Dynamic functional connectivity captures temporal variations of functional connectivity during MRI acquisition and it may be a suitable method to detect cognitive changes in Parkinson’s disease. In this study, we evaluated 118 patients with Parkinson’s disease matched for age, sex and education with 35 healthy control subjects. Patients with Parkinson’s disease were classified with normal cognition (n = 52), mild cognitive impairment (n = 46), and dementia (n = 20) based on an extensive neuropsychological evaluation. Resting state functional MRI and a sliding-window approach were used to study the dynamic functional connectivity. Dynamic analysis suggested two distinct connectivity ‘States’ across the entire group: a more frequent, segregated brain state characterized by the predominance of within-network connections, State I, and a less frequent, integrated state with strongly connected functional internetwork components, State II. In Parkinson’s disease, State I occurred 13.89% more often than in healthy control subjects, paralleled by a proportional reduction of State II. Parkinson’s disease subgroups analyses showed the segregated state occurred more frequently in Parkinson’s disease dementia than in mild cognitive impairment and normal cognition groups. Further, patients with Parkinson’s disease dementia dwelled significantly longer in the segregated State I, and showed a significant lower number of transitions to the strongly interconnected State II compared to the other subgroups. Our study indicates that dementia in Parkinson’s disease is characterized by altered temporal properties in dynamic connectivity. In addition, our results show that increased dwell time in the segregated state and reduced number of transitions between states are associated with presence of dementia in Parkinson’s disease. Further studies on dynamic functional connectivity changes could help to better understand the progressive dysfunction of networks between Parkinson’s disease cognitive states.

Background. Parkinson's disease (PD) is a progressive neurodegenerative disorder which may be misdiagnosed with atypical conditions such as Multiple System Atrophy (MSA), due to overlapping clinical features. MicroRNAs (miRNAs) are small noncoding RNAs with a key role in post-transcriptional gene regulation. We hypothesized that identification of a distinct set of circulating miRNAs (cmiRNAs) could distinguish patients affected by PD from MSA and healthy individuals. Results. Using TaqMan Low Density Array technology, we analysed 754 miRNAs and found 9 cmiRNAs differentially expressed in PD and MSA patients compared to healthy controls. We also validated a set of 4 differentially expressed cmiRNAs in PD and MSA patients versus controls. More specifically, miR-339-5p was downregulated, whereas miR-223*, miR-324-3p and mir-24 were upregulated in both diseases. We found cmiRNAs specifically deregulated in PD (downregulation of miR-30c and miR-148b) and in MSA (upregulation of miR-148b). Finally, comparing MSA and PD, we identified 3 upregulated cmiRNAs in MSA serum (miR-24, miR-34b, miR-148b). Conclusions. Our results suggest that cmiRNA signatures discriminate PD from MSA patients and healthy controls and may be considered specific, non-invasive biomarkers for differential diagnosis.

Mild cognitive impairment (PD-MCI) and dementia (PDD) are among the most frequent non-motor symptoms in Parkinson’s disease (PD). PD-MCI is six times more likely than age-matched controls to develop dementia and the PDD prevalence is 80% after 15–20 years of disease. Therefore, research has focused on the identification of early dementia biomarkers including specific cognitive at-risk profiles hoping to implement therapeutic interventions when they are most likely to be efficacious. However, given the heterogeneous neuropathological, neurochemical, and neuropsychological nature of cognitive deficits, definition of a comprehensive cognitive model of PDD is a challenge. Evidence from neuroimaging studies using different methods and techniques suggests that in addition to degeneration of the dopaminergic system, other mechanisms have a role including β-amyloid and tau deposition, and that specific cognitive scales could help identifying a malignant profile. Prospective studies combining neuroimaging techniques and specific cognitive tests are required to define the interplay between the various neurodegenerative processes and the contribution of structural disconnection in brain functional networks, heralding the development of dementia in PD.

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