Dopamine Depletion Alters Macroscopic Network Dynamics in Parkinson’s Disease

Abstract

Parkinson’s disease is primarily characterised by diminished dopaminergic function, however the impact of these impairments on large-scale brain dynamics remains unclear. It has been difficult to disentangle the direct effects of Parkinson’s disease from compensatory changes that reconfigure the functional signature of the whole brain network. To examine the causal role of dopamine depletion in network-level topology, we investigated time-varying network structure in 37 individuals with idiopathic Parkinson’s disease, both ‘On’ and ‘Off’ dopamine replacement therapy, along with 50 age-matched, healthy control subjects using resting-state functional MRI. By tracking dynamic network-level topology, we found that the Parkinson’s disease ‘Off’ state was associated with greater network-level integration than in the ‘On’ state. The extent of integration in the ‘Off’ state inversely correlated with motor symptom severity, suggesting that a shift toward a more integrated network topology may be a compensatory mechanism associated with preserved motor function in the dopamine depleted ‘Off’ state. Furthermore, we were able to demonstrate that measures of both cognitive and brain reserve (i.e., premorbid intelligence and whole brain grey matter volume) had a positive relationship with the relative increase in network integration observed in the dopaminergic ‘Off’ state. This suggests that each of these factors plays an important role in promoting network integration in the dopaminergic ‘Off’ state. Our findings provide a mechanistic basis for understanding the PD ‘Off’ state and provide a further conceptual link with network-level reconfiguration. Together, our results highlight the mechanisms responsible for pathological and compensatory change in Parkinson’s disease.

Association of specific biotypes in patients with Parkinson disease and disease progression

“…In summary, we hypothesize that the different rates of symptom progression relate to different brain reserves. 13,16 Brain reserve describes the differences in brain volume and structure that may support maintenance of function despite pathology. 13,44 Gross or regional brain volume reflects the quantity of neurons, neuronal integrity, and synaptic densities, which determine the ability of the brain to engage in compensatory activity.…”

“…In summary, we hypothesize that the different rates of symptom progression relate to different brain reserves. 13 , 16 …”

“…12 Brain volume may mediate brain reserve, which promotes the resilience of large-scale brain networks and helps maintain normal function in the face of neurodegeneration. [13][14][15][16] Previous studies have shown that subcortical volume loss reflects clinical measures of disease severity and is related to the development of cognitive impairment. [17][18][19][20][21] These studies raise the intriguing possibility that T1-weighted MRI measures of brain volume could be leveraged to identify biotypes of PD.…”

Longitudinal functional connectivity changes related to dopaminergic decline in Parkinson’s disease

“…In contrast, we found increased intraregional functional connectivity of the posterior putamen, suggesting a compensatory mechanism that develops in response to marked dopamine decline in the posterior putamen ( Helmich et al, 2010 ). It has been demonstrated that noradrenaline, serotonin and acetylcholine are also affected in PD, although to a lesser degree than dopamine, thus it is possible that other neurotransmitter systems might play a role in mediating changes in basal ganglia functional connectivity patterns ( Shine et al, 2019 ). Lastly, we found reduced substantia nigra functional connectivity with the thalamus extending to the caudate and putamen, which is generally consistent with results reported by Wu et al (2012) who also showed additional reductions to the globus pallidus, insula and SMA in PD patients as compared to the healthy controls ( Wu et al, 2012 ).…”

Flexible Brain Transitions Between Hierarchical Network Segregation and Integration Predict Human Behavior

“…To test the reasonableness of the hierarchical segregation and integration (i.e., which have been widely used to reflect functional segregation and integration in brain FC networks 3,19,20,36,37 . As expected, However, it should also be noted that the graph-based network measures were highly variable for a similar higher segregated process in these subsystems.…”