Deciphering the neural mechanisms of miR-134 in major depressive disorder with population-based and person-specific imaging transcriptomic techniques
Lou, Jing1; Liu, Kai2,3; Wen, Junyan4; He, Yini1; Sun, Yuqing1; Tian, Xiaohan1; Hu, Ke5,6; Deng, Yanjia2; Liu, Bing1,7,8; Wen, Ge4
刊名PSYCHIATRY RESEARCH
2023-11-01
卷号329页码:12
关键词Major depressive disorder (MDD) miR-134 Two -stage cross -scale imaging transcriptomic analyses Biomarkers Multi-omics
ISSN号0165-1781
DOI10.1016/j.psychres.2023.115551
通讯作者Deng, Yanjia(landseerd@xzhmu.edu.cn) ; Liu, Bing(bing.liu@bnu.edu.cn) ; Wen, Ge(wenge@smu.edu.cn)
英文摘要MiR-134 has emerged as a potential molecular biomarker for the detection and management of major depressive disorder (MDD). Nevertheless, the specific effects of miR-134 as a regulatory element on brain function and its implications for the clinical presentation of MDD are not yet fully understood. In order to investigate the potential neural mechanisms that contribute to the relationship between miR-134 and MDD, we employed a par-allel two-stage cross-scale multi-omics approach. This involved utilizing the anterior cingulate cortex (ACC) functional connectivity as a means to connect microscopic molecular structures with macroscopic brain function in two separate cohorts: the MDD-I dataset (56 MDD patients and 51 healthy controls) and the MDD-II dataset (57 MDD patients and 52 healthy controls). We found a stable ACC functional dysconnectivity pattern of MDD and established the hierarchical cross-scale association from molecular organizations of miR-134 target genes to macroscopic brain functional dysconnectivity and associated behavior, as revealed by population-based analysis. Additionally, our person-specific imaging transcriptomic study revealed that individual exosomal miR-134 expression levels impact on individual clinical symptoms of MDD by modulating ACC-related functional dysconnectivity. Together, our findings provide compelling evidence of the correlation between miR-134 and depression across multi scales within the gene-brain-behavior context.
资助项目National Natural Science Foundation of China[82271980] ; Startup Funds of Beijing Normal University
WOS关键词STRUCTURED INTERVIEW GUIDE ; ANTERIOR CINGULATE CORTEX ; FUNCTIONAL CONNECTIVITY ; BRAIN ; DYSFUNCTION ; PLASTICITY ; MICRORNAS ; GENETICS ; ANXIETY ; ATLAS
WOS研究方向Psychiatry
语种英语
出版者ELSEVIER IRELAND LTD
WOS记录号WOS:001102884900001
资助机构National Natural Science Foundation of China ; Startup Funds of Beijing Normal University
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/55225]  
专题脑图谱与类脑智能实验室
通讯作者Deng, Yanjia; Liu, Bing; Wen, Ge
作者单位1.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
2.Xuzhou Med Univ, Sch Med Imaging, Xuzhou 221006, Peoples R China
3.Xuzhou Med Univ, Affiliated Hosp, Dept Radiol, Xuzhou 221004, Peoples R China
4.Southern Med Univ, Nanfang Hosp, Dept Imaging, 28 Yongning St, Guangzhou 510515, Peoples R China
5.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
6.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
7.Beijing Normal Univ, IDG McGovern Inst Brain Res, Beijing 100875, Peoples R China
8.Chinese Inst Brain Res, Beijing 102206, Peoples R China
推荐引用方式
GB/T 7714
Lou, Jing,Liu, Kai,Wen, Junyan,et al. Deciphering the neural mechanisms of miR-134 in major depressive disorder with population-based and person-specific imaging transcriptomic techniques[J]. PSYCHIATRY RESEARCH,2023,329:12.
APA Lou, Jing.,Liu, Kai.,Wen, Junyan.,He, Yini.,Sun, Yuqing.,...&Wen, Ge.(2023).Deciphering the neural mechanisms of miR-134 in major depressive disorder with population-based and person-specific imaging transcriptomic techniques.PSYCHIATRY RESEARCH,329,12.
MLA Lou, Jing,et al."Deciphering the neural mechanisms of miR-134 in major depressive disorder with population-based and person-specific imaging transcriptomic techniques".PSYCHIATRY RESEARCH 329(2023):12.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace