Executive processes in Parkinson's disease: FDG-PET and network analysis

Significant progress has been made in our understanding of the neurobiology of Parkinson’s disease (PD). Post-mortem studies are an important step and could help to comprehend not only the progression of motor symptoms, but also the involvement of other clinical domains, including cognition, behavior and impulse control disorders (ICDs). The correlation of neuropathological extension of the disease with the clinical stages remains challenging. Molecular imaging, including positron emission tomography (PET) and single photon computed tomography (SPECT), could allow for bridging the gap by providing in vivo evidence of disease extension. In the last decade, we have observed a plethora of reports describing improvements in the sensitivity of neuroimaging techniques. These data contribute to increasing the accuracy of PD diagnosis, differentiating PD from other causes of parkinsonism and also obtaining a surrogate marker of disease progression. FDG-PET has been used to measure cerebral metabolic rates of glucose, a proxy for neuronal activity, in PD. Many studies have shown that this technique could be used in early PD, where reduced metabolic activity correlates with disease progression and could predict histopathological diagnosis. The aim of this work is to report two particular cases of PD in which the assessment of brain metabolic activity (from FDG-PET) has been combined with clinical aspects of non-motor symptoms. Integration of information on neuropsychological and metabolic imaging allows us to improve the treatment of PD patients irrespective of age.

Download Full-text

Gene Co-Expression Network Analysis Implicates microRNA Processing in Parkinson’s Disease Pathogenesis

Neurodegenerative Diseases ◽

10.1159/000490427 ◽

2018 ◽

Vol 18 (4) ◽

pp. 191-199 ◽

Cited By ~ 3

Author(s):

Jason A. Chen

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Network Analysis ◽

Statistical Power ◽

Association Studies ◽

Model Systems ◽

Specific Cell ◽

Genome Wide Association Studies ◽

Microrna Processing ◽

Highly Correlated

Background: Recent advances in genetics have provided insights into important inherited causes of Parkinson’s disease (PD), but the underlying biological mechanisms are still incompletely understood. Gene expression studies have pointed toward the dysregulation of neuroinflammation, mitochondrial function, and protein degradation pathways. Objective: We aimed to identify groups of dysregulated genes in PD. Methods: In order to increase statistical power and control for potential confounders, we re-analyzed transcriptomic data from PD patients and model systems, integrating additional genomic data using a systems biology approach. Using weighted gene co-expression network analysis, we partitioned genes into co-expressed modules. Results: One co-expression module, M13, had an expression trajectory that was highly correlated with PD, was not characterized by any specific cell type markers, and was enriched in PD genes identified by genome-wide association studies. Genes within M13 seemed to be related to global microRNA biogenesis, and DICER1 and AGO3 were highly connected within the module. The NUCKS1 gene, previously identified as part of the PARK16 locus, was also a hub gene within M13. Conclusion: These results suggest that microRNA processing and function may play a role in the pathogenesis of PD, and thus may represent a useful target for future drug development.

Download Full-text

Swallowing Assessment in Parkinson’s Disease: Patient and Investigator Reported Outcome Measures are not Aligned

Dysphagia ◽

10.1007/s00455-020-10201-3 ◽

2020 ◽

Author(s):

M. R. A. van Hooren ◽

R. Vos ◽

M. G. M. H. Florie ◽

W. Pilz ◽

B. Kremer ◽

...

Keyword(s):

Neural Network ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Network Analysis ◽

Outcome Measures ◽

Treatment Plan ◽

Neural Network Analysis ◽

Mlp Neural Network ◽

Swallowing Assessment ◽

The Relationship

Abstract This study determines the relationship between patient and investigator reported outcome measures (PROMs versus IROMs) on oropharyngeal dysphagia (OD) in Parkinson’s disease (PD). The PROMs used are the MD Anderson Dysphagia Inventory (MDADI) and the Dysphagia Severity Scale (DSS). The IROMs used are fiberoptic endoscopic evaluation of swallowing (FEES) and videofluoroscopy of swallowing (VFS). Ninety dysphagic PD patients were included. Multilayer perceptron (MLP) neural network analysis was used to investigate the relationship between PROMs and IROMs on OD in PD. MLP neural network analysis showed a moderate agreement between PROMs and IROMs, with an area under the curve between 0.6 and 0.7. Two-step cluster analysis revealed several clusters of patients with similar scores on FEES and/or VFS variables, but with significant different scores on MDADI and DSS variables. This study highlights that there are PD patients with similar FEES and/or VFS findings that cannot be lumped together under the same pathophysiological umbrella due to their differences in PROMs. Since the exact origin of these differences is not fully understood, it seems appropriate for the time being to take into account the different dimensions of OD during the swallowing assessment so that they can be included in a patient-tailored treatment plan.

Download Full-text