Frontoparietal network’s coupling of brain function and cerebrospinal fluid dynamics reduced in Parkinson’s disease with cognitive impairment
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Background Most Parkinson’s disease patients often develop to cognitive impairment and glymphatic system dysfunction may underlie this symptom. Recent studies proved that the coupling strength of global blood-oxygen-level-dependent (gBOLD) signals and cerebrospinal fluid (CSF) inflow dynamically reflects glymphatic function. As different brain networks contribute distinctly to cognition. We examined Yeo-7 network’s BOLD-CSF coupling in PD to uncover the specific neural mechanisms linking glymphatic dysfunction to cognitive impairment. Methods Structural and resting-state functional MRI, clinical motor (Unified Parkinson’s Disease Rating Scale, UPDRS), and cognitive (Mini-mental State Examination, MMSE) assessments were collected from 122 PD patients(45 with mild cognitive impairment(MCI)/ 77 with normal cognition(NC)) and 39 healthy controls (HCs). Based on the Dice coefficient from the Neuroparc OSF registered repository, we mapped ninety AAL brain regions to seven Yeo brain networks. Global and network-specific BOLD-CSF coupling strengths were computed. Statistical analyses compared group differences and examined correlations between BOLD-CSF and clinical measures. Results Consistent with prior research, decreased gBOLD-CSF coupling correlated with lower MMSE scores. Compared to HCs, PD-MCI patients showed weaker coupling in the frontoparietal network (FPN) and limbic network (LN). Notably, MMSE scores demonstrated negative correlation specifically with FPN coupling. Among PD subgroups, PD-MCI patients exhibited higher UPDRS-II scores than PD-NC. In the PD-MCI group, UPDRS-II scores positively correlated with global, LN and FPN BOLD-CSF coupling. Conclusions These findings support BOLD-CSF coupling strength may serve as a PD-MCI biomarker and reveal distinct pathological features between PD-MCI and PD-NC subtypes.