Application of proteomics in diagnosis of ADHD, schizophrenia, major depression, and suicidal behavior

Systematic Review and Meta-Analysis of Mass Spectrometry Proteomics Applied to Human Peripheral Fluids to Assess Potential Biomarkers of Schizophrenia

Mass spectrometry (MS)-based techniques can be a powerful tool to identify neuropsychiatric disorder biomarkers, improving prediction and diagnosis ability. Here, we evaluate the efficacy of MS proteomics applied to human peripheral fluids of schizophrenia (SCZ) patients to identify disease biomarkers and relevant networks of biological pathways. Following PRISMA guidelines, a search was performed for studies that used MS proteomics approaches to identify proteomic differences between SCZ patients and healthy control groups (PROSPERO database: CRD42021274183). Nineteen articles fulfilled the inclusion criteria, allowing the identification of 217 differentially expressed proteins. Gene ontology analysis identified lipid metabolism, complement and coagulation cascades, and immune response as the main enriched biological pathways. Meta-analysis results suggest the upregulation of FCN3 and downregulation of APO1, APOA2, APOC1, and APOC3 in SCZ patients. Despite the proven ability of MS proteomics to characterize SCZ, several confounding factors contribute to the heterogeneity of the findings. In the future, we encourage the scientific community to perform studies with more extensive sampling and validation cohorts, integrating omics with bioinformatics tools to provide additional comprehension of differentially expressed proteins. The produced information could harbor potential proteomic biomarkers of SCZ, contributing to individualized prognosis and stratification strategies, besides aiding in the differential diagnosis.

The relationship of suicidal ideation with psychological pain and anger rumination in patients with major depressive disorder

OBJECTıVE: The study was conducted to determine the association between ruminating anger and mental pain with suicidal ideation in patients diagnosed with major depression disorder.

METHODS

The study with 156 patients diagnosed with major depressive disorder was carried out in a cross-sectional study design. Personal Information Form, Reflection on Anger Scale, Psychological Pain Scale and Beck Depression Scale were used.

RESULTS

It was concluded that there was a statistically equal directional and linear relationship between the Meebunney and Beck depression scores of all patients diagnosed with a major depressive disorder and the total reflective anger score and its sub-dimensions. Suicidal attempts and psychological pain and depression levels were found to be effective in the increase in suicidal ideation in the patients with major depressive disorder.

CONCLUSIONS

Studies with larger samples are recommended to determine the factors that may pose a risk of suicidal ideation in patients diagnosed with majör depressive disorder.

Alterations in Gene Expression in Depression: Prospects for Personalize Patient Treatment

The number of people around the world suffering from depression has dramatically increased in last few decades. It has been predicted that by 2020 depression will become the second most common cause of disability. Furthermore, depression is often misdiagnosed and confused with other psychiatric disorders showing similar symptoms, i.e., anxiety and bipolar disorder, due to the fact that diagnosing is often carried out by medical workers who are not psychiatrically trained. These facts prompt us to prepare this review which focuses on alterations in gene expression in depression. We believe that an in-depth knowledge of molecular bases of behavior in depression and other mood disorders would be of a great benefit for the correct diagnosing of these disorders, as well as for prescribing a treatment that best suits each individual depending on expression alterations in depression-related genes. Therefore, the main aim of this review is to promote further translational research on the biochemistry of mood disorders and take the results further for the design of new targeted therapeutics that can be used for personalized treatment with minimal adverse effects.