Multimodal Functional Neuroimaging in Parkinson's Disease: The Network Degeneration Hypothesis and Characteristics in GBA Variant Carriers
Parkinson’s disease is a neurodegenerative disorder with distinct clinical and histopathological features. It is defined by asymmetric hypokinesia, rigidity, resting tremor, degeneration of nigrostriatal dopaminergic projections and α-synuclein deposits spreading slowly towards the cerebral cortex....
Parkinson-Erkrankung, Morbus Parkinson, Neurodegeneration, multimodale Bildgebung, Neuroimaging, funktionelle Magnetresonanztomographie, Positro
Parkinson’s disease, neurodegeneration, multimodal imaging, neuroimaging, functional magnetic resonance imaging, positron emission tomography
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|Parkinson’s disease is a neurodegenerative disorder with distinct clinical and histopathological features. It is defined by asymmetric hypokinesia, rigidity, resting tremor, degeneration of nigrostriatal dopaminergic projections and α-synuclein deposits spreading slowly towards the cerebral cortex. Despite these relatively straightforward patterns, the variety of clinical courses, additional signs and symptoms, as well as contributing pathogenic and risk factors is remarkably diverse.
It has been hypothesized that neurodegeneration spreads along functional networks, as evidence suggests for Alzheimer’s disease and other forms of dementia. Most people with Parkinson’s disease develop cognitive impairment, which in the earlier stages are more likely explained by functional network alterations than cortical cell loss and α synuclein deposits.
Alterations in the GBA gene stand out as the most important genetic risk factor for Parkinson’s disease and are linked to faster progression of motor and cognitive symptoms. The better known mutations cause the lysosomal storage disorder Gaucher’s disease, while the variants p.E365K and p.T408M, which are only associated with Parkinson’s disease, are more frequent. Their pathogenic effects require further investigation.
A large-scale research project with extensive neuroimaging data collection, clinical-behavioral examination and laboratory testing was conducted with the aims to deepen pathophysiological knowledge, advancing biomarker development and clinical subtyping. A cohort of 62 Parkinson’s disease patients and 25 demographically matched healthy controls was recruited. The neuroimaging protocol included resting-state functional magnetic resonance imaging and positron emission tomography using the tracers [18F]fluorodeoxyglucose and 6-[18F]fluoro-L-Dopa. Detailed assessment of motor symptoms, a cognitive test battery, a gene panel analysis and gas-chromatography coupled to mass-spectrometry of blood plasma metabolites were performed.
In the Parkinson’s disease group compared to healthy controls, glucose hypometabolism was detected in a cluster corresponding to the lateral-caudal substantia nigra and temporo-occipital cortical regions. Dopamine synthesis capacity was reduced with peaks in the bilateral posterior putamen, correlating with ipsilateral nigral activity. Dopamine depleted clusters were used to define seeds in a whole-brain resting-state functional connectivity analysis, revealing hypoconnectivity with the sensorimotor network and parts of the default mode network. In the hypoconnected clusters surrounding the inferior parietal region, connectivity with the putamen correlated positively with cortical glucose metabolism, although no significant hypometabolism was measured in this region in the whole-brain [18F]fluorodeoxyglucose PET group comparison. Motor symptom severity and Mini-Mental State Exam scores correlated with neuroimaging parameters. These results for the first time demonstrate correlations between clinical signs and trimodal neuroimaging markers of dysfunction along the entire nigro-striato-cortical axis, supporting the hypothesis of network-dependent degeneration. This interpretation is strengthened by an analysis of longitudinal data in a subgroup of this cohort which has been published in the meantime.
The gene panel analysis identified 13 of the participants with Parkinson’s disease as heterozygous GBA variant carriers (7 with p.E365K, 6 with p.T408M) and 42 as non-carriers. Both groups were demographically and clinically similar. Carriers’ global cognitive performance was slightly but significantly lower than non-carriers’. Levels of several plasma metabolites were different between groups. Expression of a metabolic covariance pattern of brain activity associated with Parkinson’s disease was more pronounced in variant carriers, and glucose metabolism was significantly lower in the medial and lateral parieto-occipital cortex. The distribution of hypometabolism resembled hypoactivity seen in dementia with Lewy bodies. Lower anterior striatal dopamine synthesis capacity in carriers suggested more advanced degeneration, while functional connectivity anticorrelations between striatal and occipital regions, which had been previously described in Parkinson’s disease dementia, were detected as potential correlates of the increased risk for cognitive decline. As disease-modifying therapies targeting glucocerebrosidase, the enzyme encoded by GBA, are being investigated, neuroimaging markers could be useful to monitor treatment effects.
Further conclusions can be drawn when both studies’ results are regarded in conjunction. There was no direct overlap between findings in each modality, therefore it is unlikely that the comparison between Parkinson’s disease patients and controls was distorted by the inclusion of GBA variant carriers in the patient group. Some regions were, however, affected in both studies across different modalities. For example, in the inferior parietal cortex, where hypoconnectivity correlated with metabolism in Parkinson’s disease, [18F]fluorodeoxyglucose uptake was significantly reduced in carriers of GBA variants compared to non-carriers. Assuming that disconnection leads to hypoactivity, this implies that network degeneration might be more advanced in carriers.
In conclusion, these studies demonstrate previously unknown interconnections between multimodal measures of brain function, genetics and behavior in Parkinson’s disease. These findings might guide the development of biomarkers for clinical trials and personalized patient care.