Mariangela Pierantozzi

Autonomic symptoms in Parkinson’s disease result from variable involvement of the central and peripheral systems, but many aspects remain unclear. The analysis of functional connectivity has shown promising results in assessing the pathophysiology of Parkinson’s disease. This study aims to investigate the association between autonomic symptoms and cortical functional connectivity in early Parkinson’s disease patients using high-density EEG. 53 early Parkinson’s disease patients (F/M 18/35) and 49 controls (F/M 20/29) were included. Autonomic symptoms were evaluated using the Scales for Outcomes in Parkinson’s disease–Autonomic Dysfunction score. Data were recorded with a 64-channel EEG system. We analyzed cortical functional connectivity, based on weighted phase-lag index, in θ-α-β-low-γ bands. A network-based statistic was used to perform linear regression between Scales for Outcomes in Parkinson’s disease–Autonomic Dysfunction score and functional connectivity in Parkinson’s disease patients. We observed a positive relation between the Scales for Outcomes in Parkinson’s disease–Autonomic Dysfunction score and α-functional connectivity (network τ = 2.8, P = 0.038). Regions with higher degrees were insula and limbic lobe. Moreover, we found positive correlations between the mean connectivity of this network and the gastrointestinal, cardiovascular, and thermoregulatory domains of Scales for Outcomes in Parkinson’s disease–Autonomic Dysfunction. Our results revealed abnormal functional connectivity in specific areas in Parkinson’s disease patients with greater autonomic symptoms. Insula and limbic areas play a significant role in the regulation of the autonomic system. Increased functional connectivity in these regions might represent the central compensatory mechanism of peripheral autonomic dysfunction in Parkinson’s disease.

Introduction: Sleep disorders are frequent non-motor symptoms affecting patients with Parkinson’s disease (PD). Insomnia represents the most common sleep disorder. Parkinson’s disease Sleep Scale 2 (PDSS-2) is a specific tool to investigate sleep problems in PD. The General Sleep Disturbances Scale (GSDS) was a general scale validated for the Italian population. Our goal was to assess the psychometric characteristics of PDSS-2 and the GSDS in this population, calculating a cut-off score for insomnia symptoms by using subitems of PDSS-2. Methods: Patients admitted at the PD Unit of the Hospital of Rome Tor Vergata outpatient clinic and those afferent to PD associations were asked to complete PDSS-2 and GSDS to be correlated to identify a cut-off for insomnia symptoms. Items 1,2,3,8,13 of PDSS-2 were used to detect insomnia. An ROC curve to assess a cut-off score for insomnia was determined. A cross-cultural analysis of PD population characteristics was performed. Results: In total, 350 PD patients were recruited. Cronbach’s alpha was high for the total score (0.828 for PDSS-2 and 0.832 for GSDS). A cross-cultural analysis did not show any significant p-value. The ROC curve yielded an AUC of 0.79 (CI: 0.75–0.84). The cut-off value for insomnia disorder based on items 1,2,3,8,13 of PDSS-2 was >10, demonstrating a sensitivity of 76% and a specificity of 69% in determining the presence of subjective insomnia symptoms in PD. Discussion: PDSS-2 is demonstrated to be a valid, specific tool to address sleep disturbances in PD patients. A cut-off score of 10 for items 1,2,3,8,13 was identified for detecting insomnia symptoms in PD patients.

Patients with Parkinson’s disease (PD) tend to sleep more frequently in the supine position and less often change head and body position during sleep. Besides sleep quality and continuity, head and body positions are crucial for glymphatic system (GS) activity. This pilot study evaluated sleep architecture and head position during each sleep stage in idiopathic PD patients without cognitive impairment, correlating sleep data to patients’ motor and non-motor symptoms (NMS). All patients underwent the multi-night recordings, which were acquired using the Sleep Profiler headband. Sleep parameters, sleep time in each head position, and percentage of slow wave activity (SWA) in sleep, stage 3 of non-REM sleep (N3), and REM sleep in the supine position were extracted. Lastly, correlations with motor impairment and NMS were performed. Twenty PD patients (65.7 ± 8.6 y.o, ten women) were included. Sleep architecture did not change across the different nights of recording and showed the prevalence of sleep performed in the supine position. In addition, SWA and N3 were more frequently in the supine head position, and N3 in the supine decubitus correlated with REM sleep performed in the same position; this latter correlated with the disease duration (correlation coefficient = 0.48, p-value = 0.03) and motor impairment (correlation coefficient = 0.53, p-value = 0.02). These preliminary results demonstrated the importance of monitoring sleep in PD patients, supporting the need for preventive strategies in clinical practice for maintaining the lateral head position during the crucial sleep stages (SWA, N3, REM), essential for permitting the GS function and activity and ensuring brain health.

Introduction: Parkinson’s disease (PD) is a multisystem disease, involving several brain structures. fMRI studies reported abnormal functional connectivity (FC) in PD. EEG is an accessible method to evaluate cortical activity, which may be used to estimate FC. For this aim, we analyzed differences in FC between patients at early stages of PD and healthy controls (HC) using high-density EEG (HD-EEG). Methods: We enrolled 20 early-stage PD patients and 19 age-matched HC. Data were recorded with a 64-channels HD-EEG system. A source-reconstruction method was used to identify brain-region activity. FC was calculated using a weighted phase-lag index in θ-α-β bands. Network-based statistic was used to compare FC between PD and HC. Results: No statistical-significant differences were observed in spectral analysis between groups. PD patients showed a hypoconnected network in α-band primarily composed by frontal lobe, associated with a hyperconnected network in β band, including frontal, sensorimotor, limbic and temporal areas. Moreover, correlation between β FC in sensorimotor areas and PD motor impairment was found (r = 0.80, p = 0.003). Conclusion: HD-EEG revealed FC alterations since early stages of PD, as a tool complementary to fMRI, and it could be a useful early or even preclinical diagnostic marker of disease.

Non-motor symptoms (NMS) characterize the Parkinson’s disease (PD) clinical picture, and as well as motor fluctuations, PD patients can also experience NMS fluctuations (NMF). The aim of this observational study was to investigate the presence of NMS and NMF in patients with PD using the recently validated Non-Motor Fluctuation Assessment questionnaire (NoMoFa) and to evaluate their associations with disease characteristics and motor impairment. Patients with PD were consecutively recruited, and NMS, NMF, motor impairment, motor fluctuations, levodopa-equivalent daily dose, and motor performance were evaluated. One-third of the 25 patients included in the study (10 females, 15 males, mean age: 69.9 ± 10.3) showed NMF, and patients with NMF presented a higher number of NMS (p < 0.01). Static NMS and NoMoFa total score were positively associated with motor performance assessed with the Global Mobility Task (p < 0.01 and p < 0.001), and the latter was also correlated with motor impairment (p < 0.05) but not with motor fluctuations. Overall, this study shows evidence that NMF are frequently reported by mild-to-moderate PD patients and associated with an increased number of NMS. The relationship between NoMoFa total score and motor functioning highlights the importance of understanding the clinical role of NMS and NMF in the management of PD patients.

Subthalamic nucleus deep-brain stimulation (STN-DBS), in addition to a rapid improvement of Parkinson’s disease (PD) motor symptoms, can exert fast, local, neuromodulator activity, reducing β-synchronous oscillations between STN and the motor cortex with possible antikinetic features. However, STN-DBS modulation of β-band synchronization in extramotor cortical areas has been scarcely explored. For this aim, we investigated DBS-induced short-term effects on EEG-based cortical functional connectivity (FC) in β bands in six PD patients who underwent STN-DBS within the past year. A 10 min, 64-channel EEG recording was performed twice: in DBS-OFF and 60 min after DBS activation. Seven age-matched controls performed EEG recordings as the control group. A source-reconstruction method was used to identify brain-region activity. The FC was calculated using a weighted phase-lag index in β bands. Group comparisons were made using the Wilcoxon test. The PD patients showed a widespread cortical hyperconnectivity in β bands in both DBS-OFF and -ON states compared to the controls. Moreover, switching on STN-DBS determined an acute reduction in β FC, primarily involving corticocortical links of frontal, sensorimotor and limbic lobes. We hypothesize that an increase in β-band connectivity in PD is a widespread cortical phenomenon and that STN-DBS could quickly reduce it in the cortical regions primarily involved in basal ganglia–cortical circuits.

Most research analyzed gut-microbiota alterations in Parkinson’s disease (PD) through cross-sectional studies, as single snapshots, without considering the time factor to either confirm methods and findings or observe longitudinal variations. In this study, we introduce the time factor by comparing gut-microbiota composition in 18 PD patients and 13 healthy controls (HC) at baseline and at least 1 year later, also considering PD clinical features. PD patients and HC underwent a fecal sampling at baseline and at a follow-up appointment. Fecal samples underwent sequencing and 16S rRNA amplicons analysis. Patients’clinical features were valued through Hoehn&Yahr (H&Y) staging-scale and Movement Disorder Society Unified PD Rating Scale (MDS-UPDRS) Part-III. Results demonstrated stability in microbiota findings in both PD patients and HC over a period of 14 months: both alfa and beta diversity were maintained in PD patients and HC over the observation period. In addition, differences in microbiota composition between PD patients and HC remained stable over the time period. Moreover, during the same period, patients did not experience any worsening of either staging or motor impairment. Our findings, highlighting the stability and reproducibility of the method, correlate clinical and microbiota stability over time and open the scenario to more extensive longitudinal evaluations.

Rapid eye movement (REM) sleep behavior disorder (RBD) is a risk factor for developing Parkinson’s disease (PD) and may represent its prodromal state. We compared neuropsychological and neuropsychiatric phenotypes of idiopathic (i) RBD, PD and healthy comparators (HC) in order to identify iRBD specific characteristics. Thirty-eight patients with iRBD, 38 PD patients with RBD (PD + RBD), 38 PD patients without RBD (PD-RBD) and 38 HC underwent a comprehensive neurological, neuropsychological and neuropsychiatric evaluation. iRBD, PD + RBD and PD-RBD performed worse than HC in short-term verbal memory, praxia, language and executive functions. iRBD had higher levels of anxiety, depression, apathy and alexithymia than HC. iRBD had higher levels of apathy than PD + RBD. Both PD groups had higher levels of anxiety and depression than HC. Surprisingly, iRBD performed better than all groups in long-term verbal memory. Patients diagnosed with iRBD are characterized by poor global cognitive performance, but better long-term memory and higher levels of depression, anxiety, alexithymia and apathy. Alexithymia and apathy in patients diagnosed with iRBD may be the expression of precocious derangement of emotional regulation, subsequently observed also in PD. Cognitive and neuropsychiatric symptoms of iRBD are early clinical manifestations of widespread neurodegeneration.