Psychiatric research: psychoproteomics, degradomics and systems biology

Neurotrauma investigation through spatial omics guided by mass spectrometry imaging: Target identification and clinical applications

Traumatic brain injury (TBI) represents one of the major public health concerns worldwide due to the increase in TBI incidence as a result of injuries from daily life accidents such as sports and motor vehicle transportation as well as military-related practices. This type of central nervous system trauma is known to predispose patients to several neurological disorders such as Parkinson's disease, Alzheimer's disease, chronic trauamatic encephalopathy, and age-related Dementia. Recently, several proteomic and lipidomic platforms have been applied on different TBI studies to investigate TBI-related mechanisms that have broadened our understanding of its distinct neuropathological complications. In this study, we provide an updated comprehensive overview of the current knowledge and novel perspectives of the spatially resolved microproteomics and microlipidomics approaches guided by mass spectrometry imaging used in TBI studies and its applications in the neurotrauma field. In this regard, we will discuss the use of the spatially resolved microproteomics and assess the different microproteomic sampling methods such as laser capture microdissection, parafilm assisted microdissection, and liquid microjunction extraction as accurate and precise techniques in the field of neuroproteomics. Additionally, we will highlight lipid profiling applications and their prospective potentials in characterizing molecular processes involved in the field of TBI. Specifically, we will discuss the phospholipid metabolism acting as a precursor for proinflammatory molecules such as eicosanoids. Finally, we will survey the current state of spatial neuroproteomics and microproteomics applications and present the various studies highlighting their findings in these fields.

Computational chemoproteomics to understand the role of selected psychoactives in treating mental health indications

We have developed the Computational Analysis of Novel Drug Opportunities (CANDO) platform to infer homology of drug behaviour at a proteomic level by constructing and analysing structural compound-proteome interaction signatures of 3,733 compounds with 48,278 proteins in a shotgun manner. We applied the CANDO platform to predict putative therapeutic properties of 428 psychoactive compounds that belong to the phenylethylamine, tryptamine, and cannabinoid chemical classes for treating mental health indications. Our findings indicate that these 428 psychoactives are among the top-ranked predictions for a significant fraction of mental health indications, demonstrating a significant preference for treating such indications over non-mental health indications, relative to randomized controls. Also, we analysed the use of specific tryptamines for the treatment of sleeping disorders, bupropion for substance abuse disorders, and cannabinoids for epilepsy. Our innovative use of the CANDO platform may guide the identification and development of novel therapies for mental health indications and provide an understanding of their causal basis on a detailed mechanistic level. These predictions can be used to provide new leads for preclinical drug development for mental health and other neurological disorders.

Cannabis and Tramadol are Prevalent among the First Episode Drug-Induced Psychosis in the Egyptian Population: Single Center Experience

(1) Background: Cannabis and tramadol are featuring prominently in Egypt; however, their prevalence in first episode psychosis is still uncertain. We aimed at determining the prevalence of cannabis and tramadol among the first-psychotic episode in Egyptian inpatients and to compare the demographic and psychopathological profiles of substance abusers versus patients with the comorbid diagnosis. (2) Methods: Patients presented with psychotic episode and admitted to Mansoura Psychiatric Department were recruited. Diagnosis of psychiatric illness and drug/substance use was carried out using the Diagnostic and Statistical Manual- Fourth Edition (DSM-IV) criteria. Standard urine tests and thin layer chromatography were performed to detect cannabis and tramadol. (3) Results: Of the 100 subjects in the study, the majority (55.6%) of patients were cannabis-only positive. Overall, cannabis-alone showed the highest frequency of substance used among the currently diagnosed psychotic disorders. According to urine tests, cannabis demonstrates the higher frequency of intake in both studied groups. 66.7% of the studied population had 1–5 years self-reported histories of substance abuse predating the first psychotic episode. (4) Conclusions: The percentage of cannabis and tramadol among the first episode psychotic patients has been unexpectedly high and the standard urine testing should be considered in emergency and mental health facilities.

Efficient and Accurate Algorithm for Cleaved Fragments Prediction (CFPA) in Protein Sequences Dataset Based on Consensus and Its Variants: A Novel Degradomics Prediction Application

Degradomics is a novel discipline that involves determination of the proteases/substrate fragmentation profile, called the substrate degradome, and has been recently applied in different disciplines. A major application of degradomics is its utility in the field of biomarkers where the breakdown products (BDPs) of different protease have been investigated. Among the major proteases assessed, calpain and caspase proteases have been associated with the execution phases of the pro-apoptotic and pro-necrotic cell death, generating caspase/calpain-specific cleaved fragments. The distinction between calpain and caspase protein fragments has been applied to distinguish injury mechanisms. Advanced proteomics technology has been used to identify these BDPs experimentally. However, it has been a challenge to identify these BDPs with high precision and efficiency, especially if we are targeting a number of proteins at one time. In this chapter, we present a novel bioinfromatic detection method that identifies BDPs accurately and efficiently with validation against experimental data. This method aims at predicting the consensus sequence occurrences and their variants in a large set of experimentally detected protein sequences based on state-of-the-art sequence matching and alignment algorithms. After detection, the method generates all the potential cleaved fragments by a specific protease. This space and time-efficient algorithm is flexible to handle the different orientations that the consensus sequence and the protein sequence can take before cleaving. It is O(mn) in space complexity and O(Nmn) in time complexity, with N number of protein sequences, m length of the consensus sequence, and n length of each protein sequence. Ultimately, this knowledge will subsequently feed into the development of a novel tool for researchers to detect diverse types of selected BDPs as putative disease markers, contributing to the diagnosis and treatment of related disorders.

Increased serum levels of spectrin degradation products in patients with schizophrenia

Objective:

Under various patho-physiological and physiological conditions, spectrin breakdown reactions generate several spectrin breakdown products of 120 kDa (SBDP120) and 145 kDa (SBDP145). Previous studies indicating that there is the existence of a raised breakdown of α-spectrin in schizophrenic left superior temporal cortices. In this study, we aimed to investigate serum levels of SBDP120 and SBDP145, which has not been previously examined, and investigate their relationships with clinical parameters in patients with schizophrenia.

Methods:

Forty-four patients with schizophrenia, followed by psychotic disorders unit, and 44 healthy controls, age and gender-matched volunteers with no psychiatric history, were included in this study. Sociodemographic form was applied to both groups. Turkish version of positive and negative syndrome scale (PANSS) were implemented to the patients. Serum SBDP120 and SBDP145 levels were determined by Enzyme-Linked Immuno Sorbent Assay.

Results:

Serum SBDP120 ng/mL and SBDP145 ng/mL levels of the patients with schizophrenia were significantly higher than healthy controls. Even more important, serum SBDP120 levels were positively correlated with PANSS scores in patients with schizophrenia.

Conclusions:

These findings may provide evidence for disturbance of neuroplasticity, membrane/cytoskeleton stability, dynamics, and remodelling in schizophrenia patients and support the neurogenerative theories for explaining the etiology of schizophrenia.

Novel Bioinformatics-Based Approach for Proteomic Biomarkers Prediction of Calpain-2 &Caspase-3 Protease Fragmentation: Application to βII-Spectrin Protein

The crucial biological role of proteases has been visible with the development of degradomics discipline involved in the determination of the proteases/substrates resulting in breakdown-products (BDPs) that can be utilized as putative biomarkers associated with different biological-clinical significance. In the field of cancer biology, matrix metalloproteinases (MMPs) have shown to result in MMPs-generated protein BDPs that are indicative of malignant growth in cancer, while in the field of neural injury, calpain-2 and caspase-3 proteases generate BDPs fragments that are indicative of different neural cell death mechanisms in different injury scenarios. Advanced proteomic techniques have shown a remarkable progress in identifying these BDPs experimentally. In this work, we present a bioinformatics-based prediction method that identifies protease-associated BDPs with high precision and efficiency. The method utilizes state-of-the-art sequence matching and alignment algorithms. It starts by locating consensus sequence occurrences and their variants in any set of protein substrates, generating all fragments resulting from cleavage. The complexity exists in space O(mn) as well as in O(Nmn) time, where N, m, and n are the number of protein sequences, length of the consensus sequence, and length per protein sequence, respectively. Finally, the proposed methodology is validated against βII-spectrin protein, a brain injury validated biomarker.

Degradomics in Neurotrauma: Profiling Traumatic Brain Injury

Degradomics has recently emerged as a subdiscipline in the omics era with a focus on characterizing signature breakdown products implicated in various disease processes. Driven by promising experimental findings in cancer, neuroscience, and metabolomic disorders, degradomics has significantly promoted the notion of disease-specific "degradome." A degradome arises from the activation of several proteases that target specific substrates and generate signature protein fragments. Several proteases such as calpains, caspases, cathepsins, and matrix metalloproteinases (MMPs) are involved in the pathogenesis of numerous diseases that disturb the physiologic balance between protein synthesis and protein degradation. While regulated proteolytic activities are needed for development, growth, and regeneration, uncontrolled proteolysis initiated under pathological conditions ultimately culminates into apoptotic and necrotic processes. In this chapter, we aim to review the protease-substrate repertoires in neural injury concentrating on traumatic brain injury. A striking diversity of protease substrates, essential for neuronal and brain structural and functional integrity, namely, encryptic biomarker neoproteins, have been characterized in brain injury. These include cytoskeletal proteins, transcription factors, cell cycle regulatory proteins, synaptic proteins, and cell junction proteins. As these substrates are subject to proteolytic fragmentation, they are ceaselessly exposed to activated proteases. Characterization of these molecules allows for a surge of "possible" therapeutic approaches of intervention at various levels of the proteolytic cascade.

Neuroproteomics Studies: Challenges and Updates

The Human Genome Project in 2003 has resulted in the complete sequence of ~99% of the human genome paving the road for the Human Proteome Project (HPP) assessing the full characterization of the translated protein map of the 20,300 protein-coding genes. Consequently, the emerging of the proteomics field has successfully been adopted as the method of choice for the proteome characterization. Proteomics is a term that is used to encompass multidisciplinary approaches combining different technologies that aim to study the entire spectrum of protein changes at a specific physiological condition. Proteomics research has shown excellent outcomes in different fields, among which is neuroscience; however, the complexity of the nervous systems necessitated the genesis of a new subdiscipline of proteomics termed as "neuroproteomics." Neuroproteomics studies involve assessing the quantitative and qualitative aspects of nervous system components encompassing global dynamic events underlying various brain-related disorders ranging from neuropsychiatric disorders, degenerative disorders, mental illness, and most importantly brain-specific neurotrauma-related injuries. In this introductory chapter, we will provide a brief historical perspective on the field of neuroproteomics. In doing so, we will highlight on the recent applications of neuroproteomics in the areas of neurotrauma, an area that has benefitted from neuroproteomics in terms of biomarker research, spatiotemporal injury mechanism, and its use to translate its findings from experimental settings to human translational applications. Importantly, this chapter will include some recommendation to the general studies in the area of neuroproteomics and the need to move from this field from being a descriptive, hypothesis-free approach to being an independent mature scientific discipline.

Differential Neuroproteomic and Systems Biology Analysis of Spinal Cord Injury

Acute spinal cord injury (SCI) is a devastating condition with many consequences and no known effective treatment. Although it is quite easy to diagnose traumatic SCI, the assessment of injury severity and projection of disease progression or recovery are often challenging, as no consensus biomarkers have been clearly identified. Here rats were subjected to experimental moderate or severe thoracic SCI. At 24h and 7d postinjury, spinal cord segment caudal to injury center versus sham samples was harvested and subjected to differential proteomic analysis. Cationic/anionic-exchange chromatography, followed by 1D polyacrylamide gel electrophoresis, was used to reduce protein complexity. A reverse phase liquid chromatography-tandem mass spectrometry proteomic platform was then utilized to identify proteome changes associated with SCI. Twenty-two and 22 proteins were up-regulated at 24 h and 7 day after SCI, respectively; whereas 19 and 16 proteins are down-regulated at 24 h and 7 day after SCI, respectively, when compared with sham control. A subset of 12 proteins were identified as candidate SCI biomarkers - TF (Transferrin), FASN (Fatty acid synthase), NME1 (Nucleoside diphosphate kinase 1), STMN1 (Stathmin 1), EEF2 (Eukaryotic translation elongation factor 2), CTSD (Cathepsin D), ANXA1 (Annexin A1), ANXA2 (Annexin A2), PGM1 (Phosphoglucomutase 1), PEA15 (Phosphoprotein enriched in astrocytes 15), GOT2 (Glutamic-oxaloacetic transaminase 2), and TPI-1 (Triosephosphate isomerase 1), data are available via ProteomeXchange with identifier PXD003473. In addition, Transferrin, Cathepsin D, and TPI-1 and PEA15 were further verified in rat spinal cord tissue and/or CSF samples after SCI and in human CSF samples from moderate/severe SCI patients. Lastly, a systems biology approach was utilized to determine the critical biochemical pathways and interactome in the pathogenesis of SCI. Thus, SCI candidate biomarkers identified can be used to correlate with disease progression or to identify potential SCI therapeutic targets.

The Effect of Chronic Methamphetamine Exposure on the Hippocampal and Olfactory Bulb Neuroproteomes of Rats

Nowadays, drug abuse and addiction are serious public health problems in the USA. Methamphetamine (METH) is one of the most abused drugs and is known to cause brain damage after repeated exposure. In this paper, we conducted a neuroproteomic study to evaluate METH-induced brain protein dynamics, following a two-week chronic regimen of an escalating dose of METH exposure. Proteins were extracted from rat brain hippocampal and olfactory bulb tissues and subjected to liquid chromatography-mass spectrometry (LC-MS/MS) analysis. Both shotgun and targeted proteomic analysis were performed. Protein quantification was initially based on comparing the spectral counts between METH exposed animals and their control counterparts. Quantitative differences were further confirmed through multiple reaction monitoring (MRM) LC-MS/MS experiments. According to the quantitative results, the expression of 18 proteins (11 in the hippocampus and 7 in the olfactory bulb) underwent a significant alteration as a result of exposing rats to METH. 13 of these proteins were up-regulated after METH exposure while 5 were down-regulated. The altered proteins belonging to different structural and functional families were involved in processes such as cell death, inflammation, oxidation, and apoptosis.

Biomarker identification in psychiatric disorders: from neuroscience to clinical practice

Patients with psychiatric disorders exhibit several neurobehavioral and neuropsychological alterations compared to healthy controls. However, signature endpoints of these behavioral manifestations have not yet been translated into clinical tests for diagnosis and follow-up measures. Recently, neuroproteomic approaches have been utilized to identify unique signature markers indicative of these disorders. Development of reliable biomarkers has the potential to revolutionize the diagnosis, classification, and monitoring of clinical responses in psychiatric diseases. However, the lack of biological gold standards, the evolving nosology of psychiatric disorders, and the complexity of the nervous system are among the major challenges that have hindered efforts to develop reliable biomarkers in the field of neuropsychiatry and drug abuse. While biomarkers currently have a limited role in the area of neuropsychiatry, several promising biomarkers have been proposed in conditions such as dementia, schizophrenia, depression, suicide, and addiction. One of the primary objectives of this review is to discuss the role of proteomics in the development of biomarkers specific to neuropsychiatry. We discuss and evaluate currently available biomarkers as well as those that are under research for clinical use in the future.

Post-genomics nanotechnology is gaining momentum: nanoproteomics and applications in life sciences

The post-genomics era has brought about new Omics biotechnologies, such as proteomics and metabolomics, as well as their novel applications to personal genomics and the quantified self. These advances are now also catalyzing other and newer post-genomics innovations, leading to convergences between Omics and nanotechnology. In this work, we systematically contextualize and exemplify an emerging strand of post-genomics life sciences, namely, nanoproteomics and its applications in health and integrative biological systems. Nanotechnology has been utilized as a complementary component to revolutionize proteomics through different kinds of nanotechnology applications, including nanoporous structures, functionalized nanoparticles, quantum dots, and polymeric nanostructures. Those applications, though still in their infancy, have led to several highly sensitive diagnostics and new methods of drug delivery and targeted therapy for clinical use. The present article differs from previous analyses of nanoproteomics in that it offers an in-depth and comparative evaluation of the attendant biotechnology portfolio and their applications as seen through the lens of post-genomics life sciences and biomedicine. These include: (1) immunosensors for inflammatory, pathogenic, and autoimmune markers for infectious and autoimmune diseases, (2) amplified immunoassays for detection of cancer biomarkers, and (3) methods for targeted therapy and automatically adjusted drug delivery such as in experimental stroke and brain injury studies. As nanoproteomics becomes available both to the clinician at the bedside and the citizens who are increasingly interested in access to novel post-genomics diagnostics through initiatives such as the quantified self, we anticipate further breakthroughs in personalized and targeted medicine.

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.

Application of proteomics to cerebrovascular disease

While neurovascular diseases such as ischemic and hemorrhagic stroke are the leading causes of disability in the world, the repertoire of therapeutic interventions has remained remarkably limited. There is a dire need to develop new diagnostic, prognostic, and therapeutic options. The study of proteomics is particularly enticing for cerebrovascular diseases such as stroke, which most likely involve multiple gene interactions resulting in a wide range of clinical phenotypes. Currently, rapidly progressing neuroproteomic techniques have been employed in clinical and translational research to help identify biologically relevant pathways, to understand cerebrovascular pathophysiology, and to develop novel therapeutics and diagnostics. Future integration of proteomic with genomic, transcriptomic, and metabolomic studies will add new perspectives to better understand the complexities of neurovascular injury. Here, we review cerebrovascular proteomics research in both preclinical (animal, cell culture) and clinical (blood, urine, cerebrospinal fluid, microdialyates, tissue) studies. We will also discuss the rewards, challenges, and future directions for the application of proteomics technology to the study of various disease phenotypes. To capture the dynamic range of cerebrovascular injury and repair with a translational targeted and discovery approach, we emphasize the importance of complementing innovative proteomic technology with existing molecular biology models in preclinical studies, and the need to advance pharmacoproteomics to directly probe clinical physiology and gauge therapeutic efficacy at the bedside.

Using gene-environment interactions to target personalized treatment in mood disorder

Mood disorders account for a substantial social and financial burden on society. Although considerable efforts to delineate the underlying pathophysiological pathways have been undertaken during the last decades, only very limited progress on diagnostic and treatment algorithms have been achieved. High hopes have been put into genetics research to elucidate the pathogenesis of mood disorders, but so far, only small and inconsistent associations could be reported. Epidemiologic and family studies have always emphasized the importance of environmental factors; especially the impact of childhood trauma in mood disorders and more recently a number of specific gene-environment interactions have been reported. It is thus likely that the combination of a patient's life history and genetic susceptibility as well as other laboratory markers might provide a better insight into mental diseases and their treatment options. In this article, we discuss the concept of gene-environment interactions in major depression and their putative role in treatment response and personalized therapy.

Systems biology and theranostic approach to drug discovery and development to treat traumatic brain injury

Traumatic brain injury is a significant disease affecting 1.4 to 2 million patients every year in the USA. Currently, there are no FDA-approved therapeutic remedies to treat TBI despite the fact that there have been over 200 clinical drug trials, all which have failed. These drugs used the traditional single drug-to-target approach of drug discovery and development. An alternative based upon the advances in genomics, proteomics, bioinformatic tools, and systems biology software has enabled us to use a Systems Biology-based approach to drug discovery and development for TBI. It focuses on disease-relevant converging pathways as potential therapeutic intervention points and is accompanied by downstream biomarkers that allow for the tracking of drug targeting and appears to correlate with disease mitigation. When realized, one is able to envision that a companion diagnostic will be codeveloped along the therapeutic compound. This "theranostic" approach is perfectly positioned to align with the emerging trend toward "personalized medicine".

Peculiarities of geriatric psychiatry: a focus on aging and depression

There is a debate on whether Geriatric Psychiatry stands for itself as a discrete specialty or whether it is an extension of clinical Geriatrics, Neurology, and Psychiatry. This review aims to outline some recent data and possible approaches to define peculiarities of Geriatric Psychiatry, focusing on certain characteristics that define the aging brain. Geriatric depression is discussed taking into consideration some data from translational research. The brain aging process is not uniform. Frontal areas show marked impairment in inhibiting irrelevant information in working memory as they age, and the recruitment of these areas occur differently than in young subjects. Executive functions also change in normal elderly. Geriatric depression is a general definition of a multidimensional disorder with multiple risk factors. Dysexecutive syndrome is considered as a key to the neuropsychology of geriatric depression, correlated with functional impairment in late life. Late-onset depression has a higher load of comordibity, of cerebrovascular disease, and of some genetic factors that may be different from early onset depression. Also, there are at least four clusters of treatment outcomes that are common in geriatric depression, which mirror the neuropsychological and clinical profiles. Research and practice in Geriatric Psychiatry should focus on the interaction of various dimensions and risk factors rather than on attempting to find a single cause to the disorders. Some answers may be found in comorbidity issues, in white matter lesions, which are more common in the elderly, and in genetic factors that impact on the aging process.

Methods in systems biology of experimental methamphetamine drug abuse

The use of methamphetamine (METH) as recreational drugs is a growing problem worldwide with recent concerns that it might cause long-lasting harmful effects to the human brain. METH is an illicit drug that is known to exert neurotoxic effects on both dopaminergic and serotonergic neural systems. Our laboratory has been studying the biochemical mechanisms underlying METH-induced neurotoxic effects both in vivo and in vitro. Our psychoproteomics METH abuse research focuses on the global alteration of cortical protein expression in rats treated with acute METH. In our analysis, an altered protein expression was identified using a multistep protein separation/proteomic platform. Differential changes of the selected proteins were further confirmed by quantitative immunoblotting. Our study identified 82 differentially expressed proteins, 40 of which were downregulated and 42 of which were upregulated post acute METH treatment. In this chapter, we describe the current protocols for the neuronal cell culture in vitro and the in vivo rat model of acute METH treatment (4 x 10 mg/kg) coupled with the description current bioinformatics analysis utilized to analyze the different implicated interaction protein/gene maps that reflected on the altered functions observed. These methods and protocols are discussed in the paradigm of the acute model of METH drug abuse and neuronal cell culture and can be applied on other models of substance abuse such as on MDMA or cocaine.

Rat genomics applied to psychiatric research

Psychiatric diseases are very debilitating and some of them highly prevalent (e.g., depression or anxiety). The rat remains one model of choice in this discipline to investigate the neural mechanisms underlying normal and pathological traits. Genomic tools are now applied to identify genes involved in psychiatric illnesses and also to provide new biomarkers for diagnostic and prognosis, new targets for treatment and more generally to better understand the functioning of the brain. In this report, we will review rat models, behavioral approaches used to model psychiatry-related traits and the major studies published in the field including genetic mapping of quantitative trait loci (QTL), transcriptomics, proteomics and transgenic models.

Recent advances in the genetics of obsessive-compulsive disorder

This article reviews recent developments in understanding the genetic etiology of obsessive-compulsive disorder (OCD). Family studies provide further support for the familial aggregation of OCD. Genome-wide linkage studies indicate that specific chromosomal regions are linked to OCD. Moreover, results from recent molecular genetic studies suggest that several candidate genes are associated with OCD. However, specific genes causing OCD have not been conclusively identified, and the molecular pathogenesis of the disorder has not been elucidated. The search for genes is complicated by the clinical and etiologic heterogeneity of OCD, as well as the possibility of gene-gene and gene-environment interactions. Despite this complexity, further refinement of the phenotype and developments in molecular and statistical genetics hold promise for further deepening our genetic understanding of OCD in the future.

Biomarkers for Parkinson's disease

With the advent of systems biological concepts there has been a surge of interest in biological factors, or biomarkers that can be measured and which allow the identification of individuals at risk. Biomarkers for Parkinson's disease have been identified which provide evidence of systemic metabolic dysregulation in this disorder. Such biomarkers can be studied in blood, serum and plasma but also in CSF and urine, and the study by Hoepken et al. in this issue has even made use of skin fibroblasts. The authors report on the induction of alpha-synuclein expression and suggest that the expression changes described might potentially allow objective PD patient diagnosis in an accessible, peripheral tissue. This mini-review aims to provide a broader perspective on PD functional genomics and seeks to illustrate in a systems biological context why the findings by Hoepken and colleagues are of clinical significance.

Methods in drug abuse neuroproteomics: methamphetamine psychoproteome

Methamphetamine (METH) is recognized as one of the most abused psychostimulants in the USA. METH is an illicit drug that is known to exert neurotoxic effects on both dopaminergic and serotonergic neural systems. Our laboratory has been studying the biochemical mechanisms underlying MDMA and METH-induced neurotoxic effects both in vivo and in vitro. Our substance abuse research focuses on the global alteration of cortical protein expression in rats treated with acute METH. Altered protein expression was identified using a multistep protein separation/proteomic platform. Differential changes of the selected proteins were further confirmed by quantitative immunoblotting. Our study identified 82 differentially expressed proteins, 40 of which were downregulated and 42 of which were upregulated post acute METH treatment. Proteins that were shown to be downregulated included collapsin response mediator protein-2 (CRMP-2), superoxide dismutase 1 (SOD 1), and phosphatidylethanolamine-binding protein-1 (PEBP-1). Proteins that were shown to be upregulated included authophagy-linked microtubule-associated protein light chain 3 (LC3), synapsin-1, and Parkinsonism-linked ubiquitin carboxy-terminal hydroxylase-L1 (UCH-L1). This differential protein expression highlights on the neurotoxic mechanism involved in METH exposure as well as to discover potential markers for METH-induced neurotoxicity. In this chapter, we describe the current protocols for the in vivo rat model of acute METH treatment (40 mg/kg) coupled with the description of the multistep separation platform applied. These methods and protocols are discussed in the paradigm of acute model of methamphetamine drug abuse and can be applied to other models of substance abuse such as to MDMA or cocaine.

The methodology of neuroproteomics

The human central nervous system (CNS) is the most complex organ in nature, composed of ten trillion cells forming complex neural networks using a quadrillion synaptic connections. Proteins, their modifications, and their interactions are integral to CNS function. The emerging field of neuroproteomics provides us with a wide-scope view of posttranslation protein dynamics within the CNS to better our understanding of its function, and more often, its dysfunction consequent to neurodegenerative disorders. This chapter reviews methodology employed in the neurosciences to study the neuroproteome in health and disease. The chapter layout parallels this volume's four parts. Part I focuses on modeling human neuropathology in animals as surrogate, accessible, and controllable platforms in our research. Part II discusses methodology used to focus analysis onto a subneuroproteome. Part III reviews analytical and bioinformatic technologies applied in neuroproteomics. Part IV discusses clinical neuroproteomics, from processing of human biofluids to translation in biomarkers research. Neuroproteomics continues to mature as a discipline, confronting the extreme complexity of the CNS proteome and its dynamics, and providing insight into the molecular mechanisms underlying how our nervous system works and how it is compromised by injury and disease.