development-standardization-an-ex-vivo-micromethod-for-intracellular

Development and Standardization of an <em>Ex Vivo</em> Micromethod for Intracellular Quantification of Vincristine in Primary ALL Cells by LC-MS/MS

Quantifying intracellular vincristine (VCR) in primary pediatric acute lymphoblastic leukemia (ALL) cells is essential for understanding sample-specific ...

Boldrini Children's Center

Modeling schizophrenia is challenging due to the uniquely human component of psychiatric disorders. Despite several advances in cellular and animal modeling, postmortem brain tissue derived from patients is still one of the extremely few sources of information that comprises brain complexity, human genetics, and patient experiences. Additionally, postmortem tissue from patients with schizophrenia can be used to drive hypotheses that can then be validated in other models, involving either other animals or an in vitro approach. While evaluating high-throughput and sensitive techniques, shotgun proteomics allows for the identification and quantitation of thousands of proteins present in biological systems. In the context of schizophrenia, proteomics can map differentially regulated proteins throughout brain regions of patients with schizophrenia, generating a large amount of information regarding the disorder's pathophysiology. In this chapter, our aim is to bring the literature up to date regarding proteomics tools applied to postmortem brains from patients with schizophrenia, additionally discussing new findings, roads, and perspectives for the comprehension of this severe disorder.

Postmortem Brains: What Can Proteomics Tell us About the Sources of Schizophrenia?

COVID-19, a complex multisystem disorder affecting the central nervous system, can also have psychiatric sequelae. In addition, clinical evidence indicates that a diagnosis of a schizophrenia spectrum disorder is a risk factor for mortality in patients with COVID-19. In this study, we aimed to explore brain-specific molecular aspects of COVID-19 by using a proteomic approach. We analyzed the brain proteome of fatal COVID-19 cases and compared it with differentially regulated proteins found in postmortem schizophrenia brains. The COVID-19 proteomic dataset revealed a strong enrichment of proteins expressed by glial and neuronal cells and processes related to diseases with a psychiatric and neurodegenerative component. Specifically, the COVID-19 brain proteome enriches processes that are hallmark features of schizophrenia. Furthermore, we identified shared and distinct molecular pathways affected in both conditions. We found that brain ageing processes are likely present in both COVID-19 and schizophrenia, albeit possibly driven by distinct processes. In addition, alterations in brain cell metabolism were observed, with schizophrenia primarily impacting amino acid metabolism and COVID-19 predominantly affecting carbohydrate metabolism. The enrichment of metabolic pathways associated with astrocytic components in both conditions suggests the involvement of this cell type in the pathogenesis. Both COVID-19 and schizophrenia influenced neurotransmitter systems, but with distinct impacts. Future studies exploring the underlying mechanisms linking brain ageing and metabolic dysregulation may provide valuable insights into the complex pathophysiology of these conditions and the increased vulnerability of schizophrenia patients to severe outcomes.

Molecular overlaps of neurological manifestations of COVID-19 and schizophrenia from a proteomic perspective.

Shotgun proteomics analysis presents multifaceted challenges, demanding diverse tool integration for insights. Addressing this complexity, OmicScope emerges as an innovative solution for quantitative proteomics data analysis. Engineered to handle various data formats, it performs data pre-processing - including joining replicates, normalization, data imputation - and conducts differential proteomics analysis for both static and longitudinal experimental designs. Empowered by Enrichr with over 224 databases, OmicScope performs Over Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA). Additionally, its Nebula module facilitates meta-analysis from independent datasets, providing a systems biology approach for enriched insights. Complete with a data visualization toolkit and accessible as Python package and a web application, OmicScope democratizes proteomics analysis, offering an efficient and high-quality pipeline for researchers.

Article	Year
Postmortem Brains: What Can Proteomics Tell us About the Sources of Schizophrenia? Advances in experimental medicine and biology\| PubMed ID: 35930222	2022
Molecular overlaps of neurological manifestations of COVID-19 and schizophrenia from a proteomic perspective. European archives of psychiatry and clinical neuroscience\| PubMed ID: 39028452	2025
OmicScope unravels systems-level insights from quantitative proteomics data. Nature communications\| PubMed ID: 39095347	2024

Guilherme Reis de-Oliveira

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