Giuseppina Maccarrone

Prefrontal cortex shotgun proteome analysis reveals altered calcium homeostasis and immune system imbalance in schizophrenia

Schizophrenia is a complex disease, likely to be caused by a combination of serial alterations in a number of genes and environmental factors. The dorsolateral prefrontal cortex (Brodmanns Area 46) is involved in schizophrenia and executes high-level functions such as working memory, differentiation of conflicting thoughts, determination of right and wrong concepts and attitudes, correct social behavior and personality expression. Global proteomic analysis of post-mortem dorsolateral prefrontal cortex samples from schizophrenia patients and non-schizophrenic individuals was performed using stable isotope labeling and shotgun proteomics. The analysis resulted in the identification of 1,261 proteins, 84 of which showed statistically significant differential expression, reinforcing previous data supporting the involvement of the immune system, calcium homeostasis, cytoskeleton assembly, and energy metabolism in schizophrenia. In addition a number of new potential markers were found that may contribute to the understanding of the pathogenesis of this complex disease.

Alterations in oligodendrocyte proteins, calcium homeostasis and new potential markers in schizophrenia anterior temporal lobe are revealed by shotgun proteome analysis

Global proteomic analysis of post-mortem anterior temporal lobe samples from schizophrenia patients and non-schizophrenia individuals was performed using stable isotope labeling and shotgun proteomics. Our analysis resulted in the identification of 479 proteins, 37 of which showed statistically significant differential expression. Pathways affected by differential protein expression include transport, signal transduction, energy pathways, cell growth and maintenance and protein metabolism. The collection of protein alterations identified here reinforces the importance of myelin/oligodendrocyte and calcium homeostasis in schizophrenia, and reveals a number of new potential markers that may contribute to the understanding of the pathogenesis of this complex disease.

Proteome analysis of the thalamus and cerebrospinal fluid reveals glycolysis dysfunction and potential biomarkers candidates for schizophrenia

Schizophrenia (SCZ) is the result of DNA alterations and environmental factors, which together lead to differential protein expression and ultimately to the development of the illness. The diagnosis is based on clinical symptoms, and the molecular background of SCZ is not completely understood. The thalamus, whose dysfunction has been associated with SCZ based in diverse lines of evidences, plays for instance a pivotal role in the central nervous system as a relay center by re-distributing auditory and visual stimuli from diverse brain regions to the cerebral cortex. We analyzed the proteome of postmortem mediodorsal thalamus (MDT) samples from 11 SCZ patients and 8 non-SCZ individuals by using quantitative shotgun-mass spectrometry and two-dimensional gel electrophoresis. Our analyses identified 551 proteins, 50 of which showed significant differential expression. The main pathways affected by the differentially expressed proteins include energy metabolism, oligodendrocyte metabolism, and cytoskeleton assembly. The potential protein biomarkers candidates myelin basic protein and myelin oligodendrocyte protein were validated by Western blot in the MDT samples and also in cerebrospinal fluid from a separate set of samples of 17 first-episode SCZ patients and 10 healthy controls. The differential expression of μ-crystallin, protein kinase C-gamma, and glial fibrillary acidic protein were confirmed in MDT. Because we found several glycolysis enzymes to be differentially expressed, we measured the levels of pyruvate and NADPH and found them to be altered in MDT. The protein changes described here corroborate the importance of myelin/oligodendrocyte and energy metabolism in SCZ and highlight new potential biomarkers candidates that may contribute to the understanding of the pathogenesis of this complex disease.

MALDI Imaging Identifies Prognostic Seven-Protein Signature of Novel Tissue Markers in Intestinal-Type Gastric Cancer

Proteomics-based approaches allow us to investigate the biology of cancer beyond genomic initiatives. We used histology-based matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry to identify proteins that predict disease outcome in gastric cancer after surgical resection. A total of 181 intestinal-type primary resected gastric cancer tissues from two independent patient cohorts were analyzed. Protein profiles of the discovery cohort (n = 63) were directly obtained from tumor tissue sections by MALDI imaging. A seven-protein signature was associated with an unfavorable overall survival independent of major clinical covariates. The prognostic significance of three individual proteins identified (CRIP1, HNP-1, and S100-A6) was validated immunohistochemically on tissue microarrays of an independent validation cohort (n = 118). Whereas HNP-1 and S100-A6 were found to further subdivide early-stage (Union Internationale Contre le Cancer [UICC]-I) and late-stage (UICC II and III) cancer patients into different prognostic groups, CRIP1, a protein previously unknown in gastric cancer, was confirmed as a novel and independent prognostic factor for all patients in the validation cohort. The protein pattern described here serves as a new independent indicator of patient survival complementing the previously known clinical parameters in terms of prognostic relevance. These results show that this tissue-based proteomic approach may provide clinically relevant information that might be beneficial in improving risk stratification for gastric cancer patients.

Proteomics and Metabolomics Analysis of a Trait Anxiety Mouse Model Reveals Divergent Mitochondrial Pathways

BACKGROUND Although anxiety disorders are the most prevalent psychiatric disorders, no molecular biomarkers exist for their premorbid diagnosis, accurate patient subcategorization, or treatment efficacy prediction. To unravel the neurobiological underpinnings and identify candidate biomarkers and affected pathways for anxiety disorders, we interrogated the mouse model of high anxiety-related behavior (HAB), normal anxiety-related behavior (NAB), and low anxiety-related behavior (LAB) employing a quantitative proteomics and metabolomics discovery approach. METHODS We compared the cingulate cortex synaptosome proteomes of HAB and LAB mice by in vivo (15)N metabolic labeling and mass spectrometry and quantified the cingulate cortex metabolomes of HAB/NAB/LAB mice. The combined data sets were used to identify divergent protein and metabolite networks by in silico pathway analysis. Selected differentially expressed proteins and affected pathways were validated with immunochemical and enzymatic assays. RESULTS Altered levels of up to 300 proteins and metabolites were found between HAB and LAB mice. Our data reveal alterations in energy metabolism, mitochondrial import and transport, oxidative stress, and neurotransmission, implicating a previously nonhighlighted role of mitochondria in modulating anxiety-related behavior. CONCLUSIONS Our results offer insights toward a molecular network of anxiety pathophysiology with a focus on mitochondrial contribution and provide the basis for pinpointing affected pathways in anxiety-related behavior.

Proteome analysis of schizophrenia brain tissue

Abstract Objectives. Proteome analysis has emerged as a promising strategy to the identification of potential biomarkers and to further confirm the importance of certain pathways in the schizophrenia (SCZ) pathophysiology. Reviewing the results of 13 proteome studies in SCZ brain tissue, we aimed to provide information regarding potential proteins biomarkers as well as information about the pathophysiology of the disease. Methods and results. Using two-dimensional gel electrophoresis and shotgun mass spectrometry, 31 proteins were consistently found differentially expressed in the brains of SCZ patients. The most frequent protein alterations reported in SCZ were related to brain energy metabolism, brain plasticity, and synaptic function, processes that are thought to belong to the core of the biology of this disease. The recurrent identification and validation of inter-related protein clusters, determined in different samples and approaches, strongly reinforces the putative involvement of certain pathways in SCZ. Conclusions. The availability of reliable markers not only paves the way to the development of new therapeutic strategies but also points out the possibility of their use as peripheral blood markers that may potentially contribute to the early SCZ detection and early therapeutic intervention, both of which can reduce the social and cognitive consequences of the disease.

MALDI imaging mass spectrometry reveals COX7A2, TAGLN2 and S100-A10 as novel prognostic markers in Barrett's adenocarcinoma.

To characterize proteomic changes found in Barretts adenocarcinoma and its premalignant stages, the proteomic profiles of histologically defined precursor and invasive carcinoma lesions were analyzed by MALDI imaging MS. For a primary proteomic screening, a discovery cohort of 38 fresh frozen Barretts adenocarcinoma patient tissue samples was used. The goal was to find proteins that might be used as markers for monitoring cancer development as well as for predicting regional lymph node metastasis and disease outcome. Using mass spectrometry for protein identification and validating the results by immunohistochemistry on an independent validation set, we could identify two of 60 differentially expressed m/z species between Barretts adenocarcinoma and the precursor lesion: COX7A2 and S100-A10. Furthermore, among 22 m/z species that are differentially expressed in Barretts adenocarcinoma cases with and without regional lymph node metastasis, one was identified as TAGLN2. In the validation set, we found a correlation of the expression levels of COX7A2 and TAGLN2 with a poor prognosis while S100-A10 was confirmed by multivariate analysis as a novel independent prognostic factor in Barretts adenocarcinoma. Our results underscore the high potential of MALDI imaging for revealing new biologically significant molecular details from cancer tissues which might have potential for clinical application. This article is part of a Special Issue entitled: Translational Proteomics.

Proteomic and Metabolomic Profiling of a Trait Anxiety Mouse Model Implicate Affected Pathways

Depression and anxiety disorders affect a great number of people worldwide. Whereas singular factors have been associated with the pathogenesis of psychiatric disorders, growing evidence emphasizes the significance of dysfunctional neural circuits and signaling pathways. Hence, a systems biology approach is required to get a better understanding of psychiatric phenotypes such as depression and anxiety. Furthermore, the availability of biomarkers for these disorders is critical for improved diagnosis and monitoring treatment response. In the present study, a mouse model presenting with robust high versus low anxiety phenotypes was subjected to thorough molecular biomarker and pathway discovery analyses. Reference animals were metabolically labeled with the stable 15N isotope allowing an accurate comparison of protein expression levels between the high anxiety-related behavior versus low anxiety-related behavior mouse lines using quantitative mass spectrometry. Plasma metabolomic analyses identified a number of small molecule biomarkers characteristic for the anxiety phenotype with particular focus on myo-inositol and glutamate as well as the intermediates involved in the tricarboxylic acid cycle. In silico analyses suggested pathways and subnetworks as relevant for the anxiety phenotype. Our data demonstrate that the high anxiety-related behavior and low anxiety-related behavior mouse model is a valuable tool for anxiety disorder drug discovery efforts.

Cerebrospinal Fluid Biomarkers for Major Depression Confirm Relevance of Associated Pathophysiology

Individual characteristics of pathophysiology and course of depressive episodes are at present not considered in diagnostics. There are no biological markers available that can assist in categorizing subtypes of depression and detecting molecular variances related to disease-causing mechanisms between depressed patients. Identification of such differences is important to create patient subgroups, which will benefit from medications that specifically target the pathophysiology underlying their clinical condition. To detect characteristic biological markers for major depression, we analyzed the cerebrospinal fluid (CSF) proteome of depressed vs control persons, using two-dimensional polyacrylamide gel electrophoresis and time-of-flight (TOF) mass spectrometry peptide profiling. Proteins of interest were identified by matrix-assisted laser desorption ionization TOF mass spectrometry (MALDI-TOF-MS). Validation of protein markers was performed by immunoblotting. We found 11 proteins and 144 peptide features that differed significantly between CSF from depressed patients and controls. In addition, we detected differences in the phosphorylation pattern of several CSF proteins. A subset of the differentially expressed proteins implicated in brain metabolism or central nervous system disease was validated by immunoblotting. The identified proteins are involved in neuroprotection and neuronal development, sleep regulation, and amyloid plaque deposition in the aging brain. This is one of the first hypothesis-free studies that identify characteristic protein expression differences in CSF of depressed patients. Proteomic approaches represent a powerful tool for the identification of disease markers for subgroups of patients with major depression.

Profiling of mouse synaptosome proteome and phosphoproteome by IEF

Synapses play important roles in neurotransmission and neuroplasticity. For an in‐depth analysis of the synaptic proteome and phosphoproteome, synaptosomal proteins from whole mouse brain were analyzed by IEF and MS resulting in the largest synaptosome proteome described to date, with 2980 unique proteins identified with two or more peptides. At the same time, 118 synaptosomal phosphoproteins were identified, eight of which are reported for the first time as phosphorylated. Expression of selected proteins in synaptosomes was investigated by Western blot. We demonstrate that IEF is a powerful method to interrogate complex samples such as brain tissue both at the proteome and the phosphoproteome level without the need of additional enrichment for phosphoproteins. The detailed synaptoproteome data set reported here will help to elucidate the molecular complexity of the synapse and contribute to our understanding of synaptic systems biology in health and disease.