Protein phosphorylation patterns in serum from schizophrenia patients and healthy controls

Effects of olanzapine on serum protein phosphorylation patterns in patients with schizophrenia

PURPOSE

Previous studies have shown that blood serum phosphoproteins are altered in schizophrenia patients in comparison to controls. However, it is not known whether phosphoproteins are also changed in response to treatment with antipsychotics.

EXPERIMENTAL DESIGN

Blood samples were taken from patients (n = 23) at baseline and after 6 weeks of olanzapine treatment. Immobilized metal ion affinity chromatography (IMAC) was used for enrichment of serum phosphoproteins and these were analyzed by label-free LC-MS in expression mode (LC-MS(E) ).

RESULTS

We identified 11 proteins that were changed significantly in overall abundance and 45 proteins that showed changes in phosphorylation after the antipsychotic treatment. The altered phosphoproteins were mainly involved in the acute phase response, lipid and glucose homeostasis (LXR), retinoic acid signaling (RXR), and complement pathways. Some of the proteins showed a marked increase in phosphorylation, including apolipoprotein A-I (3.4-fold), alpha-1-anti-chymotrypsin (3.1-fold), and apolipoprotein B-100 (2.2-fold). In addition, several proteins showed either decreased phosphorylation (e.g. complement C4A, collagen alpha-1 chain, complement factor H) or a mixture of increased and decreased phoshphorylation (e.g. afamin, complement C5, complement factor B). Finally, 24 of the altered phosphoproteins showed opposite directional changes in a comparison of baseline schizophrenia patients before and after treatment with olanzapine. These included alpha-1B-glycoprotein, apolipoprotein A-IV, vitamin D-binding protein, and prothrombin.

CONCLUSIONS AND CLINICAL RELEVANCE

These data demonstrate the potential for future studies of serum phosphoproteins as a readout of physiological function and might have utility in studies aimed at identification of biomarkers for drug response prediction or monitoring.

Recent developments in proteomic methods and disease biomarkers

Proteomic methodologies for identification and analysis of biomarkers have gained more attention during recent years and have evolved rapidly. Identification and detection of disease biomarkers are important to foresee outbreaks of certain diseases thereby avoiding surgery and other invasive and expensive medical treatments for patients. Thus, more research into discovering new biomarkers and new methods for faster and more accurate detection is needed. It is often difficult to detect and measure biomarkers because of their low concentrations and the complexity of their respective matrices. Therefore it is hard to find and validate methods for accurate screening methods suitable for clinical use. The most recent developments during the last three years and also some historical considerations of proteomic methodologies for identification and validation of disease biomarkers are presented in this review.

Analysis of differentially expressed novel post-translational modifications of plasma apolipoprotein E in Taiwanese females with breast cancer

APOE ε2 or ε4 alleles being used as indicators of breast cancer risk are controversial in Taiwanese females. We provide a concept for relative comparisons of post-translational modifications (PTMs) of plasma apolipoprotein E (ApoE) between normal controls and breast cancer patients to investigate the association of ApoE with breast cancer risk. APOE polymorphisms (ApoE isoforms) were not assessed in this study. The relative modification ratio (%) of 15 targeted and 21 modified peptides were evaluated by 1D SDS-PAGE, in-gel digestion, and label-free nano-LC/MS to compare normal controls with breast cancer patients. Plasma levels of the ApoE protein did not significantly differ between normal controls and breast cancer patients. Eleven sites with novel PTMs were identified from 7 pairs of differentially expressed targeted and modified peptides according to the relative modification ratio including methylation at the E3 (↑1.45-fold), E7 (↑1.45-fold), E11 (↑1.19-fold), E77 (↑2.02-fold), E87 (↑2.02-fold), and Q98 (↑1.62-fold) residues; dimethylation at the Q187 (↑1.44-fold) residue; dihydroxylation at the R92 (↑1.25-fold), K95 (↑1.25-fold), and R103 (↑1.25-fold) residues; and glycosylation at the S129 (↑1.14-fold) residue. The clustered methylation and dihydroxylation of plasma ApoE proteins may play a role in breast cancer.

The proteome of schizophrenia

On observing schizophrenia from a clinical point of view up to its molecular basis, one may conclude that this is likely to be one of the most complex human disorders to be characterized in all aspects. Such complexity is the reflex of an intricate combination of genetic and environmental components that influence brain functions since pre-natal neurodevelopment, passing by brain maturation, up to the onset of disease and disease establishment. The perfect function of tissues, organs, systems, and finally the organism depends heavily on the proper functioning of cells. Several lines of evidence, including genetics, genomics, transcriptomics, neuropathology, and pharmacology, have supported the idea that dysfunctional cells are causative to schizophrenia. Together with the above-mentioned techniques, proteomics have been contributing to understanding the biochemical basis of schizophrenia at the cellular and tissue level through the identification of differentially expressed proteins and consequently their biochemical pathways, mostly in the brain tissue but also in other cells. In addition, mass spectrometry-based proteomics have identified and precisely quantified proteins that may serve as biomarker candidates to prognosis, diagnosis, and medication monitoring in peripheral tissue. Here, we review all data produced by proteomic investigation in the last 5 years using tissue and/or cells from schizophrenic patients, focusing on postmortem brain tissue and peripheral blood serum and plasma. This information has provided integrated pictures of the biochemical systems involved in the pathobiology, and has suggested potential biomarkers, and warrant potential targets to alternative treatment therapies to schizophrenia.

Transcriptome alterations of mitochondrial and coagulation function in schizophrenia by cortical sequencing analysis

Background

Transcriptome sequencing of brain samples provides detailed enrichment analysis of differential expression and genetic interactions for evaluation of mitochondrial and coagulation function of schizophrenia. It is implicated that schizophrenia genetic and protein interactions may give rise to biological dysfunction of energy metabolism and hemostasis. These findings may explain the biological mechanisms responsible for negative and withdraw symptoms of schizophrenia and antipsychotic-induced venous thromboembolism.

We conducted a comparison of schizophrenic candidate genes from literature reviews and constructed the schizophrenia-mediator network (SCZMN) which consists of schizophrenic candidate genes and associated mediator genes by applying differential expression analysis to BA22 RNA-Seq brain data. The network was searched against pathway databases such as PID, Reactome, HumanCyc, and Cell-Map. The candidate complexes were identified by MCL clustering using CORUM for potential pathogenesis of schizophrenia.

Results

Published BA22 RNA-Seq brain data of 9 schizophrenic patients and 9 controls samples were analyzed. The differentially expressed genes in the BA22 brain samples of schizophrenia are proposed as schizophrenia candidate marker genes (SCZCGs). The genetic interactions between mitochondrial genes and many under-expressed SCZCGs indicate the genetic predisposition of mitochondria dysfunction in schizophrenia. The biological functions of SCZCGs, as listed in the Pathway Interaction Database (PID), indicate that these genes have roles in DNA binding transcription factor, signal and cancer-related pathways, coagulation and cell cycle regulation and differentiation pathways.

In the query-query protein-protein interaction (QQPPI) network of SCZCGs, TP53, PRKACA, STAT3 and SP1 were identified as the central "hub" genes. Mitochondrial function was modulated by dopamine inhibition of respiratory complex I activity. The genetic interaction between mitochondria function and schizophrenia may be revealed by DRD2 linked to NDUFS7 through protein-protein interactions of FLNA and ARRB2.

The biological mechanism of signaling pathway of coagulation cascade was illustrated by the PPI network of the SCZCGs and the coagulation-associated genes. The relationship between antipsychotic target genes (DRD2/3 and HTR2A) and coagulation factor genes (F3, F7 and F10) appeared to cascade the following hemostatic process implicating the bottleneck of coagulation genetic network by the bridging of actin-binding protein (FLNA).

Conclusions

It is implicated that the energy metabolism and hemostatic process have important roles in the pathogenesis for schizophrenia. The cross-talk of genetic interaction by these co-expressed genes and reached candidate genes may address the key network in disease pathology. The accuracy of candidate genes evaluated from different quantification tools could be improved by crosstalk analysis of overlapping genes in genetic networks.

Variation and quantification among a target set of phosphopeptides in human plasma by multiple reaction monitoring and SWATH-MS2 data-independent acquisition

Human plasma contains proteins that reflect overall health and represents a rich source of proteins for identifying and understanding disease pathophysiology. However, few studies have investigated changes in plasma phosphoproteins. In addition, little is known about the normal variations in these phosphoproteins, especially with respect to specific sites of modification. To address these questions, we evaluated variability in plasma protein phosphorylation in healthy individuals using multiple reaction monitoring (MRM) and SWATH-MS2 data-independent acquisition. First, we developed a discovery workflow for phosphopeptide enrichment from plasma and identified targets for MRM assays. Next, we analyzed plasma from healthy donors using an analytical workflow consisting of MRM and SWATH-MS2 that targeted phosphopeptides from 58 and 68 phosphoproteins, respectively. These two methods produced similar results showing low variability in 13 phosphosites from 10 phosphoproteins (CVinter < 30%) and high interpersonal variation of 16 phosphosites from 14 phosphoproteins (CVinter > 30%). Moreover, these phosphopeptides originate from phosphoproteins involved in cellular processes governing homeostasis, immune response, cell-extracellular matrix interactions, lipid and sugar metabolism, and cell signaling. This limited assessment of technical and biological variability in phosphopeptides generated from plasma phosphoproteins among healthy volunteers constitutes a reference for future studies that target protein phosphorylation as biomarkers.

Technological advances for deciphering the complexity of psychiatric disorders: merging proteomics with cell biology

Proteomic studies have increased our understanding of the molecular pathways affected in psychiatric disorders. Mass spectrometry and two-dimensional gel electrophoresis analyses of post-mortem brain samples from psychiatric patients have revealed effects on synaptic, cytoskeletal, antioxidant and mitochondrial protein networks. Multiplex immunoassay profiling studies have found alterations in hormones, growth factors, transport and inflammation-related proteins in serum and plasma from living first-onset patients. Despite these advances, there are still difficulties in translating these findings into platforms for improved treatment of patients and for discovery of new drugs with better efficacy and side effect profiles. This review describes how the next phase of proteomic investigations in psychiatry should include stringent replication studies for validation of biomarker candidates and functional follow-up studies which can be used to test the impact on physiological function. All biomarker candidates should now be tested in series with traditional and emerging cell biological approaches. This should include investigations of the effects of post-translational modifications, protein dynamics and network analyses using targeted proteomic approaches. Most importantly, there is still an urgent need for development of disease-relevant cellular models for improved translation of proteomic findings into a means of developing novel drug treatments for patients with these life-altering disorders.

Ecto-protein kinases and phosphatases: an emerging field for translational medicine

Progress in translational research has led to effective new treatments of a large number of diseases. Despite this progress, diseases including cancer and cardiovascular disorders still are at the top in death statistics and disorders such as osteoporosis and osteoarthritis represent an increasing disease burden in the aging population. Novel strategies in research are needed more than ever to overcome such diseases. The growing field of extracellular protein phosphorylation provides excellent opportunities to make major discoveries of disease mechanisms that can lead to novel therapies. Reversible phosphorylation/dephosphorylation of sites in the extracellular domains of matrix, cell-surface and trans-membrane proteins is emerging as a critical regulatory mechanism in health and disease. Moreover, a new concept is emerging from studies of extracellular protein phosphorylation: in cells where ATP is stored within secretory vesicles and released by exocytosis upon cell-stimulation, phosphorylation of extracellular proteins can operate as a messenger operating uniquely in signaling pathways responsible for long-term cellular adaptation. Here, we highlight new concepts that arise from this research, and discuss translation of the findings into clinical applications such as development of diagnostic disease markers and next-generation drugs.

Multiplatform metabolome and proteome profiling identifies serum metabolite and protein signatures as prospective biomarkers for schizophrenia

Schizophrenia is a severe mental illness with a biological basis. However, the search for reliable biomarkers suitable for clinical routine has been futile so far. Accordingly, there is a need for innovative approaches such as genomics and proteomics to achieve this goal. In the present study, we compared metabolomic and proteomic data from 26 schizophrenia patients as well as from unaffected controls carefully matched for age and gender in a multi-platform approach. The combined analysis identified many signatures with initially good biomarker characteristics. After statistical analysis and comparison of these identified serum metabolites (analysed by Gas Chromatography Mass Spectrometry) and hydrophobic serum proteins (analysed by matrix-assisted laser desorption ionisation mass spectrometry), several markers (e.g., 2-piperidinec carboxylic acid, 6-deoxy-mannofuranose, galactoseoxime and a serum peptide of m/z 3177) were determined as having the best discriminating value between the groups. Our findings represent a proof of principle indicating that metabolomic and proteomic approaches can be successfully used in psychiatric biomarker research, even though the results should be regarded as preliminary with a need for replication in larger samples.

The use of proteomic biomarkers for improved diagnosis and stratification of schizophrenia patients

Schizophrenia is characterized by a wide spectrum of clinical manifestations, including strong effects on mood and behavior. Patients can also suffer from serious comorbidities including immune system or metabolic abnormalities. Recent advances using proteomic profiling approaches have increased our understanding of these molecular effects and have laid the groundwork for unraveling the heterogeneity of this broadly defined disease. These findings could lead to improved diagnosis and stratification of patients through identification of biochemically different disease subtypes and personalized medicine approaches. The inclusion of molecular signatures in psychiatry will be an important leap forward in providing more effective treatment of patients suffering from this debilitating disorder.

Recent advances in quantitative neuroproteomics

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.