期刊
TRANSLATIONAL PSYCHIATRY
卷 6, 期 -, 页码 -出版社
SPRINGERNATURE
DOI: 10.1038/tp.2016.131
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资金
- Health Research Board [HRB: HRA_POR/2012/32]
- Science Foundation Ireland (SFI) [SFI/12/RC/2273, 02/CE/B124, 07/CE/B1368]
- European Community [FP7/2007-2013, 201714]
- NARSAD Young Investigator Grant from the Brain and Behaviour Research Foundation [20771]
There is a growing emphasis in the field of psychiatry on the need to identify candidate biomarkers to aid in diagnosis and clinical management of depression, particularly with respect to predicting response to specific therapeutic strategies. MicroRNAs are small nucleotide sequences with the ability to regulate gene expression at the transcriptomic level and emerging evidence from a range of studies has highlighted their biomarker potential. Here we compared healthy controls (n = 20) with patients diagnosed with major depression (n = 40) and who were treatment-resistant to identify peripheral microRNA biomarkers, which could be used for diagnosis and to predict response to electroconvulsive therapy (ECT) and ketamine (KET) infusions, treatments that have previously shown to be effective in treatment-resistant depression (TRD). At baseline and after treatment, blood samples were taken and symptom severity scores rated using the Hamilton Depression Rating Scale (HDRS). Samples were analyzed for microRNA expression using microarray and validated using quantitative PCR. As expected, both treatments reduced HDRS scores. Compared with controls, the baseline expression of the microRNA let-7b was less by similar to 40% in TRD patients compared with controls. The baseline expression of let-7c was also lower by similar to 50% in TRD patients who received ECT. Bioinformatic analysis revealed that let-7b and let-7c regulates the expression of 27 genes in the PI3k-Akt-mTOR signaling pathway, which has previously been reported to be dysfunctional in depression. The expression of miR-16, miR-182, miR-451 and miR-223 were similar to that in controls. Baseline microRNA expression could not predict treatment response and microRNAs were unaffected by treatment. Taken together, we have identified let-7b and let-7c as candidate biomarkers of major depression.
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