Synaptosomal Proteome of the Orbitofrontal Cortex from Schizophrenia Patients Using Quantitative Label-Free and iTRAQ-Based Shotgun Proteomics.
Erika VelásquezFabio C S NogueiraIngrid VelásquezAndrea SchmittPeter FalkaiGilberto Barbosa DomontDaniel Martins-de-SouzaPublished in: Journal of proteome research (2017)
Schizophrenia is a chronic and incurable neuropsychiatric disorder that affects about one percent of the world population. The proteomic characterization of the synaptosome fraction of the orbitofrontal cortex is useful for providing valuable information about the molecular mechanisms of synaptic functions in these patients. Quantitative analyses of synaptic proteins were made with eight paranoid schizophrenia patients and a pool of eight healthy controls free of mental diseases. Label-free and iTRAQ labeling identified a total of 2018 protein groups. Statistical analyses revealed 12 and 55 significantly dysregulated proteins by iTRAQ and label-free, respectively. Quantitative proteome analyses showed an imbalance in the calcium signaling pathway and proteins such as reticulon-1 and cytochrome c, related to endoplasmic reticulum stress and programmed cell death. Also, it was found that there is a significant increase in limbic-system-associated membrane protein and α-calcium/calmodulin-dependent protein kinase II, associated with the regulation of human behavior. Our data contribute to a better understanding about apoptosis as a possible pathophysiological mechanism of this disease as well as neural systems supporting social behavior in schizophrenia. This study also is a joint effort of the Chr 15 C-HPP team and the Human Brain Proteome Project of B/D-HPP. All MS proteomics data are deposited in the ProteomeXchange Repository under PXD006798.
Keyphrases
- label free
- end stage renal disease
- endoplasmic reticulum stress
- bipolar disorder
- ejection fraction
- newly diagnosed
- chronic kidney disease
- signaling pathway
- protein kinase
- electronic health record
- multiple sclerosis
- patient reported outcomes
- machine learning
- cell death
- induced apoptosis
- big data
- cell proliferation
- epithelial mesenchymal transition
- deep learning
- small molecule
- ms ms
- artificial intelligence