| MicroRNA132 associated multimodal neuroimaging patterns in unmedicated major depressive disorder | |
Qi, Shile1,2,3 ; Yang, Xiao4,5,6; Zhao, Liansheng4,5,6; Calhoun, Vince D.7,8,9,10; Perrone-Bizzozero, Nora9,10; Liu, Shengfeng1,2; Jiang, Rongtao1,2,3; Jiang, Tianzi1,2,3,11; Sui, Jing1,2,3,7,8,11; Ma, Xiaohong4,5,6
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| Source Publication | BRAIN
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| 2018-03-01 | |
| Volume | 141Issue:3Pages:916-926 |
| Subtype | Article |
| Abstract | There is compelling evidence that epigenetic factors contribute to the manifestation of depression, in which microRNA132 (miR-132) is suggested to play a pivotal role in the pathogenesis and neuronal mechanisms underlying the symptoms of depression. Additionally, several depression-associated genes [MECP2, ARHGAP32 (p250GAP), CREB, and period genes] were experimentally validated as miR-132 targets. However, most studies regarding miR-132 in major depressive disorder are based on post-mortem, animal models or genetic comparisons. This work will be the first attempt to investigate how miR-132 dysregulation may impact covariation of multimodal brain imaging data in 81 unmedicated major depressive patients and 123 demographically-matched healthy controls, as well as in a medication-naive subset of major depressive patients. MiR-132 values in blood (patients4controls) was used as a prior reference to guide fusion of three MRI features: fractional amplitude of low frequency fluctuations, grey matter volume, and fractional anisotropy. The multimodal components correlated with miR-132 also show significant group difference in loadings. Results indicate that (i) higher miR-132 levels in major depressive disorder are associated with both lower fractional amplitude of low frequency fluctuations and lower grey matter volume in fronto-limbic network; and (ii) the identified brain regions linked with increased miR-132 levels were also associated with poorer cognitive performance in attention and executive function. Using a data-driven, supervised-learning method, we determined that miR-132 dysregulation in major depressive disorder is associated with multi-facets of brain function and structure in fronto-limbic network (the key network for emotional regulation and memory), which deepens our understanding of how miR-132 dysregulation in major depressive disorders contribute to the loss of specific brain areas and is linked to relevant cognitive impairments. |
| Keyword | Major Depressive Disorder Microrna132 Supervised Multimodal Fusion Fronto-limbic Network Unmedicated |
| WOS Headings | Science & Technology ; Life Sciences & Biomedicine |
| DOI | 10.1093/brain/awx366 |
| WOS Keyword | VOXEL-BASED MORPHOMETRY ; MOOD DISORDERS ; SCHIZOPHRENIA ; AMYGDALA ; METAANALYSIS ; PLASTICITY ; VOLUME ; ABNORMALITIES ; CONNECTIVITY ; HIPPOCAMPUS |
| Indexed By | SCI ; SSCI |
| Language | 英语 |
| Funding Organization | National High-Tech Development Program (863 plan)(2015AA020513) ; '100 Talents Plan' of Chinese Academy of Sciences ; Chinese National Natural Science Foundation(81471367 ; Strategic Priority Research Program of the Chinese Academy of Sciences(XDB02060005) ; National Science and Technology Support plan(2015BAI13B02) ; NIH(R01EB005846 ; 81671344 ; 1R01MH094524 ; 61773380) ; P20GM103472) |
| WOS Research Area | Neurosciences & Neurology |
| WOS Subject | Clinical Neurology ; Neurosciences |
| WOS ID | WOS:000426813600033 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/20782 |
| Collection | 脑网络组研究中心 |
| Corresponding Author | Sui, Jing |
| Affiliation | 1.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China 4.Sichuan Univ, West China Hosp, Psychiat Lab, Chengdu, Sichuan, Peoples R China 5.Sichuan Univ, State Key Lab Biotherapy, Mental Hlth Ctr, West China Hosp, Chengdu, Sichuan, Peoples R China 6.Sichuan Univ, West China Hosp, Huaxi Brain Res Ctr, Chengdu, Sichuan, Peoples R China 7.Mind Res Network, Albuquerque, NM USA 8.Univ New Mexico, Dept Elect & Comp Engn, Albuquerque, NM 87131 USA 9.Univ New Mexico, Dept Neurosci & Psychiat, Albuquerque, NM 87131 USA 10.Yale Univ, Dept Psychiat, New Haven, CT 06520 USA 11.Chinese Acad Sci, Inst Automat, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing, Peoples R China |
| First Author Affilication | Institute of Automation, Chinese Academy of Sciences; Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
| Corresponding Author Affilication | Institute of Automation, Chinese Academy of Sciences; Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China; Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China |
| Recommended Citation GB/T 7714 | Qi, Shile,Yang, Xiao,Zhao, Liansheng,et al. MicroRNA132 associated multimodal neuroimaging patterns in unmedicated major depressive disorder[J]. BRAIN,2018,141(3):916-926. |
| APA | Qi, Shile.,Yang, Xiao.,Zhao, Liansheng.,Calhoun, Vince D..,Perrone-Bizzozero, Nora.,...&Ma, Xiaohong.(2018).MicroRNA132 associated multimodal neuroimaging patterns in unmedicated major depressive disorder.BRAIN,141(3),916-926. |
| MLA | Qi, Shile,et al."MicroRNA132 associated multimodal neuroimaging patterns in unmedicated major depressive disorder".BRAIN 141.3(2018):916-926. |
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| 2018_brain_QI_miR132（1019KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Download | |
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