Identification of diagnostic markers for major depressive disorder by cross-validation of data from whole blood samples

Identification and Analyses of Crucial Genes Associated with Pathogenesis of Major Depressive Disorder

Background

Major depressive disorder is a debilitating mental condition that causes severe disability leading to a high fatality rate. No valid blood-based biomarkers for major depressive disorder are currently available. The purpose of this research is to investigate gene biomarkers and pathways that may be linked to major depressive disorder pathogenesis.

Methods

Two microarray databases were retrieved from Gene Expression Omnibus for screening of candidate differentially expressed genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed followed by protein-protein interaction network of differentially expressed genes.

Results

About 1181 differentially expressed genes were identified from the microarray databases. Gene Ontology analyses indicated that these differentially expressed genes were significantly enriched in mRNA splicing via spliceosome, neutrophil degranulation, peptide antigen assembly with MHC class II protein complex, and immunoglobulin production-mediated immune response. The most enriched Kyoto Encyclopedia of Genes and Genomes pathway terms of the 10 significant were Hematopoietic cell lineage. About 20 genes were identified as hub genes after pathway analyses, mostly involved in colorectal cancer and the composition of ribosomes and protein processing, including KRAS, CD86, RPL9, RPL3, and RPL18.

Conclusion

New candidate genes have been identified using bioinformatic approaches that suggest their involvement in the pathogenesis of major depressive disorder and serve as potential genetic diagnostic markers as well as new therapeutic targets.

EEG alpha band characteristics in patients with a depressive episode within recurrent and bipolar depression

BACKGROUND

The search for biological markers for the differential diagnosis of recurrent depression and bipolar depression is an important undertaking in modern psychiatry. Electroencephalography (EEG) is one of the promising tools in addressing this challenge.

AIM

To identify differences in the quantitative characteristics of the electroencephalographic alpha band activity in patients with a depressive episode within the framework of recurrent depression and bipolar depression.

METHODS

Two groups of patients (all women) were formed: one consisting of subjects with recurrent depressive disorder and one with subjects experiencing a current mild/moderate episode (30 patients), and subjects with bipolar affective disorder or a current episode of mild or moderate depression (30 patients). The groups did not receive pharmacotherapy and did not differ in their socio-demographic parameters or total score on the Hamilton depression scale. A baseline electroencephalogram was recorded, and the quantitative characteristics of the alpha band activity were analyzed, including the absolute spectral power, interhemispheric coherence, and EEG activation.

RESULTS

The patients with recurrent depressive disorder demonstrated statistically significantly lower values of the average absolute spectral power of the alpha band (z=2.481; p=0.042), as well as less alpha attenuation from eyes closed to eyes open (z=2.573; p=0.035), as compared with the patients with bipolar affective disorder.

CONCLUSION

The presented quantitative characteristics of alpha activity are confirmation that patients with affective disorders of different origins also display distinctive electrophysiological features which can become promising biomarkers and could help separate bipolar depression from the recurrent type.

The Complexity and Multiplicity of the Specific cAMP Phosphodiesterase Family: PDE4, Open New Adapted Therapeutic Approaches

Cyclic nucleotides (cAMP, cGMP) play a major role in normal and pathologic signaling. Beyond receptors, cyclic nucleotide phosphodiesterases; (PDEs) rapidly convert the cyclic nucleotide in its respective 5′-nucleotide to control intracellular cAMP and/or cGMP levels to maintain a normal physiological state. However, in many pathologies, dysregulations of various PDEs (PDE1-PDE11) contribute mainly to organs and tissue failures related to uncontrolled phosphorylation cascade. Among these, PDE4 represents the greatest family, since it is constituted by 4 genes with multiple variants differently distributed at tissue, cellular and subcellular levels, allowing different fine-tuned regulations. Since the 1980s, pharmaceutical companies have developed PDE4 inhibitors (PDE4-I) to overcome cardiovascular diseases. Since, they have encountered many undesired problems, (emesis), they focused their research on other PDEs. Today, increases in the knowledge of complex PDE4 regulations in various tissues and pathologies, and the evolution in drug design, resulted in a renewal of PDE4-I development. The present review describes the recent PDE4-I development targeting cardiovascular diseases, obesity, diabetes, ulcerative colitis, and Crohn’s disease, malignancies, fatty liver disease, osteoporosis, depression, as well as COVID-19. Today, the direct therapeutic approach of PDE4 is extended by developing allosteric inhibitors and protein/protein interactions allowing to act on the PDE interactome.

Brain differential gene expression and blood cross-validation of a molecular signature of patients with major depressive disorder

INTRODUCTION

The agreement between clinicians diagnosing major depressive disorder (MDD) is poor. The objective of this study was to identify a reproducible and robust gene expression marker capable of differentiating MDD from healthy control (HC) subjects.

MATERIALS AND METHODS

Brain and blood gene expression datasets were searched, which included subjects with MDD and HC. The largest database including different areas of brain samples (GSE80655) was used to identify an initial gene expression marker. Tests of robustness and reproducibility were then implemented in 13 brain and 7 blood independent datasets. Correlations between expression in brain and blood samples were also examined. Finally, an enrichment analysis to explore the marker biological meaning was completed.

RESULTS

Twenty-eight genes were differentially expressed in GSE80655, of which 23 were critical to differentiate MDD from HC. The accuracy obtained using the 23 genes was 0.77 and 0.8, before and after the forward selection model, respectively. The gene marker's robustness and reproducibility were between the range of 0.46 and 0.63 in the other brain datasets and between 0.45 and 0.78 for the blood datasets. Brain and blood expression tended to correlate in some samples. Thirteen of the 23 genes were related to stress and immune response.

CONCLUSION

A 23 gene expression marker was able to distinguish subjects with MDD from HC, with adequate reproducibility and low robustness in the independent databases investigated. This gene set was similarly expressed in the brain and blood and involved genes related to stress and immune response.

The Role of Mitochondria in Mood Disorders: From Physiology to Pathophysiology and to Treatment

Mitochondria are cellular organelles involved in several biological processes, especially in energy production. Several studies have found a relationship between mitochondrial dysfunction and mood disorders, such as major depressive disorder and bipolar disorder. Impairments in energy production are found in these disorders together with higher levels of oxidative stress. Recently, many agents capable of enhancing antioxidant defenses or mitochondrial functioning have been studied for the treatment of mood disorders as adjuvant therapy to current pharmacological treatments. A better knowledge of mitochondrial physiology and pathophysiology might allow the identification of new therapeutic targets and the development and study of novel effective therapies to treat these specific mitochondrial impairments. This could be especially beneficial for treatment-resistant patients. In this article, we provide a focused narrative review of the currently available evidence supporting the involvement of mitochondrial dysfunction in mood disorders, the effects of current therapies on mitochondrial functions, and novel targeted therapies acting on mitochondrial pathways that might be useful for the treatment of mood disorders.

Stanniocalcin-1 Overexpression Prevents Depression-Like Behaviors Through Inhibition of the ROS/NF-κB Signaling Pathway

Background: Depression is a burdensome psychiatric disorder presenting with disordered inflammation and neural plasticity. We conducted this study with an aim to explore the effect of stanniocalcin-1 (STC1) on inflammation and neuron injury in rats with depression-like behaviors. Methods: A model of depression-like behaviors was established in Wistar rats by stress stimulation. Adeno-associated virus (AAV)-packaged STC1 overexpression sequence or siRNA against STC1 was introduced into rats to enhance or silence the STC1 expression. Moreover, we measured pro-inflammatory and anti-inflammatory proteins, superoxide dismutase (SOD), catalase (CAT), malondialdehyde (MDA) and reactive oxygen species (ROS) production. An in vitro model was induced in hippocampal neurons by CORT to explore the effect of STC1 on the neuron viability, toxicity and apoptosis. RT-qPCR and Western blot assay were employed to determine the expression of STC1 and nuclear factor κB (NF-κB) signaling pathway-related genes. Results: STC1 was under-expressed in the hippocampus of rats with depression-like behaviors, while its overexpression could reduce the depression-like behaviors in the stress-stimulated rats. Furthermore, overexpression of STC1 resulted in enhanced neural plasticity, reduced release of pro-inflammatory proteins, elevated SOD and CAT and diminished MDA level in the hippocampus of rats with depression-like behaviors. Overexpressed STC1 blocked the ROS/NF-κB signaling pathway, thereby enhancing the viability of CORT-treated neurons while repressing their toxicity and apoptosis. Conclusion: Collectively, overexpression of STC1 inhibits inflammation and protects neuron injury in rats with depression-like behaviors by inactivating the ROS/NF-κB signaling pathway.

Dissecting major depression: The role of blood biomarkers and adverse childhood experiences in distinguishing clinical subgroups

BACKGROUND

The syndromic diagnosis of major depressive disorder (MDD) is associated with individual differences in prognosis, course, treatment response, and outcome. There is evidence that patients with a history to adverse childhood experiences (ACEs) may belong to a distinct clinical subgroup. The combination of data on ACEs and blood biomarkers could allow the identification of diagnostic MDD subgroups.

METHODS

We selected several blood markers (global DNA methylation, and VEGF-a, TOLLIP, SIRT1, miR-34a genes) among factors that contribute to the pathogenetic mechanisms of MDD. We examined their level in 37 MDD patients and 30 healthy subjects. ACEs were measured by the Parental Bonding Instrument and the Childhood Trauma Questionnaire.

RESULTS

We found significant differences between patients and healthy subjects in three biomarkers (TOLLIP, VEGF-a, and global DNA methylation), independently from the confounding effect of parental care received. By contrast, SIRT1 differences were modulated by quality of parental care. The lowest levels of SIRT1 were recorded in patients with active symptoms and low maternal/paternal care. miR-34a and SIRT1 levels were associated with MDD symptoms especially in early-life stressed patients.

LIMITATIONS

Small sample size, no information on personality comorbidity and suicidal history, cross-sectional definition of remission, and lack of follow-up.

CONCLUSIONS

Our findings suggest that the levels of global DNA methylation, TOLLIP, and VEGF-a reflect pathophysiological changes associated with MDD that are independent from the long-term effects of low parental care. This study also suggests that SIRT1 may be an additional variable distinguishing the ecophenotype that includes MDD patients with exposure to ACEs.

MCM2 and NUSAP1 Are Potential Biomarkers for the Diagnosis and Prognosis of Pancreatic Cancer

Pancreatic cancer (PC) is one of the most malignant tumors. Despite considerable progress in the treatment of PC, the prognosis of patients with PC is poor. The aim of this study was to identify potential biomarkers for the diagnosis and prognosis of PC. First, the original data of three independent mRNA expression datasets were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases and screened for differentially expressed genes (DEGs) using the R software. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the DEGs were performed, and a protein-protein interaction (PPI) network was constructed to screen for hub genes. The hub genes were analyzed for genetic variations, as well as for survival, prognostic, and diagnostic value, using the cBioPortal and Gene Expression Profiling Interactive Analysis (GEPIA) databases and the pROC package. After screening for potential biomarkers, the mRNA and protein levels of the biomarkers were verified at the tissue and cellular levels using the Cancer Cell Line Encyclopedia, GEPIA, and the Human Protein Atlas. As a result, a total of 248 DEGs were identified. The GO terms enriched in DEGs were related to the separation of mitotic sister chromatids and the binding of the spindle to the extracellular matrix. The enriched pathways were associated with focal adhesion, ECM-receptor interaction, and phosphatidylinositol 3-kinase (PI3K)/AKT signaling. The top 20 genes were selected from the PPI network as hub genes, and based on the analysis of multiple databases, MCM2 and NUSAP1 were identified as potential biomarkers for the diagnosis and prognosis of PC. In conclusion, our results show that MCM2 and NUSAP1 can be used as potential biomarkers for the diagnosis and prognosis of PC. The study also provides new insights into the underlying molecular mechanisms of PC.

Protein Kinase A Is Involved in Neuropathic Pain by Activating the p38MAPK Pathway to Mediate Spinal Cord Cell Apoptosis

Neuropathic pain is a serious clinical problem to be solved. This study is aimed at investigating protein kinase A (PKA) expression in neuropathic pain and its possible mechanisms of involvement. A neuropathic pain-related gene expression dataset was downloaded from Gene Expression Omnibus, and differentially expressed genes were screened using the R software. cytoHubba was used to screen for hub genes. A spared nerve injury (SNI) rat model was established, and the paw withdrawal threshold was determined using von Frey filaments. Western blotting and immunofluorescence were used to detect the expression and cellular localization, respectively, of key proteins in the spinal cord. Western blot, ELISA, and TUNEL assays were used to detect cell signal transduction, inflammation, and apoptosis, respectively. Pka was identified as a key gene involved in neuropathic pain. After SNI, mechanical allodynia occurred, PKA expression in the spinal cord increased, the p38MAPK pathway was activated, and spinal cord inflammation and apoptosis occurred in rats. PKA colocalized with neurons, astrocytes, and microglia, and apoptotic cells were mainly neurons. Intrathecal injection of a PKA inhibitor not only relieved mechanical hyperalgesia, inflammatory reaction, and apoptosis in SNI rats but also inhibited p38MAPK pathway activation. However, intrathecal injection of a p38MAPK inhibitor attenuated mechanical hyperalgesia, inflammation, and apoptosis, but did not affect PKA expression. In conclusion, PKA is involved in neuropathic pain by activating the p38MAPK pathway to mediate spinal cord cell apoptosis.

Weighted Gene Coexpression Network Analysis Identifies Specific Modules and Hub Genes Related to Major Depression

PURPOSE

Despite advances in characterizing the neurobiology of emotional disorders, there is still a significant lack of scientific understanding of the pathophysiological mechanisms governing major depressive disorder (MDD). This study attempted to elucidate the molecular circuitry of MDD and to identify more potential genes associated with the pathogenesis of the disease.

PATIENTS AND METHODS

Microarray data from the GSE98793 dataset were downloaded from the NCBI Gene Expression Omnibus (GEO) database, including 128 patients with MDD and 64 healthy controls. Weighted gene coexpression network analysis (WGCNA) was performed to find modules of differentially expressed genes (DEGs) with high correlations followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to obtain further biological insight into the top three key modules. The protein-protein interaction (PPI) network, the modules from the PPI network, and the gene annotation enrichment of modules were analyzed, as well.

RESULTS

We filtered 3276 genes that were considered significant DEGs for further WGCNA analysis. By performing WGCNA, we found that the turquoise, blue and brown functional modules were all strongly correlated with MDD development, including immune response, neutrophil degranulation, ribosome biogenesis, T cell activation, glycosaminoglycan biosynthetic process, and protein serine/threonine kinase activator activity. Hub genes were identified in the key functional modules that might have a role in the progression of MDD. Functional annotation showed that these modules primarily enriched such KEGG pathways as the TNF signaling pathway, T cell receptor signaling pathway, primary immunodeficiency, Th1, Th2 and Th17 cell differentiation, autophagy and RNA degradation and oxidative phosphorylation. These results suggest that these genes are closely related to autophagy and cellular immune function.

CONCLUSION

The results of this study may help to elucidate the pathophysiology of MDD development at the molecular level and explore the potential molecular mechanisms for new interventional strategies.