Research code: 0
Ethics code: IR.IAU.K.REC.1403.90
Clinical trials code: 0
Clinical care and Health Promotion Research Center, Karaj Branch, Islamic Azad University, Karaj, Iran , mar.rahimi20@gmail.com
Abstract: (457 Views)
Background and Aims: Psychiatric disorders are typically viewed as neuropsychological and neurobehavioral conditions that impair the ability to comprehend new or complex information. It is estimated that over 450 million people worldwide experience various mental disorders, with major depression anticipated to be the most disabling by 2030. Major depressive disorder (MDD), also known as unipolar disorder, is characterized by prolonged periods of depression across different situations and contexts, low self-esteem, and a lack of interest in activities that are normally enjoyable, lasting for at least two weeks. To diagnose MDD, it is essential to exclude any history of manic or hypomanic episodes. In children and adolescents, MDD may present as irritability. According to the DSM-5, other depressive disorders include persistent depressive disorder (formerly known as dysthymia), disruptive mood dysregulation disorder, premenstrual dysphoric disorder, substance/medication-induced depressive disorder, and depressive disorder due to another medical condition, and unspecified depressive disorder. Depression can impact both mental and physical health. Although the clinical cure rate for MDD is high, the treatment and recurrence rates are less favorable due to patients' lack of understanding and reluctance to adhere to regular treatment.
Globally, major depressive disorder (MDD) is consistently among the most prevalent mental disorders, affecting 322 million people worldwide. The average age of individuals with this disorder is 30.4 years. The prevalence of MDD is twice as high in women compared to men and affects one in six adults over their lifetime. The lifetime prevalence is estimated to be around 10-15%. The World Health Organization predicts that by 2030, MDD will account for 13% of the total global disease burden, surpassing cardiovascular disorders. MDD is a significant cause of suicide and morbidity among adolescents and young adults, making accurate diagnosis and effective care crucial for these age groups.
This disorder can cause significant suffering and poor performance in work, school, and home environments. While antidepressants can treat depression, their effectiveness varies. Most antidepressant medications, which primarily target monoamine pathways, are effective, but over 30% of patients do not achieve remission even after multiple treatment trials. Current interventions for MDD include behavioral activation, Acceptance and Commitment Therapy (ACT), problem-focused therapy, functional analytic psychotherapy, mindfulness-based cognitive therapy, and cognitive-behavioral analytic psychotherapy. Treatment for MDD often requires a combination of antidepressants, antipsychotics, psychotherapy, or electroconvulsive therapy. However, a lack of understanding about MDD or an unwillingness to seek formal treatment can negatively impact recovery rates. The complexity of MDD makes it difficult for most patients to fully understand the disorder.
Major depressive disorder (MDD) is influenced by both hereditary and environmental factors. Genetic contributions to MDD are well-documented through family, twin, and adoption studies. However, high discordance rates in studies of monozygotic twins suggest significant non-genetic influences, such as stressful life events, which can elevate the risk of developing depression. The heritability of MDD is estimated to be between 30% and 50%. The high prevalence, moderate heritability, and polygenic nature of MDD pose significant challenges for genetic mapping compared to other psychiatric disorders.
Environmental factors, such as sexual, physical, or emotional abuse during childhood, are significantly linked to an increased risk of developing MDD. Although no single mechanism can account for all aspects of the disorder, MDD is associated with changes in regional brain volumes, particularly the hippocampus, and functional alterations in brain circuits, including the cognitive control network and the affective-salience network. Additionally, disruptions in key neurobiological stress-responsive systems, such as the hypothalamic-pituitary-adrenal axis and the immune system, are observed in MDD. Treatment primarily involves psychotherapy and pharmacological interventions. For patients with treatment-resistant MDD who do not respond to multiple augmentation or combination therapies, electroconvulsive therapy has the strongest empirical support.
Major depressive disorder (MDD) is a complex, multifactorial disorder likely influenced by numerous individual genetic variations, similar to many other psychiatric disorders. The causes of MDD are intricate and involve a combination of genetic, immune system, and endocrine factors, often triggered by stress-related psychosocial conditions. Acute stress and major depression share similar pathophysiological changes, such as inflammatory states, metabolic alterations, and a prothrombotic state. The roles of genetic and epigenetic factors in the development and progression of MDD have been recognized, with nearly 200 genes associated with the disorder identified so far. By conducting genetic analyses to identify risk types, we can enhance our understanding of MDD's development, potentially leading to better prevention strategies and the creation of newer, more effective treatments.
Psychiatric disorders significantly impact patients' quality of life and impose substantial economic burdens on their families. The considerable phenotypic variability among patients complicates the investigation of their pathogenesis. However, bioinformatics is emerging as a promising tool for diagnosing psychiatric disorders by identifying sensitive biomarkers and exploring related signaling pathways. Bioinformatics studies now facilitate the discovery of key genes associated with diseases like depression. Advances in bioinformatics, coupled with high-throughput assessments of brain and behavior, have provided technologies for rapidly identifying and characterizing the roles of biological systems in behavioral processes. This progress has led to the identification of new molecular targets for research, diagnostics, and therapies. Although much of this research is in its early stages, significant advancements are being made, and practical applications are already emerging. This study utilizes bioinformatics data to investigate the genes contributing to depression. In molecular biology, techniques such as signal processing and 3D imaging generate abundant raw data that can be used for disease diagnosis and treatment. Bioinformatics is also crucial for analyzing gene and protein regulation and expression. By identifying genes that contribute to MDD, rapid and cost-effective computational methods can be employed to diagnose the disorder and develop effective treatment solutions.
Methods: In the present study, microarray was used from the Gene Expression Omnibus (GEO) database on 32 samples, including 10 samples from healthy individuals, 10 samples from patients with MDD and 10 samples from patients diagnosed with MDD but recovered. Data analysis was performed using R software. In addition, inflammation-related genes were extracted from the MSigDB database for further analysis.
Finally, protein-protein interaction (PPI) analysis and hub gene selection were analyzed using Cytoscape software.
Results: In the present study, a total of 1179 genes were identified as DEGs between MDD and healthy subjects, of which 648 were up-regulated and 531 were down-regulated. 18 genes are shared between DEGs and genes related to inflammatory processes, termed inflammation-related DEGs.
This study identified the genes IL-1β (interleukin 1 beta), TLR2 (toll-like receptor 2), IFNAR2 (interferon alpha and beta receptor subunit 1), TLR1 (toll-like receptor 1) and C5AR1 (complement receptor 1 C5a) as key genes in major depressive disorder.
Conclusion: This study had limitations such as lack of access to other databases and the inability to cite some articles. It is suggested that clinical and laboratory studies be carried out to confirm and complete the present study and to use this information for better diagnosis and treatment of this disorder. The key genes obtained by analysing the data in the present study provide important information for revealing the molecular mechanism and targeted treatment of depression disorder, and in the future, with more studies, the aforementioned genes can be used in the diagnosis and correct treatment of this disease. However, depression is still a major public health problem and governments should support the necessary research to develop interventions and better prevention and treatment.
Globally, major depressive disorder (MDD) is consistently among the most prevalent mental disorders, affecting 322 million people worldwide. The average age of individuals with this disorder is 30.4 years. The prevalence of MDD is twice as high in women compared to men and affects one in six adults over their lifetime. The lifetime prevalence is estimated to be around 10-15%. The World Health Organization predicts that by 2030, MDD will account for 13% of the total global disease burden, surpassing cardiovascular disorders. MDD is a significant cause of suicide and morbidity among adolescents and young adults, making accurate diagnosis and effective care crucial for these age groups.
This disorder can cause significant suffering and poor performance in work, school, and home environments. While antidepressants can treat depression, their effectiveness varies. Most antidepressant medications, which primarily target monoamine pathways, are effective, but over 30% of patients do not achieve remission even after multiple treatment trials. Current interventions for MDD include behavioral activation, Acceptance and Commitment Therapy (ACT), problem-focused therapy, functional analytic psychotherapy, mindfulness-based cognitive therapy, and cognitive-behavioral analytic psychotherapy. Treatment for MDD often requires a combination of antidepressants, antipsychotics, psychotherapy, or electroconvulsive therapy. However, a lack of understanding about MDD or an unwillingness to seek formal treatment can negatively impact recovery rates. The complexity of MDD makes it difficult for most patients to fully understand the disorder.
Major depressive disorder (MDD) is influenced by both hereditary and environmental factors. Genetic contributions to MDD are well-documented through family, twin, and adoption studies. However, high discordance rates in studies of monozygotic twins suggest significant non-genetic influences, such as stressful life events, which can elevate the risk of developing depression. The heritability of MDD is estimated to be between 30% and 50%. The high prevalence, moderate heritability, and polygenic nature of MDD pose significant challenges for genetic mapping compared to other psychiatric disorders.
Environmental factors, such as sexual, physical, or emotional abuse during childhood, are significantly linked to an increased risk of developing MDD. Although no single mechanism can account for all aspects of the disorder, MDD is associated with changes in regional brain volumes, particularly the hippocampus, and functional alterations in brain circuits, including the cognitive control network and the affective-salience network. Additionally, disruptions in key neurobiological stress-responsive systems, such as the hypothalamic-pituitary-adrenal axis and the immune system, are observed in MDD. Treatment primarily involves psychotherapy and pharmacological interventions. For patients with treatment-resistant MDD who do not respond to multiple augmentation or combination therapies, electroconvulsive therapy has the strongest empirical support.
Major depressive disorder (MDD) is a complex, multifactorial disorder likely influenced by numerous individual genetic variations, similar to many other psychiatric disorders. The causes of MDD are intricate and involve a combination of genetic, immune system, and endocrine factors, often triggered by stress-related psychosocial conditions. Acute stress and major depression share similar pathophysiological changes, such as inflammatory states, metabolic alterations, and a prothrombotic state. The roles of genetic and epigenetic factors in the development and progression of MDD have been recognized, with nearly 200 genes associated with the disorder identified so far. By conducting genetic analyses to identify risk types, we can enhance our understanding of MDD's development, potentially leading to better prevention strategies and the creation of newer, more effective treatments.
Psychiatric disorders significantly impact patients' quality of life and impose substantial economic burdens on their families. The considerable phenotypic variability among patients complicates the investigation of their pathogenesis. However, bioinformatics is emerging as a promising tool for diagnosing psychiatric disorders by identifying sensitive biomarkers and exploring related signaling pathways. Bioinformatics studies now facilitate the discovery of key genes associated with diseases like depression. Advances in bioinformatics, coupled with high-throughput assessments of brain and behavior, have provided technologies for rapidly identifying and characterizing the roles of biological systems in behavioral processes. This progress has led to the identification of new molecular targets for research, diagnostics, and therapies. Although much of this research is in its early stages, significant advancements are being made, and practical applications are already emerging. This study utilizes bioinformatics data to investigate the genes contributing to depression. In molecular biology, techniques such as signal processing and 3D imaging generate abundant raw data that can be used for disease diagnosis and treatment. Bioinformatics is also crucial for analyzing gene and protein regulation and expression. By identifying genes that contribute to MDD, rapid and cost-effective computational methods can be employed to diagnose the disorder and develop effective treatment solutions.
Methods: In the present study, microarray was used from the Gene Expression Omnibus (GEO) database on 32 samples, including 10 samples from healthy individuals, 10 samples from patients with MDD and 10 samples from patients diagnosed with MDD but recovered. Data analysis was performed using R software. In addition, inflammation-related genes were extracted from the MSigDB database for further analysis.
Finally, protein-protein interaction (PPI) analysis and hub gene selection were analyzed using Cytoscape software.
Results: In the present study, a total of 1179 genes were identified as DEGs between MDD and healthy subjects, of which 648 were up-regulated and 531 were down-regulated. 18 genes are shared between DEGs and genes related to inflammatory processes, termed inflammation-related DEGs.
This study identified the genes IL-1β (interleukin 1 beta), TLR2 (toll-like receptor 2), IFNAR2 (interferon alpha and beta receptor subunit 1), TLR1 (toll-like receptor 1) and C5AR1 (complement receptor 1 C5a) as key genes in major depressive disorder.
Conclusion: This study had limitations such as lack of access to other databases and the inability to cite some articles. It is suggested that clinical and laboratory studies be carried out to confirm and complete the present study and to use this information for better diagnosis and treatment of this disorder. The key genes obtained by analysing the data in the present study provide important information for revealing the molecular mechanism and targeted treatment of depression disorder, and in the future, with more studies, the aforementioned genes can be used in the diagnosis and correct treatment of this disease. However, depression is still a major public health problem and governments should support the necessary research to develop interventions and better prevention and treatment.
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