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Distinct alterations in Parkinson's medication-state and disease-state connectivity.

ABSTRACT: Altered brain connectivity has been described in people with Parkinson's disease and in response to dopaminergic medications. However, it is unclear whether dopaminergic medications primarily 'normalize' disease related connectivity changes or if they induce unique alterations in brain connectivity. Further, it is unclear how these disease- and medication-associated changes in brain connectivity relate differently to specific motor manifestations of disease, such as bradykinesia/rigidity and tremor. In this study, we applied a novel covariance projection approach in combination with a bootstrapped permutation test to resting state functional MRI data from 57 Parkinson's disease and 20 healthy control participants to determine the Parkinson's medication-state and disease-state connectivity changes associated with different motor manifestations of disease. First, we identified brain connections that best classified Parkinson's disease ON versus OFF dopamine and Parkinson's disease versus healthy controls, achieving 96.9 ± 5.9% and 72.7 ± 12.4% classification accuracy, respectively. Second, we investigated the connections that significantly contribute to the classifications. We found that the connections greater in Parkinson's disease OFF compared to ON dopamine are primarily between motor (cerebellum and putamen) and posterior cortical regions, such as the posterior cingulate cortex. By contrast, connections that are greater in ON compared to OFF dopamine are between the right and left medial prefrontal cortex. We also identified the connections that are greater in healthy control compared to Parkinson's disease and found the most significant connections are associated with primary motor regions, such as the striatum and the supplementary motor area. Notably, these are different connections than those identified in Parkinson's disease OFF compared to ON. Third, we determined which of the Parkinson's medication-state and disease-state connections are associated with the severity of different motor symptoms. We found two connections correlate with both bradykinesia/rigidity severity and tremor severity, whereas four connections correlate with only bradykinesia/rigidity severity, and five connections correlate with only tremor severity. Connections that correlate with only tremor severity are anchored by the cerebellum and the supplemental motor area, but only those connections that include the supplemental motor area predict dopaminergic improvement in tremor. Our results suggest that dopaminergic medications do not simply 'normalize' abnormal brain connectivity associated with Parkinson's disease, but rather dopamine drives distinct connectivity changes, only some of which are associated with improved motor symptoms. In addition, the dissociation between of connections related to severity of bradykinesia/rigidity versus tremor highlights the distinct abnormalities in brain circuitry underlying these specific motor symptoms.

SUBMITTER: Ng B

PROVIDER: S-EPMC5608603 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Distinct alterations in Parkinson's medication-state and disease-state connectivity.

Ng Bernard B Varoquaux Gael G Poline Jean Baptiste JB Thirion Bertrand B Greicius Michael D MD Poston Kathleen L KL

NeuroImage. Clinical 20170906

Altered brain connectivity has been described in people with Parkinson's disease and in response to dopaminergic medications. However, it is unclear whether dopaminergic medications primarily 'normalize' disease related connectivity changes or if they induce unique alterations in brain connectivity. Further, it is unclear how these disease- and medication-associated changes in brain connectivity relate differently to specific motor manifestations of disease, such as bradykinesia/rigidity and tre ...[more]

PMID: 28971008

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Project description:Since anatomic MRI is presently not able to directly discern neuronal loss in Parkinson's Disease (PD), studying the associated functional connectivity (FC) changes seems a promising approach toward developing non-invasive and non-radioactive neuroimaging markers for this disease. While several groups have reported such FC changes in PD, there are also significant discrepancies between studies. Investigating the reproducibility of PD-related FC changes on independent datasets is therefore of crucial importance. We acquired resting-state fMRI scans for 43 subjects (27 patients and 16 normal controls, with 2 replicate scans per subject) and compared the observed FC changes with those obtained in two independent datasets, one made available by the PPMI consortium (91 patients, 18 controls) and a second one by the group of Tao Wu (20 patients, 20 controls). Unfortunately, PD-related functional connectivity changes turned out to be non-reproducible across datasets. This could be due to disease heterogeneity, but also to technical differences. To distinguish between the two, we devised a method to directly check for disease heterogeneity using random splits of a single dataset. Since we still observe non-reproducibility in a large fraction of random splits of the same dataset, we conclude that functional heterogeneity may be a dominating factor behind the lack of reproducibility of FC alterations in different rs-fMRI studies of PD. While global PD-related functional connectivity changes were non-reproducible across datasets, we identified a few individual brain region pairs with marginally consistent FC changes across all three datasets. However, training classifiers on each one of the three datasets to discriminate PD scans from controls produced only low accuracies on the remaining two test datasets. Moreover, classifiers trained and tested on random splits of the same dataset (which are technically homogeneous) also had low test accuracies, directly substantiating disease heterogeneity.

Dataset Information

Distinct alterations in Parkinson's medication-state and disease-state connectivity.

Publications

Distinct alterations in Parkinson's medication-state and disease-state connectivity.

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