建立路易体疾病中心脏儿茶酚胺缺乏症的进展模型

David S Goldstein, Mark J Pekker, Patti Sullivan, Risa Isonaka, Yehonatan Sharabi
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引用次数: 0

摘要

背景路易体病(LBDs)的特征是左心室心肌交感神经递质去甲肾上腺素缺乏,交感神经神经元内沉积α-突触核蛋白(αS)。因此,枸杞多糖症是一种自主神经突触核蛋白病。计算模型揭示了枸杞多糖症患者残余心肌交感去甲肾上腺素能神经的多种功能异常,包括去甲肾上腺素合成、囊泡储存和循环减少。我们报告了一个扩展模型,该模型可预测枸杞多糖症的进展以及遗传倾向和治疗对进展的影响。方法和结果 该模型结合了心脏交感神经激活和多巴胺代谢产物 3,4-二羟基苯乙醛介导的自体毒性。我们测试了该模型预测纵向经验数据的能力,这些数据基于心脏交感神经成像、与特定神经元内反应相关的基因变异的影响、抑制单胺氧化酶以减少 3,4-二羟基苯乙醛生成的治疗以及死后心肌组织中儿茶酚胺和 αS 的含量。新模型产生了心肌去甲肾上腺素含量的三相下降。枸杞多糖症患者连续心脏 18F 多巴胺正电子发射断层扫描的经验数据证实了这一模式。该模型还正确预测了有关基因变异和单胺氧化酶抑制作用以及心肌儿茶酚胺和 αS 水平的经验数据。结论 本计算模型预测,随着枸杞多糖病的进展,心肌去甲肾上腺素含量会出现三相下降。根据该模型,在从第一阶段向第二阶段过渡时开始的疾病调节干预措施可延缓有症状疾病的发生。计算模型与临床前自律神经突触素病的生物标志物相结合,可实现对枸杞多糖病的早期检测和更有效的治疗。
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Modeling the Progression of Cardiac Catecholamine Deficiency in Lewy Body Diseases.

Background Lewy body diseases (LBDs) feature deficiency of the sympathetic neurotransmitter norepinephrine in the left ventricular myocardium and sympathetic intra-neuronal deposition of the protein alpha-synuclein (αS). LBDs therefore are autonomic synucleinopathies. Computational modeling has revealed multiple functional abnormalities in residual myocardial sympathetic noradrenergic nerves in LBDs, including decreased norepinephrine synthesis, vesicular storage, and recycling. We report an extended model that enables predictions about the progression of LBDs and effects of genetic predispositions and treatments on that progression. Methods and Results The model combines cardiac sympathetic activation with autotoxicity mediated by the dopamine metabolite 3,4-dihydroxyphenylacetaldehyde. We tested the model by its ability to predict longitudinal empirical data based on cardiac sympathetic neuroimaging, effects of genetic variations related to particular intra-neuronal reactions, treatment by monoamine oxidase inhibition to decrease 3,4-dihydroxyphenylacetaldehyde production, and post-mortem myocardial tissue contents of catecholamines and αS. The new model generated a triphasic decline in myocardial norepinephrine content. This pattern was confirmed by empirical data from serial cardiac 18F-dopamine positron emission tomographic scanning in patients with LBDs. The model also correctly predicted empirical data about effects of genetic variants and monoamine oxidase inhibition and about myocardial levels of catecholamines and αS. Conclusions The present computational model predicts a triphasic decline in myocardial norepinephrine content as LBDs progress. According to the model, disease-modifying interventions begun at the transition from the first to the second phase delay the onset of symptomatic disease. Computational modeling coupled with biomarkers of preclinical autonomic synucleinopathy may enable early detection and more effective treatment of LBDs.

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