Vivian Buarque¹, Wanessa dos Santos¹, Talita Laurentino¹, Camila Nascimento¹

Schizophrenia is a complex psychiatric syndrome characterized by symptoms including delusions, hallucinations, and impaired executive functions. Its pathophysiology involves dysregulation of dopaminergic, glutamatergic, and neuroinflammatory systems, along with alterations in synaptic connectivity and myelination. Affecting approximately 0.32% of the global population, it ranks among the leading causes of disability worldwide, with severity ranging from mild to severely debilitating presentations. The heterogeneity of clinical presentations, combined with the lack of objective diagnostic tools, underscores the importance of the search for biomarkers. Untargeted proteomic studies have proven valuable in investigating schizophrenia\'s molecular mechanisms, offering insights into cell signaling cascades, immune dysregulation, and alterations in metabolic pathways, as well as the identification of potential biomarkers, which are often detectable in blood samples. While cerebral alterations such as reduced prefrontal cortex and hippocampal volume are well-established in the disorder, the communication between the brain and peripheral tissues remains poorly understood. Here, we conducted a systematic review and meta-analysis of proteomic profiles from post-mortem prefrontal cortex and blood samples of schizophrenia patients, aiming to identify biomarkers and differentially expressed proteins. The search was conducted across five databases (PubMed, Embase, Scopus, Web of Science, and Semantic Scholar). Focusing on publications between 2019 and 2024, with inclusion criteria comprised mass spectrometry-based proteomic studies of brain or peripheral tissues from patients diagnosed with schizophrenia according to DSM-IV or ICD-10 criteria. Studies using animal models or other biological materials were excluded. As a result, eight studies were selected, including two with brain samples and six with blood samples. Preliminary results include the analysis of three studies–two based on peripheral samples and one on brain-derived data. Raw data was performed using MaxQuant, followed by  differential expression analysis in R software using the DEqMS package. The false discovery rate was controlled using the Benjamini-Hochberg correction. A total of 1,890  differentially expressed proteins in the brain and 193 in blood, when comparing schizophrenia and control samples. A comparative analysis across tissue identified  82 commonly dysregulated proteins. Functional enrichment analysis based on Gene Ontology terms was performed using the WebGestalt tool. Among the enriched biological pathways, the five most significantly enriched biological pathways were: protein-containing complex remodeling, acute inflammatory response, humoral immune response, regulation of response to wounding, and coagulation. Additionally, a protein–protein interaction analysis was performed, demonstrating  strong interconnectivity among the identified proteins (p-value: <1.0e-16). Our preliminary data reinforce the involvement of inflammation in schizophrenia disease, potentially systemic, and highlight the importance of investigating the neuroimmune crosstalk, between the periphery and the brain. These preliminary findings may guide future research, aimed at further elucidating the molecular mechanism of schizophrenia and identifying  potential diagnostic biomarkers and therapeutic targets.

Agradecimentos: I am grateful to FAPESP for the essential financial support that made this study possible. I extend my deepest thanks to my advisor, Camila Nascimento, for her dedicated guidance, continuous encouragement, and valuable contributions throughout all stages of this work. I also thank researchers Wanessa dos Santos and Talita Laurentino for their technical and scientific support, as well as for the constructive discussions throughout the project. This work was only possible thanks to their commitment and to FAPESP's investment in training young researchers and advancing science in the field of mental health.