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See detailGBA variants in Parkinson’s disease: clinical, metabolomic and multimodal neuroimaging phenotypes
Greuel, Andrea; Trezzi, Jean-Pierre UL; Glaab, Enrico UL et al

in Movement Disorders (in press)

Background: Alterations in the GBA gene (NM_000157.3) are the most important genetic risk factor for Parkinson’s disease. Biallelic GBA mutations cause the lysosomal storage disorder Gaucher´s disease ... [more ▼]

Background: Alterations in the GBA gene (NM_000157.3) are the most important genetic risk factor for Parkinson’s disease. Biallelic GBA mutations cause the lysosomal storage disorder Gaucher´s disease. The GBA variants p.E365K and p.T408M are associated with Parkinson’s but not with Gaucher´s disease. The pathophysiological role of these variants needs to be further explored. Objective: This study analyzed the clinical, neuropsychological, metabolic and neuroimaging phenotypes of Parkinson’s disease patients carrying the GBA variants p.E365K and p.T408M. Methods: GBA was sequenced in 56 mid-stage Parkinson’s disease patients. Carriers of GBA variants were compared to non-carriers regarding clinical history and symptoms, neuropsychological features, metabolomics and multimodal neuroimaging. Blood plasma gas chromatography coupled to mass spectrometry, [18F]FDopa PET, [18F]FDG PET, and resting-state fMRI were performed. Results: Sequence analysis detected 13 heterozygous GBA variant carriers (seven with p.E365K, six with p.T408M). One patient carried a GBA mutation (p.N409S) and was excluded. Clinical history and symptoms were not significantly different between groups. Global cognitive performance was lower in variant carriers. Metabolomic group differences were suggestive of more severe Parkinson’s disease-related alterations in carriers versus non-carriers. [18F]FDopa and [18F]FDG PET showed signs of a more advanced disease; [18F]FDG PET and fMRI showed similarities with Lewy body dementia and Parkinson’s disease dementia in carriers. Conclusions: This is the first study to comprehensively assess (neuro-)biological phenotypes of GBA variants in Parkinson’s disease. Metabolomics and neuroimaging detected more significant group differences than clinical and behavioral evaluation. These alterations could be promising to monitor effects of disease-modifying treatments targeting glucocerebrosidase metabolism. [less ▲]

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See detailIntegrative analysis of blood metabolomics and PET brain neuroimaging data for Parkinson's disease
Glaab, Enrico UL; Trezzi, Jean-Pierre UL; Greuel, Andrea et al

in Neurobiology of Disease (2019), 124(1), 555-562

The diagnosis of Parkinson's disease (PD) often remains a clinical challenge. Molecular neuroimaging can facilitate the diagnostic process. The diagnostic potential of metabolomic signatures has recently ... [more ▼]

The diagnosis of Parkinson's disease (PD) often remains a clinical challenge. Molecular neuroimaging can facilitate the diagnostic process. The diagnostic potential of metabolomic signatures has recently been recognized. Methods: We investigated whether the joint data analysis of blood metabolomics and PET imaging by machine learning provides enhanced diagnostic discrimination and gives further pathophysiological insights. Blood plasma samples were collected from 60 PD patients and 15 age- and gender-matched healthy controls. We determined metabolomic profiles by gas chromatography coupled to mass spectrometry (GC-MS). In the same cohort and at the same time we performed FDOPA PET in 44 patients and 14 controls and FDG PET in 51 patients and 16 controls. 18 PD patients were available for a follow-up exam after one year. Both data sets were analysed by two machine learning approaches, applying either linear support vector machines or random forests within a leave-one-out cross-validation and computing receiver operating characteristic (ROC) curves. Results: In the metabolomics data, the baseline comparison between cases and controls as well as the followup assessment of patients pointed to metabolite changes associated with oxidative stress and inflammation. For the FDOPA and FDG PET data, the diagnostic predictive performance (DPP) in the ROC analyses was highest when combining imaging features with metabolomics data (ROC AUC for best FDOPA + metabolomics model: 0.98; AUC for best FDG + metabolomics model: 0.91). DPP was lower when using only PET attributes or only metabolomics signatures. Conclusion: Integrating blood metabolomics data combined with PET data considerably enhances the diagnostic discrimination power. Metabolomic signatures also indicate interesting disease-inherent changes in cellular processes, including oxidative stress response and inflammation. [less ▲]

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See detailCombining PET imaging and blood metabolomics data to improve machine learning models for Parkinson’s disease diagnosis
Glaab, Enrico UL; Trezzi, Jean-Pierre UL; Greuel et al

Poster (2018, October 08)

Objective: To investigate whether the integration of PET imaging and metabolomics data can provide improved machine learning models for PD diagnosis. Background: The reliable diagnosis of PD can remain ... [more ▼]

Objective: To investigate whether the integration of PET imaging and metabolomics data can provide improved machine learning models for PD diagnosis. Background: The reliable diagnosis of PD can remain challenging, even at the motor stage. PET imaging can be used to confirm the clinical diagnosis. However, limitations in the robustness of predictive features extracted from the data and the costs associated with PET imaging restrict its application. Using blood metabolomics data as an additional information source may provide improved combined diagnostic models and/or an initial filter to decide on whether to apply PET imaging. Methods: Metabolomics profiling of blood plasma samples using gas chromatography coupled to mass spectrometry (GC­MS) was conducted in 60 IPD patients and 15 healthy controls. After pre-processing, these data were compared to neuroimaging data for subsets of the same individuals using FDOPA PET (44 patients and 14 controls) and FDG PET (51 patients and 15 controls). Machine learning models using linear support vector machines were trained on 50% of the data and evaluated on a 50% hold­out test set using Receiver Operating Characteristic (ROC) curves. Next, standardized FDOPA and FDG PET intensity measurements were combined with those from the metabolomics data to build and evaluate sample classification models in the same manner as for the individual datasets. Results: Both for the FDOPA and FDG PET data, the predictive performance given by the area under the ROC curve (AUC) was highest when combining imaging features with those from the metabolomics data (AUC for FDOPA + metabolomics: 0.98; AUC for FDG + metabolomics: 0.91). The performance was generally lower when using only the respective PET attributes (FDOPA: 0.94, FDG: 0.8) or only the metabolomics data (AUC: 0.66). [less ▲]

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See detailBehavioural outcomes of subthalamic stimulation and medical therapy versus medical therapy alone for Parkinson's disease with early motor complications (EARLYSTIM trial): secondary analysis of an open-label randomised trial.
Lhommee, Eugenie; Wojtecki, Lars; Czernecki, Virginie et al

in The Lancet. Neurology (2018), 17(3), 223-231

BACKGROUND: Although subthalamic stimulation is a recognised treatment for motor complications in Parkinson's disease, reports on behavioural outcomes are controversial, which represents a major challenge ... [more ▼]

BACKGROUND: Although subthalamic stimulation is a recognised treatment for motor complications in Parkinson's disease, reports on behavioural outcomes are controversial, which represents a major challenge when counselling candidates for subthalamic stimulation. We aimed to assess changes in behaviour in patients with Parkinson's disease receiving combined treatment with subthalamic stimulation and medical therapy over a 2-year follow-up period as compared with the behavioural evolution under medical therapy alone. METHODS: We did a parallel, open-label study (EARLYSTIM) at 17 surgical centres in France (n=8) and Germany (n=9). We recruited patients with Parkinson's disease who were disabled by early motor complications. Participants were randomly allocated (1:1) to either medical therapy alone or bilateral subthalamic stimulation plus medical therapy. The primary outcome was mean change in quality of life from baseline to 2 years. A secondary analysis was also done to assess behavioural outcomes. We used the Ardouin Scale of Behavior in Parkinson's Disease to assess changes in behaviour between baseline and 2-year follow-up. Apathy was also measured using the Starkstein Apathy Scale, and depression was assessed with the Beck Depression Inventory. The secondary analysis was done in all patients recruited. We used a generalised estimating equations (GEE) regression model for individual items and mixed model regression for subscores of the Ardouin scale and the apathy and depression scales. This trial is registered with ClinicalTrials.gov, number NCT00354133. The primary analysis has been reported elsewhere; this report presents the secondary analysis only. FINDINGS: Between July, 2006, and November, 2009, 251 participants were recruited, of whom 127 were allocated medical therapy alone and 124 were assigned bilateral subthalamic stimulation plus medical therapy. At 2-year follow-up, the levodopa-equivalent dose was reduced by 39% (-363.3 mg/day [SE 41.8]) in individuals allocated bilateral subthalamic stimulation plus medical therapy and was increased by 21% (245.8 mg/day [40.4]) in those assigned medical therapy alone (p<0.0001). Neuropsychiatric fluctuations decreased with bilateral subthalamic stimulation plus medical therapy during 2-year follow-up (mean change -0.65 points [SE 0.15]) and did not change with medical therapy alone (-0.02 points [0.15]); the between-group difference in change from baseline was significant (p=0.0028). At 2 years, the Ardouin scale subscore for hyperdopaminergic behavioural disorders had decreased with bilateral subthalamic stimulation plus medical therapy (mean change -1.26 points [SE 0.35]) and had increased with medical therapy alone (1.12 points [0.35]); the between-group difference was significant (p<0.0001). Mean change from baseline at 2 years in the Ardouin scale subscore for hypodopaminergic behavioural disorders, the Starkstein Apathy Scale score, and the Beck Depression Inventory score did not differ between treatment groups. Antidepressants were stopped in 12 patients assigned bilateral subthalamic stimulation plus medical therapy versus four patients allocated medical therapy alone. Neuroleptics were started in nine patients assigned medical therapy alone versus one patient allocated bilateral subthalamic stimulation plus medical therapy. During the 2-year follow-up, two individuals assigned bilateral subthalamic stimulation plus medical therapy and one patient allocated medical therapy alone died by suicide. INTERPRETATION: In a large cohort with Parkinson's disease and early motor complications, better overall behavioural outcomes were noted with bilateral subthalamic stimulation plus medical therapy compared with medical therapy alone. The presence of hyperdopaminergic behaviours and neuropsychiatric fluctuations can be judged additional arguments in favour of subthalamic stimulation if surgery is considered for disabling motor complications. FUNDING: German Federal Ministry of Education and Research, French Programme Hospitalier de Recherche Clinique National, and Medtronic. [less ▲]

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See detailFDG-PET and metabolomics in PD-associated GBA variants
Greuel, Andrea; Trezzi, Jean-Pierre; Glaab, Enrico UL et al

in Movement Disorders (2018), 33(2), 599

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See detailA new rechargeable device for deep brain stimulation: a prospective patient satisfaction survey.
Timmermann, Lars; Schupbach, Michael; Hertel, Frank UL et al

in European neurology (2013), 69(4), 193-9

BACKGROUND: Deep brain stimulation (DBS) is highly successful in treating Parkinson's disease (PD), dystonia, and essential tremor (ET). Until recently implantable neurostimulators were nonrechargeable ... [more ▼]

BACKGROUND: Deep brain stimulation (DBS) is highly successful in treating Parkinson's disease (PD), dystonia, and essential tremor (ET). Until recently implantable neurostimulators were nonrechargeable, battery-driven devices, with a lifetime of about 3-5 years. This relatively short duration causes problems for patients (e.g. programming and device-use limitations, unpredictable expiration, surgeries to replace depleted batteries). Additionally, these batteries (relatively large with considerable weight) may cause discomfort. To overcome these issues, the first rechargeable DBS device was introduced: smaller, lighter and intended to function for 9 years. METHODS: Of 35 patients implanted with the rechargeable device, 21 (including 8 PD, 10 dystonia, 2 ET) were followed before and 3 months after surgery and completed a systematic survey of satisfaction with the rechargeable device. RESULTS: Overall patient satisfaction was high (83.3 +/- 18.3). Dystonia patients tended to have lower satisfaction values for fit and comfort of the system than PD patients. Age was significantly negatively correlated with satisfaction regarding process of battery recharging. CONCLUSIONS: Dystonia patients (generally high-energy consumption, severe problems at the DBS device end-of-life) are good, reliable candidates for a rechargeable DBS system. In PD, younger patients, without signs of dementia and good technical understanding, might have highest benefit. [less ▲]

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