Dataset Information

Plasma microRNA Array Analysis Identifies Overexpressed miR-19b-3p as a Biomarker of Bipolar Depression Distinguishing From Unipolar Depression.

ABSTRACT: Objectives:The clinical characteristics of bipolar disorder (current major depressive episode) (BD) overlap with unipolar depressive disorder (UD), which makes it difficult to perform an accurate diagnosis. We identified plasma microRNAs (miRNAs) that distinguished BD from UD and explored the relationship between miRNA expression levels and clinical characteristics. Methods:Total miRNAs from blood plasma from seven UD patients, seven BD patients, and six controls were analyzed. The identified miRNAs were validated in a separate population group. Depression severity and early life adversities were assessed. Bioinformatic analysis was conducted to investigate the target genes that were identified and the pathways associated with the altered miRNAs. Results:Compared to controls, 42 miRNAs were differentially expressed in patients. miR-19b-3p, miR-3921, and miR-1180-3p were selected to validate the microarray results. Only miR-19b-3p was validated as down-regulated in patients. The primary predicted genes associated with miR-19b-3p were MAPK1, PTEN, and PRKAA1. The most relevant KEGG pathways included mTOR, FoxO, and the PI3-K/Akt signaling pathway. BD patients were more likely to have higher expression levels of miR-19b-3p and more severe childhood trauma experience compared to UD patients. Conclusions:Plasma miR-19b-3p is a potential non-invasive biomarker that might be useful in distinguishing UD from BD. miR-19b3p was predicted to be involved in the pathway of inflammatory dysregulation associated with experiencing early childhood trauma.

SUBMITTER: Chen Y

PROVIDER: S-EPMC7432143 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Plasma microRNA Array Analysis Identifies Overexpressed miR-19b-3p as a Biomarker of Bipolar Depression Distinguishing From Unipolar Depression.

Chen Yu Y Shi Jiabo J Liu Haiyan H Wang Qiang Q Chen Xiangxiang X Tang Hao H Yan Rui R Yao Zhijian Z Lu Qing Q

Frontiers in psychiatry 20200811

<h4>Objectives</h4>The clinical characteristics of bipolar disorder (current major depressive episode) (BD) overlap with unipolar depressive disorder (UD), which makes it difficult to perform an accurate diagnosis. We identified plasma microRNAs (miRNAs) that distinguished BD from UD and explored the relationship between miRNA expression levels and clinical characteristics.<h4>Methods</h4>Total miRNAs from blood plasma from seven UD patients, seven BD patients, and six controls were analyzed. Th ...[more]

PMID: 33192625

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Project description:ImportanceThe structural abnormalities in the brain that accurately differentiate unipolar depression (UD) and bipolar depression (BD) remain unidentified.ObjectivesFirst, to investigate and compare morphometric changes in UD and BD, and to replicate the findings at 2 independent neuroimaging sites; second, to differentiate UD and BD using multivariate pattern classification techniques.Design, setting, and participantsIn a 2-center cross-sectional study, structural gray matter data were obtained at 2 independent sites (Pittsburgh, Pennsylvania, and Münster, Germany) using 3-T magnetic resonance imaging. Voxel-based morphometry was used to compare local gray and white matter volumes, and a novel pattern classification approach was used to discriminate between UD and BD, while training the classifier at one imaging site and testing in an independent sample at the other site. The Pittsburgh sample of participants was recruited from the Western Psychiatric Institute and Clinic at the University of Pittsburgh from 2008 to 2012. The Münster sample was recruited from the Department of Psychiatry at the University of Münster from 2010 to 2012. Equally divided between the 2 sites were 58 currently depressed patients with bipolar I disorder, 58 age- and sex-matched unipolar depressed patients, and 58 matched healthy controls.Main outcomes and measuresMagnetic resonance imaging was used to detect structural differences between groups. Morphometric analyses were applied using voxel-based morphometry. Pattern classification techniques were used for a multivariate approach.ResultsAt both sites, individuals with BD showed reduced gray matter volumes in the hippocampal formation and the amygdala relative to individuals with UD (Montreal Neurological Institute coordinates x = -22, y = -1, z = 20; k = 1938 voxels; t = 4.75), whereas individuals with UD showed reduced gray matter volumes in the anterior cingulate gyrus compared with individuals with BD (Montreal Neurological Institute coordinates x = -8, y = 32, z = 3; k = 979 voxels; t = 6.37; all corrected P < .05). Reductions in white matter volume within the cerebellum and hippocampus were found in individuals with BD. Pattern classification yielded up to 79.3% accuracy (P < .001) by differentiating the 2 depressed groups, training and testing the classifier at one site, and up to 69.0% accuracy (P < .001), training the classifier at one imaging site (Pittsburgh) and testing it at the other independent sample (Münster). Medication load did not alter the pattern of results.Conclusions and relevanceIndividuals with UD and those with BD are differentiated by structural abnormalities in neural regions supporting emotion processing. Neuroimaging and multivariate pattern classification techniques are promising tools to differentiate UD from BD and show promise as future diagnostic aids.

Dataset Information

Plasma microRNA Array Analysis Identifies Overexpressed miR-19b-3p as a Biomarker of Bipolar Depression Distinguishing From Unipolar Depression.

Publications

Plasma microRNA Array Analysis Identifies Overexpressed miR-19b-3p as a Biomarker of Bipolar Depression Distinguishing From Unipolar Depression.

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