4 research outputs found

    Monitoring of 30 marker candidates in early Parkinson disease as progression markers

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    Objective: This was a longitudinal single-center cohort study to comprehensively explore multimodal progression markers for Parkinson disease (PD) in patients with recently diagnosed PD (n = 123) and age-matched, neurologically healthy controls (HC; n = 106). Methods: Thirty tests at baseline and after 24 months covered nonmotor symptoms (NMS), cognitive function, and REM sleep behavior disorder (RBD) by polysomnography (PSG), voxel-based morphometry (VBM) of the brain by MRI, and CSF markers. Linear mixed-effect models were used to estimate differences of rates of change and to provide standardized effect sizes (d) with 95% confidence intervals (CI). Results: A composite panel of 10 informative markers was identified. Significant relative worsening (PD vs HC) was seen with the following markers: the Unified Parkinson's Disease Rating Scale I (d 0.39; CI 0.09–0.70), the Autonomic Scale for Outcomes in Parkinson's Disease (d 0.25; CI 0.06–0.46), the Epworth Sleepiness Scale (d 0.47; CI 0.24–0.71), the RBD Screening Questionnaire (d 0.44; CI 0.25–0.64), and RBD by PSG (d 0.37; CI 0.19–0.55) as well as VBM units of cortical gray matter (d −0.2; CI −0.3 to −0.09) and hippocampus (d −0.15; CI −0.27 to −0.03). Markers with a relative improvement included the Nonmotor Symptom (Severity) Scale (d −0.19; CI −0.36 to −0.02) and 2 depression scales (Beck Depression Inventory d −0.18; CI −0.36 to 0; Montgomery-Åsberg Depression Rating Scale d −0.26; CI −0.47 to −0.04). Unexpectedly, cognitive measures and select laboratory markers were not significantly changed in PD vs HC participants. Conclusions: Current CSF biomarkers and cognitive scales do not represent useful progression markers. However, sleep and imaging measures, and to some extent NMS, assessed using adequate scales, may be more informative markers to quantify progression

    The comorbidity profiles and medication issues of patients with multiple system atrophy: a systematic cross-sectional analysis

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    Background Multiple system atrophy (MSA) is a complex and fatal neurodegenerative movement disorder. Understanding the comorbidities and drug therapy is crucial for MSA patients’ safety and management. Objectives To investigate the pattern of comorbidities and aspects of drug therapy in MSA patients. Methods Cross-sectional data of MSA patients according to Gilman et al. (2008) diagnostic criteria and control patients without neurodegenerative diseases (non-ND) were collected from German, multicenter cohorts. The prevalence of comorbidities according to WHO ICD-10 classification and drugs administered according to WHO ATC system were analyzed. Potential drug-drug interactions were identified using AiDKlinik®. Results The analysis included 254 MSA and 363 age- and sex-matched non-ND control patients. MSA patients exhibited a significantly higher burden of comorbidities, in particular diseases of the genitourinary system. Also, more medications were prescribed MSA patients, resulting in a higher prevalence of polypharmacy. Importantly, the risk of potential drug-drug interactions, including severe interactions and contraindicated combinations, was elevated in MSA patients. When comparing MSA-P and MSA-C subtypes, MSA-P patients suffered more frequently from diseases of the genitourinary system and diseases of the musculoskeletal system and connective tissue. Conclusions MSA patients face a substantial burden of comorbidities, notably in the genitourinary system. This, coupled with increased polypharmacy and potential drug interactions, highlights the complexity of managing MSA patients. Clinicians should carefully consider these factors when devising treatment strategies for MSA patients

    Imaging biomarkers in Parkinson’s disease and Parkinsonian syndromes: current and emerging concepts

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    Abstract Two centuries ago in 1817, James Parkinson provided the first medical description of Parkinson’s disease, later refined by Jean-Martin Charcot in the mid-to-late 19th century to include the atypical parkinsonian variants (also termed, Parkinson-plus syndromes). Today, Parkinson’s disease represents the second most common neurodegenerative disorder with an estimated global prevalence of over 10 million. Conversely, atypical parkinsonian syndromes encompass a group of relatively heterogeneous disorders that may share some clinical features with Parkinson’s disease, but are uncommon distinct clinicopathological diseases. Decades of scientific advancements have vastly improved our understanding of these disorders, including improvements in in vivo imaging for biomarker identification. Multimodal imaging for the visualization of structural and functional brain changes is especially important, as it allows a ‘window’ into the underlying pathophysiological abnormalities. In this article, we first present an overview of the cardinal clinical and neuropathological features of, 1) synucleinopathies: Parkinson’s disease and other Lewy body spectrum disorders, as well as multiple system atrophy, and 2) tauopathies: progressive supranuclear palsy, and corticobasal degeneration. A comprehensive presentation of well-established and emerging imaging biomarkers for each disorder are then discussed. Biomarkers for the following imaging modalities are reviewed: 1) structural magnetic resonance imaging (MRI) using T1, T2, and susceptibility-weighted sequences for volumetric and voxel-based morphometric analyses, as well as MRI derived visual signatures, 2) diffusion tensor MRI for the assessment of white matter tract injury and microstructural integrity, 3) proton magnetic resonance spectroscopy for quantifying proton-containing brain metabolites, 4) single photon emission computed tomography for the evaluation of nigrostriatal integrity (as assessed by presynaptic dopamine transporters and postsynaptic dopamine D2 receptors), and cerebral perfusion, 5) positron emission tomography for gauging nigrostriatal functions, glucose metabolism, amyloid and tau molecular imaging, as well as neuroinflammation, 6) myocardial scintigraphy for dysautonomia, and 7) transcranial sonography for measuring substantia nigra and lentiform nucleus echogenicity. Imaging biomarkers, using the ‘multimodal approach’, may aid in making early, accurate and objective diagnostic decisions, highlight neuroanatomical and pathophysiological mechanisms, as well as assist in evaluating disease progression and therapeutic responses to drugs in clinical trials
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