Recent advances in polygenic scores: translation, equitability, methods and FAIR tools.

Polygenic scores (PGS) can be used for risk stratification by quantifying individuals' genetic predisposition to disease, and many potentially clinically useful applications have been proposed. Here, we review the latest potential benefits of PGS in the clinic and challenges to implementation. PGS could augment risk stratification through combined use with traditional risk factors (demographics, disease-specific risk factors, family history, etc.), to support diagnostic pathways, to predict groups with therapeutic benefits, and to increase the efficiency of clinical trials. However, there exist challenges to maximizing the clinical utility of PGS, including FAIR (Findable, Accessible, Interoperable, and Reusable) use and standardized sharing of the genomic data needed to develop and recalculate PGS, the equitable performance of PGS across populations and ancestries, the generation of robust and reproducible PGS calculations, and the responsible communication and interpretation of results. We outline how these challenges may be overcome analytically and with more diverse data as well as highlight sustained community efforts to achieve equitable, impactful, and responsible use of PGS in healthcare.

The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

The Ontology of Biological Attributes (OBA) - Computational Traits for the Life Sciences.

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focused measurable trait data. Moreover, variations in gene expression in response to environmental disturbances even without any genetic alterations can also be associated with particular biological attributes. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource.

The NHGRI-EBI GWAS Catalog (www.ebi.ac.uk/gwas) is a FAIR knowledgebase providing detailed, structured, standardised and interoperable genome-wide association study (GWAS) data to >200 000 users per year from academic research, healthcare and industry. The Catalog contains variant-trait associations and supporting metadata for >45 000 published GWAS across >5000 human traits, and >40 000 full P-value summary statistics datasets. Content is curated from publications or acquired via author submission of prepublication summary statistics through a new submission portal and validation tool. GWAS data volume has vastly increased in recent years. We have updated our software to meet this scaling challenge and to enable rapid release of submitted summary statistics. The scope of the repository has expanded to include additional data types of high interest to the community, including sequencing-based GWAS, gene-based analyses and copy number variation analyses. Community outreach has increased the number of shared datasets from under-represented traits, e.g. cancer, and we continue to contribute to awareness of the lack of population diversity in GWAS. Interoperability of the Catalog has been enhanced through links to other resources including the Polygenic Score Catalog and the International Mouse Phenotyping Consortium, refinements to GWAS trait annotation, and the development of a standard format for GWAS data.

Sequencing-based genome-wide association studies reporting standards.

Genome sequencing has recently become a viable genotyping technology for use in genome-wide association studies (GWASs), offering the potential to analyze a broader range of genome-wide variation, including rare variants. To survey current standards, we assessed the content and quality of reporting of statistical methods, analyses, results, and datasets in 167 exome- or genome-wide-sequencing-based GWAS publications published from 2014 to 2020; 81% of publications included tests of aggregate association across multiple variants, with multiple test models frequently used. We observed a lack of standardized terms and incomplete reporting of datasets, particularly for variants analyzed in aggregate tests. We also find a lower frequency of sharing of summary statistics compared with array-based GWASs. Reporting standards and increased data sharing are required to ensure sequencing-based association study data are findable, interoperable, accessible, and reusable (FAIR). To support that, we recommend adopting the standard terminology of sequencing-based GWAS (seqGWAS). Further, we recommend that single-variant analyses be reported following the same standards and conventions as standard array-based GWASs and be shared in the GWAS Catalog. We also provide initial recommended standards for aggregate analyses metadata and summary statistics.

Workshop proceedings: GWAS summary statistics standards and sharing.

Genome-wide association studies (GWASs) have enabled robust mapping of complex traits in humans. The open sharing of GWAS summary statistics (SumStats) is essential in facilitating the larger meta-analyses needed for increased power in resolving the genetic basis of disease. However, most GWAS SumStats are not readily accessible because of limited sharing and a lack of defined standards. With the aim of increasing the availability, quality, and utility of GWAS SumStats, the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) GWAS Catalog organized a community workshop to address the standards, infrastructure, and incentives required to promote and enable sharing. We evaluated the barriers to SumStats sharing, both technological and sociological, and developed an action plan to address those challenges and ensure that SumStats and study metadata are findable, accessible, interoperable, and reusable (FAIR). We encourage early deposition of datasets in the GWAS Catalog as the recognized central repository. We recommend standard requirements for reporting elements and formats for SumStats and accompanying metadata as guidelines for community standards and a basis for submission to the GWAS Catalog. Finally, we provide recommendations to enable, promote, and incentivize broader data sharing, standards and FAIRness in order to advance genomic medicine.

Denser brain capillary network with preserved pericytes in Alzheimer's disease.

Pericytes are vascular mural cells that surround capillaries of the central nervous system (CNS). They are crucial for brain development and contribute to CNS homeostasis by regulating blood-brain barrier function and cerebral blood flow. It has been suggested that pericytes are lost in Alzheimer's disease (AD), implicating this cell type in disease pathology. Here, we have employed state-of-the-art stereological morphometry techniques as well as tissue clearing and two-photon imaging to assess the distribution of pericytes in two independent cohorts of AD (n = 16 and 13) and non-demented controls (n = 16 and 4). Stereological quantification revealed increased capillary density with a normal pericyte population in the frontal cortex of AD brains, a region with early amyloid ß deposition. Two-photon analysis of cleared frontal cortex tissue confirmed the preservation of pericytes in AD cases. These results suggest that pericyte demise is not a general hallmark of AD pathology.

The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019.

The GWAS Catalog delivers a high-quality curated collection of all published genome-wide association studies enabling investigations to identify causal variants, understand disease mechanisms, and establish targets for novel therapies. The scope of the Catalog has also expanded to targeted and exome arrays with 1000 new associations added for these technologies. As of September 2018, the Catalog contains 5687 GWAS comprising 71673 variant-trait associations from 3567 publications. New content includes 284 full P-value summary statistics datasets for genome-wide and new targeted array studies, representing 6 × 109 individual variant-trait statistics. In the last 12 months, the Catalog's user interface was accessed by ∼90000 unique users who viewed >1 million pages. We have improved data access with the release of a new RESTful API to support high-throughput programmatic access, an improved web interface and a new summary statistics database. Summary statistics provision is supported by a new format proposed as a community standard for summary statistics data representation. This format was derived from our experience in standardizing heterogeneous submissions, mapping formats and in harmonizing content. Availability: https://www.ebi.ac.uk/gwas/.

A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog.

The accurate description of ancestry is essential to interpret, access, and integrate human genomics data, and to ensure that these benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the representation of ancestry information. Here we describe a framework for the accurate and standardized description of sample ancestry, and validate it by application to the NHGRI-EBI GWAS Catalog. We confirm known biases and gaps in diversity, and find that African and Hispanic or Latin American ancestry populations contribute a disproportionately high number of associations. It is our hope that widespread adoption of this framework will lead to improved analysis, interpretation, and integration of human genomics data.

Identification of a molecular profile associated with immune status in first-onset schizophrenia patients.

OBJECTIVES: Alterations in immunological parameters have been reported for schizophrenia although little is known about the effects of inflammatory status on immune-related functional changes at disease onset. Here, we have investigated such T cell-dependent molecular changes in first-onset, antipsychotic-naive schizophrenia patients using a novel ex vivo blood culture system. METHODS: Blood samples from patients (n=17) and controls (n=17) were collected into stimulant-containing or null control TruCulture™ tubes, incubated 24 hours and the concentrations of 107 immune and metabolic molecules measured in the conditioned media using the HumanMAP™ immunoassay system. RESULTS: Nine molecules showed altered release from schizophrenia blood cells compared to those from controls and this was replicated in an independent cohort. In silico pathway analysis showed that these molecules had roles in endothelial cell function, inflammation, acute phase response and fibrinolysis pathways. Importantly, five of these molecules showed altered release only after stimulation. CONCLUSIONS: This study has identified a reproducible peripheral molecular signature associated with altered immune function in first-onset schizophrenia subjects. This suggests that immune status can affect the biomarker profile which could be important for personalized medicine strategies. Furthermore, whole blood culture analysis may be useful in the identification of diagnostic tools or novel treatment strategies due to ease-of-use and clinical accessibility.

Schizophrenia: metabolic aspects of aetiology, diagnosis and future treatment strategies.

Despite decades of research, the pathophysiology and aetiology of schizophrenia remains incompletely understood. The disorder is frequently accompanied by metabolic symptoms including dyslipidaemia, hyperinsulinaemia, type 2 diabetes and obesity. These symptoms are a common side effect of currently available antipsychotic medications. However, reports of metabolic dysfunction in schizophrenia predate the antipsychotic era and have also been observed in first onset patients prior to antipsychotic treatment. Here, we review the evidence for abnormalities in metabolism in schizophrenia patients, both in the central nervous system and periphery. Molecular analysis of post mortem brain tissue has pointed towards alterations in glucose metabolism and insulin signalling pathways, and blood-based molecular profiling analyses have demonstrated hyperinsulinaemia and abnormalities in secretion of insulin and co-released factors at first presentation of symptoms. Nonetheless, such features are not observed for all subjects with the disorder and not all individuals with such abnormalities suffer the symptoms of schizophrenia. One interpretation of these data is the presence of an underlying metabolic vulnerability in a subset of individuals which interacts with environmental or genetic factors to produce the overt symptoms of the disorder. Further investigation of metabolic aspects of schizophrenia may prove critical for diagnosis, improvement of existing treatment based on patient stratification/personalised medicine strategies and development of novel antipsychotic agents.

Metabolic, hormonal and stress-related molecular changes in post-mortem pituitary glands from schizophrenia subjects.

OBJECTIVES: To identify a molecular profile for schizophrenia using post-mortem pituitaries from schizophrenia and control subjects. METHODS: Molecular profiling analysis of pituitaries from schizophrenia (n = 14) and control (n = 15) subjects was carried out using a combination of liquid chromatography tandem mass spectrometry (LC-MS(E)), multiplex analyte profiling (MAP), two-dimensional difference gel electrophoresis (2D-DIGE) and Western blot analysis. RESULTS: This led to identification of differentially expressed molecules in schizophrenia patients including hypothalamic-pituitary-adrenal axis-associated constituents such as cortisol, pro-adrenocorticotropic hormone, arginine vasopressin precursor, agouti-related protein, growth hormone, prolactin and secretagogin, as well as molecules associated with lipid transport and metabolism such as apolipoproteins A1, A2, C3 and H. Altered levels of secretagogin in serum from a cohort of living first onset schizophrenia patients were also detected, suggesting disease association and illustrating the potential for translating some components of this molecular profile to serum-based assays. CONCLUSIONS: Future studies on the molecules identified here may lead to new insights into schizophrenia pathophysiology and pave the way for translation of novel diagnostics for use in a clinical setting.

Testes sanguíneos de biomarcadores para diagnóstico e tratamento de desordens mentais: foco em esquizofrenia / Biomarker blood tests for diagnosis and management of mental disorders: focus on schizophrenia

A descoberta e a aplicação clínica de biomarcadores para desordens mentais são confrontadas com muitos desafios. Em geral, os atuais métodos de descoberta e validação de biomarcadores não produziram os resultados que foram inicialmente aguardados depois da finalização do Projeto Genoma Humano. Isso se deve principalmente à falta de processos padronizados conectando a descoberta de marcadores com tecnologias para a validação e a tradução para uma plataforma que ofereça precisão e fácil uso em clínica. Como consequência, a maior parte dos psiquiatras e praticantes em geral são relutantes em aceitar que testes de biomarcadores pode suplementar ou substituir os métodos de diagnóstico utilizados baseados em entrevista. Apesar disso, agências regulatórias concordam agora que melhoras nos correntes métodos são essenciais. Além disso, essas agências estipularam que biomarcadores são importantes para o desenvolvimento de futuras drogas e iniciaram esforços no sentido de modernizar métodos e técnicas para suportar esses esforços. Aqui revisamos os desafios encontrados por essa tentativa do ponto de vista de psiquiatras, praticantes em geral, agências reguladoras e cientistas de biomarcadores. Também descrevemos o desenvolvimento de um novo teste sanguíneo molecular para esquizofrenia como um primeiro passo a esse objetivo

The discovery and clinical application of biomarkers for mental disorders is faced with many challenges. In general, the current methods for discovery and validation of biomarkers have not produced the results which were first anticipated after completion of the human genome project. This is mostly due to the lack of a standardized pipeline connecting marker discovery with technologies for validation and translation to a platform that offers accuracy and ease of use in a clinical setting. As a consequence, most psychiatrists and general practitioners are still reluctant to accept that biomarker tests can supplement or replace the long standing interview-based methods for diagnosis. Despite this, the regulatory agencies now agree that improvements over the current methods are essential. Furthermore, these agencies stipulate that biomarkers are important for future drug development and have initiated efforts to modernize methods and techniques to support these efforts. Here, we review the challenges faced by this endeavour from the point of view of psychiatrists, general practitioners, the regulatory agencies and biomarker scientists. We also describe the development of a novel molecular blood-test for schizophrenia as a first promising step towards achieving this goal

Explorando o componente inflamatório da esquizofrenia / Targeting the inflammatory component of schizophrenia

A esquizofrenia é uma doença heterogênea caracterizada por um conjunto de manifestações clínicas. Um grande número de estudos ao longo dos últimos 20 anos apontou para anormalidades no sistema imune em pacientes que sofrem dessa condição. Em adição, tem sido mostrado que a psicose e a disfunção cognitiva associadas com a esquizofrenia estão ligadas a doenças autoimunes. Aqui, revisamos a evidência que sugere que um status pró-inflamatório do sistema imune induz sintomas psicopatológicos e pode estar envolvido na fisiopatologia dessa principal doença mental. Também propomos que futuros estudos pré-clínicos e clínicos deveriam levar em conta tais causas predefinidas e o status do componente inflamatório. Estratificação de pacientes e estratégias de medicina personalizadas baseadas no direcionamento ao componente inflamatório da doença poderiam ajudar na redução de sintomas e da progressão da doença. Por fim, isso poderia levar a novos conceitos na identificação de alvos moleculares em esquizofrenia e estratégias de descoberta de drogas

Schizophrenia is a heterogeneous disease characterised by an array of clinical manifestations. A large number of studies over the last 20 years have pointed towards immune system abnormalities in patients suffering from this condition. In addition, the psychosis and cognitive dysfunction associated with schizophrenia have been shown to be linked with autoimmune diseases. Here, we review the evidence, which suggests that a pro-inflammatory status of the immune system induces psychopathologic symptoms and may be involved in the pathophysiology of this major mental illness. We also propose that future preclinical and clinical studies should take such pre-defined causes and the dynamic status of the inflammatory component into account. Patient stratification and personalised medicine strategies based on targeting the inflammatory component of the disease could help in alleviation of symptoms and slowing disease progression. Ultimately, this could also lead to novel concepts in schizophrenia target/molecular identification and drug discovery strategies

Estudos traducionais de neuropsiquiatria e esquizofrenia: modelos animais genéticos e de neurodesenvolvimento / Translational neuropsychiatry of genetic and neurodevelopmental animal models of schizophrenia

Sintomas psiquiátricos são subjetivos por natureza e tendem a se sobrepor entre diferentes desordens. Sendo assim, a criação de modelos de uma desordem neuropsiquiátrica encontra desafios pela falta de conhecimento dos fundamentos da fisiopatologia e diagnósticos precisos. Modelos animais são usados para testar hipóteses de etiologia e para representar a condição humana tão próximo quanto possível para aumentar nosso entendimento da doença e avaliar novos alvos para a descoberta de drogas. Nesta revisão, modelos animais genéticos e de neurodesenvolvimento de esquizofrenia são discutidos com respeito a achados comportamentais e neurofisiológicos e sua associação com a condição clínica. Somente modelos animais específicos de esquizofrenia podem, em último caso, levar a novas abordagens diagnósticas e descoberta de drogas. Argumentamos que biomarcadores moleculares são importantes para aumentar a tradução de animais a humanos, já que faltam a especificidade e a fidelidade necessárias às leituras comportamentais para avaliar sintomas psiquiátricos humanos

Psychiatric symptoms are subjective by nature and tend to overlap between different disorders. The modelling of a neuropsychiatric disorder therefore faces challenges because of missing knowledge of the fundamental pathophysiology and a lack of accurate diagnostics. Animal models are used to test hypotheses of aetiology and to represent the human condition as close as possible to increase our understanding of the disease and to evaluate new targets for drug discovery. In this review, genetic and neurodevelopmental animal models of schizophrenia are discussed with respect to behavioural and neurophysiological findings and their association with the clinical condition. Only specific animal models of schizophrenia may ultimately lead to novel diagnostic approaches and drug discovery. We argue that molecular biomarkers are important to improve animal to human translation since behavioural readouts lack the necessary specificity and reliability to assess human psychiatric symptoms

Comparison of peripheral and central schizophrenia biomarker profiles.

We have recently shown that a molecular biomarker signature comprised of inflammatory, hormonal and growth factors occurs in the blood serum from first onset schizophrenia patients. Here, we use the same platform to investigate post mortem brain tissue (Brodmann area 10) from schizophrenia patients who were mainly chronically ill and drug treated. Twenty-one analytes are differentially expressed in post-mortem brain tissue. Comparison with our previous mRNA profiling studies of the same patient samples in another frontal cortical area showed that 9 of these molecules were also altered at the transcriptional level. Furthermore, 9 of the molecules were also altered in serum from living first onset schizophrenia patients compared to controls. We propose a model in which the brain and periphery are coordinated through hormones and other regulatory molecules released into the blood via the diffuse neuroendocrine system. These findings provide further evidence for the systemic nature of schizophrenia and give added validity to the concept that schizophrenia can be investigated through studies of blood-based biomarkers.

Proteomic analysis of the maternal protein restriction rat model for schizophrenia: identification of translational changes in hormonal signaling pathways and glutamate neurotransmission.

Previous studies have found that some first onset schizophrenia patients show signs of impaired insulin signaling. Also, epidemiological studies have shown that periods of suboptimal nutrition including protein deficiencies during pregnancy can lead to increased incidence of metabolic conditions and psychiatric disorders in the offspring. For these reasons, we have carried out a molecular profiling analysis of blood serum and brain tissues from adult offspring produced by the maternal low protein (LP) rat model. The results showed similar changes to those seen in schizophrenia. Multiplex immunoassay profiling identified changes in the levels of insulin, adiponectin, and leptin along with alterations in inflammatory and vascular system-related proteins such as osteopontin, macrophage colony-stimulating factor 1, and vascular cell adhesion molecule 1. LC-MS(E) proteomic profiling showed that glutamatergic pathways were altered in frontal cortex, while signaling pathways and cytoskeletal proteins involved in hormonal secretion and synaptic remodeling were altered in the hypothalamus. Taken together, these studies indicate that the LP rat model recapitulates several pathophysiological attributes seen in schizophrenia patients. We propose that the LP model may have utility for drug discovery efforts, especially to identify compounds that modulate the metabolic and glutamatergic systems.

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

BACKGROUND: Establishing preclinical models is essential for novel drug discovery in schizophrenia. Most existing models are characterized by abnormalities in behavioral readouts, which are informative, but do not necessarily translate to the symptoms of the human disease. Therefore, there is a necessity of characterizing the preclinical models from a molecular point of view. Selective reaction monitoring (SRM) has already shown promise in preclinical and clinical studies for multiplex measurement of diagnostic, prognostic and treatment-related biomarkers. METHODS: We have established an SRM assay for multiplex analysis of 7 enzymes of the glycolysis pathway which is already known to be affected in human schizophrenia and in the widely-used acute PCP rat model of schizophrenia. The selected enzymes were hexokinase 1 (Hk1), aldolase C (Aldoc), triosephosphate isomerase (Tpi1), glyceraldehyde-3-phosphate dehydrogenase (Gapdh), phosphoglycerate mutase 1 (Pgam1), phosphoglycerate kinase 1 (Pgk1) and enolase 2 (Eno2). The levels of these enzymes were analyzed using SRM in frontal cortex from brain tissue of PCP treated rats. RESULTS: Univariate analyses showed statistically significant altered levels of Tpi1 and alteration of Hk1, Aldoc, Pgam1 and Gapdh with borderline significance in PCP rats compared to controls. Most interestingly, multivariate analysis which considered the levels of all 7 enzymes simultaneously resulted in generation of a bi-dimensional chart that can distinguish the PCP rats from the controls. CONCLUSIONS: This study not only supports PCP treated rats as a useful preclinical model of schizophrenia, but it also establishes that SRM mass spectrometry could be used in the development of multiplex classification tools for complex psychiatric disorders such as schizophrenia.

The methylazoxymethanol acetate (MAM-E17) rat model: molecular and functional effects in the hippocampus.

Administration of the DNA-alkylating agent methylazoxymethanol acetate (MAM) on embryonic day 17 (E17) produces behavioral and anatomical brain abnormalities, which model some aspects of schizophrenia. This has lead to the premise that MAM rats are a neurodevelopmental model for schizophrenia. However, the underlying molecular pathways affected in this model have not been elucidated. In this study, we investigated the molecular phenotype of adult MAM rats by focusing on the frontal cortex and hippocampal areas, as these are known to be affected in schizophrenia. Proteomic and metabonomic analyses showed that the MAM treatment on E17 resulted primarily in deficits in hippocampal glutamatergic neurotransmission, as seen in some schizophrenia patients. Most importantly, these results were consistent with our finding of functional deficits in glutamatergic neurotransmission, as identified using electrophysiological recordings. Thus, this study provides the first molecular evidence, combined with functional validation, that the MAM-E17 rat model reproduces hippocampal deficits relevant to the pathology of schizophrenia.

Proteomic technologies for biomarker studies in psychiatry: advances and needs.

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