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单胺能神经递质和应激激素系统模型中慢性抗抑郁药治疗性神经适应性的计算分析

Computational Analysis of Therapeutic Neuroadaptation to Chronic Antidepressant in a Model of the Monoaminergic Neurotransmitter and Stress Hormone Systems.

作者信息

Camacho Mariam B, Vijitbenjaronk Warut D, Anastasio Thomas J

机构信息

Computational Neurobiology Laboratory, Neuroscience Program, Medical Scholars Program, University of Illinois College of Medicine at Urbana-Champaign, Urbana, IL, United States.

Computational Neurobiology Laboratory, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, United States.

出版信息

Front Pharmacol. 2019 Oct 25;10:1215. doi: 10.3389/fphar.2019.01215. eCollection 2019.

DOI:10.3389/fphar.2019.01215
PMID:31708770
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6823241/
Abstract

The clinical practice of selective serotonin reuptake inhibitor (SSRI) augmentation relies heavily on trial-and-error. Unfortunately, the drug combinations prescribed today fail to provide relief for many depressed patients. In order to identify potentially more effective treatments, we developed a computational model of the monoaminergic neurotransmitter and stress-steroid systems that neuroadapts to chronic administration of combinations of antidepressant drugs and hormones by adjusting the strengths of its transmitter-system components (TSCs). We used the model to screen 60 chronically administered drug/hormone pairs and triples, and identified as potentially therapeutic those combinations that raised the monoamines (serotonin, norepinephrine, and dopamine) but lowered cortisol following neuroadaptation in the model. We also evaluated the contributions of individual and pairs of TSCs to therapeutic neuroadaptation with chronic SSRI using sensitivity, correlation, and linear temporal-logic analyses. All three approaches revealed that therapeutic neuroadaptation to chronic SSRI is an overdetermined process that depends on multiple TSCs, providing a potential explanation for the clinical finding that no single antidepressant regimen alleviates depressive symptoms in all patients.

摘要

选择性5-羟色胺再摄取抑制剂(SSRI)增效的临床实践在很大程度上依赖反复试验。遗憾的是,如今所开的药物组合无法为许多抑郁症患者缓解症状。为了确定可能更有效的治疗方法,我们开发了一种单胺能神经递质和应激类固醇系统的计算模型,该模型通过调整其递质系统组件(TSC)的强度来对长期使用的抗抑郁药物和激素组合产生神经适应性变化。我们使用该模型筛选了60种长期使用的药物/激素对和三联组合,并确定那些在模型中产生神经适应性变化后能提高单胺类物质(5-羟色胺、去甲肾上腺素和多巴胺)但降低皮质醇水平的组合具有潜在治疗作用。我们还使用敏感性、相关性和线性时间逻辑分析评估了单个TSC和TSC对在长期使用SSRI治疗时产生治疗性神经适应性变化的贡献。所有这三种方法都表明,对长期使用SSRI产生的治疗性神经适应性变化是一个由多个因素决定的过程,这取决于多个TSC,这为临床上没有单一抗抑郁治疗方案能缓解所有患者抑郁症状这一发现提供了一个潜在的解释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb6b/6823241/d54f976379a4/fphar-10-01215-g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb6b/6823241/cb1fcd092b87/fphar-10-01215-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb6b/6823241/d54f976379a4/fphar-10-01215-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb6b/6823241/5145fc13dae7/fphar-10-01215-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb6b/6823241/3780c78d7240/fphar-10-01215-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb6b/6823241/378e0f357638/fphar-10-01215-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb6b/6823241/5321890b309a/fphar-10-01215-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb6b/6823241/0567dc55eeb7/fphar-10-01215-g006.jpg
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本文引用的文献

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Computational Model of Antidepressant Response Heterogeneity as Multi-pathway Neuroadaptation.作为多途径神经适应的抗抑郁反应异质性计算模型
Front Pharmacol. 2017 Dec 20;8:925. doi: 10.3389/fphar.2017.00925. eCollection 2017.
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Activation of indoleamine 2, 3- dioxygenase pathway by olanzapine augments antidepressant effects of venlafaxine in mice.奥氮平激活吲哚胺 2,3-双加氧酶通路增强文拉法辛在小鼠中的抗抑郁作用。
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Editorial: Computational and Experimental Approaches in Multi-target Pharmacology.
社论:多靶点药理学中的计算与实验方法
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Depression Is the Leading Cause of Disability Around the World.抑郁症是全球致残的主要原因。
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Oxytocin mitigated the depressive-like behaviors of maternal separation stress through modulating mitochondrial function and neuroinflammation.催产素通过调节线粒体功能和神经炎症减轻了母体分离应激所致的抑郁样行为。
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