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

Martins-de-Souza, Daniel; Alsaif, Murtada; Ernst, Agnes; Harris, Laura W.; Aerts, Nancy; Lenaerts, Ilse; Peeters, Pieter J.; Amess, Bob; Rahmoune, Hassan; Bahn, Sabine; Guest, Paul C.

doi:10.1186/1756-0500-5-146

Cited by 32 publications

(23 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Third, the “omics” discovery approaches suffer from the heterogeneity of the sampled populations which involves interspecies and genetic variations (Cowan et al, 2002; O’Tuathaigh et al, 2012). Such heterogeneity could account, in part, for the conflicting results associated with the limited experimental reproducibility (Fathi et al, 2009; Martins-de-Souza et al, 2012). Furthermore, as most studies rely on postmortem human tissue, challenges encompass the inability to find enough samples (Korolainen et al, 2010; Sequeira et al, 2012), along with the inherent limitations of neuropathological analysis to discriminate between changes caused by the NP disorders themselves and those derived from postmortem artifacts, or other confounding factors (Huang et al, 2006; Harris et al, 2007).…”

Section: Resultsmentioning

confidence: 99%

Systems Biology, Bioinformatics, and Biomarkers in Neuropsychiatry

Alawieh¹,

Zaraket²,

Li³

et al. 2012

Front. Neurosci.

View full text Add to dashboard Cite

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.

show abstract

Section: Resultsmentioning

confidence: 99%

Systems Biology, Bioinformatics, and Biomarkers in Neuropsychiatry

Alawieh¹,

Zaraket²,

Li³

et al. 2012

Front. Neurosci.

View full text Add to dashboard Cite

show abstract

“…In agreement with these data, another proteomic study using a selected reaction monitoring assay indicates alterations in energy metabolism including glycolytic enzymes. The most consistent data include aldolase C (ALDOC), γ-enolase (ENO2), hexokinase (HK1), phosphoglycerate mutase 1 (PGAM1), aconitate hydratase (ACO2) and triosephosphate isomerase (TPI1) [17,28]. HK is a rate-limiting enzyme of glycolysis, and among the isozymes, HK1 is the only one that is predominantly bound to mitochondria.…”

Section: Glycolysis Pathway and Oxidative Stressmentioning

confidence: 94%

Proteomic Characterization of the Brain and Cerebrospinal Fluid of Schizophrenia Patients

Café-Mendes

Gattaz

Schmitt

et al. 2014

Advances in Biological Psychiatry

Self Cite

View full text Add to dashboard Cite

As a multifactorial mental disorder, schizophrenia presents a complex combination of genetic, neurodevelopmental and environmental components. These lead to difficulties in comprehending the molecular basis of schizophrenia as well as in identifying biomarkers. These issues can be tackled by proteomics, which has been used increasingly along with genetics and other '-omics' approaches. In the present chapter, we explore some advances in proteomic studies involving brain tissue and cerebrospinal fluid collected from schizophrenic patients. We demonstrate that proteomic findings have been confirmed by other approaches, and added new information about the role of synaptic connectivity, oxidative stress, glucose metabolism and cytoskeletal alterations as core features of the disease pathophysiology. Integrative systems analysis including proteomics is a valid strategy for understanding the molecular basis of schizophrenia and may indicate the way to future clinical applications. SchizophreniaSchizophrenia is a severe mental disorder with a lifetime prevalence of 0.3-0.7% and presenting a heterogeneous range of symptoms [1]. It is a multifactorial disorder composed of a number of etiological factors of small effect that may be triggered by environmental components [2]. The causes of schizophrenia are strongly determined by genetics, but also by other factors such as epistatic (interaction between two or more genes controlling a single phenotype) and environmental ones (epigenetics). This is supported by the fact that 90% of individuals who develop schizophrenia have no history of schizophrenic parents or relatives. This conclusion does not exclude the heritable factor of schizophrenia, which is high (up to 80%), but reinforces the fact that environmental factors influence the onset/development of the disease [3]. Although interactions occur and are responsible for the establishment of the Martins-de-Souza D (ed): Proteomics and Metabolomics in Psychiatry.

show abstract

“…A MRM assay was developed to examine the levels of 7 glycolytic enzymes (HK1, ALDOC, TPI1, GAPDH, PGAM1, PGK1 and ENO2) that were previously shown to be affected in post-mortem brain tissue from schizophrenic patients using 2D-gel and MS-based quantitative methods [173] (Table 6). They used a model of psychosis, in which rats were treated with the NMDA antagonist phencyclidine (PCP).…”

Section: Quantitative Mass Spectrometry-based Techniquesmentioning

confidence: 99%

Recent advances in quantitative neuroproteomics

Craft

Chen

Nairn

2013

Methods

122

View full text Add to dashboard Cite

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

show abstract

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

Cited by 32 publications

References 39 publications

Systems Biology, Bioinformatics, and Biomarkers in Neuropsychiatry

Systems Biology, Bioinformatics, and Biomarkers in Neuropsychiatry

Proteomic Characterization of the Brain and Cerebrospinal Fluid of Schizophrenia Patients

Recent advances in quantitative neuroproteomics

Contact Info

Product

Resources

About