Camacho Mariam B, Anastasio Thomas J
Computational Neurobiology Laboratory, Beckman Institute for Advanced Science and Technology, Neuroscience Program, Medical Scholars Program, University of Illinois College of Medicine at Urbana-Champaign, Urbana, IL, United States.
Computational Neurobiology Laboratory, Department of Molecular and Integrative Physiology, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States.
Front Pharmacol. 2017 Dec 20;8:925. doi: 10.3389/fphar.2017.00925. eCollection 2017.
Current hypotheses cannot fully explain the clinically observed heterogeneity in antidepressant response. The therapeutic latency of antidepressants suggests that therapeutic outcomes are achieved not by the acute effects of the drugs, but rather by the homeostatic changes that occur as the brain adapts to their chronic administration. We present a computational model that represents the known interactions between the monoaminergic neurotransmitter-producing brain regions and associated non-monoaminergic neurotransmitter systems, and use the model to explore the possible ways in which the brain can homeostatically adjust to chronic antidepressant administration. The model also represents the neuron-specific neurotransmitter receptors that are known to adjust their strengths (expressions or sensitivities) in response to chronic antidepressant administration, and neuroadaptation in the model occurs through sequential adjustments in these receptor strengths. The main result is that the model can reach similar levels of adaptation to chronic administration of the same antidepressant drug or combination along many different pathways, arriving correspondingly at many different receptor strength configurations, but not all of those adapted configurations are also associated with therapeutic elevations in monoamine levels. When expressed as the percentage of adapted configurations that are also associated with elevations in one or more of the monoamines, our modeling results largely agree with the percentage efficacy rates of antidepressants and antidepressant combinations observed in clinical trials. Our neuroadaptation model provides an explanation for the clinical reports of heterogeneous outcomes among patients chronically administered the same antidepressant drug regimen.
目前的假说尚无法完全解释临床上观察到的抗抑郁反应的异质性。抗抑郁药的治疗潜伏期表明,治疗效果并非由药物的急性作用产生,而是由大脑适应其长期给药后发生的稳态变化所导致。我们提出了一个计算模型,该模型描述了产生单胺能神经递质的脑区与相关非单胺能神经递质系统之间已知的相互作用,并使用该模型探索大脑对长期抗抑郁药给药进行稳态调节的可能方式。该模型还体现了已知会在长期抗抑郁药给药后调节其强度(表达或敏感性)的神经元特异性神经递质受体,并且模型中的神经适应性是通过这些受体强度的顺序调节而发生的。主要结果是,该模型可以沿着许多不同途径达到与长期给予相同抗抑郁药或联合用药相似的适应水平,相应地达到许多不同的受体强度配置,但并非所有这些适应配置都与单胺水平的治疗性升高相关。当以也与一种或多种单胺升高相关的适应配置的百分比来表示时,我们的建模结果在很大程度上与临床试验中观察到的抗抑郁药及抗抑郁药联合用药的有效率百分比相符。我们的神经适应性模型为长期接受相同抗抑郁药治疗方案的患者出现异质性结果的临床报告提供了解释。