| Literature DB >> 28780410 |
Yu Wang1, Huili Jiang1, Hong Meng2, Jun Lu1, Jing Li1, Xuhui Zhang1, Xinjing Yang1, Bingcong Zhao1, Yang Sun1, Tuya Bao3.
Abstract
Data from clinical investigations and laboratory fundings have provided preliminary evidence for the effectiveness and safety of acupuncture therapy in depression. However, the mechanisms underlying the antidepressant response of acupuncture are not fully elucidated. To elucidate the potential effects of acupuncture for depression on the hippocampal genome-wide transcriptome at the molecular level, we evaluated the transcriptomic profile of depression rats under treatment of acupuncture, and fluoxetine. We identified a very significant effect of acupucture intervention, with 107 genes differentially expressed in acupuncture vs. model group; while 41 genes between fluoxetine vs. model group. Notably, the 54 differentially expressed genes between acupuncture and fluoxetine showed the significantly different effect between acupuncture and fluoxetine. Through GO (gene ontology) functional term and KEGG (kyoto encyclopedia of genes and genomes) pathway analysis, we identified that the upregulation of gene sets were related to inflammatory response, innate immunity and immune response. We found that toll-like receptor signalling pathway and NOD like receptor signalling pathway were associated with the function of inflammatory response, innate immunity and immune response. Importantly, acupuncture reversed the upregulation of gene sets that were related to inflammatory response, innate immunity and immune response (including toll-like receptor signalling pathway and NOD like receptor signalling pathway), which might be critical for the pathogenesis of depression and provide evidence for the antidepressive effects of acupuncture by regulating inflammatory response, innate immunity and immune response via toll-like receptor signalling pathway and NOD like receptor signalling pathway.Entities:
Keywords: Chronic restraint stress; Depressive disorder; Hippocampus; RNA-sequencing (RNA-seq); Transcriptome
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Year: 2017 PMID: 28780410 DOI: 10.1016/j.brainresbull.2017.07.021
Source DB: PubMed Journal: Brain Res Bull ISSN: 0361-9230 Impact factor: 4.077