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.

中文翻译：

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MicroRNA132 与未经药物治疗的重度抑郁症的多模式神经影像模式相关。

有令人信服的证据表明表观遗传因素导致抑郁症的表现，其中 microRNA132 (miR-132) 被认为在抑郁症症状的发病机制和神经元机制中发挥着关键作用。此外，一些与抑郁症相关的基因 [ MECP2、ARHGAP32 (p250GAP)、CREB ​​和周期基因] 经实验验证为 miR-132 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尸检、动物模型或遗传比较。这项工作将首次尝试调查 miR-132 失调如何影响 81 名未接受药物治疗的重度抑郁症患者和 123 名人口统计匹配的健康对照者以及未接受药物治疗的重度抑郁症患者中多模式脑成像数据的协变。血液中的 MiR-132 值（患者>对照）用作指导融合三个 MRI 特征的先前参考：低频波动的分数幅度、灰质体积和分数各向异性。与 miR-132 相关的多模式成分在负荷上也显示出显着的组间差异。结果表明 (i) 重度抑郁症中较高的 miR-132 水平与较低的低频波动分数幅度和较低的额边缘网络灰质体积相关；(ii) 已确定的与 miR-132 水平升高相关的大脑区域也与注意力和执行功能方面的认知表现较差有关。使用数据驱动的监督学习方法，我们确定重度抑郁症中的 miR-132 失调与额叶边缘网络（情绪调节和记忆的关键网络）中的大脑功能和结构的多个方面相关，这加深了我们对重度抑郁症中 miR-132 失调如何导致特定大脑区域丧失以及与相关认知障碍相关的理解。