Back

Both brain network topology and striatal dopamine depletion mediate the effects of autonomic dysfunction on disease burden of Parkinson's disease

Chen, Z.; Li, G.; Zhou, L.; Zhang, L.; Liu, J.

2023-09-23 neurology
10.1101/2023.09.21.23295938 medRxiv
Show abstract

BackgroundAutonomic dysfunction is one of the most common non-motor symptoms in Parkinsons disease (PD). Whether autonomic dysfunction contributes to disease progression and brain network abnormalities in PD remain largely unknown. The objective of this study is to evaluate how autonomic dysfunction affects clinical features and brain networks of PD patients. MethodsPD patients from Parkinsons Progression Markers Initiative (PPMI) database were included if they received magnetic resonance imaging. According to the scores of Scale for Outcomes in Parkinsons Disease-Autonomic (SCOPA-AUT), PD patients were classified into lower quartile group (SCOPA-AUT score rank: 0%~25%), interquartile group (SCOPA-AUT score rank: 26%~75%), and upper quartile group (SCOPA-AUT score rank: 76%~100%) based on their SCOPA-AUT score quartiles to examine how autonomic dysfunction shapes clinical manifestations and brain networks. ResultsPD patients in the upper quartile group showed more severe motor and non-motor symptoms, as well as more deficits in dopamine transporter binding compared to lower quartile group. Additionally, they also showed statistically different topological properties in structural and functional network compared to lower quartile group. Both structural and functional network metrics mediated the effects of autonomic dysfunction on clinical symptoms of PD patients. Reduced dopamine transporter binding also contributed to the effects of autonomic dysfunction on disease burden of PD patients. ConclusionsPD patients with more severe autonomic dysfunction exhibit worse disease and impairment of brain network topology. Both network topology and striatal dopamine depletion mediate the effects of autonomic dysfunction on clinical symptoms of PD patients.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.