Deciphering the neural mechanisms of miR-134 in major depressive disorder with population-based and person-specific imaging transcriptomic techniques

doi:10.1016/j.psychres.2023.115551

CASIA OpenIR > 脑图谱与类脑智能实验室

	Deciphering the neural mechanisms of miR-134 in major depressive disorder with population-based and person-specific imaging transcriptomic techniques
	Lou, Jing 1; Liu, Kai 2,3; Wen, Junyan 4; He, Yini 1; Sun, Yuqing1 ; Tian, Xiaohan 1; Hu, Ke 5,6; Deng, Yanjia 2; Liu, Bing1,7,8 ; Wen, Ge 4
发表期刊	PSYCHIATRY RESEARCH
ISSN	0165-1781
	2023-11-01
卷号	329 页码:12
通讯作者	Deng, Yanjia(landseerd@xzhmu.edu.cn) ; Liu, Bing(bing.liu@bnu.edu.cn) ; Wen, Ge(wenge@smu.edu.cn)
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.
关键词	Major depressive disorder (MDD) miR-134 Two -stage cross -scale imaging transcriptomic analyses Biomarkers Multi-omics
DOI	10.1016/j.psychres.2023.115551
关键词[WOS]	STRUCTURED INTERVIEW GUIDE ; ANTERIOR CINGULATE CORTEX ; FUNCTIONAL CONNECTIVITY ; BRAIN ; DYSFUNCTION ; PLASTICITY ; MICRORNAS ; GENETICS ; ANXIETY ; ATLAS
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[82271980] ; Startup Funds of Beijing Normal University
项目资助者	National Natural Science Foundation of China ; Startup Funds of Beijing Normal University
WOS研究方向	Psychiatry
WOS类目	Psychiatry
WOS记录号	WOS:001102884900001
出版者	ELSEVIER IRELAND LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/55226
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.