Gene expression and association analysis of the epithelial membrane protein 1 gene in major depressive disorder in the Japanese population

Mental depression: Relation to different disease status, newer treatments and its association with COVID-19 pandemic (Review)

The present study aimed to review major depression, including its types, epidemiology, association with different diseases status and treatments, as well as its correlation with the current COVID-19 pandemic. Mental depression is a common disorder that affects most individuals at one time or another. During depression, there are changes in mood and behavior, accompanied by feelings of defeat, hopelessness, or even suicidal thoughts. Depression has a direct or indirect relation with a number of other diseases including Alzheimer's disease, stroke, epilepsy, diabetes, cardiovascular disease and cancer. In addition, antidepressant drugs have several side effects including sedation, increased weight, indigestion, sexual dysfunction, or a decrease in blood pressure. Stopping medication may cause a relapse of the symptoms of depression and pose a risk of attempted suicide. The pandemic of COVID-19 has affected the mental health of individuals, including patients, individuals contacting patients and medical staff with a number of mental disorders that may adversely affect the immune ability of their bodies. Some of the drugs currently included in the protocols for treating COVID-19 may negatively affect the mental health of patients. Evidence accumulated over the years indicates that serotonin (5HT) deficiencies and norepinephrine (NE) in the brain can lead to mental depression. Drugs that increase levels of NE and 5HT are commonly used in the treatment of depression. The common reason for mood disorders, including mania and bipolar disease are not clearly understood. It is assumed that hyperactivity in specific parts of the brain and excessive activity of neurotransmitters may be involved. Early diagnosis and developing new treatment strategies are essential for the prevention of the severe consequences of depression. In addition, extensive research should be directed towards the investigation of the mental health disturbances occurring during and/or after COVID-19 infection. This may lead to the incorporation of a suitable antidepressant into the current treatment protocols.

Does refining the phenotype improve replication rates? A review and replication of candidate gene studies on Major Depressive Disorder and Chronic Major Depressive Disorder

Replication has been poor for previously reported candidate genes involved in Major Depressive Disorder (MDD). One possible reason is phenotypic and genetic heterogeneity. The present study replicated genetic associations with MDD as defined in DSM-IV and with a more narrowly defined MDD subtype with a chronic and severe course. We first conducted a systematic review of genetic association studies on MDD published between September 2007 and June 2012 to identify all reported candidate genes. Genetic associations were then tested for all identified single nucleotide polymorphisms (SNPs) and the entire genes using data from the GAIN genome-wide association study (MDD: n = 1,352; chronic MDD subsample: n = 225; controls: n =  1,649). The 1,000 Genomes database was used as reference for imputation. From 157 studies identified inthe literature, 81 studies reported significant associations with MDD, involving 245 polymorphisms in 97 candidate genes, from which we were able to investigate 185 SNPs in 89 genes. We replicated nine candidate SNPs in eight genes for MDD and six in five genes for chronic MDD. However, these were not more than expected by chance. At gene level, we replicated 18 genes for MDD and 17 genes for chronic MDD, both significantly more than expected by chance. We showed that replication rates were improved for MDD compared to a previous, highly similar, replication study based on studies published before 2007. Effect sizes of the SNPs and replication rates of the candidate genes were improved in the chronic subsample compared to the full sample. Nonetheless, replication rates were still poor.

Gene expression: biomarker of antidepressant therapy?

While antidepressant therapy is an essential treatment of major depression, a substantial group of treated patients do not respond to therapy, or suffer from severe side effects. Moreover, the time of onset of the clinical improvement is often delayed. Antidepressants as currently available usually enhance serotonergic, noradrenergic and dopaminergic neurotransmission and may contribute to the inadequate remission rates for major depression. Therefore biomarkers enabling the identification of subgroups of patients and also finding unprecedented targets would provide the basis for personalized medication and thus improve treatment efficacy and reduce side effects. Several pharmacogenetic studies on antidepressant treatment response using single nucleotide polymorphism (SNPs) mapping have been performed but provided only modest findings. Therefore the analysis of gene expression to integrate genomic activity and environmental effects promises a new approach to cope with the complexity of factors influencing antidepressant treatment. Here gene expression studies focusing on candidate genes and genome-wide approaches using RNA derived from peripheral blood cells are reviewed. The most promising findings exist for hypothalamic-pituitary-adrenal (HPA) axis, inflammation and neuroplasticity related genes. However, straightforward translation into tailored treatment is still unlikely. Contradictory results limit the clinical use of the findings. Future studies are necessary, which could include functional analysis and consider gene-environment interactions.

Depression pathogenesis and treatment: what can we learn from blood mRNA expression?

Alterations in several biological systems, including the neuroendocrine and immune systems, have been consistently demonstrated in patients with major depressive disorder. These alterations have been predominantly studied using easily accessible systems such as blood and saliva. In recent years there has been an increasing body of evidence supporting the use of peripheral blood gene expression to investigate the pathogenesis of depression, and to identify relevant biomarkers. In this paper we review the current literature on gene expression alterations in depression, focusing in particular on three important and interlinked biological domains: inflammation, glucocorticoid receptor functionality and neuroplasticity. We also briefly review the few existing transcriptomics studies. Our review summarizes data showing that patients with major depressive disorder exhibit an altered pattern of expression in several genes belonging to these three biological domains when compared with healthy controls. In particular, we show evidence for a pattern of 'state-related' gene expression changes that are normalized either by remission or by antidepressant treatment. Taken together, these findings highlight the use of peripheral blood gene expression as a clinically relevant biomarker approach.

Responder and nonresponder patients exhibit different peripheral transcriptional signatures during major depressive episode

To date, it remains impossible to guarantee that short-term treatment given to a patient suffering from a major depressive episode (MDE) will improve long-term efficacy. Objective biological measurements and biomarkers that could help in predicting the clinical evolution of MDE are still warranted. To better understand the reason nearly half of MDE patients respond poorly to current antidepressive treatments, we examined the gene expression profile of peripheral blood samples collected from 16 severe MDE patients and 13 matched controls. Using a naturalistic and longitudinal design, we ascertained mRNA and microRNA (miRNA) expression at baseline, 2 and 8 weeks later. On a genome-wide scale, we detected transcripts with roles in various biological processes as significantly dysregulated between MDE patients and controls, notably those involved in nucleotide binding and chromatin assembly. We also established putative interactions between dysregulated mRNAs and miRNAs that may contribute to MDE physiopathology. We selected a set of mRNA candidates for quantitative reverse transcriptase PCR (RT-qPCR) to validate that the transcriptional signatures observed in responders is different from nonresponders. Furthermore, we identified a combination of four mRNAs (PPT1, TNF, IL1B and HIST1H1E) that could be predictive of treatment response. Altogether, these results highlight the importance of studies investigating the tight relationship between peripheral transcriptional changes and the dynamic clinical progression of MDE patients to provide biomarkers of MDE evolution and prognosis.