Identification of a metabolic brain network characterizing essential tremor

Essential tremor (ET) is one of the most common movement disorders in adulthood, characterized by an action tremor of the upper extremities. In addition, a significant amount of patients exhibit cognitive impairments. The pathophysiology of the disease is still poorly understood. The cerebellum and the cerebello-thalamo-cortical network appear to have a central role in pathophysiological processes. We aimed to identify a disease-specific network on a metabolic basis (ETRP) as well as to investigate the effect of deep brain stimulation (DBS) on the network as well as the correlation between network expression, tremor severity, disease duration and cognitive impairment. Lastly, the goal was to compare network-level metabolic brain changes in ET and the Parkinson's disease-related pattern (PDRP). Sixteen ET patients and eighteen age- and gender-matched healthy controls underwent clinical tremor assessment using the Fahn Tolosa Marin scale to assess tremor severity, 18F-fluorodesoxyglucose PET of the brain and neuropsychological testing. For network validation a second, independent cohort of 8 ET patients with DBS were used with the stimulator turned ON and OFF. For network identification, a multivariate spatial covariance analysis, called scaled subprofile model based on principal component analysis (SSM/PCA), was applied to the FDG PET scans. Topographic Profile Rating (TPR) has been utilized prospectively on individual images to assess the pattern expression. ANOVA and Kruskal-Wallis with post-hoc corrections tests, Student’s t-test and Chi square tests were used to compare demographical, clinical and neuropsychological data. ETRP was characterized by relative hypermetabolism in the cerebellum, brain stem and temporo-occipital areas. Relatively decreased metabolic activity was shown in fronto-temporal and parietal cortices, including the primary motor cortex. Network expression showed inverse correlation with tremor severity and disease duration indicating a compensatory role of the network. Positive correlation was found between ETRP expression and cognitive impairment. DBS significantly reduced tremor severity: however, it did not have any impact on cognitive performance or network expression. ET patients performed significantly worse on neurocognitive testing, with notable deficits observed in working memory, verbal memory, and executive functions. The results indicate that ET is characterized by distinct functional changes at the network level, associated with both tremor genesis and cognition. The cerebellum plays a key role in the pathophysiology of ET. The negative correlation of network expression with disease duration and tremor severity indicates a possible compensatory function of the network, which decreases with disease progression. Some previous studies have suggested a temporary cerebellar hypermetabolism in ET patients primarily serving as a compensatory mechanism that subsides over time. Furthermore, an association between cognitive deficits and altered cerebello-cortical connectivity has been observed, which is consistent with the findings in this study. This study revealed a positive correlation between PDRP and ETRP expression; however, the minimal overlap in voxel weights suggests that Parkinson’s disease and ET are characterized by different metabolic disease-related patterns and mechanisms. The different correlations of ETRP with motor and cognitive symptoms suggest different neuronal mechanisms for tremor and cognitive deficits.