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• W4220671154 endingPage "3873" @default.
• W4220671154 startingPage "3873" @default.
• W4220671154 abstract "Major depressive disorder (MDD) is a life-impairing disorder, and early successful treatment is important for a favorable prognosis. However, early response to antidepressants differs widely among individuals, and is difficult to predict pre-treatment. As miRNAs have been reported to play important roles in depression, identification of miRNAs associated with antidepressant treatment responses and their interacting genes and pathways will be beneficial in understanding the predictors and molecular mechanisms of depression treatment. This randomized control trial examined miRNAs correlated with the early therapeutic effect of selective serotonin reuptake inhibitors (SSRIs; paroxetine or sertraline) and mirtazapine monotherapy. Before medication, we comprehensively analyzed the miRNA expression of 92 depressed participants and identified genes and pathways interacting with miRNAs. A total of 228 miRNAs were significantly correlated with depressive symptoms improvements after 2 weeks of SSRIs treatment, with miR-483.5p showing the most robust correlation. These miRNAs are involved in 21 pathways, including TGF-β, glutamatergic synapse, long-term depression, and the mitogen-activated protein kinase (MAPK) signaling pathways. Using these miRNAs enabled us to predict SSRI response at week 2 with a 57% difference. This study shows that pre-treatment levels of miRNAs could be used to predict early responses to antidepressant administration, a knowledge of genes, and an identification of genes and pathways associated with the antidepressant response." @default.
• W4220671154 created "2022-04-03" @default.
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• W4220671154 date "2022-03-31" @default.
• W4220671154 modified "2023-10-05" @default.
• W4220671154 title "Multiple Pre-Treatment miRNAs Levels in Untreated Major Depressive Disorder Patients Predict Early Response to Antidepressants and Interact with Key Pathways" @default.
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• W4220671154 doi "https://doi.org/10.3390/ijms23073873" @default.
• W4220671154 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35409234" @default.
• W4220671154 hasPublicationYear "2022" @default.
• W4220671154 type Work @default.
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