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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., Competing Interests: Declarations. Conflict of interest: The authors declare that they have no conflict of interest., (© 2024. Springer-Verlag GmbH Germany, part of Springer Nature.)

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., (© 2024. The Author(s).)

Here, we describe a proteomic pipeline to use a human microglial cell line as a biological model to study schizophrenia. In order to maximize the proteome coverage, we apply two-dimensional liquid chromatography coupled with ultra-definition MS E mass spectrometry (LC-UDMS E ) using a data-independent acquisition (DIA) approach, with an optimization of drift time collision energy.

Here we describe a mass spectrometry-based proteomics workflow to discovery proteins differentially regulated in brains collected postmortem from mental, neurological, or substance abuse disorders (MNS) patients. One way to maximize protein detection is to carry out enrichment of cellular compartments such as the nucleus, mitochondria and cytosol. Subcellular fractionation improves proteome coverage and may shed light on the role of these organelles in the pathophysiology of MNS.

Brain disorders are among the most complex and difficult to understand of human disorders in terms of pathophysiology and etiology. Differently from other human diseases such as cancer, which uses biomarkers in clinical practice, there are no prognostic and diagnostic biomarkers available for psychiatric disorders. Those associated with the likelihood of a successful medication are also not existent, impairing treatment strategies. Proteomics is a suitable tool for identifying such biomarkers to be validated and further implemented in the clinic. Here we present a protocol for the proteome analyses of blood plasma and serum collected in vivo, aiming for the discovery of potential biomarkers and the comprehension of the molecular bases of diseases and treatments.

Psychiatric disorders are one of the biggest burdens to society, with significant personal and economical costs. Schizophrenia (SCZ), among them, is still poorly understood, and its molecular characterization is crucial to improve patients' diagnosis and treatment. The combination of genetic, biochemical, and environmental factors leads to systemic alterations, which are yet to be fully comprehended. Thus, understanding those missing links by connecting some molecular reports of SCZ is essential. From postmortem brain to animal models and cell culture, new tools are emerging, including recent advances in proteomics, and there is a need to apply them to solve these problems. Here, we review some of those features, mainly related to where proteomics could help, and discuss whether those new technologies could and should be applied to psychiatric disorder studies., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)