首页|Beijing University of Chinese Medicine Reports Findings in Depression (Identific ation of mitophagy-related genes and analysis of immune infiltration in the astr ocytes based on machine learning in the pathogenesis of major depressive disorde r)
Beijing University of Chinese Medicine Reports Findings in Depression (Identific ation of mitophagy-related genes and analysis of immune infiltration in the astr ocytes based on machine learning in the pathogenesis of major depressive disorde r)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Mental Health Diseases and Conditions - Depression is the subject of a report. According to news repor ting originating in Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Major depressive disorder (MDD) is a pervasive mental and mood disorder with complicated and heterogeneous etiology. Mitophagy, a selective au tophagy of cells, specifically eliminates dysfunctional mitochondria.” The news reporters obtained a quote from the research from the Beijing Universit y of Chinese Medicine, “The mitochondria dysfunction in the astrocytes is regard ed as a critical pathogenetic mechanism of MDD. However, studies on the mitophag y of astrocytes in MDD are scarce. To explore the impact of mitophagy on the ast rocytes, we used bioinformatic methods to analyze the correlation between astroc yte-related genes and mitophagy-related genes in MDD. The microarray dataset of MDD was downloaded from the Gene Expression Omnibus database and identified astr ocyte- and mitophagy-related differentially expressed genes (AMRDEGs). We used t hree machine learning algorithms to identify hub AMRDEGs and constructed a diagn ostic prediction model. Also, we analyzed transcription factor-gene and gene-mic roRNA interaction networks, and the immune infiltration in MDD and healthy contr ols. Besides, we performed consensus clustering analysis, immune infiltration an alysis, and gene set variation analysis of MDD samples. The present research ide ntified 3 hub AMRDEGs (GRN, NDUFAF4, and SNCA), and a good diagnostic model with potential clinical applications was constructed and validated. Besides, we iden tified 6 transcription factors and 14 microRNAs. The immune infiltration analysi s showed that MDD was closely related to immune cells. Gene set variant analysis showed that MDD was related to immune and mitochondrial metabolism and inflamma tory signaling pathways. We identified 3 hub AMRDEGs, new biomarkers for treatin g and diagnosing MDD and associated with immuno-inflammation.”
BeijingPeople’s Republic of ChinaAsi aAstrocytesCyborgsDepressionEmerging TechnologiesGeneticsHealth and MedicineMachine LearningMajor Depressive DisorderMental HealthMental Hea lth Diseases and ConditionsNeuroglia
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