The application of selective reaction monitoring confirms dysregulation of glycolysis in a preclinical model of schizophrenia

Neurotoxic/Neuroprotective Effects of Clozapine and the Positive Allosteric Modulator of mGluR2 JNJ-46356479 in Human Neuroblastoma Cell Cultures

Current antipsychotics (APs) effectively control positive psychotic symptoms, mainly by blocking dopamine (DA) D2 receptors, but have little effect on negative and cognitive symptoms. Increased glutamate (GLU) release would trigger neurotoxicity, leading to apoptosis and synaptic pruning, which is involved in the pathophysiology of schizophrenia. New pharmacological strategies are being developed such as positive allosteric modulators (PAMs) of the metabotropic GLU receptor 2 (mGluR2) that inhibit the presynaptic release of GLU. We previously reported that treatment of adult mice with JNJ-46356479 (JNJ), a recently developed mGluR2 PAM, partially improved neuropathological deficits and schizophrenia-like behavior in a postnatal ketamine mouse model. In the present study, we evaluated, for the first time, the putative neuroprotective and antiapoptotic activity of JNJ in a human neuroblastoma cell line and compared it with the effect of clozapine (CLZ) as a clinical AP with the highest efficacy and with apparent utility in managing negative symptoms. Specifically, we measured changes in cell viability, caspase 3 activity and apoptosis, as well as in the expression of key genes involved in survival and cell death, produced by CLZ and JNJ alone and in combination with a high DA or GLU concentration as apoptosis inducers. Our results suggest that JNJ is not neurotoxic and attenuates apoptosis, particularly by decreasing the caspase 3 activation induced by DA and GLU, as well as increasing and decreasing the number of viable and apoptotic cells, respectively, only when cultures were exposed to GLU. Its effects seem to be less neurotoxic and more neuroprotective than those observed with CLZ. Moreover, JNJ partially normalized altered expression levels of glycolytic genes, which could act as a protective factor and be related to its putative neuroprotective effect. More studies are needed to define the mechanisms of action of this GLU modulator and its potential to become a novel therapeutic agent for schizophrenia.

Cellular messenger molecules mediating addictive drug-induced cognitive impairment: cannabinoids, ketamine, methamphetamine, and cocaine

Background

Cognitive impairment is a commonly reported symptom with increasing life spans. Numerous studies have focused on identifying precise targets to relieve or reduce cognitive impairment; however, its underlying mechanism remains elusive. Most patients or animals exposed to addictive drugs exhibit cognitive impairment. Accordingly, the present review discusses the molecular changes induced by addictive drugs to clarify potential mechanisms that mediate cognitive impairments.

Main body

We investigated changes in cognitive function using four drugs: cannabinoids, ketamine, methamphetamine, and cocaine. Chronic administration of most addictive drugs reduces overall cognitive functions, such as working, spatial, and long-term recognition memories. Levels of several transcription factors involved in neuronal differentiation, as well as functional components of neurotransmitter receptors in neuronal cells, are reportedly altered. In addition, inflammatory factors showed a generally increasing trend. These impairments could be mediated by neuroinflammation, synaptic activity, and neuronal plasticity.

Conclusion

This review outlines the effects of acute or chronic drug use and potential molecular alterations in the central nervous system. In the central nervous system, addictive drug-induced changes in molecular pathways associated with cognitive function might play a pivotal role in elucidating the pathogenesis of cognitive impairment.

Screening of immune biomarkers in different breeds of chickens infected with J subgroup of avian leukemia virus by proteomic

Avian leucosis (AL) is a disease characterized by tumors and is caused by the avian leukosis virus (ALV). Because of the high variability of viruses and complex pathogenic mechanisms, screening and breeding J subgroup of ALV (ALV-J) resistant avian breeds is one of the strategies for prevention and treatment of AL, thus screening of significant immune markers is needed to promote the development of disease-resistant breeds. In this study, data-independent acquisition (DIA) technology was used to detect the DEPs of three breeds of chicken according to different comparison to investigate the potential markers. Results showed special DEPs for spleen development of each breed were detected, such as PCNT, DDB2, and ZNF62. These DEPs were involved in intestinal immune network used in production of IgA signaling pathways and related to immune response which can be used as potential markers for spleen development in different breeds. The DEPs such as RAB44 and TPN involved in viral myocarditis, transcriptional misregulation in cancer, and tuberculosis can be used as potential markers of spleen immune response after ALV-J infection in chickens. Pair-wise analysis was performed for the three breeds after the infection of ALV-J. The proteins such as RFX1, TAF10, and VH1 were differently expressed between three breeds. These DEPs involved in antigen processing and expression, acute myelogenous leukemia, and viral carcinogenesis can be used as potential immune markers after ALV-J infection of different genetic backgrounds. The screening of potential markers at protein level provides a strong theoretical research basis for disease resistance breeding in poultry.

Mini-review: Brain energy metabolism and its role in animal models of depression, bipolar disorder, schizophrenia and autism

Mitochondria are cellular organelles essential for energy metabolism and antioxidant defense. Mitochondrial impairment is implicated in many psychiatric disorders, including depression, bipolar disorder, schizophrenia, and autism. To characterize and eventually find effective treatments of bioenergetic impairment in psychiatric disease, researchers find animal models indispensable. The present review focuses on brain energetics in several environmental, genetic, drug-induced, and surgery-induced animal models of depression, bipolar disorder, schizophrenia, and autism. Most reported deficits included decreased activity in the electron transport chain, increased oxidative damage, decreased antioxidant defense, decreased ATP levels, and decreased mitochondrial potential. Models of depression, bipolar disorder, schizophrenia, and autism shared many bioenergetic deficits. This is in concordance with the absence of a disease-specific brain energy phenotype in human patients. Unfortunately, due to the absence of null results in examined literature, indicative of reporting bias, we refrain from making generalized conclusions. Present review can be a valuable tool for comparing current findings, generating more targeted hypotheses, and selecting fitting models for further preclinical research.

Proteomic Analysis of the Early Development of the Phalaenopsis amabilis Flower Bud under Low Temperature Induction Using the iTRAQ/MRM Approach

Phalaenopsis amabilis, one of the most important plants in the international flower market due to its graceful shape and colorful flowers, is an orchid that undergoes vernalization and requires low-temperature treatment for flowering. There have been few reports on the proteomics of the development of flower buds. In this study, isobaric tags for relative and absolute quantification (iTRAQ) were used to identify 5064 differentially expressed proteins in P. amabilis under low-temperature treatment; of these, 42 were associated with early floral induction, and 18 were verified by mass spectrometry multi-reaction monitoring (MRM). The data are available via ProteomeXchange under identifier PXD013908. Among the proteins associated with the vernalization pathway, PEQU_11434 (glycine-rich RNA-binding protein GRP1A-like) and PEQU_19304 (FT, VRN3 homolog) were verified by MRM, and some other important proteins related to vernalization and photoperiod pathway that were detected by iTRAQ but not successfully verified by MRM, such as PEQU_11045 (UDP-N-acetylglucosamine diphosphorylase), phytochromes A (PEQU_13449, PEQU_35378), B (PEQU_09249), and C (PEQU_41401). Our data revealed a regulation network of the early development of flower buds in P. amabilis under low temperature induction.

Ketogenic diet for schizophrenia: clinical implication

PURPOSE OF REVIEW

The aim of this article is to review recent findings on the efficacy of ketogenic diet in preclinical models and in patients with schizophrenia. This review will also highlight emerging evidence for compromised glucose and energy metabolism in schizophrenia, which provides a strong rationale and a potential mechanism of action for ketogenic diet.

RECENT FINDINGS

Recent transcriptomic, proteomic and metabolomic evidence from postmortem prefrontal cortical samples and in-vivo NMR spectroscopy results support the hypothesis that there is a bioenergetics dysfunction characterized by abnormal glucose handling and mitochondrial dysfunctions resulting in impaired synaptic communication in the brain of people with schizophrenia. Ketogenic diet, which provides alternative fuel to glucose for bioenergetic processes in the brain, normalizes schizophrenia-like behaviours in translationally relevant pharmacological and genetic mouse models. Furthermore, recent case studies demonstrate that ketogenic diet produces improvement in psychiatric symptoms as well as metabolic dysfunctions and body composition in patients with schizophrenia.

SUMMARY

These results support that ketogenic diet may present a novel therapeutic approach through restoring brain energy metabolism in schizophrenia. Randomized controlled clinical trials are needed to further show the efficacy of ketogenic diet as a co-treatment to manage both clinical symptoms and metabolic abnormalities inherent to the disease and resulted by antipsychotic treatment.

Ketogenic diet prevents impaired prepulse inhibition of startle in an acute NMDA receptor hypofunction model of schizophrenia

Recent transcriptomic, proteomic and metabolomics studies have highlighted an abnormal cerebral glucose and energy metabolism as one of the potential pathophysiological mechanisms of schizophrenia. This raises the possibility that a metabolically-based intervention might have therapeutic value in the management of schizophrenia, a notion supported by our recent results that a low carbohydrate/high-fat therapeutic ketogenic diet (KD) prevented a variety of behavioural abnormalities induced by pharmacological inhibition of NMDA glutamate receptors. Here we asked if the beneficial effects of KD can be generalised to impaired prepulse inhibition of startle (PPI), a translationally validated endophenotype of schizophrenia, in a pharmacological model in mice. Furthermore, we addressed the issue of whether the effect of KD is linked to the calorie-restricted state typical of the initial phase of KD. We fed male C57BL/6 mice a KD for 7 weeks and tested PPI at 3 and 7 weeks, in the presence and absence of a significant digestible energy deficit, respectively. We used an NMDA receptor hypo-function model of schizophrenia induced by acute injection of dizocilpine (MK-801). We found that KD effectively prevented MK-801-induced PPI impairments at both 3 and 7 weeks, irrespective of the presence or absence of digestible energy deficit. Furthermore, there was a lack of correlation between PPI and body weight changes. These results support the efficacy of the therapeutic KD in a translational model of schizophrenia and furthermore provide evidence against the role of calorie restriction in its mechanism of action.

Integrated analysis of transcriptomic and proteomic data from tree peony (P. ostii) seeds reveals key developmental stages and candidate genes related to oil biosynthesis and fatty acid metabolism

Tree peony (Paeonia section Moutan DC.) seeds are an excellent source of beneficial natural compounds that promote health, and they contain high levels of alpha-linolenic acid (ALA). In recent years, tree peony has been emerging as an oil crop. Therefore, combined analysis of the transcriptome and proteome of tree peony (P. ostii) seeds at 25, 32, 39, 53, 67, 81, 88, 95, and 109 days after pollination (DAP) was conducted to better understand the transcriptional and translational regulation of seed development and oil biosynthesis. A total of 38,482 unigenes and 2841 proteins were identified. A total of 26,912 differentially expressed genes (DEGs) and 592 differentially expressed proteins (DEPs) were clustered into three groups corresponding to the rapid growth, seed inclusion enrichment and conversion, and late dehydration and mature stages of seed development. Fifteen lipid metabolism pathways were identified at both the transcriptome and proteome levels. Pathway enrichment analysis revealed that a period of rapid fatty acid biosynthesis occurred at 53-88 DAP. Furthermore, 211 genes and 35 proteins associated with the fatty acid metabolism pathway, 63 genes and 11 proteins associated with the biosynthesis of unsaturated fatty acids (UFAs), and 115 genes and 24 proteins associated with ALA metabolism were identified. Phylogenetic analysis revealed that 16 putative fatty acid desaturase (FAD)-encoding genes clustered into four FAD groups, eight of which exhibited the highest expression at 53 DAP, suggesting that they play an important role in ALA accumulation. RT-qPCR analysis indicated that the temporal expression patterns of oil biosynthesis genes were largely similar to the RNA-seq results. The expression patterns of fatty acid metabolism- and seed development-related proteins determined by MRM were also highly consistent with the results obtained in the proteomic analysis. Correlation analysis indicated significant differences in the number and abundance of DEGs and DEPs but a high level of consistency in expression patterns and metabolic pathways. The results of the present study represent the first combined transcriptomic and proteomic analysis of tree peony seeds and provide insight into tree peony seed development and oil accumulation.

Phosphoglycerate Mutase 1 Promotes Cell Proliferation and Neuroblast Differentiation in the Dentate Gyrus by Facilitating the Phosphorylation of cAMP Response Element-Binding Protein

In a previous study, we observed a significant increase in phosphoglycerate mutase 1 (PGAM1) levels after pyridoxine treatment. In the present study, we investigated the effects of PGAM1 on novel object recognition, cell proliferation, and neuroblast differentiation in the dentate gyrus. We generated a Tat-PGAM1 fusion protein to cross the blood-brain barrier and neuronal plasma membrane. We administered the Tat peptide, control-PGAM1, or Tat-PGAM1 fusion protein to 8-week-old mice once a day for 3 weeks and tested novel object recognition memory. The mice were then euthanized to conduct western blot analysis for polyhistidine expression and immunohistochemical analysis for Ki67, doublecortin, and phosphorylated cAMP response element-binding protein. Mice treated with Tat peptide showed similar exploration times for familiar and new objects and the discrimination index was significantly lower in this group than in the control group. Tat-PGAM1 moderately increased the exploration time of new objects when compared to familiar objects, while the discrimination index was significantly higher in the Tat-PGAM1-treated group, but not in the control-PGAM1-treated group, when compared with the control group. Higher PGAM1 protein expression was observed in the hippocampus of Tat-PGAM1-treated mice when compared with the hippocampi of control, Tat peptide-, and control-PGAM1-treated mice, using western blot analysis. In addition, the numbers of proliferating cells and differentiated neuroblasts were significantly lower in the Tat peptide-treated group than in the control group. In contrast, the numbers of proliferating cells and differentiated neuroblasts in the dentate gyrus were higher in the Tat-PGAM1-treated group than in the control group. Administration of Tat-PGAM1 significantly facilitated the phosphorylation of cAMP response element-binding protein in the dentate gyrus. Administration of control-PGAM1 did not show any significant effects on novel object recognition, cell proliferation, and neuroblast differentiation in the dentate gyrus. These results suggest that PGAM1 plays a role in cell proliferation and neuroblast differentiation in the dentate gyrus via the phosphorylation of cAMP response element-binding protein in the hippocampus.

Proteomic Analysis of Hippocampus in a Mouse Model of Depression Reveals Neuroprotective Function of Ubiquitin C-terminal Hydrolase L1 (UCH-L1) via Stress-induced Cysteine Oxidative Modifications

Chronic physical restraint stress increases oxidative stress in the brain, and dysregulation of oxidative stress can be one of the causes of major depressive disorder. To understand the underlying mechanisms, we undertook a systematic proteomic analysis of hippocampus in a chronic restraint stress mouse model of depression. Combining two-dimensional gel electrophoresis (2D-PAGE) for protein separation with nanoUPLC-ESI-q-TOF tandem mass spectrometry, we identified sixty-three protein spots that changed in the hippocampus of mice subjected to chronic restraint stress. We identified and classified the proteins that changed after chronic stress, into three groups respectively functioning in neural plasticity, metabolic processes and protein aggregation. Of these, 5 proteins including ubiquitin C-terminal hydrolase L1 (UCH-L1), dihydropyrimidinase-related protein 2 (DPYL2), haloacid dehalogenase-like hydrolase domain-containing protein 2 (HDHD2), actin-related protein 2/3 complex subunit 5 (ARPC5) and peroxiredoxin-2 (PRDX2), showed pI shifts attributable to post-translational modifications. Further analysis indicated that UCH-L1 underwent differential oxidations of 2 cysteine residues following chronic stress. We investigated whether the oxidized form of UCH-L1 plays a role in stressed hippocampus, by comparing the effects of UCH-L1 and its Cys mutants on hippocampal cell line HT-22 in response to oxidative stress. This study demonstrated that UCH-L1 wild-type and cysteine to aspartic acid mutants, but not its cysteine to serine mutants, afforded neuroprotective effects against oxidative stress; there were no discernible differences between wild-type UCH-L1 and its mutants in the absence of oxidative stress. These findings suggest that cysteine oxidative modifications of UCH-L1 in the hippocampus play key roles in neuroprotection against oxidative stress caused in major depressive disorder.

Alteration of Neuronal Excitability and Short-Term Synaptic Plasticity in the Prefrontal Cortex of a Mouse Model of Mental Illness

Using a genetic mouse model that faithfully recapitulates a DISC1 genetic alteration strongly associated with schizophrenia and other psychiatric disorders, we examined the impact of this mutation within the prefrontal cortex. Although cortical layering, cytoarchitecture, and proteome were found to be largely unaffected, electrophysiological examination of the mPFC revealed both neuronal hyperexcitability and alterations in short-term synaptic plasticity consistent with enhanced neurotransmitter release. Increased excitability of layer II/III pyramidal neurons was accompanied by consistent reductions in voltage-activated potassium currents near the action potential threshold as well as by enhanced recruitment of inputs arising from superficial layers to layer V. We further observed reductions in both the paired-pulse ratios and the enhanced short-term depression of layer V synapses arising from superficial layers consistent with enhanced neurotransmitter release at these synapses. Recordings from layer II/III pyramidal neurons revealed action potential widening that could account for enhanced neurotransmitter release. Significantly, we found that reduced functional expression of the voltage-dependent potassium channel subunit K_v1.1 substantially contributes to both the excitability and short-term plasticity alterations that we observed. The underlying dysregulation of K_v1.1 expression was attributable to cAMP elevations in the PFC secondary to reduced phosphodiesterase 4 activity present in Disc1 deficiency and was rescued by pharmacological blockade of adenylate cyclase. Our results demonstrate a potentially devastating impact of Disc1 deficiency on neural circuit function, partly due to K_v1.1 dysregulation that leads to a dual dysfunction consisting of enhanced neuronal excitability and altered short-term synaptic plasticity.SIGNIFICANCE STATEMENT Schizophrenia is a profoundly disabling psychiatric illness with a devastating impact not only upon the afflicted but also upon their families and the broader society. Although the underlying causes of schizophrenia remain poorly understood, a growing body of studies has identified and strongly implicated various specific risk genes in schizophrenia pathogenesis. Here, using a genetic mouse model, we explored the impact of one of the most highly penetrant schizophrenia risk genes, DISC1, upon the medial prefrontal cortex, the region believed to be most prominently dysfunctional in schizophrenia. We found substantial derangements in both neuronal excitability and short-term synaptic plasticity-parameters that critically govern neural circuit information processing-suggesting that similar changes may critically, and more broadly, underlie the neural computational dysfunction prototypical of schizophrenia.

Opportunities and Challenges of Multiplex Assays: A Machine Learning Perspective

Multiplex assays that allow the simultaneous measurement of multiple analytes in small sample quantities have developed into a widely used technology. Their implementation spans across multiple assay systems and can provide readouts of similar quality as the respective single-plex measures, albeit at far higher throughput. Multiplex assay systems are therefore an important element for biomarker discovery and development strategies but analysis of the derived data can face substantial challenges that may limit the possibility of identifying meaningful biological markers. This chapter gives an overview of opportunities and challenges of multiplexed biomarker analysis, in particular from the perspective of machine learning aimed at identification of predictive biological signatures.

Employing proteomics to unravel the molecular effects of antipsychotics and their role in schizophrenia

Schizophrenia is an incurable neuropsychiatric disorder managed mostly by treatment of the patients with antipsychotics. However, the efficacy of these drugs has remained only low to moderate despite intensive research efforts since the early 1950s when chlorpromazine, the first antipsychotic, was synthesized. In addition, antipsychotic treatment can produce often undesired severe side effects in the patients and addressing these remains a large unmet clinical need. One of the reasons for the low effectiveness of these drugs is the limited knowledge about the molecular mechanisms of schizophrenia, which impairs the development of new and more effective treatments. Recently, proteomic studies of clinical and preclinical samples have identified changes in the levels of specific proteins in response to antipsychotic treatment, which have converged on molecular pathways such as cell communication and signaling, inflammation and cellular growth, and maintenance. The findings of these studies are summarized and discussed in this review and we suggest that this provides validation of proteomics as a useful tool for mining drug mechanisms of action and potentially for pinpointing novel molecular targets that may enable development of more effective medications.

MK-801 treatment affects glycolysis in oligodendrocytes more than in astrocytes and neuronal cells: insights for schizophrenia

Schizophrenia is a debilitating mental disorder, affecting more than 30 million people worldwide. As a multifactorial disease, the underlying causes of schizophrenia require analysis by multiplex methods such as proteomics to allow identification of whole protein networks. Previous post-mortem proteomic studies on brain tissues from schizophrenia patients have demonstrated changes in activation of glycolytic and energy metabolism pathways. However, it is not known whether these changes occur in neurons or in glial cells. To address this question, we treated neuronal, astrocyte, and oligodendrocyte cell lines with the NMDA receptor antagonist MK-801 and measured the levels of six glycolytic enzymes by Western blot analysis. MK-801 acts on the glutamatergic system and has been proposed as a pharmacological means of modeling schizophrenia. Treatment with MK-801 resulted in significant changes in the levels of glycolytic enzymes in all cell types. Most of the differences were found in oligodendrocytes, which had altered levels of hexokinase 1 (HK1), enolase 2 (ENO2), phosphoglycerate kinase (PGK), and phosphoglycerate mutase 1 after acute MK-801 treatment (8 h), and HK1, ENO2, PGK, and triosephosphate isomerase (TPI) following long term treatment (72 h). Addition of the antipsychotic clozapine to the cultures resulted in counter-regulatory effects to the MK-801 treatment by normalizing the levels of ENO2 and PGK in both the acute and long term cultures. In astrocytes, MK-801 affected only aldolase C (ALDOC) under both acute conditions and HK1 and ALDOC following long term treatment, and TPI was the only enzyme affected under long term conditions in the neuronal cells. In conclusion, MK-801 affects glycolysis in oligodendrocytes to a larger extent than neuronal cells and this may be modulated by antipsychotic treatment. Although cell culture studies do not necessarily reflect the in vivo pathophysiology and drug effects within the brain, these results suggest that neurons, astrocytes, and oligodendrocytes are affected differently in schizophrenia. Employing in vitro models using neurotransmitter agonists and antagonists may provide new insights about the pathophysiology of schizophrenia which could lead to a novel system for drug discovery.

The proteome of schizophrenia

On observing schizophrenia from a clinical point of view up to its molecular basis, one may conclude that this is likely to be one of the most complex human disorders to be characterized in all aspects. Such complexity is the reflex of an intricate combination of genetic and environmental components that influence brain functions since pre-natal neurodevelopment, passing by brain maturation, up to the onset of disease and disease establishment. The perfect function of tissues, organs, systems, and finally the organism depends heavily on the proper functioning of cells. Several lines of evidence, including genetics, genomics, transcriptomics, neuropathology, and pharmacology, have supported the idea that dysfunctional cells are causative to schizophrenia. Together with the above-mentioned techniques, proteomics have been contributing to understanding the biochemical basis of schizophrenia at the cellular and tissue level through the identification of differentially expressed proteins and consequently their biochemical pathways, mostly in the brain tissue but also in other cells. In addition, mass spectrometry-based proteomics have identified and precisely quantified proteins that may serve as biomarker candidates to prognosis, diagnosis, and medication monitoring in peripheral tissue. Here, we review all data produced by proteomic investigation in the last 5 years using tissue and/or cells from schizophrenic patients, focusing on postmortem brain tissue and peripheral blood serum and plasma. This information has provided integrated pictures of the biochemical systems involved in the pathobiology, and has suggested potential biomarkers, and warrant potential targets to alternative treatment therapies to schizophrenia.

Distinct proteomic profiles in post-mortem pituitary glands from bipolar disorder and major depressive disorder patients

Disturbances of the hypothalamic-pituitary-adrenal axis have been implicated in the pathophysiology of bipolar disorder (BD) and major depressive disorder (MDD). To examine this further, we carried out proteomic profiling of post-mortem pituitaries from 13 BD and 14 MDD patients, in comparison to 15 controls. Liquid chromatography-mass spectrometry (LC-MS(E)) analysis showed that BD patients had significantly increased levels of the major pituitary hormones pro-opiomelanocortin (POMC) and galanin. BD patients also showed changes in proteins associated with gene transcription, stress response, lipid metabolism and growth signalling. In contrast, LC-MS(E) profiling revealed that MDD patients had significantly decreased levels of the prohormone-converting enzyme carboxypeptidease E and follow-up enzymatic analysis showed decreased activity of prolyl-oligopeptidase convertase. This suggested that altered prohormone processing may occur in pituitaries of MDD patients. In addition, MDD patients had significant changes in proteins involved in intracellular transport and cytoskeletal signalling. Finally, we carried out selective reaction monitoring (SRM) mass spectrometry profiling for validation of protein changes in key biological pathways. This confirmed increased POMC levels in BD patients with no change in the levels of this prohormone in MDD. This study demonstrates that proteomic profiling analysis of the pituitary can lead to new insights into the pathophysiology of BD and MDD. Also, given that the pituitary directly releases a variety of bioactive molecules into the bloodstream, many of the proteins identified here could serve as focal points in the search for peripheral biomarkers in clinical or drug treatment studies of BD and MDD patients.

Proteomic analysis of post mortem brain tissue from autism patients: evidence for opposite changes in prefrontal cortex and cerebellum in synaptic connectivity-related proteins

Background

Autism is a neurodevelopmental disorder characterized by impaired language, communication and social skills. Although genetic studies have been carried out in this field, none of the genes identified have led to an explanation of the underlying causes. Here, we have investigated molecular alterations by proteomic profiling of post mortem brain samples from autism patients and controls. The analysis focussed on prefrontal cortex and cerebellum as previous studies have found that these two brain regions are structurally and functionally connected, and they have been implicated in autism.

Methods

Post mortem prefrontal cortex and cerebellum samples from autism patients and matched controls were analysed using selected reaction monitoring mass spectrometry (SRM-MS). The main objective was to identify significantly altered proteins and biological pathways and to compare these across these two brain regions.

Results

Targeted SRM-MS resulted in identification of altered levels of proteins related to myelination, synaptic vesicle regulation and energy metabolism. This showed decreased levels of the immature astrocyte marker vimentin in both brain regions, suggesting a decrease in astrocyte precursor cells. Also, decreased levels of proteins associated with myelination and increased synaptic and energy-related proteins were found in the prefrontal cortex, indicative of increased synaptic connectivity. Finally, opposite directional changes were found for myelination and synaptic proteins in the cerebellum.

Conclusion

These findings suggest altered structural and/or functional connectivity in the prefrontal cortex and cerebellum in autism patients, as shown by opposite effects on proteins involved in myelination and synaptic function. Further investigation of these findings could help to increase our understanding of the mechanisms underlying autism relating to brain connectivity, with the ultimate aim of facilitating novel therapeutic approaches.

Data Pre-Processing for Label-Free Multiple Reaction Monitoring (MRM) Experiments

Multiple Reaction Monitoring (MRM) conducted on a triple quadrupole mass spectrometer allows researchers to quantify the expression levels of a set of target proteins. Each protein is often characterized by several unique peptides that can be detected by monitoring predetermined fragment ions, called transitions, for each peptide. Concatenating large numbers of MRM transitions into a single assay enables simultaneous quantification of hundreds of peptides and proteins. In recognition of the important role that MRM can play in hypothesis-driven research and its increasing impact on clinical proteomics, targeted proteomics such as MRM was recently selected as the Nature Method of the Year. However, there are many challenges in MRM applications, especially data pre‑processing where many steps still rely on manual inspection of each observation in practice. In this paper, we discuss an analysis pipeline to automate MRM data pre‑processing. This pipeline includes data quality assessment across replicated samples, outlier detection, identification of inaccurate transitions, and data normalization. We demonstrate the utility of our pipeline through its applications to several real MRM data sets.

Modeling combined schizophrenia-related behavioral and metabolic phenotypes in rodents

Schizophrenia is a chronic, debilitating disorder with a complex behavioral and cognitive phenotype underlined by a similarly complex etiology involving an interaction between susceptibility genes and environmental factors during early development. Limited progress has been made in developing novel pharmacotherapy, partly due to a lack of valid animal models. The recent recognition of the potentially causal role of central and peripheral energy metabolism in the pathophysiology of schizophrenia raises the need of research on animal models that combine both behavioral and metabolic phenotypic domains, similar to what have been identified in humans. In this review we focus on selected genetic (DBA/2J mice, leptin receptor mutants, and PSD-93 knockout mice), early neurodevelopmental (maternal protein deprivation) and pharmacological (acute phencyclidine) animal models that capture the combined behavioral and metabolic abnormalities shown by schizophrenic patients. In reviewing behavioral phenotypes relevant to schizophrenia we apply the principles established by the Research Domain Criteria (RDoC) for better translation. We demonstrate that etiologically diverse manipulations such as specific breeding, deletion of genes that are primarily involved in metabolic regulation and in synaptic plasticity, as well as early metabolic deprivation and adult pharmacological challenge of the glutamate system can lead to schizophrenia-related behavioral and metabolic phenotypes, which suggest that these pathways might be interlinked. We propose that using animal models that combine different domains of schizophrenia can be used as a translationally valid approach to capture the system-level complex interplay between peripheral and central processes in the development of psychopathology.

Serum proteomic analysis identifies sex-specific differences in lipid metabolism and inflammation profiles in adults diagnosed with Asperger syndrome

Background

The higher prevalence of Asperger Syndrome (AS) and other autism spectrum conditions in males has been known for many years. However, recent multiplex immunoassay profiling studies have shown that males and females with AS have distinct proteomic changes in serum.

Methods

Here, we analysed sera from adults diagnosed with AS (males = 14, females = 16) and controls (males = 13, females = 16) not on medication at the time of sample collection, using a combination of multiplex immunoassay and shotgun label-free liquid chromatography mass spectrometry (LC-MS^E). The main objective was to identify sex-specific serum protein changes associated with AS.

Results

Multiplex immunoassay profiling led to identification of 16 proteins that were significantly altered in AS individuals in a sex-specific manner. Three of these proteins were altered in females (ADIPO, IgA, APOA1), seven were changed in males (BMP6, CTGF, ICAM1, IL-12p70, IL-16, TF, TNF-alpha) and six were changed in both sexes but in opposite directions (CHGA, EPO, IL-3, TENA, PAP, SHBG). Shotgun LC-MS^E profiling led to identification of 13 serum proteins which had significant sex-specific changes in the AS group and, of these, 12 were altered in females (APOC2, APOE, ARMC3, CLC4K, FETUB, GLCE, MRRP1, PTPA, RN149, TLE1, TRIPB, ZC3HE) and one protein was altered in males (RGPD4). The free androgen index in females with AS showed an increased ratio of 1.63 compared to controls.

Conclusion

Taken together, the serum multiplex immunoassay and shotgun LC-MS^E profiling results indicate that adult females with AS had alterations in proteins involved mostly in lipid transport and metabolism pathways, while adult males with AS showed changes predominantly in inflammation signalling. These results provide further evidence that the search for biomarkers or novel drug targets in AS may require stratification into male and female subgroups, and could lead to the development of novel targeted treatment approaches.

Brain quantitative proteomics combining GeLC-MS and isotope-coded protein labeling (ICPL)

Proteomics has been revolutionized by the rapid advance of mass spectrometric instrumentations and techniques. Parallel methodologies for the quantification of proteomes also evolved, including in vitro stable isotope labeling. Here, we present a protocol for employing isotope-coded protein labeling (ICPL) as part of a shotgun proteomics workflow denoting its advantages and disadvantages. This protocol is suitable to studying any proteome of interest, only requiring a specific sample preparation and protein identification. Given our expertise, descriptions here are centered on the study of brain disorders.

Long-term artificial sweetener acesulfame potassium treatment alters neurometabolic functions in C57BL/6J mice

With the prevalence of obesity, artificial, non-nutritive sweeteners have been widely used as dietary supplements that provide sweet taste without excessive caloric load. In order to better understand the overall actions of artificial sweeteners, especially when they are chronically used, we investigated the peripheral and central nervous system effects of protracted exposure to a widely used artificial sweetener, acesulfame K (ACK). We found that extended ACK exposure (40 weeks) in normal C57BL/6J mice demonstrated a moderate and limited influence on metabolic homeostasis, including altering fasting insulin and leptin levels, pancreatic islet size and lipid levels, without affecting insulin sensitivity and bodyweight. Interestingly, impaired cognitive memory functions (evaluated by Morris Water Maze and Novel Objective Preference tests) were found in ACK-treated C57BL/6J mice, while no differences in motor function and anxiety levels were detected. The generation of an ACK-induced neurological phenotype was associated with metabolic dysregulation (glycolysis inhibition and functional ATP depletion) and neurosynaptic abnormalities (dysregulation of TrkB-mediated BDNF and Akt/Erk-mediated cell growth/survival pathway) in hippocampal neurons. Our data suggest that chronic use of ACK could affect cognitive functions, potentially via altering neuro-metabolic functions in male C57BL/6J mice.

Recent advances in quantitative neuroproteomics

The field of proteomics is undergoing rapid development in a number of different areas including improvements in mass spectrometric platforms, peptide identification algorithms and bioinformatics. In particular, new and/or improved approaches have established robust methods that not only allow for in-depth and accurate peptide and protein identification and modification, but also allow for sensitive measurement of relative or absolute quantitation. These methods are beginning to be applied to the area of neuroproteomics, but the central nervous system poses many specific challenges in terms of quantitative proteomics, given the large number of different neuronal cell types that are intermixed and that exhibit distinct patterns of gene and protein expression. This review highlights the recent advances that have been made in quantitative neuroproteomics, with a focus on work published over the last five years that applies emerging methods to normal brain function as well as to various neuropsychiatric disorders including schizophrenia and drug addiction as well as of neurodegenerative diseases including Parkinson's disease and Alzheimer's disease. While older methods such as two-dimensional polyacrylamide electrophoresis continued to be used, a variety of more in-depth MS-based approaches including both label (ICAT, iTRAQ, TMT, SILAC, SILAM), label-free (label-free, MRM, SWATH) and absolute quantification methods, are rapidly being applied to neurobiological investigations of normal and diseased brain tissue as well as of cerebrospinal fluid (CSF). While the biological implications of many of these studies remain to be clearly established, that there is a clear need for standardization of experimental design and data analysis, and that the analysis of protein changes in specific neuronal cell types in the central nervous system remains a serious challenge, it appears that the quality and depth of the more recent quantitative proteomics studies is beginning to shed light on a number of aspects of neuroscience that relates to normal brain function as well as of the changes in protein expression and regulation that occurs in neuropsychiatric and neurodegenerative disorders.

Systems biology, bioinformatics, and biomarkers in neuropsychiatry

Although neuropsychiatric (NP) disorders are among the top causes of disability worldwide with enormous financial costs, they can still be viewed as part of the most complex disorders that are of unknown etiology and incomprehensible pathophysiology. The complexity of NP disorders arises from their etiologic heterogeneity and the concurrent influence of environmental and genetic factors. In addition, the absence of rigid boundaries between the normal and diseased state, the remarkable overlap of symptoms among conditions, the high inter-individual and inter-population variations, and the absence of discriminative molecular and/or imaging biomarkers for these diseases makes difficult an accurate diagnosis. Along with the complexity of NP disorders, the practice of psychiatry suffers from a "top-down" method that relied on symptom checklists. Although checklist diagnoses cost less in terms of time and money, they are less accurate than a comprehensive assessment. Thus, reliable and objective diagnostic tools such as biomarkers are needed that can detect and discriminate among NP disorders. The real promise in understanding the pathophysiology of NP disorders lies in bringing back psychiatry to its biological basis in a systemic approach which is needed given the NP disorders' complexity to understand their normal functioning and response to perturbation. This approach is implemented in the systems biology discipline that enables the discovery of disease-specific NP biomarkers for diagnosis and therapeutics. Systems biology involves the use of sophisticated computer software "omics"-based discovery tools and advanced performance computational techniques in order to understand the behavior of biological systems and identify diagnostic and prognostic biomarkers specific for NP disorders together with new targets of therapeutics. In this review, we try to shed light on the need of systems biology, bioinformatics, and biomarkers in neuropsychiatry, and illustrate how the knowledge gained through these methodologies can be translated into clinical use providing clinicians with improved ability to diagnose, manage, and treat NP patients.

Translational strategies to schizophrenia from a proteomic perspective

There is an urgent necessity of designing translational strategies to schizophrenia, a mental disorder that affects 30 million people worldwide. Proteomic studies have been providing data enough to pave the way for that, but these need to be connected in a concise manner in order to translate laboratorial findings to real improvements in the lives of the patients.

Translational strategies to schizophrenia from a proteomic perspective

There is an urgent necessity of designing translational strategies to schizophrenia, a mental disorder that affects 30 million people worldwide. Proteomic studies have been providing data enough to pave the way for that, but these need to be connected in a concise manner in order to translate laboratorial findings to real improvements in the lives of the patients.