AND CLINICAL RELEVANCE

In vivo ¹⁵ N metabolic labeling allows the simultaneous investigation of protein expression and turnover, enabling detailed protein dynamics studies. We report for the first time protein turnover data for the DPYSL2, DPYSL3, and DPYSL5 protein family members. As DPYSL proteins have important functions for nervous system maturation, our data provide useful information on their molecular fate during brain development.

Approaches for targeted proteomics and its potential applications in neuroscience

An extensive guide on practicable and significant quantitative proteomic approaches in neuroscience research is important not only because of the existing overwhelming limitations but also for gaining valuable understanding into brain function and deciphering proteomics from the workbench to the bedside. Early methodologies to understand the functioning of biological systems are now improving with high-throughput technologies, which allow analysis of various samples concurrently, or of thousand of analytes in a particular sample. Quantitative proteomic approaches include both gel-based and non-gel-based methods that can be further divided into different labelling approaches. This review will emphasize the role of existing technologies, their advantages and disadvantages, as well as their applications in neuroscience. This review will also discuss advanced approaches for targeted proteomics using isotope-coded affinity tag (ICAT) coupled with laser capture microdissection (LCM) followed by liquid chromatography tandem mass spectrometric (LC-MS/MS) analysis. This technology can further be extended to single cell proteomics in other areas of biological sciences and can be combined with other 'omics' approaches to reveal the mechanism of a cellular alterations. This approach may lead to further investigation in basic biology, disease analysis and surveillance, as well as drug discovery. Although numerous challenges still exist, we are confident that this approach will increase the understanding of pathological mechanisms involved in neuroendocrinology, neuropsychiatric and neurodegenerative disorders by delivering protein biomarker signatures for brain dysfunction.

Proteomics strategies for bipolar disorder evaluation: From sample preparation to validation

Bipolar disorder (BD) is a complex and costly psychiatric disorder, which affects one hundred million people worldwide. Due to its heterogeneity, correct BD diagnosis is still a challenge. In order to overcome this issue, different bioanalytical strategies have been proposed in the literature recently. Among these strategies, proteomic approaches have arisen as some of the most promising in the area. Thus, recent applications suggest protein profiles to further refine the proteome of BD as well as the discovery of novel protein biomarkers to facilitate diagnostics. In this review, the state-of-art of proteomic research in BD is summarized. Furthermore, important aspects of proteomics for understanding of BD, such as sample type and size, sampling, sample preparation, gel-based and gel-free proteomics, proteomic quantitative and protein validation are overviewed.

Serum proteomic profiling of major depressive disorder

Much has still to be learned about the molecular mechanisms of depression. This study aims to gain insight into contributing mechanisms by identifying serum proteins related to major depressive disorder (MDD) in a large psychiatric cohort study. Our sample consisted of 1589 participants of the Netherlands Study of Depression and Anxiety, comprising 687 individuals with current MDD (cMDD), 482 individuals with remitted MDD (rMDD) and 420 controls. We studied the relationship between MDD status and the levels of 171 serum proteins detected on a multi-analyte profiling platform using adjusted linear regression models. Pooled analyses of two independent validation cohorts (totaling 78 MDD cases and 156 controls) was carried out to validate our top markers. Twenty-eight analytes differed significantly between cMDD cases and controls (P < 0.05), whereas 10 partly overlapping markers differed significantly between rMDD cases and controls. Antidepressant medication use and comorbid anxiety status did not substantially impact on these findings. Sixteen of the cMDD-related markers had been assayed in the pooled validation cohorts, of which seven were associated with MDD. The analytes prominently associated with cMDD related to diverse cell communication and signal transduction processes (pancreatic polypeptide, macrophage migration inhibitory factor, ENRAGE, interleukin-1 receptor antagonist and tenascin-C), immune response (growth-regulated alpha protein) and protein metabolism (von Willebrand factor). Several proteins were implicated in depression. Changes were more prominent in cMDD, suggesting that molecular alterations in serum are associated with acute depression symptomatology. These findings may help to establish serum-based biomarkers of depression and could improve our understanding of its pathophysiology.

What Have Mass Spectrometry-Based Proteomics and Metabolomics (Not) Taught Us about Psychiatric Disorders?

Understanding the molecular causes and finding appropriate therapies for psychiatric disorders are challenging tasks for research; -omics technologies are used to elucidate the molecular mechanisms underlying brain dysfunction in a hypothesis-free manner. In this review, we will focus on mass spectrometry-based proteomics and metabolomics and address how these approaches have contributed to our understanding of psychiatric disorders. Specifically, we will discuss what we have learned from mass spectrometry-based proteomics and metabolomics studies in rodent models and human cohorts, outline current limitations and discuss the potential of these methods for future applications in psychiatry.

Can proteomics-based diagnostics aid clinical psychiatry?

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

Salivary proteomics and biomarkers in neurology and psychiatry

Biomarkers are greatly needed in the fields of neurology and psychiatry, to provide objective and earlier diagnoses of CNS conditions. Proteomics and other omics MS-based technologies are tools currently being utilized in much recent CNS research. Saliva is an interesting alternative biomaterial for the proteomic study of CNS disorders, with several advantages. Collection is noninvasive and saliva has many proteins. It is easier to collect than blood and can be collected by professionals without formal medical training. For psychiatric and neurological patients, supplying a saliva sample is less anxiety-provoking than providing a blood sample, and is less embarrassing than producing a urine specimen. The use of saliva as a biomaterial has been researched for the diagnosis of and greater understanding of several CNS conditions, including neurodegenerative diseases, autism, and depression. Salivary biomarkers could be used to rule out nonpsychiatric conditions that are often mistaken for psychiatric/neurological conditions, such as fibromyalgia, and potentially to assess cognitive ability in individuals with compromised brain function. As MS and omics technology advances, the sensitivity and utility of assessing CNS conditions using distal human biomaterials such as saliva is becoming increasingly possible.

The contribution of proteomic studies in humans, animal models, and after antidepressant treatments to investigate the molecular neurobiology of major depression

The neurobiological basis of major depressive disorder (MDD) is only partially understood. The proposed hypotheses postulate dysregulations of monoaminergic and other neurotransmitter pathways, impaired stress responses, insufficient neurogenetic and neurotrophic processes generating maladaptive neuroplasticity, inappropriate inflammatory and metabolic responses. Proteomic approaches can provide useful contributions to the investigation of the molecular neurobiology of MDD due to their open-ended nature. Studies performed in brain regions of MDD patients which had received antidepressant (AD) treatment showed that affected proteins mainly belonged to energy pathways, transport of molecules, signaling, and synaptic transmission. Studies performed in animal models offer the advantage of more controlled experimental conditions at the expense of potential loss in relevance. The design of proteomic investigations included experiments carried out in MDD models, in naive animals treated with ADs, and in animal models subjected to AD treatments. A comparison of results suggested an overlap of several modulated pathways between MDD patients and animal models. Examples include the regulation of energy metabolism, especially oxidative phosphorylation and glycolysis, signal transduction pathways, including calcium-calmodulin kinase II, synaptic proteins, and cytoskeletal proteins. Nevertheless, the paucity of studies performed in human brains requires additional studies to confirm the correspondence.

Proteomics, metabolomics, and protein interactomics in the characterization of the molecular features of major depressive disorder

Omics technologies emerged as complementary strategies to genomics in the attempt to understand human illnesses. In general, proteomics technologies emerged earlier than those of metabolomics for major depressive disorder (MDD) research, but both are driven by the identification of proteins and/or metabolites that can delineate a comprehensive characterization of MDD's molecular mechanisms, as well as lead to the identification of biomarker candidates of all types—prognosis, diagnosis, treatment, and patient stratification. Also, one can explore protein and metabolite interactomes in order to pinpoint additional molecules associated with the disease that had not been picked up initially. Here, results and methodological aspects of MDD research using proteomics, metabolomics, and protein interactomics are reviewed, focusing on human samples.

Acute phase plasma proteins are altered by electroconvulsive stimulation

Electroconvulsive therapy (ECT) is an effective antidepressant treatment, but its molecular mechanisms of action remain to be fully elucidated. To better understand the effects of ECT, we conducted a proteomic study to characterize global changes in plasma protein abundance induced by electroconvulsive stimulation (ECS) in the animal model equivalent of ECT. Male Sprague-Dawley rats were administered a single or repeat (10 sessions) course of ECS, and compared with sham-ECS administered animals. Quantitative differential protein expression analysis was performed, using 2-dimensional difference in gel electrophoresis (2D DiGE), on immunodepleted plasma. Proteins were selected for identification by liquid chromatography tandem mass spectrometry (LC-MS/MS): 150 protein spots were significantly altered following a single ECS and 178, following repeated ECS. In total, 18 proteins were identified by LC-MS/MS. Many of these were acute-phase response proteins, previously reported to be increased in depressed patients. Changes in the abundance of two proteins of interest were confirmed by other measures. Repeat ECS was found to significantly reduce plasma levels of haptoglobin and apolipoprotein A-IV, although these changes were no longer evident 4 weeks after the repeated ECS. Our results implicate the immune system-induced acute phase protein response in ECS action while identifying potential plasma biomarkers for ECS.

Time-dependent metabolomic profiling of Ketamine drug action reveals hippocampal pathway alterations and biomarker candidates

Ketamine, an N-methyl-D-aspartate receptor (NMDAR) antagonist, has fast-acting antidepressant activities and is used for major depressive disorder (MDD) patients who show treatment resistance towards drugs of the selective serotonin reuptake inhibitor (SSRI) type. In order to better understand Ketamine's mode of action, a prerequisite for improved drug development efforts, a detailed understanding of the molecular events elicited by the drug is mandatory. In the present study we have carried out a time-dependent hippocampal metabolite profiling analysis of mice treated with Ketamine. After a single injection of Ketamine, our metabolomics data indicate time-dependent metabolite level alterations starting already after 2 h reflecting the fast antidepressant effect of the drug. In silico pathway analyses revealed that several hippocampal pathways including glycolysis/gluconeogenesis, pentose phosphate pathway and citrate cycle are affected, apparent by changes not only in metabolite levels but also connected metabolite level ratios. The results show that a single injection of Ketamine has an impact on the major energy metabolism pathways. Furthermore, seven of the identified metabolites qualify as biomarkers for the Ketamine drug response.

Behavioral extremes of trait anxiety in mice are characterized by distinct metabolic profiles

No comprehensive metabolic profile of trait anxiety is to date available. To identify metabolic biosignatures for different anxiety states, we compared mice selectively inbred for ∼ 40 generations for high (HAB), normal (NAB) or low (LAB) anxiety-related behavior. Using a mass spectrometry-based targeted metabolomics approach, we quantified the levels of 257 unique metabolites in the cingulate cortex and plasma of HAB, NAB and LAB mice. We then pinpointed affected molecular systems in anxiety-related behavior by an in silico pathway and network prediction analysis followed by validation of in silico predicted alterations with molecular assays. We found distinct metabolic profiles for different trait anxiety states and detected metabolites with altered levels both in cingulate cortex and plasma. Metabolomics data revealed common candidate biomarkers in cingulate cortex and plasma for anxiety traits and in silico pathway analysis implicated amino acid metabolism, pyruvate metabolism, oxidative stress and apoptosis in the regulation of anxiety-related behavior. We report characteristic biosignatures for trait anxiety states and provide a network map of pathways involved in anxiety-related behavior. Pharmacological targeting of these pathways will enable a mechanism-based approach for identifying novel therapeutic targets for anxiety disorders.

Quantitative clinical proteomic study of autopsied human infarcted brain specimens to elucidate the deregulated pathways in ischemic stroke pathology

Ischemic stroke, still lacking an effective neuroprotective therapy is the third leading cause of global mortality and morbidity. Here, we have applied an 8-plex iTRAQ-based 2D-LC-MS/MS strategy to study the commonly regulated infarct proteome from three different brain regions (putamen, thalamus and the parietal lobe) of female Japanese patients. Infarcts were compared with age-, post-mortem interval- and location-matched control specimens. The iTRAQ experiment confidently identified 1520 proteins with 0.1% false discovery rate. Bioinformatics data mining and immunochemical validation of pivotal perturbed proteins revealed a global failure of the cellular energy metabolism in the infarcted tissues as seen by the parallel down-regulation of proteins related to glycolysis, pyruvate dehydrogenase complex, TCA cycle and oxidative phosphorylation. The concomitant down-regulation of all participating proteins (SLC25A11, SLC25A12, GOT2 and MDH2) of malate-aspartate shuttle might be responsible for the metabolic in-coordination between the cytosol and mitochondria resulting in the failure of energy metabolism. The levels of proteins related to reactive gliosis (VIM, GFAP) and anti-inflammatory response (ANXA1, ANXA2) showed an increasing trend. The elevation of ferritin (FTL, FTH1) may indicate an iron-mediated oxidative imbalance aggravating the mitochondrial failure and neurotoxicity. The deregulated proteins could be useful as potential therapeutic targets or biomarkers for ischemic stroke.

BIOLOGICAL SIGNIFICANCE

Clinical proteomics of stroke has been lagging behind other areas of clinical proteomics like Alzheimer's disease or schizophrenia. Our study is the first quantitative clinical proteomics study where iTRAQ-2D-LC-MS/MS has been utilized in the area of ischemic stroke to obtain a comparative profile of human ischemic infarcts and age-, sex-, location- and post-mortem interval-matched control brain specimens. Different pathological attributes of ischemic stroke well-known through basic and pre-clinical research such as failure of cellular energy metabolism, reactive gliosis, activation of anti-inflammatory response and aberrant iron metabolism have been observed at the bedside. Our dataset could act as a reference for similar studies done in the future using ischemic brain samples from various brain banks across the world. A meta-analysis of these studies could help to map the pathological proteome specific to ischemic stroke that will guide the scientific community to better evaluate the pros and cons of the pre-clinical models for efficacy and mechanistic studies. Infarct being the core of injury should have the most intense regulation for several key proteins involved in the pathophysiology of ischemic stroke. Hence, a part of the up-regulated proteome could leak into the general circulation that may offer candidates of interest as potential biomarkers. In support of our proposed hypothesis, we report ferritin in the current study as one of the most elevated proteins in the infarct, which has been documented as a biomarker in the context of ischemic stroke by an independent study. Overall, our approach has the potential to identify probable therapeutic targets and biomarkers in the area of ischemic stroke.

Mass spectrometry for the detection of potential psychiatric biomarkers

The search for molecules that can act as potential biomarkers is increasing in the scientific community, including in the field of psychiatry. The field of proteomics is evolving and its indispensability for identifying biomarkers is clear. Among proteomic tools, mass spectrometry is the core technique for qualitative and quantitative identification of protein markers. While significant progress has been made in the understanding of biomarkers for neurodegenerative diseases such as Alzheimer's disease, multiple sclerosis and Parkinson's disease, psychiatric disorders have not been as extensively investigated. Recent and successful applications of mass spectrometry-based proteomics in fields such as cardiovascular disease, cancer, infectious diseases and neurodegenerative disorders suggest a similar path for psychiatric disorders. In this brief review, we describe mass spectrometry and its use in psychiatric biomarker research and highlight some of the possible challenges of undertaking this type of work. Further, specific examples of candidate biomarkers are highlighted. A short comparison of proteomic with genomic methods for biomarker discovery research is presented. In summary, mass spectrometry-based techniques may greatly facilitate ongoing efforts to understand molecular mechanisms of psychiatric disorders.

Improved detection of quantitative differences using a combination of spectral counting and MS/MS total ion current

Label-free quantitative strategies are commonly used in shotgun proteomics to detect differences in protein abundance between biological sample groups. Here, we have employed a combination of two such approaches, spectral counting (SpC) and average MS/MS total ion current (MS(2) TIC), for the analysis of rat kidney mitochondria in response to metabolic acidosis. In total, 49 proteins were observed to be significantly altered in response to metabolic acidosis (p-value < 0.05). Of these, 32 proteins were uniquely observed as significantly different by SpC, 14 by MS(2) TIC, and only 3 by both approaches. Western blot analysis was performed on a subset of these proteins to validate the observed abundance differences. This study illustrates the utility and ease of combining these two label-free quantitative approaches to increase the number of detected protein abundance differences in the shotgun analysis of complex biological samples.

O potencial da rotulação metabólica de 15N para a pesquisa de esquizofrenia

Pesquisas em psiquiatria ainda necessitam de estudos não dirigidos por hipóteses para revelar fundamentos neurobiológicos e biomarcadores moleculares para distúrbios psiquiátricos. Metodologias proteômicas disponibilizam uma série de ferramentas para esses fins. Apresentamos o princípio de rotulação metabólica utilizando 15N para proteômica quantitativa e suas aplicações em modelos animais de fenótipos psiquiátricos com um foco particular em esquizofrenia. Exploramos o potencial de rotulação metabólica por 15N em diferentes tipos de experimentos, bem como suas considerações metodológicas.

Potential biomarkers in psychiatry: focus on the cholesterol system

Measuring biomarkers to identify and assess illness is a strategy growing in popularity and relevance. Although already in clinical use for treating and predicting cancer, no biological measurement is used clinically for any psychiatric disorder. Biomarkers could predict the course of a medical problem, and aid in determining how and when to treat. Several studies have indicated that of candidate psychiatric biomarkers detected using proteomic techniques, cholesterol and associated proteins, specifically apolipoproteins (Apos), may be of interest. Cholesterol is necessary for brain development and its synthesis continues at a lower rate in the adult brain. Apos are the protein component of lipoproteins responsible for lipid transport. There is extensive evidence that the levels of cholesterol and Apos may be disturbed in psychiatric disorders, including autistic spectrum disorders (ASD). Here, we describe putative serum biomarkers for psychiatric disorders, and the role of cholesterol and Apos in central nervous system (CNS) disorders.

Myelination and oxidative stress alterations in the cerebellum of the G72/G30 transgenic schizophrenia mouse model

G72/G30 is a primate-specific locus that has been repeatedly implicated as a risk factor in genetic studies of schizophrenia. The function of the longest G72 splice variant (LG72 protein) encoded by this locus is not fully understood. To investigate the role of the LG72 protein in vivo, we have generated transgenic (G72Tg) mice carrying the G72/G30 locus that exhibit schizophrenia-like symptoms. We investigated protein expression alterations in the cerebella of G72Tg compared to wild type (WT) mice using a proteomics approach based on in vivo(15)N metabolic labeling and quantitative mass spectrometry (MS). Our data revealed expression level differences of proteins involved in myelin-related processes, oxidative stress and mitochondrial function. Furthermore, in silico pathway analyses suggested common regulators and targets for the observed protein alterations. Our work sheds light on the functional role of the LG72 protein and pinpoints molecular correlates of schizophrenia-like behavior.

The 15N isotope effect in Escherichia coli: a neutron can make the difference

Several techniques based on stable isotope labeling are used for quantitative MS. These include stable isotope metabolic labeling methods for cells in culture as well as live organisms with the assumption that the stable isotope has no effect on the proteome. Here, we investigate the (15) N isotope effect on Escherichia coli cultures that were grown in either unlabeled ((14) N) or (15) N-labeled media by LC-ESI-MS/MS-based relative protein quantification. Consistent protein expression level differences and altered growth rates were observed between (14) N and (15) N-labeled cultures. Furthermore, targeted metabolite analyses revealed altered metabolite levels between (14) N and (15) N-labeled bacteria. Our data demonstrate for the first time that the introduction of the (15) N isotope affects protein and metabolite levels in E. coli and underline the importance of implementing controls for unbiased protein quantification using stable isotope labeling techniques.

Neuropattern: a new translational tool to detect and treat stress pathology I. Strategical consideration

Translational research is most prominently represented by the search for biomarkers and preclinical research. Aside from generating such new measures and methodologies, translational research additionally refers to translation of integrated knowledge. This strategy involves synthesis, exchange, and dissemination of available knowledge, with the goal of improving health services and health care systems. For stress-related disorders, such as depression and anxiety disorders, this strategy meets numerous challenges, as the great majority of these patients are treated by family physicians. Here, we introduce Neuropattern, a new diagnostic tool, which allows translation of psychobiological knowledge to this stress "bedside." Neuropatterns are conceptualized endophenotypes of the activity and reactivity status of neurobiological interfaces, which participate in the crosstalk between the brain and peripheral organs under stressful conditions. Neuropattern can easily be implemented in routine clinical work, and helps the physician to individualize those therapeutic interventions that are already available.

The (15)N isotope effect as a means for correlating phenotypic alterations and affected pathways in a trait anxiety mouse model

Stable isotope labeling techniques hold great potential for accurate quantitative proteomics comparisons by MS. To investigate the effect of stable isotopes in vivo, we metabolically labeled high anxiety-related behavior (HAB) mice with the heavy nitrogen isotope (15)N. (15)N-labeled HAB mice exhibited behavioral alterations compared to unlabeled ((14)N) HAB mice in their depression-like phenotype. To correlate behavioral alterations with changes on the molecular level, we explored the (15)N isotope effect on the brain proteome by comparing protein expression levels between (15)N-labeled and (14)N HAB mouse brains using quantitative MS. By implementing two complementary in silico pathway analysis approaches, we were able to identify altered networks in (15)N-labeled HAB mice, including major metabolic pathways such as the tricarboxylic acid (TCA) cycle and oxidative phosphorylation. Here, we discuss the affected pathways with regard to their relevance for the behavioral phenotype and critically assess the utility of exploiting the (15)N isotope effect for correlating phenotypic and molecular alterations.

Identification of proteomic signatures associated with depression and psychotic depression in post-mortem brains from major depression patients

Major depressive disorder (MDD) is a leading cause of disability worldwide and results tragically in the loss of almost one million lives in Western societies every year. This is due to poor understanding of the disease pathophysiology and lack of empirical medical tests for accurate diagnosis or for guiding antidepressant treatment strategies. Here, we have used shotgun proteomics in the analysis of post-mortem dorsolateral prefrontal cortex brain tissue from 24 MDD patients and 12 matched controls. Brain proteomes were pre-fractionated by gel electrophoresis and further analyzed by shotgun data-independent label-free liquid chromatography-mass spectrometry. This led to identification of distinct proteome fingerprints between MDD and control subjects. Some of these differences were validated by Western blot or selected reaction monitoring mass spectrometry. This included proteins associated with energy metabolism and synaptic function and we also found changes in the histidine triad nucleotide-binding protein 1 (HINT1), which has been implicated recently in regulation of mood and behavior. We also found differential proteome profiles in MDD with (n=11) and without (n=12) psychosis. Interestingly, the psychosis fingerprint showed a marked overlap to changes seen in the brain proteome of schizophrenia patients. These findings suggest that it may be possible to contribute to the disease understanding by distinguishing different subtypes of MDD based on distinct brain proteomic profiles.

Psychiatric disorder biomarker discovery using quantitative proteomics

To date, no molecular biomarker exists for any psychiatric disorder. To identify phenotype-specific biomarkers and investigate the molecular underpinnings of anxiety pathophysiology, we interrogated the well-established mouse model of high (HAB), normal (NAB) and low (LAB) anxiety-related behavior by in vivo (15)N metabolic labeling and quantitative proteomics. The (15)N metabolic labeling approach enables accurate quantification due to the early mixing of the labeled and unlabeled samples under comparison, thus avoiding the biased experimental error introduction during handling. Differentially expressed proteins between HAB and LAB mice can be validated with non-mass-spectrometry-based methods. In silico pathway analysis enables identification of protein networks implicated in anxiety neural circuits. The presented workflow provides a precise and non-hypothesis-driven tool for identifying candidate biomarkers using animal models of psychiatric disorders.

Proteomics and metabolomics analysis of a trait anxiety mouse model reveals divergent mitochondrial pathways

BACKGROUND

Although anxiety disorders are the most prevalent psychiatric disorders, no molecular biomarkers exist for their premorbid diagnosis, accurate patient subcategorization, or treatment efficacy prediction. To unravel the neurobiological underpinnings and identify candidate biomarkers and affected pathways for anxiety disorders, we interrogated the mouse model of high anxiety-related behavior (HAB), normal anxiety-related behavior (NAB), and low anxiety-related behavior (LAB) employing a quantitative proteomics and metabolomics discovery approach.

METHODS

We compared the cingulate cortex synaptosome proteomes of HAB and LAB mice by in vivo (15)N metabolic labeling and mass spectrometry and quantified the cingulate cortex metabolomes of HAB/NAB/LAB mice. The combined data sets were used to identify divergent protein and metabolite networks by in silico pathway analysis. Selected differentially expressed proteins and affected pathways were validated with immunochemical and enzymatic assays.

RESULTS

Altered levels of up to 300 proteins and metabolites were found between HAB and LAB mice. Our data reveal alterations in energy metabolism, mitochondrial import and transport, oxidative stress, and neurotransmission, implicating a previously nonhighlighted role of mitochondria in modulating anxiety-related behavior.

CONCLUSIONS

Our results offer insights toward a molecular network of anxiety pathophysiology with a focus on mitochondrial contribution and provide the basis for pinpointing affected pathways in anxiety-related behavior.

Biomarkers in development of psychotropic drugs

Biomarkers have been receiving increasing attention, especially in the field of psychiatry. In contrast to the availability of potent therapeutic tools including pharmacotherapy, psychotherapy, and biological therapies, unmet needs remain in terms of onset of action, stability of response, and further improvement of the clinical course. Biomarkers are objectively measured characteristics which serve as indicators of the causes of illnesses, their clinical course, and modification by treatment. There exist a variety of markers: laboratory markers which comprise the determination of genetic and epigenetic markers, neurotransmitters, hormones, cytokines, neuropeptides, enzymes, and others as single measures; electrophysiological markers which usually comprise electroencephalography (EEG) measures, and in particular sleep EEG and evoked potentials, magnetic encephalography, electrocardiogram, facial electromyography, skin conductance, and others; brain imaging techniques such as cranial computed tomography, magnetic resonance imaging, functional MRl, magnetic resonance spectroscopy, positron emission tomography, and single photon emission computed tomography; and behavioral approaches such as cue exposure and challenge tests which can be used to induce especially emotional processes in anxiety and depression. Examples for each of these domains are provided in this review. With a view to developing more individually tailored therapeutic strategies, the characterization of patients and the courses of different types of treatment will become even more important in the future.

General overview: biomarkers in neuroscience research

Biomarkers are in demand for disease diagnosis, treatment response monitoring, and development of novel therapeutics. Biomarker discovery in neuroscience is challenging due to absence of robust molecular correlates and the interpatient heterogeneity that characterizes neuropsychiatric disorders. Because of the complexity of these disorders, a panel of biomarkers derived from different platforms will be required to precisely reflect disease-related alterations. Animal models of psychiatric phenotypes as well as -omics and imaging methodologies are important tools for biomarker discovery. However, the limitations of current research concerning sample handling and collection, candidate biomarker validation, and a lack of interdisciplinary approaches need to be addressed. Ultimately, the coordinated effort of relevant stakeholders including researchers, physicians, and funding organizations together with standardization initiatives will be vital to overcome the present challenges and to advance personalized health care using sensitive and specific biomarkers.

Proteomic technologies for biomarker studies in psychiatry: advances and needs

In the postgenome era, proteomics has arisen as a promising tool for more complete comprehension of diseases and for biomarker discovery. Some of these objectives have already been partly achieved for illnesses such as cancer. In the case of psychiatric conditions, however, proteomic advances have had a less profound impact. Here, we outline the necessity of improving and applying proteomic methods for biomarker discovery and validation in the field of psychiatric disorders. While proteomic-based applications in neurosciences have increased in accuracy and sensitivity over the past 10 years, the development of orthogonal validation technologies has fallen behind. These issues are discussed along with the importance of integrating systems biology approaches and combining proteomics with other research approaches. The future development of such technologies may put proteomics closer to clinical applications in psychiatry.