David S Goldstein, Mark J Pekker, Patti Sullivan, Risa Isonaka, Yehonatan Sharabi
{"title":"建立路易体疾病中心脏儿茶酚胺缺乏症的进展模型","authors":"David S Goldstein, Mark J Pekker, Patti Sullivan, Risa Isonaka, Yehonatan Sharabi","doi":"10.1161/JAHA.121.024411","DOIUrl":null,"url":null,"abstract":"<p><p>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 <sup>18</sup>F-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.</p>","PeriodicalId":17189,"journal":{"name":"Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9238705/pdf/","citationCount":"0","resultStr":"{\"title\":\"Modeling the Progression of Cardiac Catecholamine Deficiency in Lewy Body Diseases.\",\"authors\":\"David S Goldstein, Mark J Pekker, Patti Sullivan, Risa Isonaka, Yehonatan Sharabi\",\"doi\":\"10.1161/JAHA.121.024411\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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 <sup>18</sup>F-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.</p>\",\"PeriodicalId\":17189,\"journal\":{\"name\":\"Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9238705/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1161/JAHA.121.024411\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/5/27 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1161/JAHA.121.024411","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/5/27 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
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.