9 resultados para Parkinson disease

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Pochi studi hanno indagato il profilo dei sintomi non-motori nella malattia di Parkinson associata al gene glucocerebrosidasi (GBA). Questo studio è mirato alla caratterizzazione dei sintomi non-motori, con particolare attenzione alla valutazione delle funzioni neurovegetativa, cognitiva e comportamentale, nel parkinsonismo associato a mutazione del gene GBA con la finalità di verificare se tali sintomi non-motori siano parte dello spettro clinico di questi pazienti. E’ stato condotto su una coorte di pazienti affetti da malattia di Parkinson che erano stati tutti sottoposti ad una analisi genetica per la ricerca di mutazioni in uno dei geni finora associati alla malattia di Parkinson. All’interno di questa coorte omogenea sono stati identificati due gruppi diversi in relazione al genotipo (pazienti portatori della mutazione GBA e pazienti non portatori di nessuna mutazione) e le caratteristiche non-motorie sono state confrontate nei due gruppi. Sono state pertanto indagati il sistema nervoso autonomo, mediante studio dei riflessi cardiovascolari e analisi dei sintomi disautonomici, e le funzioni cognitivo-comportamentali in pazienti affetti da malattia di Parkinson associata a mutazione del gene GBA. I risultati sono stati messi a confronto con il gruppo di controllo. Lo studio ha mostrato che i pazienti affetti da malattia di Parkinson associata a mutazione del gene GBA presentavano maggiore frequenza di disfunzioni ortosimpatiche, depressione, ansia, apatia, impulsività, oltre che di disturbi del controllo degli impulsi rispetto ai pazienti non portatori. In conclusione, i pazienti GBA positivi possono esprimere una sintomatologia non-motoria multidominio con sintomi autonomici, cognitivi e comportamentali in primo piano. Pertanto l’impostazione terapeutica in questi pazienti dovrebbe includere una accurata valutazione dei sintomi non-motori e un loro monitoraggio nel follow up clinico, allo scopo di ottimizzare i risultati e ridurre i rischi di complicazioni.

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During recent years a consistent number of central nervous system (CNS) drugs have been approved and introduced on the market for the treatment of many psychiatric and neurological disorders, including psychosis, depression, Parkinson disease and epilepsy. Despite the great advancements obtained in the treatment of CNS diseases/disorders, partial response to therapy or treatment failure are frequent, at least in part due to poor compliance, but also genetic variability in the metabolism of psychotropic agents or polypharmacy, which may lead to sub-therapeutic or toxic plasma levels of the drugs, and finally inefficacy of the treatment or adverse/toxic effects. With the aim of improving the treatment, reducing toxic/side effects and patient hospitalisation, Therapeutic Drug Monitoring (TDM) is certainly useful, allowing for a personalisation of the therapy. Reliable analytical methods are required to determine the plasma levels of psychotropic drugs, which are often present at low concentrations (tens or hundreds of nanograms per millilitre). The present PhD Thesis has focused on the development of analytical methods for the determination of CNS drugs in biological fluids, including antidepressants (sertraline and duloxetine), antipsychotics (aripiprazole), antiepileptics (vigabatrin and topiramate) and antiparkinsons (pramipexole). Innovative methods based on liquid chromatography or capillary electrophoresis coupled to diode-array or laser-induced fluorescence detectors have been developed, together with the suitable sample pre-treatment for interference removal and fluorescent labelling in case of LIF detection. All methods have been validated according to official guidelines and applied to the analysis of real samples obtained from patients, resulting suitable for the TDM of psychotropic drugs.

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In this PhD thesis 3 projects were addressed focusing on the melanopsin retinal ganglion cells (mRGCs) system and its relevance for circadian rhythms and sleep in neurodegeneration. The first project was aimed at completing the characterization of mRGCs system in hereditary optic neuropathies (LHON and DOA). We confirmed that mRGCs are relatively spared also in post-mortem retinal specimens of a DOA case and pupillometric evaluation of LHON patients showed preservation of the pupillary light reflex, with attenuated responses compared to controls. Cell studies failed to indicate a protective role exerted by melanopsin itself. The second project was aimed at characterizing the possible occurrence of optic neuropathy and rest-activity circadian rhythm dysfunction in Alzheimer (AD) and Parkinson disease (PD), as well as, at histological level, the possible involvement of mRGCs in AD. OCT studies demonstrated a subclinical optic neuropathy in both AD and PD patients, with a different pattern involving the superior and nasal quadrants in AD and the temporal quadrant in PD. Actigraphic studies demonstrated a tendency towards an increased intradaily variability (IV) and reduced relative amplitude (RA) of rest-activity circadian rhythm in AD and a significant increased IV a reduced RA in PD. Immunohistochemical analysis of post-mortem retinal specimens and optic nerve cross-sections of neuropathologically confirmed AD cases demonstrated a significant loss of mRGCs and a nearly significant loss of axons in AD compared to controls. The mRGCs were affected in AD independently from age and magnitude of axonal loss. Overall these results suggest a role of the mRGCs system in the pathogenesis of circadian dysfunction in AD. The third project was aimed at evaluating the possible association between a single nucleotide polymorphism of the OPN4 gene and chronotype or SAD, failing to find any significant association with chronotype, but showing a non-significant increment of TT genotype in SAD.

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Aim of this study is to describe the possible diagnostic value of sleep disturbances in the differential diagnosis of neurodegenerative diseases characterized by parkinsonism at onset. 42 consecutive patients with parkinsonian features and disease duration up to 3 years were included in the BO-ProPark study. Each patient was evaluated twice, at baseline (T0) and 16 months later (T1). Patients were diagnosed as Parkinson disease (PD, 27 patients), PD plus (PD with cognitive impairment/dementia or dysautonomia, 4 patients) and parkinsonian syndrome (PS, 11 patients). All patients underwent a full night video-polysomnography scored by a neurologist blinded to the clinical diagnosis. Sleep efficiency and total sleep time were reduced in all patients; wake after sleep onset was higher in patients with atypical parkinsonisms than in PD patients. No significant differences between groups of patients were detected in other sleep parameters. The mean percentage of epochs with enhanced tonic muscle EMG activity during REM sleep was higher in PD plus and PS than in PD. No difference in phasic muscle EMG activity during REM sleep was seen between the two groups. REM behaviour disorder was more frequent in PD plus and PS than in PD patients. Our data suggest that REM sleep motor control is more frequently impaired at disease onset in patients with PS and PD plus compared to PD patients. The presence of RBD or an enhanced tonic muscle EMG activity in a patient with recent onset parkinsonian features should suggest a diagnosis of atypical parkinsonism, rather than PD. More data are needed to establish the diagnostic value of these features in the differential diagnosis of parkinsonisms. The evaluation of sleep disorders may be a useful tool in the differential diagnosis of parkinsonism at onset.

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Background: cognitive impairment is one of the non motor features widely descripted in parkinsonian syndrome, it has been related to the motor characteristics of the parkinsonian syndrome, associated with neuropsychiatric dysfunction and the characteristic sleep and autonomic features. It has been shown to be highly prevalent at all disease stages and to contribute significantly to disability. Objectives: aim of this study is to evaluate longitudinally the cognitive and behavioral characteristics of patients with a parkinsonian syndrome at onset; to describe the cognitive and behavioral characteristics of each parkinsonian syndrome; to define in PD patients at onset the presence of MCI or Parkinson disease dementia; to correlate the cognitive and behavioral characteristics with the features of the parkinsonian syndrome and with the associated sleep and autonomic features. Results: we recruited 55 patients, 22 did not present cognitive impairment both at T0 and at T1. 18 patients presented a progression of cognitive impairment. Progressive cognitively impaired patients were older and presented the worst motor phenotype. Progression of cognitive impairment was not associated to sleep and autonomic features. Conclusion: the evaluation of cognitive impairment could not be useful as a predictor of a correct diagnosis but each non motor domain will help to clarify and characterize the motor syndrome. The diagnosis of parkinsonian disorders lies in building a clinical profile in conjunction with other clinical characteristics such as mode of presentation, disease progression, response to medications, sleep and autonomic features.

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Impairment of postural control is a common consequence of Parkinson's disease (PD) that becomes more and more critical with the progression of the disease, in spite of the available medications. Postural instability is one of the most disabling features of PD and induces difficulties with postural transitions, initiation of movements, gait disorders, inability to live independently at home, and is the major cause of falls. Falls are frequent (with over 38% falling each year) and may induce adverse consequences like soft tissue injuries, hip fractures, and immobility due to fear of falling. As the disease progresses, both postural instability and fear of falling worsen, which leads patients with PD to become increasingly immobilized. The main aims of this dissertation are to: 1) detect and assess, in a quantitative way, impairments of postural control in PD subjects, investigate the central mechanisms that control such motor performance, and how these mechanism are affected by levodopa; 2) develop and validate a protocol, using wearable inertial sensors, to measure postural sway and postural transitions prior to step initiation; 3) find quantitative measures sensitive to impairments of postural control in early stages of PD and quantitative biomarkers of disease progression; and 4) test the feasibility and effects of a recently-developed audio-biofeedback system in maintaining balance in subjects with PD. In the first set of studies, we showed how PD reduces functional limits of stability as well as the magnitude and velocity of postural preparation during voluntary, forward and backward leaning while standing. Levodopa improves the limits of stability but not the postural strategies used to achieve the leaning. Further, we found a strong relationship between backward voluntary limits of stability and size of automatic postural response to backward perturbations in control subjects and in PD subjects ON medication. Such relation might suggest that the central nervous system presets postural response parameters based on perceived maximum limits and this presetting is absent in PD patients OFF medication but restored with levodopa replacement. Furthermore, we investigated how the size of preparatory postural adjustments (APAs) prior to step initiation depend on initial stance width. We found that patients with PD did not scale up the size of their APA with stance width as much as control subjects so they had much more difficulty initiating a step from a wide stance than from a narrow stance. This results supports the hypothesis that subjects with PD maintain a narrow stance as a compensation for their inability to sufficiently increase the size of their lateral APA to allow speedy step initiation in wide stance. In the second set of studies, we demonstrated that it is possible to use wearable accelerometers to quantify postural performance during quiet stance and step initiation balance tasks in healthy subjects. We used a model to predict center of pressure displacements associated with accelerations at the upper and lower back and thigh. This approach allows the measurement of balance control without the use of a force platform outside the laboratory environment. We used wearable accelerometers on a population of early, untreated PD patients, and found that postural control in stance and postural preparation prior to a step are impaired early in the disease when the typical balance and gait intiation symptoms are not yet clearly manifested. These novel results suggest that technological measures of postural control can be more sensitive than clinical measures. Furthermore, we assessed spontaneous sway and step initiation longitudinally across 1 year in patients with early, untreated PD. We found that changes in trunk sway, and especially movement smoothness, measured as Jerk, could be used as an objective measure of PD and its progression. In the third set of studies, we studied the feasibility of adapting an existing audio-biofeedback device to improve balance control in patients with PD. Preliminary results showed that PD subjects found the system easy-to-use and helpful, and they were able to correctly follow the audio information when available. Audiobiofeedback improved the properties of trunk sway during quiet stance. Our results have many implications for i) the understanding the central mechanisms that control postural motor performance, and how these mechanisms are affected by levodopa; ii) the design of innovative protocols for measuring and remote monitoring of motor performance in the elderly or subjects with PD; and iii) the development of technologies for improving balance, mobility, and consequently quality of life in patients with balance disorders, such as PD patients with augmented biofeedback paradigms.

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With life expectancies increasing around the world, populations are getting age and neurodegenerative diseases have become a global issue. For this reason we have focused our attention on the two most important neurodegenerative diseases: Parkinson’s and Alzheimer’s. Parkinson’s disease is a chronic progressive neurodegenerative movement disorder of multi-factorial origin. Environmental toxins as well as agricultural chemicals have been associated with PD. Has been observed that N/OFQ contributes to both neurotoxicity and symptoms associated with PD and that pronociceptin gene expression is up-regulated in rat SN of 6-OHDA and MPP induced experimental parkinsonism. First, we investigated the role of N/OFQ-NOP system in the pathogenesis of PD in an animal model developed using PQ and/or MB. Then we studied Alzheimer's disease. This disorder is defined as a progressive neurologic disease of the brain leading to the irreversible loss of neurons and the loss of intellectual abilities, including memory and reasoning, which become severe enough to impede social or occupational functioning. Effective biomarker tests could prevent such devastating damage occurring. We utilized the peripheral blood cells of AD discordant monozygotic twin in the search of peripheral markers which could reflect the pathology within the brain, and also support the hypothesis that PBMC might be a useful model of epigenetic gene regulation in the brain. We investigated the mRNA levels in several genes involve in AD pathogenesis, as well DNA methylation by MSP Real-Time PCR. Finally by Western Blotting we assess the immunoreactivity levels for histone modifications. Our results support the idea that epigenetic changes assessed in PBMCs can also be useful in neurodegenerative disorders, like AD and PD, enabling identification of new biomarkers in order to develop early diagnostic programs.

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Advances in biomedical signal acquisition systems for motion analysis have led to lowcost and ubiquitous wearable sensors which can be used to record movement data in different settings. This implies the potential availability of large amounts of quantitative data. It is then crucial to identify and to extract the information of clinical relevance from the large amount of available data. This quantitative and objective information can be an important aid for clinical decision making. Data mining is the process of discovering such information in databases through data processing, selection of informative data, and identification of relevant patterns. The databases considered in this thesis store motion data from wearable sensors (specifically accelerometers) and clinical information (clinical data, scores, tests). The main goal of this thesis is to develop data mining tools which can provide quantitative information to the clinician in the field of movement disorders. This thesis will focus on motor impairment in Parkinson's disease (PD). Different databases related to Parkinson subjects in different stages of the disease were considered for this thesis. Each database is characterized by the data recorded during a specific motor task performed by different groups of subjects. The data mining techniques that were used in this thesis are feature selection (a technique which was used to find relevant information and to discard useless or redundant data), classification, clustering, and regression. The aims were to identify high risk subjects for PD, characterize the differences between early PD subjects and healthy ones, characterize PD subtypes and automatically assess the severity of symptoms in the home setting.

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Parkinson’s disease is a neurodegenerative disorder due to the death of the dopaminergic neurons of the substantia nigra of the basal ganglia. The process that leads to these neural alterations is still unknown. Parkinson’s disease affects most of all the motor sphere, with a wide array of impairment such as bradykinesia, akinesia, tremor, postural instability and singular phenomena such as freezing of gait. Moreover, in the last few years the fact that the degeneration in the basal ganglia circuitry induces not only motor but also cognitive alterations, not necessarily implicating dementia, and that dopamine loss induces also further implications due to dopamine-driven synaptic plasticity got more attention. At the present moment, no neuroprotective treatment is available, and even if dopamine-replacement therapies as well as electrical deep brain stimulation are able to improve the life conditions of the patients, they often present side effects on the long term, and cannot recover the neural loss, which instead continues to advance. In the present thesis both motor and cognitive aspects of Parkinson’s disease and basal ganglia circuitry were investigated, at first focusing on Parkinson’s disease sensory and balance issues by means of a new instrumented method based on inertial sensor to provide further information about postural control and postural strategies used to attain balance, then applying this newly developed approach to assess balance control in mild and severe patients, both ON and OFF levodopa replacement. Given the inability of levodopa to recover balance issues and the new physiological findings than underline the importance in Parkinson’s disease of non-dopaminergic neurotransmitters, it was therefore developed an original computational model focusing on acetylcholine, the most promising neurotransmitter according to physiology, and its role in synaptic plasticity. The rationale of this thesis is that a multidisciplinary approach could gain insight into Parkinson’s disease features still unresolved.