Life SciencesNeurosciencePeer-reviewed journal article
A direct estrogenic involvement in the expression of human hypocretin
Haimei LiiD, Xinlu Chen, Jingyi DongiD, Ripeng Liu, Jinfeng DuaniD, Manli HuangiD, Shaohua HuiD, Jing LüiD
Abstract
BackgroundHypocretin-1 may play an important role in depression, which was increased in female depression in LHA in our previous study. Estrogen acts through its nuclear transcriptional receptors. MethodsWe studied the possibility of a direct action of estrogen receptors on the expression of human hypocretin. To explore the activation of ERs by hypocretin, we first investigated the potential presence of co-localization of the estrogen receptors (ERs) in hypocretin-immunoreactive neurons in the lateral hypothalamic area (LHA) in human and nuclear ERs in hypocretin immunoreactive neuroblastoma SK-N-SH cells. We investigated the relationship between E2 and hypocretin in female rats. After we explored the regulating role of exogenous estrogen on hypocretin gene expression via ERs through Chromatin immunoprecipitation, Electrophoretic mobility shift assay and Luciferase assay. ResultsWe found that hypocretin-1 plasma level was significantly higher in female depression. Estrogen receptors (ER and ER{beta}) and hypocretin are co-localized in female depression LHA, PC12 and SK-N-SH cell lines. The estrogen receptor response elements (EREs) existing in the hypocretin promoter region may directly regulate the expression of hypocretin, the synchronicity of change of hypocretin and estradiol both in hypothalamus and plasma was verified in female rats. With the presence of estradiol, there is specific binding between human ER and the Hypocretin-ERE. Expression of ER combined with estradiol repressed hypocretin promoter activity through the ERE. Conclusionswe defined that estradiol may affect hypocretin neurons in the human hypothalamus via ER binding to the Hypocretin-ERE directly, which may thus lead to the sex-specific pathogenesis of depression.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 7
- FWCI
- 1.70
- Field percentile
- top 18%
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