Neurobiological underpinnings of treatment-resistant depression, a debilitating condition associated with significant functional impairment, have not been elucidated. Consequently, the aim of this study was to use animal models of response and resistance to antidepressant treatment, in an attempt to identify differences in associated transcriptional responses. Flinders Sensitive Line rats were subjected to maternal separation (MS) and chronically treated with Escitalopram or Nortriptyline. Antidepressants reduced immobility time in the forced swim test in non-MS rats, while lack of antidepressant behavioural response was observed in MS animals. We developed a novel bioinformatic algorithm that enabled identification of transcriptional signatures in hippocampus and pre-frontal cortex that discriminate vehicle- and antidepressant-treated subjects in both MS and non-MS rats. Functional annotation analysis showed that in antidepressant-responder rats the most enriched pathways included IQGAPs activation, toll-like receptor trafficking, energy metabolism, and regulation of endopeptidase activity. The analysis of interacting proteins implicated synaptic vesicles and neurotransmitter release, ubiquitin regulation, cytoskeleton organisation and carbohydrate metabolism. In contrast, in treatment-resistant MS rats, main expression changes were revealed in ribosomal proteins, inflammatory responses, transcriptional/epigenetic regulation, and small GTPases. Susceptibility signature shared Rtn1, Zdhhc5, Igsf6, and Sim1 genes with the latest depression GWAS meta-analysis, while antidepressant resistance signature shared Ctnnd1, Rbms3, Atp1a3, and Pla2r1 genes. In conclusion, this study demonstrated that distinct transcriptional signatures are associated with behavioural response or non-response to antidepressant treatment. The identification of genes involved in antidepressant response will increase the comprehension of the neurobiological underpinnings of treatment-resistant depression, thus contributing to identification of novel therapeutic targets.

中文翻译：

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经历母体分离的弗林德斯敏感系大鼠抗抑郁治疗反应/无反应的基因表达特征

尚未阐明难治性抑郁症的神经生物学基础，这是一种与显着功能障碍相关的衰弱状态。因此，本研究的目的是使用抗抑郁药治疗反应和抵抗的动物模型，试图确定相关转录反应的差异。Flinders Sensitive Line 大鼠接受母体分离 (MS) 并长期用艾司西酞普兰或去甲替林治疗。在非 MS 大鼠的强迫游泳试验中，抗抑郁药减少了不动时间，而在 MS 动物中观察到缺乏抗抑郁药的行为反应。我们开发了一种新的生物信息学算法，该算法能够识别海马体和前额叶皮层中的转录特征，从而区分 MS 和非 MS 大鼠中的载体和抗抑郁药治疗对象。功能注释分析表明，在抗抑郁反应大鼠中，最丰富的通路包括 IQGAPs 激活、toll 样受体运输、能量代谢和内肽酶活性的调节。相互作用蛋白的分析涉及突触小泡和神经递质释放、泛素调节、细胞骨架组织和碳水化合物代谢。相比之下，在抗治疗的 MS 大鼠中，核糖体蛋白、炎症反应、转录/表观遗传调控和小 GTP 酶的主要表达变化。磁化率签名共享 Rtn1，Zdhhc5、Igsf6 和 Sim1 基因与最新的抑郁症 GWAS 荟萃分析，而抗抑郁药耐药特征共享 Ctnnd1、Rbms3、Atp1a3 和 Pla2r1 基因。总之，这项研究表明，不同的转录特征与抗抑郁药治疗的行为反应或无反应有关。识别参与抗抑郁反应的基因将增加对难治性抑郁症的神经生物学基础的理解，从而有助于识别新的治疗靶点。这项研究表明，不同的转录特征与抗抑郁药治疗的行为反应或无反应有关。识别参与抗抑郁反应的基因将增加对难治性抑郁症的神经生物学基础的理解，从而有助于识别新的治疗靶点。这项研究表明，不同的转录特征与抗抑郁药治疗的行为反应或无反应有关。识别参与抗抑郁反应的基因将增加对难治性抑郁症的神经生物学基础的理解，从而有助于识别新的治疗靶点。