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.

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.

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.