Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China.
University of Chinese Academy of Sciences, China.
Brain. 2018 Mar 1;141(3):916-926. doi: 10.1093/brain/awx366.
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-naïve subset of major depressive patients. MiR-132 values in blood (patients > controls) 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.
有确凿的证据表明,表观遗传因素导致了抑郁症的发生,其中 microRNA132(miR-132)被认为在抑郁症的发病机制和神经元机制中起着关键作用。此外,一些与抑郁症相关的基因 [MECP2、ARHGAP32(p250GAP)、CREB 和周期基因] 已被实验验证为 miR-132 的靶标。然而,大多数关于 miR-132 在重度抑郁症中的研究都是基于死后、动物模型或遗传比较。这项工作将首次尝试研究 miR-132 失调如何影响 81 名未经药物治疗的重度抑郁症患者和 123 名年龄匹配的健康对照者以及未经药物治疗的重度抑郁症患者亚组的多模态脑成像数据的协变量。血液中的 miR-132 值(患者>对照)被用作指导融合三种 MRI 特征的先验参考:低频波动的分数幅度、灰质体积和分数各向异性。与 miR-132 相关的多模态成分的负荷也表现出显著的组间差异。结果表明:(i)重度抑郁症患者中 miR-132 水平较高与额-边缘网络中低频波动的分数幅度较低和灰质体积较低有关;(ii)与 miR-132 水平升高相关的鉴定出的脑区也与注意力和执行功能认知表现较差有关。使用数据驱动的、有监督的学习方法,我们确定 miR-132 在重度抑郁症中的失调与额-边缘网络中的多方面脑功能和结构有关(情感调节和记忆的关键网络),这加深了我们对 miR-132 失调如何导致特定脑区丧失以及与相关认知障碍相关的理解。