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

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

[1]  S. Wijmenga,et al.  NMR and pattern recognition methods in metabolomics: from data acquisition to biomarker discovery: a review. , 2012, Analytica chimica acta.

[2]  W. R. Wikoff,et al.  Pharmacometabolomic mapping of early biochemical changes induced by sertraline and placebo , 2013, Translational Psychiatry.

[3]  W. Drevets,et al.  Cerebrospinal Fluid Metabolome in Mood Disorders-Remission State has a Unique Metabolic Profile , 2012, Scientific Reports.

[4]  E. Domenici,et al.  Early-life stress and antidepressants modulate peripheral biomarkers in a gene–environment rat model of depression , 2010, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[5]  P. Xie,et al.  Comparative proteomic analysis of plasma from major depressive patients: identification of proteins associated with lipid metabolism and immunoregulation. , 2012, The international journal of neuropsychopharmacology.

[6]  F. Holsboer,et al.  Increased anxiety-related behaviour in Hint1 knockout mice , 2011, Behavioural Brain Research.

[7]  Florian Holsboer,et al.  Phenome-transcriptome correlation unravels anxiety and depression related pathways. , 2011, Journal of psychiatric research.

[8]  Trey Ideker,et al.  Cytoscape 2.8: new features for data integration and network visualization , 2010, Bioinform..

[9]  Nicola Zamboni,et al.  Novel biological insights through metabolomics and 13C-flux analysis. , 2009, Current opinion in microbiology.

[10]  D. Hochstrasser,et al.  From Proteins to Proteomes: Large Scale Protein Identification by Two-Dimensional Electrophoresis and Arnino Acid Analysis , 1996, Bio/Technology.

[11]  M. Mann,et al.  Stable Isotope Labeling by Amino Acids in Cell Culture, SILAC, as a Simple and Accurate Approach to Expression Proteomics* , 2002, Molecular & Cellular Proteomics.

[12]  Eiichiro Fukusaki,et al.  In Vivo 15N‐Enrichment of Metabolites in Suspension Cultured Cells and Its Application to Metabolomics , 2006, Biotechnology progress.

[13]  J. Lindon,et al.  'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. , 1999, Xenobiotica; the fate of foreign compounds in biological systems.

[14]  Andre Terzic,et al.  18O-assisted dynamic metabolomics for individualized diagnostics and treatment of human diseases , 2012, Croatian medical journal.

[15]  T. Raedler,et al.  CSF-studies in neuropsychiatric disorders. , 2006, Neuro endocrinology letters.

[16]  A. Görg,et al.  High-resolution two-dimensional electrophoresis with isoelectric focusing in immobilized pH gradients. , 1983, Journal of biochemical and biophysical methods.

[17]  B. Hammock,et al.  Mass spectrometry-based metabolomics. , 2007, Mass spectrometry reviews.

[18]  D. Martins‐de‐Souza Proteomics is not only a biomarker discovery tool , 2009 .

[19]  R. Yolken,et al.  Disease-specific alterations in frontal cortex brain proteins in schizophrenia, bipolar disorder, and major depressive disorder , 2000, Molecular Psychiatry.

[20]  P. Falkai,et al.  Differential expression of HINT1 in schizophrenia brain tissue , 2012, European Archives of Psychiatry and Clinical Neuroscience.

[21]  D. Huhman,et al.  Mass Spectrometry Strategies in Metabolomics* , 2011, The Journal of Biological Chemistry.

[22]  Chunfu Wu,et al.  Urinary metabonomic study on biochemical changes in chronic unpredictable mild stress model of depression. , 2010, Clinica chimica acta; international journal of clinical chemistry.

[23]  O. Fiehn,et al.  Evaluation of sampling and extraction methodologies for the global metabolic profiling of Saccharophagus degradans. , 2010, Analytical chemistry.

[24]  K. Hensley,et al.  Collapsin Response Mediator Protein-2: An Emerging Pathologic Feature and Therapeutic Target for Neurodisease Indications , 2011, Molecular Neurobiology.

[25]  R. Kuick,et al.  Approach to stationary two‐dimensional pattern: Influence of focusing time and Immobiline/carrier ampholytes concentrations , 1988, Electrophoresis.

[26]  P. Guest,et al.  Phosphoproteomic differences in major depressive disorder postmortem brains indicate effects on synaptic function , 2012, European Archives of Psychiatry and Clinical Neuroscience.

[27]  S. Gygi,et al.  Quantitative analysis of complex protein mixtures using isotope-coded affinity tags , 1999, Nature Biotechnology.

[28]  A. Gingras,et al.  Drafting the CLN3 protein interactome in SH-SY5Y human neuroblastoma cells: a label-free quantitative proteomics approach. , 2013, Journal of proteome research.

[29]  K. Parker,et al.  Multiplexed Protein Quantitation in Saccharomyces cerevisiae Using Amine-reactive Isobaric Tagging Reagents*S , 2004, Molecular & Cellular Proteomics.

[30]  Rima Kaddurah-Daouk,et al.  Metabolomics: A Global Biochemical Approach to the Study of Central Nervous System Diseases , 2009, Neuropsychopharmacology.

[31]  Rawi Ramautar,et al.  CE‐MS for metabolomics: Developments and applications in the period 2010–2012 , 2013, Electrophoresis.

[32]  J. Stanley,et al.  In vivo Magnetic Resonance Spectroscopy and its Application to Neuropsychiatric Disorders , 2002, Canadian journal of psychiatry. Revue canadienne de psychiatrie.

[33]  F. Holsboer,et al.  Proteomics and Metabolomics Analysis of a Trait Anxiety Mouse Model Reveals Divergent Mitochondrial Pathways , 2011, Biological Psychiatry.

[34]  D. Kell,et al.  A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations , 2001, Nature Biotechnology.

[35]  W. Jia,et al.  Metabonomics approach to assessing the modulatory effects of St John's wort, ginsenosides, and clomipramine in experimental depression. , 2012, Journal of proteome research.

[36]  N. Reo NMR-BASED METABOLOMICS , 2002, Drug and chemical toxicology.

[37]  André Schrattenholz,et al.  Systems biology approaches and tools for analysis of interactomes and multi-target drugs. , 2010, Methods in molecular biology.

[38]  J. Quevedo,et al.  Mitochondrial Dysfunction and Psychiatric Disorders , 2009, Neurochemical Research.

[39]  P. Guest,et al.  The role of energy metabolism dysfunction and oxidative stress in schizophrenia revealed by proteomics. , 2011, Antioxidants & redox signaling.

[40]  L. Carboni,et al.  Peripheral Biomarkers in Animal Models of Major Depressive Disorder , 2013, Disease markers.

[41]  T. Nikolskaya,et al.  Biological networks and analysis of experimental data in drug discovery. , 2005, Drug discovery today.

[42]  D. Charney,et al.  Is There Anything Really Novel on the Antidepressant Horizon? , 2012, Current Psychiatry Reports.

[43]  Y. Yang,et al.  Proteomics reveals energy and glutathione metabolic dysregulation in the prefrontal cortex of a rat model of depression , 2013, Neuroscience.

[44]  C W Turck,et al.  Proteome-Based Pathway Modelling of Psychiatric Disorders , 2011, Pharmacopsychiatry.

[45]  C. Turck,et al.  Quantitative proteomics for investigating psychiatric disorders , 2011, Proteomics. Clinical applications.

[46]  Joachim Thiery,et al.  LC-MS-based metabolomics in the clinical laboratory. , 2012, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[47]  P. O’Farrell High resolution two-dimensional electrophoresis of proteins. , 1975, The Journal of biological chemistry.

[48]  M. Vidal,et al.  Interactome Mapping of the Phosphatidylinositol 3-Kinase-Mammalian Target of Rapamycin Pathway Identifies Deformed Epidermal Autoregulatory Factor-1 as a New Glycogen Synthase Kinase-3 Interactor* , 2010, Molecular & Cellular Proteomics.

[49]  Kyla Pennington,et al.  Proteomic analysis of the anterior cingulate cortex in the major psychiatric disorders: Evidence for disease‐associated changes , 2006, Proteomics.

[50]  Peng Xie,et al.  Plasma metabonomics as a novel diagnostic approach for major depressive disorder. , 2012, Journal of proteome research.

[51]  Claire K. Sanders,et al.  A surface display yeast two-hybrid screening system for high-throughput protein interactome mapping. , 2009, Analytical biochemistry.

[52]  J. Yates,et al.  Direct analysis of protein complexes using mass spectrometry , 1999, Nature Biotechnology.

[53]  Peilin Jia,et al.  A comprehensive network and pathway analysis of candidate genes in major depressive disorder , 2011, BMC Systems Biology.

[54]  Peng Xie,et al.  Identification and Validation of Urinary Metabolite Biomarkers for Major Depressive Disorder* , 2012, Molecular & Cellular Proteomics.

[55]  C. Barbas,et al.  LC-MS metabolomics of polar compounds. , 2012, Bioanalysis.

[56]  M. Thase,et al.  Emerging drugs for major depressive disorder , 2012, Expert opinion on emerging drugs.

[57]  H. Ressom,et al.  LC-MS-based metabolomics. , 2012, Molecular bioSystems.

[58]  Rima Kaddurah-Daouk,et al.  A preliminary metabolomic analysis of older adults with and without depression , 2007, International journal of geriatric psychiatry.

[59]  D. Martins‐de‐Souza Comprehending depression through proteomics. , 2012, The international journal of neuropsychopharmacology.

[60]  P. Aloy,et al.  Three-dimensional modeling of protein interactions and complexes is going 'omics. , 2011, Current opinion in structural biology.

[61]  R. Krishnan,et al.  Pretreatment metabotype as a predictor of response to sertraline or placebo in depressed outpatients: a proof of concept , 2011, Translational Psychiatry.

[62]  B. Coulombe Mapping the disease protein interactome: toward a molecular medicine GPS to accelerate drug and biomarker discovery. , 2011, Journal of proteome research.

[63]  T. Schneider-Axmann,et al.  Different apolipoprotein E, apolipoprotein A1 and prostaglandin-H2 D-isomerase levels in cerebrospinal fluid of schizophrenia patients and healthy controls , 2010, The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry.

[64]  Xin Lu,et al.  Metabonomics study of urine and plasma in depression and excess fatigue rats by ultra fast liquid chromatography coupled with ion trap-time of flight mass spectrometry. , 2010, Molecular bioSystems.

[65]  H. Brown,et al.  Sum of the parts: mass spectrometry-based metabolomics. , 2013, Biochemistry.

[66]  D. Martins‐de‐Souza Biomarkers for Psychiatric Disorders: Where Are We Standing? , 2013, Disease markers.

[67]  A. Valencia,et al.  Computational methods for the prediction of protein interactions. , 2002, Current opinion in structural biology.

[68]  Christine A. Miller,et al.  Cerebrospinal Fluid Biomarkers for Major Depression Confirm Relevance of Associated Pathophysiology , 2012, Neuropsychopharmacology.

[69]  T. Weichhart,et al.  The PI3K/Akt/mTOR pathway in innate immune cells: emerging therapeutic applications , 2008, Annals of the rheumatic diseases.

[70]  M. Webster,et al.  Identification of proteomic signatures associated with depression and psychotic depression in post-mortem brains from major depression patients , 2012, Translational Psychiatry.

[71]  J. Enghild,et al.  Vesicular signalling and immune modulation as hedonic fingerprints: proteomic profiling in the chronic mild stress depression model , 2012, Journal of psychopharmacology.

[72]  Jia Bei Wang,et al.  Anti-depressant and anxiolytic like behaviors in PKCI/HINT1 knockout mice associated with elevated plasma corticosterone level , 2009, BMC Neuroscience.

[73]  D. Oxley,et al.  Disease Biomarkers in Cerebrospinal Fluid of Patients with First-Onset Psychosis , 2006, PLoS medicine.

[74]  R. McIntyre,et al.  Crosstalk between metabolic and neuropsychiatric disorders , 2012, F1000 biology reports.

[75]  Damian Szklarczyk,et al.  STRING v9.1: protein-protein interaction networks, with increased coverage and integration , 2012, Nucleic Acids Res..

[76]  Xuemei Qin,et al.  Metabolomics study on the anti-depression effect of xiaoyaosan on rat model of chronic unpredictable mild stress. , 2010, Journal of ethnopharmacology.

[77]  M. Dimatteo,et al.  Depression is a risk factor for noncompliance with medical treatment: meta-analysis of the effects of anxiety and depression on patient adherence. , 2000, Archives of internal medicine.

[78]  Edward T. Bullmore,et al.  Plasma Protein Biomarkers for Depression and Schizophrenia by Multi Analyte Profiling of Case-Control Collections , 2010, PloS one.

[79]  F. Holsboer,et al.  Characterization of the B-Raf interactome in mouse hippocampal neuronal cells. , 2011, Journal of proteomics.

[80]  D. Martins‐de‐Souza Is the word ‘biomarker’ being properly used by proteomics research in neuroscience? , 2010, European Archives of Psychiatry and Clinical Neuroscience.

[81]  E Gianazza,et al.  Isoelectric focusing in immobilized pH gradients: principle, methodology and some applications. , 1982, Journal of biochemical and biophysical methods.

[82]  K. Krishnan,et al.  Metabolomic Differences in Heart Failure Patients With and Without Major Depression , 2010, Journal of geriatric psychiatry and neurology.

[83]  Coral Barbas,et al.  Gas chromatography-mass spectrometry (GC-MS)-based metabolomics. , 2011, Methods in molecular biology.

[84]  Yan Gao,et al.  Antidepressive behaviors induced by enriched environment might be modulated by glucocorticoid levels , 2009, European Neuropsychopharmacology.

[85]  J. Thomas-Oates,et al.  Metabolomic applications of HILIC-LC-MS. , 2010, Mass spectrometry reviews.

[86]  M. Ünlü,et al.  Difference gel electrophoresis. A single gel method for detecting changes in protein extracts , 1997, Electrophoresis.

[87]  D. Martins‐de‐Souza Translational strategies to schizophrenia from a proteomic perspective , 2012 .

[88]  F. Holsboer,et al.  Blood Mononuclear Cell Proteome Suggests Integrin and Ras Signaling as Critical Pathways for Antidepressant Treatment Response , 2014, Biological Psychiatry.

[89]  P. Guest,et al.  Biomarker blood tests for diagnosis and management of mental disorders: focus on schizophrenia , 2012 .

[90]  D. Fuchs,et al.  Immune changes and neurotransmitters: Possible interactions in depression? , 2014, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[91]  C. Turck,et al.  To label or not to label: Applications of quantitative proteomics in neuroscience research , 2012, Proteomics.

[92]  P. Guest,et al.  Proteomic approaches to unravel the complexity of schizophrenia , 2012, Expert review of proteomics.

[93]  F. Holsboer,et al.  Proteomic and Metabolomic Profiling of a Trait Anxiety Mouse Model Implicate Affected Pathways* , 2011, Molecular & Cellular Proteomics.

[94]  D. Martins‐de‐Souza,et al.  Large-scale analyses of schizophrenia proteome , 2012 .

[95]  G. Schmitt-Ulms,et al.  Co-immunoprecipitations revisited: an update on experimental concepts and their implementation for sensitive interactome investigations of endogenous proteins , 2007, Analytical and bioanalytical chemistry.

[96]  M. Mann,et al.  Peptide separation with immobilized pI strips is an attractive alternative to in‐gel protein digestion for proteome analysis , 2008, Proteomics.

[97]  P. Guest,et al.  Proteomic technologies for biomarker studies in psychiatry: advances and needs. , 2011, International review of neurobiology.