Network Correlates Between Autonomic Dysfunction and Clinical Burden in Parkinson’s Disease - Feifei Lin; Weiting Tang; Kangyan Yang; Sizhe Zhou; Yuxuan Shi; Jindong Ding Peterson; Binwen Huang; Jun Liu; Yong You; Zhichun Chen (Translational Medical Engineering, 2026)
Objective: This study aimed to characterize how autonomic dysfunction relates to clinical phenotypic profiles and whole-brain network organization in Parkinson’s disease (PD). We additionally investigated putative neurobiological pathways that may link autonomic impairment to clinical disease burden, to yield mechanistic insights for developing novel therapeutic strategies in future translational studies. Methods: We integrated clinical assessments, neuroimaging, and dopamine transporter (DAT) scan data sourced from the Parkinson’s Progression Markers Initiative (PPMI) cohort to decode the underlying network‑level correlates connecting autonomic dysfunction to clinical deterioration. Results: More severe autonomic dysfunction was significantly correlated with increased motor and non‑motor symptom burden as well as reduced striatal DAT uptake. Network analyses further revealed that worse autonomic status was associated with widespread reductions in intra‑ and inter‑hemispheric functional connectivity and altered local topological properties within the bilateral posterior cingulate gyri (PCG). Formal mediation analyses showed that PCG topological and functional connectivity alterations may serve as associative intermediates in the relationship between autonomic dysfunction and aggravated clinical symptoms. Conclusion: Autonomic dysfunction is closely correlated with greater clinical severity and widespread functional network alterations in PD, supporting its potential value as a candidate biomarker for disease staging. Cross‑sectional mediation analyses further suggest that brain network abnormalities may represent associative correlates linking autonomic impairment and clinical symptom burden. Collectively, these exploratory findings highlight plausible network targets that could inform future neuromodulation investigations for PD patients with prominent autonomic dysfunction.