Proteomic analysis of lymphoblastoid cells derived from monozygotic twins discordant for bipolar disorder: a preliminary study

Proteome analysis of the prefrontal cortex and the application of machine learning models for the identification of potential biomarkers related to suicide

Introduction

Suicide is a significant public health problem, with increased rates in low- and middle-income countries such as Mexico; therefore, suicide prevention is important. Suicide is a complex and multifactorial phenomenon in which biological and social factors are involved. Several studies on the biological mechanisms of suicide have analyzed the proteome of the dorsolateral prefrontal cortex (DLPFC) in people who have died by suicide. The aim of this work was to analyze the protein expression profile in the DLPFC of individuals who died by suicide in comparison to age-matched controls in order to gain information on the molecular basis in the brain of these individuals and the selection of potential biomarkers for the identification of individuals at risk of suicide. In addition, this information was analyzed using machine learning (ML) algorithms to propose a model for predicting suicide.

Methods

Brain tissue (Brodmann area 9) was sampled from male cases (n=9) and age-matched controls (n=7). We analyzed the proteomic differences between the groups using two-dimensional polyacrylamide gel electrophoresis and mass spectrometry. Bioinformatics tools were used to clarify the biological relevance of the differentially expressed proteins. In addition, this information was analyzed using machine learning (ML) algorithms to propose a model for predicting suicide.

Results

Twelve differentially expressed proteins were also identified (t 14 ≤ 0.5). Using Western blotting, we validated the decrease in expression of peroxiredoxin 2 and alpha-internexin in the suicide cases. ML models were trained using densitometry data from the 2D gel images of each selected protein and the models could differentiate between both groups (control and suicide cases).

Discussion

Our exploratory pathway analysis highlighted oxidative stress responses and neurodevelopmental pathways as key processes perturbed in the DLPFC of suicides. Regarding ML models, KNeighborsClassifier was the best predicting conditions. Here we show that these proteins of the DLPFC may help to identify brain processes associated with suicide and they could be validated as potential biomarkers of this outcome.

Human-Induced Pluripotent Stem Cell (iPSC)-Derived GABAergic Neuron Differentiation in Bipolar Disorder

Bipolar disorder (BP) is a recurring psychiatric condition characterized by alternating episodes of low energy (depressions) followed by manias (high energy). Cortical network activity produced by GABAergic interneurons may be critical in maintaining the balance in excitatory/inhibitory activity in the brain during development. Initially, GABAergic signaling is excitatory; with maturation, these cells undergo a functional switch that converts GABAA channels from depolarizing (excitatory) to hyperpolarizing (inhibitory), which is controlled by the intracellular concentration of two chloride transporters. The earliest, NKCC1, promotes chloride entry into the cell and depolarization, while the second (KCC2) stimulates movement of chloride from the neuron, hyperpolarizing it. Perturbations in the timing or expression of NKCC1/KCC2 may affect essential morphogenetic events including cell proliferation, migration, synaptogenesis and plasticity, and thereby the structure and function of the cortex. We derived induced pluripotent stem cells (iPSC) from BP patients and undiagnosed control (C) individuals, then modified a differentiation protocol to form GABAergic interneurons, harvesting cells at sequential stages of differentiation. qRT-PCR and RNA sequencing indicated that after six weeks of differentiation, controls transiently expressed high levels of NKCC1. Using multi-electrode array (MEA) analysis, we observed that BP neurons exhibit increased firing, network bursting and decreased synchrony compared to C. Understanding GABA signaling in differentiation may identify novel approaches and new targets for treatment of neuropsychiatric disorders such as BP.

Maximizing the value of twin studies in health and behaviour

In the classical twin design, researchers compare trait resemblance in cohorts of identical and non-identical twins to understand how genetic and environmental factors correlate with resemblance in behaviour and other phenotypes. The twin design is also a valuable tool for studying causality, intergenerational transmission, and gene-environment correlation and interaction. Here we review recent developments in twin studies, recent results from twin studies of new phenotypes and recent insights into twinning. We ask whether the results of existing twin studies are representative of the general population and of global diversity, and we conclude that stronger efforts to increase representativeness are needed. We provide an updated overview of twin concordance and discordance for major diseases and mental disorders, which conveys a crucial message: genetic influences are not as deterministic as many believe. This has important implications for public understanding of genetic risk prediction tools, as the accuracy of genetic predictions can never exceed identical twin concordance rates.

Manganese exposure causes movement deficit and changes in the protein profile of the external globus pallidus in Sprague Dawley rats

Manganese (Mn) is required for normal brain development and function. Excess Mn may trigger a parkinsonian movement disorder but the underlying mechanisms are incompletely understood. We explored changes in the brain proteomic profile and movement behavior of adult Sprague Dawley (SD) rats systemically treated with or without 1.0 mg/mL MnCl₂ for 3 months. Mn treatment significantly increased the concentration of protein-bound Mn in the external globus pallidus (GP), as demonstrated by inductively coupled plasma mass spectrometry. Behavioral study showed that Mn treatment induced movement deficits, especially of skilled movement. Proteome analysis by two-dimensional fluorescence difference gel electrophoresis coupled with mass spectrometry revealed 13 differentially expressed proteins in the GP of Mn-treated versus Mn-untreated SD rats. The differentially expressed proteins were mostly involved in glycolysis, metabolic pathways, and response to hypoxia. Selected pathway class analysis of differentially expressed GP proteins, which included phosphoglycerate mutase 1 (PGAM1), primarily identified enrichment in glycolytic process and innate immune response. In conclusion, perturbation of brain energy production and innate immune response, in which PGAM1 has key roles, may contribute to the movement disorder associated with Mn neurotoxicity.

A Shotgun Proteomic Platform for a Global Mapping of Lymphoblastoid Cells to Gain Insight into Nasu-Hakola Disease

Nasu-Hakola Disease (NHD) is a recessively inherited systemic leukodystrophy disorder characterized by a combination of frontotemporal presenile dementia and lytic bone lesions. NHD is known to be genetically related to a structural defect of TREM2 and DAP12, two genes that encode for different subunits of the membrane receptor signaling complex expressed by microglia and osteoclast cells. Because of its rarity, molecular or proteomic studies on this disorder are absent or scarce, only case reports based on neuropsychological and genetic tests being reported. In light of this, the aim of this paper is to provide evidence on the potential of a label-free proteomic platform based on the Multidimensional Protein Identification Technology (MudPIT), combined with in-house software and on-line bioinformatics tools, to characterize the protein expression trends and the most involved pathways in NHD. The application of this approach on the Lymphoblastoid cells from a family composed of individuals affected by NHD, healthy carriers and control subjects allowed for the identification of about 3000 distinct proteins within the three analyzed groups, among which proteins anomalous to each category were identified. Of note, several differentially expressed proteins were associated with neurodegenerative processes. Moreover, the protein networks highlighted some molecular pathways that may be involved in the onset or progression of this rare frontotemporal disorder. Therefore, this fully automated MudPIT platform which allowed, for the first time, the generation of the whole protein profile of Lymphoblastoid cells from Nasu-Hakola subjects, could be a valid approach for the investigation of similar neurodegenerative diseases.

Identification of altered protein expression in major depressive disorder and bipolar disorder patients using liquid chromatography-tandem mass spectrometry

Emerging high-throughput proteomic technologies have recently been considered as a powerful means of identifying substrates involved in mood disorders. We performed proteomic profiling using liquid chromatography-tandem mass spectrometry to identify dysregulated proteins in plasma samples of 42 and 45 patients with major depressive disorder (MDD) and bipolar disorder (BD), respectively, in comparison to 51 healthy controls (HCs). Fourteen and six proteins in MDD and BD patients, respectively, were differentially expressed compared to HCs, among which coagulation factor XIII A chain (F13A1), platelet basic protein (PPBP), platelet facor 4 (PF4), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and thymosin beta-4 (TMSB4X) were altered in both disorders. For proteins dysregulated in both, except F13A1, higher fold changes were observed in MDD than in BD patients. These findings may help identify candidate biomarkers of mood disorders and elucidate their underlying pathophysiology and biochemical abnormalities.

Smelling the Dark Proteome: Functional Characterization of PITH Domain-Containing Protein 1 (C1orf128) in Olfactory Metabolism

The Human Proteome Project (HPP) consortium aims to functionally characterize the dark proteome. On the basis of the relevance of olfaction in early neurodegeneration, we have analyzed the dark proteome using data mining in public resources and omics data sets derived from the human olfactory system. Multiple dark proteins localize at synaptic terminals and may be involved in amyloidopathies such as Alzheimer's disease (AD). We have characterized the dark PITH domain-containing protein 1 (PITHD1) in olfactory metabolism using bioinformatics, proteomics, in vitro and in vivo studies, and neuropathology. PITHD1^-/- mice exhibit olfactory bulb (OB) proteome changes related to synaptic transmission, cognition, and memory. OB PITHD1 expression increases with age in wild-type (WT) mice and decreases in Tg2576 AD mice at late stages. The analysis across 6 neurological disorders reveals that olfactory tract (OT) PITHD1 is specifically upregulated in human AD. Stimulation of olfactory neuroepithelial (ON) cells with PITHD1 alters the ON phosphoproteome, modifies the proliferation rate, and induces a pro-inflammatory phenotype. This workflow applied by the Spanish C-HPP and Human Brain Proteome Project (HBPP) teams across the ON-OB-OT axis can be adapted as a guidance to decipher functional features of dark proteins. Data are available via ProteomeXchange with identifiers PXD018784 and PXD021634.

A logical relationship for schizophrenia, bipolar, and major depressive disorder. Part 1: Evidence from chromosome 1 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was investigated systematically (Aukes et al., Genetics in Medicine, 2012, 14, 338-341) and any two or even three of these disorders could coexist in some families. Furthermore, evidence from symptomatology and psychopharmacology also imply the existence of intrinsic connections between these three major psychiatric disorders. A total of 71,445 SNPs on chromosome 1 were genotyped on 119 SCZ, 253 BPD (type-I), 177 MDD cases and 1000 controls and further validated in 986 SCZ patients in the population of Shandong province of China. Outstanding psychosis genes are systematically revealed( ATP1A4, ELTD1, FAM5C, HHAT, KIF26B, LMX1A, NEGR1, NFIA, NR5A2, NTNG1, PAPPA2, PDE4B, PEX14, RYR2, SYT6, TGFBR3, TTLL7, and USH2A). Unexpectedly, flanking genes for up to 97.09% of the associated SNPs were also replicated in an enlarged cohort of 986 SCZ patients. From the perspective of etiological rather than clinical psychiatry, bipolar, and major depressive disorder could be subtypes of schizophrenia. Meanwhile, the varied clinical feature and prognosis might be the result of interaction of genetics and epigenetics, for example, irreversible or reversible shut down, and over or insufficient expression of certain genes, which may gives other aspects of these severe mental disorders.

High polygenic burden is associated with blood DNA methylation changes in individuals with suicidal behavior

Suicidal behavior is result of the interaction of several contributors, including genetic and environmental factors. The integration of approaches considering the polygenic component of suicidal behavior, such as polygenic risk scores (PRS) and DNA methylation is promising for improving our understanding of the complex interplay between genetic and environmental factors in this behavior. The aim of this study was the evaluation of DNA methylation differences between individuals with high and low genetic burden for suicidality. The present study was divided into two phases. In the first phase, genotyping with the Psycharray chip was performed in a discovery sample of 568 Mexican individuals, of which 149 had suicidal behavior (64 individuals with suicidal ideation, 50 with suicide attempt and 35 with completed suicide). Then, a PRS analysis based on summary statistics from the Psychiatric Genomic Consortium was performed in the discovery sample. In a second phase, we evaluated DNA methylation differences between individuals with high and low genetic burden for suicidality in a sub-sample of the discovery sample (target sample) of 94 subjects. We identified 153 differentially methylated sites between individuals with low and high-PRS. Among genes mapped to differentially methylated sites, we found genes involved in neurodevelopment (CHD7, RFX4, KCNA1, PLCB1, PITX1, NUMBL) and ATP binding (KIF7, NUBP2, KIF6, ATP8B1, ATP11A, CLCN7, MYLK, MAP2K5). Our results suggest that genetic variants might increase the predisposition to epigenetic variations in genes involved in neurodevelopment. This study highlights the possible implication of polygenic burden in the alteration of epigenetic changes in suicidal behavior.

Proteomic Study Reveals the Involvement of Energy Metabolism in the Fast Antidepressant Effect of (2R, 6R)-Hydroxy Norketamine

PURPOSE

Depression is a major disabling psychiatric disorder which causes severe financial burden and social consequences worldwide. Recently, (2R, 6R)-hydroxynorketamine (HNK), a metabolite of ketamine, showed strong antidepressant effect through N-methyl-D-aspartate (NMDA) antagonizing independent mechanism. In the current study the goal is to identify the potential intracellular molecules and pathways that might be involved in different therapeutic effects underlying HNK as compared to NMDA antagonist MK-801.

EXPERIMENTAL DESIGN

Forced-swim behavioral test, 2D fluorescence difference gel electrophoresis, and MALDI-TOF-MS/MS proteomics are used.

RESULTS

Compared to saline group, 14 differential proteins are identified in MK-801 treated group, with six proteins significantly up-regulated, while in HNK treated group 18 distinct proteins are identified with 11 proteins significantly up-regulated. Likewise, two proteins are significantly upregulated in HNK treated group when compared to MK-801 treated group. Among these differentially expressed proteins, phosphoglycerate mutase 1, malate dehydrogenase/ cytoplasmic, and triosephosphate isomerase are co-affected by MK-801 and HNK treatment. Representative protein expression changes are quantified by western blot, showing consistent results as determined by MALDI-TOF-MS/MS.

CONCLUSION AND CLINICAL RELEVANCE

The core protection mechanisms of HNK observed herein involves improving the abnormal ATP synthesis, impaired glycolysis, and the defense system therefore provides mechanistic insight and molecular targets for novel antidepressants.

Seeking for potential pathogenic genes of major depressive disorder in the Gene Expression Omnibus database

INTRODUCTION

Major depressive disorder (MDD) is one of the most common mental disorders worldwide. The aim of this study was to identify potential pathological genes in MDD.

METHODS

We searched and downloaded gene expression data from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) in MDD. Then, Kyoto Encyclopedia of Genes and Genomes pathway, Gene Ontology analysis, and protein-protein interaction (PPI) network were applied to investigate the biological function of identified DEGs. The quantitative real-time polymerase chain reaction and a published dataset were used to validate the result of bioinformatics analysis.

RESULTS

A total of 514 DEGs were identified in MDD. In the PPI network, some hub genes with high degrees were identified, such as EEF2, RPL26L1, RPLP0, PRPF8, LSM3, DHX9, RSRC1, and AP2B1. The result of in vitro validation of RPL26L1, RSRC1, TOMM20L, RPLPO, PRPF8, AP2B1, STIP1, and C5orf45 was consistent with the bioinformatics analysis. Electronic validation of C5orf45, STIP1, PRPF8, AP2B1, and SLC35E1 was consistent with the bioinformatics analysis.

DISCUSSION

The deregulated genes could be used as potential pathological factors of MDD. In addition, EEF2, RPL26L1, RPLP0, PRPF8, LSM3, DHX9, RSRC1, and AP2B1 might be therapeutic targets for MDD.

A multisystem composite biomarker as a preliminary diagnostic test in bipolar disorder

OBJECTIVE

Diagnosis and management of bipolar disorder (BD) are limited by the absence of available laboratory tests. We aimed to combine data from different molecular levels and tissues into a composite diagnostic and state biomarker.

METHODS

Expression levels of 19 candidate genes in peripheral blood, plasma levels of BDNF, NT-3, IL-6 and IL-18, leukocyte counts, and urinary markers of oxidative damage to DNA and RNA were measured in 37 adult rapid-cycling patients with BD in different affective states during a 6- to 12-month period and in 40 age- and gender-matched healthy individuals in a longitudinal, repeated measures design comprising a total of 211 samples. A composite biomarker was constructed using data-driven variable selection.

RESULTS

The composite biomarker discriminated between patients with BD and healthy control individuals with an area under the receiver operating characteristic curve (AUC) of 0.83 and a sensitivity of 73% and specificity of 71% corresponding with a moderately accurate test. Discrimination between manic and depressive states had a moderate accuracy, with an AUC of 0.82 and a sensitivity of 92% and a specificity of 40%.

CONCLUSION

Combining individual biomarkers across tissues and molecular systems could be a promising avenue for research in biomarker models in BD.

Genetic biomarkers for differential diagnosis of major depressive disorder and bipolar disorder: A systematic and critical review

Depressive symptoms are present in the depressive mood state of bipolar disorder (BPD) and major depression disorder (MDD). Often, in clinical practice, BPD patients are misdiagnosed with MDD. Therefore, genetic biomarkers could contribute to the improvement of differential diagnosis between BPD and MDD. This systematic and critical review aimed to find in literature reliable genetic biomarkers that may show differences between BPD and MDD. This systematic review followed the PRISMA-P method. The terms used to search PubMed, Scopus, PsycINFO, and Web of Science were depress*, bipolar, diagnos*, genetic*, biomark*. After applying the selection criteria, N = 27 studies were selected, being n = 9 about biomarkers for BPD; n = 15, about MDD; and n = 3 for distinguishing MDD from BPD. A total of N = 3086 subjects were assessed in the selected studies (n = 486 in BPD group; n = 1212 in MDD group; and n = 1388, healthy control group). The articles were dated up to June 2017. Of the N = 27 studies, n = 16 assessed gene, n = 1 miRNA, n = 2 lcnRNA and n = 3 protein expressions, n = 4 methylation, and n = 4 polymorphisms. Some studies applied more than one of these genetic analyses. To find reliable genetic biomarkers we have taken into account the methodological care during the studies development and their validity. The genetic biomarkers selected are related to genes that play a fundamental role in synaptic plasticity, neurogenesis, mood control, brain ageing, immune-inflammatory processes and mitochondrial respiratory chain. BDNF gene expression was one of the genetic biomarkers that highlighted because of its capacity of distinguishing BPD and MDD groups, and being adequately reproduced by more than one selected study.

Proteomic Studies of Psychiatric Disorders

Many diseases result from programming effects in utero. This chapter describes recent advances in proteomic studies which have improved our understanding of the underlying pathophysiological pathways in the major psychiatric disorders, resulting in the development of potential novel biomarker tests. Such tests should be based on measurement of blood-based proteins given the ease of accessibility of this medium and the known connections between the periphery and the central nervous system. Most importantly, emerging biomarker tests should be developed on lab-on-a-chip and other handheld devices to enable point-of-care use. This should help to identify individuals with psychiatric disorders much sooner than ever before, which will allow more rapid treatment options for the best possible patient outcomes.

A novel relationship for schizophrenia, bipolar and major depressive disorder Part 5: a hint from chromosome 5 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was systematically reported (Aukes, M. F. Genet Med 2012, 14, 338-341) and any two or even three of these disorders could co-exist in some families. In addition, evidence from symptomatology and psychopharmacology also imply that there are intrinsic connections between these three major disorders. A total of 56,569 single nucleotide polymorphism (SNPs) on chromosome 5 were genotyped by Affymetrix Genome-Wide Human SNP array 6.0 on 119 SCZ, 253 BPD (type-I), 177 MDD patients and 1000 controls. Associated SNPs and flanking genes was screen out systematically, and cadherin pathway genes (CDH6, CDH9, CDH10, CDH12, and CDH18) belong to outstanding genes. Unexpectedly, nearly all flanking genes of the associated SNPs distinctive for BPD and MDD were replicated in an enlarged cohort of 986 SCZ patients (P ≤ 9.9E-8). Considering multiple bits of evidence, our chromosome 5 analyses implicated that bipolar and major depressive disorder might be subtypes of schizophrenia rather than two independent disease entities. Also, cadherin pathway genes play important roles in the pathogenesis of the three major mental disorders.

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.

Neurodevelopmental origins of bipolar disorder: iPSC models

Bipolar disorder (BP) is a chronic neuropsychiatric condition characterized by pathological fluctuations in mood from mania to depression. Adoption, twin and family studies have consistently identified a significant hereditary component to BP, yet there is no clear genetic event or consistent neuropathology. BP has been suggested to have a developmental origin, although this hypothesis has been difficult to test since there are no viable neurons or glial cells to analyze, and research has relied largely on postmortem brain, behavioral and imaging studies, or has examined proxy tissues including saliva, olfactory epithelium and blood cells. Neurodevelopmental factors, particularly pathways related to nervous system development, cell migration, extracellular matrix, H3K4 methylation, and calcium signaling have been identified in large gene expression and GWAS studies as altered in BP. Recent advances in stem cell biology, particularly the ability to reprogram adult somatic tissues to a pluripotent state, now make it possible to interrogate these pathways in viable cell models. A number of induced pluripotent stem cell (iPSC) lines from BP patient and healthy control (C) individuals have been derived in several laboratories, and their ability to form cortical neurons examined. Early studies suggest differences in activity, calcium signaling, blocks to neuronal differentiation, and changes in neuronal, and possibly glial, lineage specification. Initial observations suggest that differentiation of BP patient-derived neurons to dorsal telencephalic derivatives may be impaired, possibly due to alterations in WNT, Hedgehog or Nodal pathway signaling. These investigations strongly support a developmental contribution to BP and identify novel pathways, mechanisms and opportunities for improved treatments.

Cellular models to study bipolar disorder: A systematic review

BACKGROUND

There is an emerging interest in the use of cellular models to study psychiatric disorders. We have systematically reviewed the application of cellular models to understand the biological basis of bipolar disorder (BD).

METHOD

Published scientific literature in MEDLINE, PsychINFO and SCOPUS databases were identified with the following search strategy: [(Lymphoblastoid OR Lymphoblast OR Fibroblast OR Pluripotent OR Olfactory epithelium OR Olfactory mucosa) AND (Bipolar disorder OR Lithium OR Valproate OR Mania)]. Studies were included if they had used cell cultures derived from BD patients.

RESULTS

There were 65 articles on lymphoblastoid cell lines, 14 articles on fibroblasts, 4 articles on olfactory neuronal epithelium (ONE) and 2 articles on neurons reprogrammed from induced pluripotent stem cell lines (IPSC). Several parameters have been studied, and the most replicated findings are abnormalities in calcium signaling, endoplasmic reticulum (ER) stress response, mitochondrial oxidative pathway, membrane ion channels, circadian system and apoptosis related genes. These, although present in basal state, seem to be accentuated in the presence of cellular stressors (e.g. oxidative stress--rotenone; ER stress--thapsigargin), and are often reversed with in-vitro lithium.

CONCLUSION

Cellular modeling has proven useful in BD, and potential pathways, especially in cellular resilience related mechanisms have been identified. These findings show consistency with other study designs (genome-wide association, brain-imaging, and post-mortem brain expression). ONE cells and IPSC reprogrammed neurons represent the next generation of cell models in BD. Future studies should focus on family-based study designs and combine cell models with deep sequencing and genetic manipulations.

A composite peripheral blood gene expression measure as a potential diagnostic biomarker in bipolar disorder

Gene expression in peripheral blood has the potential to inform on pathophysiological mechanisms and has emerged as a viable avenue for the identification of biomarkers. Here, we aimed to identify gene expression candidate genes and to explore the potential for a composite gene expression measure as a diagnostic and state biomarker in bipolar disorder. First, messenger RNA levels of 19 candidate genes were assessed in peripheral blood mononuclear cells of 37 rapid cycling bipolar disorder patients in different affective states (depression, mania and euthymia) during a 6-12-month period and in 40 age- and gender-matched healthy control subjects. Second, a composite gene expression measure was constructed in the first half study sample and independently validated in the second half of the sample. We found downregulation of POLG and OGG1 expression in bipolar disorder patients compared with healthy control subjects. In patients with bipolar disorder, upregulation of NDUFV2 was observed in a depressed state compared with a euthymic state. The composite gene expression measure for discrimination between patients and healthy control subjects on the basis of 19 genes generated an area under the receiver-operating characteristic curve of 0.81 (P < 0.0001) in sample 1, which was replicated with a value of 0.73 (P < 0.0001) in sample 2, corresponding with a moderately accurate test. The present findings of altered POLG, OGG1 and NDUFV2 expression point to disturbances within mitochondrial function and DNA repair mechanisms in bipolar disorder. Further, a composite gene expression measure could hold promise as a potential diagnostic biomarker.

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.

Discordant twins as a tool to unravel the aetiology of bipolar disorder

This editorial focuses on discordant twins as a valuable epidemiological design for psychiatric aetiological research. First, we summarise the advantages and strengths of this design over the classical matched case-control study. Then, we draw attention to the use of this method in bipolar disorder, revising previous discordant-twin studies. A future greater use of discordant twins is desirable to gain further relevant insights in the aetiology of bipolar disorder.

Search for peripheral biomarkers in patients affected by acutely psychotic bipolar disorder: a proteomic approach

Data on neurobiological mechanisms underlying mood disorders are elusive; the aetiology of such states is multifactorial, including genetic predisposition and environmental factors. Diagnosis is currently being made only on an interview-based methodology. Biological markers, which could improve the current classification, and in perspective, stratify patients on a biological basis into more homogeneous clinically distinct subgroups, are highly needed. We describe here a comparative proteomic analysis of peripheral lymphocytes from patients affected by acute psychotic bipolar disorder (PBD) (n = 15), major depressive episode (MDE) with no personal or family history of psychosis (n = 11), and a group of demographically matched healthy controls (HC) (n = 15). All patients were evaluated by means of Structured Clinical Interview for DSM-IV-Patient version (SCID-I-P), Positive and Negative Symptoms Scale (PANSS), Young Mania Rating Scale (YMRS), Hamilton Anxiety Rating Scale (HAM-A) and Hamilton Depression Rating Scale (HAM-D-17) questionnaires. Blood lymphocytes were obtained by gradient separation, and 2-DE was carried out on protein extracts. Significant differences in protein patterns among the three groups were observed. Thirty-six protein spots were found to be differentially expressed in patients compared to controls, which collapsed into 25 different proteins after mass spectrometry identification. Twenty-one of these proteins failed to discriminate between PBD and MDE, suggesting common signatures for these disorders. Nevertheless, after the western blot validation only two of the remaining proteins, namely LIM and SH3 domain protein1, and short-chain specific acyl-CoA dehydrogenase mitochondrial protein, resulted in being significantly upregulated in PBD samples suggesting additional mechanisms that could be associated with the psychotic features of bipolar disorder.

Biomarkers in major depressive disorder: the role of mass spectrometry

Major depressive disorder (MDD) is common. Despite numerous available treatments, many individuals fail to improve clinically. MDD continues to be diagnosed exclusively via behavioral rather than biological methods. Biomarkers-which include measurements of genes, proteins, and patterns of brain activity-may provide an important objective tool for the diagnosis of MDD or in the rational selection of treatments. Proteomic analysis and validation of its results as biomarkers is less explored than other areas of biomarker research in MDD. Mass spectrometry (MS) is a comprehensive, unbiased means of proteomic analysis, which can be complemented by directed protein measurements, such as Western Blotting. Prior studies have focused on MS analysis of several human biomaterials in MDD, including human post-mortem brain, cerebrospinal fluid (CSF), blood components, and urine. Further studies utilizing MS and proteomic analysis in MDD may help solidify and establish biomarkers for use in diagnosis, identification of new treatment targets, and understanding of the disorder. The ultimate goal is the validation of a biomarker or a biomarker signature that facilitates a convenient and inexpensive predictive test for depression treatment response and helps clinicians in the rational selection of next-step treatments.