Accuracy of diagnosis in patients with presumed Parkinson's disease

Identification and validation of N-acetylputrescine in combination with non-canonical clinical features as a Parkinson's disease biomarker panel

Parkinson's disease is a progressive neurodegenerative disorder in which loss of dopaminergic neurons in the substantia nigra results in a clinically heterogeneous group with variable motor and non-motor symptoms with a degree of misdiagnosis. Only 3-25% of sporadic Parkinson's patients present with genetic abnormalities that could represent a risk factor, thus environmental, metabolic, and other unknown causes contribute to the pathogenesis of Parkinson's disease, which highlights the critical need for biomarkers. In the present study, we prospectively collected and analyzed plasma samples from 194 Parkinson's disease patients and 197 age-matched non-diseased controls. N-acetyl putrescine (NAP) in combination with sense of smell (B-SIT), depression/anxiety (HADS), and acting out dreams (RBD1Q) clinical measurements demonstrated combined diagnostic utility. NAP was increased by 28% in Parkinsons disease patients and exhibited an AUC of 0.72 as well as an OR of 4.79. The clinical and NAP panel demonstrated an area under the curve, AUC = 0.9 and an OR of 20.4. The assessed diagnostic panel demonstrates combinatorial utility in diagnosing Parkinson's disease, allowing for an integrated interpretation of disease pathophysiology and highlighting the use of multi-tiered panels in neurological disease diagnosis.

Effects of non-invasive vagus nerve stimulation on clinical symptoms and molecular biomarkers in Parkinson's disease

Non-invasive vagus nerve stimulation (nVNS) is an established neurostimulation therapy used in the treatment of epilepsy, migraine and cluster headache. In this randomized, double-blind, sham-controlled trial we explored the role of nVNS in the treatment of gait and other motor symptoms in Parkinson's disease (PD) patients. In a subgroup of patients, we measured selected neurotrophins, inflammatory markers and markers of oxidative stress in serum. Thirty-three PD patients with freezing of gait (FOG) were randomized to either active nVNS or sham nVNS. After baseline assessments, patients were instructed to deliver six 2  min stimulations (12  min/day) of the active nVNS/sham nVNS device for 1  month at home. Patients were then re-assessed. After a one-month washout period, they were allocated to the alternate treatment arm and the same process was followed. Significant improvements in key gait parameters (speed, stance time and step length) were observed with active nVNS. While serum tumor necrosis factor- α decreased, glutathione and brain-derived neurotrophic factor levels increased significantly (p < 0.05) after active nVNS treatment. Here we present the first evidence of the efficacy and safety of nVNS in the treatment of gait in PD patients, and propose that nVNS can be used as an adjunctive therapy in the management of PD patients, especially those suffering from FOG. Clinical trial registration: identifier ISRCTN14797144.

Practical Overview of 123I-Ioflupane Imaging in Parkinsonian Syndromes

Parkinsonian syndromes are a heterogeneous group of progressive neurodegenerative disorders involving the nigrostriatal dopaminergic pathway and are characterized by a wide spectrum of motor and nonmotor symptoms. These syndromes are quite common and can profoundly impact the lives of patients and their families. In addition to classic Parkinson disease, parkinsonian syndromes include multiple additional disorders known collectively as Parkinson-plus syndromes or atypical parkinsonism. These are characterized by the classic parkinsonian motor symptoms with additional distinguishing clinical features. Dopamine transporter SPECT has been developed as a diagnostic tool to assess the levels of dopamine transporters in the striatum. This imaging assessment, which uses iodine 123 (123I) ioflupane, can be useful to differentiate parkinsonian syndromes caused by nigrostriatal degeneration from other clinical mimics such as essential tremor or psychogenic tremor. Dopamine transporter imaging plays a crucial role in diagnosing parkinsonian syndromes, particularly in patients who do not clearly fulfill the clinical criteria for diagnosis. Diagnostic clarification can allow early treatment in appropriate patients and avoid misdiagnosis. At present, only the qualitative interpretation of dopamine transporter SPECT is approved by the U.S. Food and Drug Administration, but quantitative interpretation is often used to supplement qualitative interpretation. The authors provide an overview of patient preparation, common imaging findings, and potential pitfalls that radiologists and nuclear medicine physicians should know when performing and interpreting dopamine transporter examinations. Alternatives to 123I-ioflupane imaging for the evaluation of nigrostriatal degeneration are also briefly discussed. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Intenzo and Colarossi in this issue.

New horizons in Parkinson's disease in older populations

Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease. Ageing is considered to be the greatest risk factor for PD, with a complex interplay between genetics and the environment. With population ageing, the prevalence of PD is expected to escalate worldwide; thus, it is of utmost importance to reduce the burden of PD. To date, there are no therapies to cure the disease, and current treatment strategies focus on the management of symptoms. Older adults often have multiple chronic diseases and geriatric syndromes, which further complicates the management of PD. Healthcare systems and care models necessary to address the broad needs of older PD patients are largely unavailable. In this New Horizon article, we discuss various aspects of PD from an ageing perspective, including disease management. We highlight recent advancements in PD therapies and discuss new care models with the potential to improve patient's quality of life.

Glucose Metabolism Impairment in Parkinson's Disease

Impairments in systematic and regional glucose metabolism exist in patients with Parkinson's disease (PD) at every stage of the disease course, and such impairments are associated with the incidence, progression, and special phenotypes of PD, which affect each physiological process of glucose metabolism including glucose uptake, glycolysis, tricarboxylic acid cycle, oxidative phosphorylation, and pentose phosphate shunt pathway. These impairments may be attributed to various mechanisms, such as insulin resistance, oxidative stress, abnormal glycated modification, blood-brain-barrier dysfunction, and hyperglycemia-induced damages. These mechanisms could subsequently cause excessive methylglyoxal and reactive oxygen species production, neuroinflammation, abnormal aggregation of protein, mitochondrial dysfunction, and decreased dopamine, and finally result in energy supply insufficiency, neurotransmitter dysregulation, aggregation and phosphorylation of α-synuclein, and dopaminergic neuron loss. This review discusses the glucose metabolism impairment in PD and its pathophysiological mechanisms, and briefly summarized the currently-available therapies targeting glucose metabolism impairment in PD, including glucagon-likepeptide-1 (GLP-1) receptor agonists and dual GLP-1/gastric inhibitory peptide receptor agonists, metformin, and thiazoledinediones.

Microglia and Astrocytes Dysfunction and Key Neuroinflammation-Based Biomarkers in Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disease, with symptoms such as tremor, bradykinesia with rigidity, and depression appearing in the late stage of life. The key hallmark of PD is the loss or death of dopaminergic neurons in the region substantia nigra pars compacta. Neuroinflammation plays a key role in the etiology of PD, and the contribution of immunity-related events spurred the researchers to identify anti-inflammatory agents for the treatment of PD. Neuroinflammation-based biomarkers have been identified for diagnosing PD, and many cellular and animal models have been used to explain the underlying mechanism; however, the specific cause of neuroinflammation remains uncertain, and more research is underway. So far, microglia and astrocyte dysregulation has been reported in PD. Patients with PD develop neural toxicity, inflammation, and inclusion bodies due to activated microglia and a-synuclein-induced astrocyte conversion into A1 astrocytes. Major phenotypes of PD appear in the late stage of life, so there is a need to identify key early-stage biomarkers for proper management and diagnosis. Studies are under way to identify key neuroinflammation-based biomarkers for early detection of PD. This review uses a constructive analysis approach by studying and analyzing different research studies focused on the role of neuroinflammation in PD. The review summarizes microglia, astrocyte dysfunction, neuroinflammation, and key biomarkers in PD. An approach that incorporates multiple biomarkers could provide more reliable diagnosis of PD.

Incidence of Parkinson's disease and modifiable risk factors in Korean population: A longitudinal follow-up study of a nationwide cohort

Introduction

We aimed to investigate the incidence of Parkinson's disease (PD) by age and year for each sex as well as the modifiable risk factors for PD. Using data from the Korean National Health Insurance Service, 938,635 PD and dementia-free participants aged ≥40 years who underwent general health examinations were followed to December 2019.

Methods

We analyzed the PD incidence rates according to age, year and sex. To investigate the modifiable risk factors for PD, we used the Cox regression model. Additionally, we calculated the population-attributable fraction to measure the impact of the risk factors on PD.

Results

During follow-up, 9,924 of the 938,635 (1.1%) participants developed PD. The incidence of PD increased continuously from 2007 to 2018, reaching 1.34 per 1,000 person-years in 2018. The incidence of PD also increases with age, up to 80 y. Presence of hypertension (SHR = 1.09, 95% CI 1.05 to 1.14), diabetes (SHR = 1.24, 95% CI 1.17 to 1.31), dyslipidemia (SHR = 1.12, 95% CI 1.07 to 1.18), ischemic stroke (SHR = 1.26, 95% CI 1.17 to 1.36), hemorrhagic stroke (SHR = 1.26, 95% CI 1.08 to 1.47), ischemic heart disease (SHR = 1.09, 95% CI 1.02 to 1.17), depression (SHR = 1.61, 95% CI 1.53 to 1.69), osteoporosis (SHR = 1.24, 95% CI 1.18 to 1.30), and obesity (SHR = 1.06, 95% CI 1.01 to 1.10) were independently associated with a higher risk for PD.

Discussion

Our results highlight the effect of modifiable risk factors for PD in the Korean population, which will help establish health care policies to prevent the development of PD.

Detailed insight into the pathophysiology and the behavioral complications associated with the Parkinson's disease and its medications

Background

The loss of dopamine neurons in the substantia nigra, as well as other mostly catecholaminergic neurons, causes many of the motor symptoms that define Parkinson's disease. Parkinson's disease is commonly thought of as a movement disorder, the significant prevalence of psychiatric complications such as cognitive impairment, and psychosis suggests it should be considered a neuropsychiatric illness, and all behavioral complications are linked to growing disability and the medication.

Main body

Apart from the disease-induced abnormalities, there are several other side effects of the disease and also from the medication used to prevent the disease. This article focuses on the pathogenesis of Parkinson’s disease and also the behavioral abnormalities caused by the disease and its medication. The study's data were gathered by searching several review articles and research papers from a variety of sources, including Elsevier, PubMed, Research Gate, Journal of Pharmaceutical Science, etc., from the year 1985 to 2021. Parkinson's disease is a neurodegenerative disease caused by a variety of complex processes. It is responsible not just for motor symptoms, but also for a variety of behavioral symptoms that can arise as a result of the disease and/or medication.

Conclusion

Only symptomatic drugs are available; thus, finding treatments that directly address the disease mechanisms causing Parkinson’s disease is essential. To alleviate the disease's burden on patients and their families, better treatments for the neuropsychiatric repercussions of Parkinson's disease are required.

Graphical Abstract

Deep learning based diagnosis of Parkinson's Disease using diffusion magnetic resonance imaging

The diagnostic performance of a combined architecture on Parkinson's disease using diffusion tensor imaging was evaluated. A convolutional neural network was trained from multiple parcellated brain regions. A greedy algorithm was proposed to combine the models from individual regions into a complex one. Total 305 Parkinson's disease patients (aged 59.9±9.7 years old) and 227 healthy control subjects (aged 61.0±7.4 years old) were enrolled from 3 retrospective studies. The participants were divided into training with ten-fold cross-validation (N = 432) and an independent blind dataset (N = 100). Diffusion-weighted images were acquired from a 3T scanner. Fractional anisotropy and mean diffusivity were calculated and was subsequently parcellated into 90 cerebral regions of interest based on the Automatic Anatomic Labeling template. A convolutional neural network was implemented which contained three convolutional blocks and a fully connected layer. Each convolutional block consisted of a convolutional layer, activation layer, and pooling layer. This model was trained for each individual region. A greedy algorithm was implemented to combine multiple regions as the final prediction. The greedy algorithm predicted the area under curve of 94.1±3.2% from the combination of fractional anisotropy from 22 regions. The model performance analysis showed that the combination of 9 regions is equivalent. The best area under curve was 74.7±5.4% from the right postcentral gyrus. The current study proposed an architecture of convolutional neural network and a greedy algorithm to combine from multiple regions. With diffusion tensor imaging, the algorithm showed the potential to distinguish patients with Parkinson's disease from normal control with satisfactory performance.

Dopamine transporter (DAT) imaging in Parkinson's disease and related disorders

This review gives an insight into the beginnings of dopamine transporter (DAT) imaging in the early 1990s, focussing on single photon emission tomography (SPECT). The development of the method and its consolidation as a now widely used clinical tool is described. The role of DAT-SPECT in the diagnosis and differential diagnosis of PD, atypical parkinsonian syndromes and several other different neurological disorders is reviewed. Finally the clinical research using DAT-SPECT as a biomarker for the progression of PD, for the detection of a preclinical dopaminergic lesion and its correlation with neuropathological findings is outlined.

Towards Objective Quantification of Hand Tremors and Bradykinesia Using Contactless Sensors: A Systematic Review

Assessing the progression of movement disorders such as Parkinson's Disease (PD) is key in adjusting therapeutic interventions. However, current methods are still based on subjective factors such as visual observation, resulting in significant inter-rater variability on clinical scales such as UPDRS. Recent studies show the potential of sensor-based methods to address this limitation. The goal of this systematic review is to provide an up-to-date analysis of contactless sensor-based methods to estimate hand dexterity UPDRS scores in PD patients. Two hundred and twenty-four abstracts were screened and nine articles selected for analysis. Evidence obtained in a cumulative cohort of n = 187 patients and 1, 385 samples indicates that contactless sensors, particularly the Leap Motion Controller (LMC), can be used to assess UPDRS hand motor tasks 3.4, 3.5, 3.6, 3.15, and 3.17, although accuracy varies. Early evidence shows that sensor-based methods have clinical potential and might, after refinement, complement, or serve as a support to subjective assessment procedures. Given the nature of UPDRS assessment, future studies should observe whether LMC classification error falls within inter-rater variability for clinician-measured UPDRS scores to validate its clinical utility. Conversely, variables relevant to LMC classification such as power spectral densities or movement opening and closing speeds could set the basis for the design of more objective expert systems to assess hand dexterity in PD.

Heterogeneity by global and textural feature analysis in F-18 FP-CIT brain PET images for diagnosis of Parkinson's disease

BACKGROUND

The quantification of heterogeneity for the striatum and whole brain with F-18 FP-CIT PET images will be useful for diagnosis. The index obtained from texture analysis on PET images is related to pathological change that the neuronal loss of the nigrostriatal tract is heterogeneous according to the disease state. The aim of this study is to evaluate various heterogeneity indices of F-18 FP-CIT PET images in the diagnosis of Parkinson's disease (PD) patients and to access the diagnostic accuracy of the indices using machine learning (ML).

METHODS

This retrospective study included F-18 FP-CIT PET images of 31 PD and 31 age-matched health controls (HC). The volume of interest was delineated according to iso-contour lines around standardized uptake value (SUV) 3.0 g/ml for each region of the striatum by PMod 3.603. One hundred eight heterogeneity indices were calculated using CGITA to find indices from which the PD and HC were classified using statistical significance. PD group was classified by constructing a 2-dimensional or 3-dimensional phase space quantifier using these heterogeneity indices. We used 71 heterogeneity indices to classify PD from HC using ML for dimensional reduction.

RESULTS

The heterogeneity indices for classifying PD from HC were size-zone variability, contrast, inverse difference-moment, and homogeneity in the order of low P value. Three-dimensional quantifiers composed of normalized-contrast, code-similarity, and contrast were more clearly classified than 2-dimensional ones. After 71-dimensional reduction using PCA, classification was possible by logistic regression with 91.3% accuracy. The 2 groups were classified with an accuracy of 85.5% using the support vector machine and 88.4% using the random forest. The classification accuracy using the eXtreme Gradient Boosting was 95.7%, and feature importance was highest in order of SUV bias-corrected kurtosis, size-zone-variability, intensity-variability, and high-intensity-zone-variability.

CONCLUSION

It was confirmed that PD patients is more clearly classified than the conventional 2-dimensional quantifier by introducing a 3-dimensional phase space quantifier. We observed that ML can be used to classify the 2 groups in an easy and explanatory manner. For the discrimination of the disease, 24 heterogeneity indices were found to be statistically useful, and the major cut-off values of 3 heterogeneity indices were size-zone variability (1906.44), intensity variability (129.21), and high intensity zone emphasis (800.29).

Non-invasive vagus nerve stimulation improves clinical and molecular biomarkers of Parkinson's disease in patients with freezing of gait

Non-invasive vagus nerve stimulation (nVNS) is an established neurostimulation therapy used in the treatment of epilepsy, migraine and cluster headache. In this randomized, double-blind, sham-controlled crossover trial we explored the role of nVNS in the treatment of gait and other motor symptoms in Parkinson’s disease (PD) patients. In a subgroup of patients, we measured selected neurotrophin levels and markers of inflammation and oxidative stress in serum, before and after the experimental intervention. Thirty-three PD patients with associated freezing of gait were randomised to either nVNS or sham. After baseline assessments, patients were instructed to deliver 6 two-minute stimulations (total 12 min/day) of the nVNS/sham device (electroCore, Inc. USA) for one month at home. Patients were then re-assessed. After a washout period of one month, the same patients were allocated to the alternate treatment arm and the same process was followed. Significant improvements in key gait parameters were observed with nVNS, including walking speed, stance time and step length, compared to sham. Similarly, overall motor function (MDS-UPDRS III) also improved significantly following nVNS stimulation. Serum Tumor Necrosis Factor (TNF)-α and glutathione levels decreased and brain-derived neurotrophic factor (BDNF) levels increased significantly (p < 0.05) after treatment with nVNS. Here we present the first double-blind sham-controlled trial evidence of the efficacy and safety of nVNS in the treatment of gait and motor function in patients with PD.

Assessment of real life eating difficulties in Parkinson's disease patients by measuring plate to mouth movement elongation with inertial sensors

Parkinson’s disease (PD) is a neurodegenerative disorder with both motor and non-motor symptoms. Despite the progressive nature of PD, early diagnosis, tracking the disease’s natural history and measuring the drug response are factors that play a major role in determining the quality of life of the affected individual. Apart from the common motor symptoms, i.e., tremor at rest, rigidity and bradykinesia, studies suggest that PD is associated with disturbances in eating behavior and energy intake. Specifically, PD is associated with drug-induced impulsive eating disorders such as binge eating, appetite-related non-motor issues such as weight loss and/or gain as well as dysphagia—factors that correlate with difficulties in completing day-to-day eating-related tasks. In this work we introduce Plate-to-Mouth (PtM), an indicator that relates with the time spent for the hand operating the utensil to transfer a quantity of food from the plate into the mouth during the course of a meal. We propose a two-step approach towards the objective calculation of PtM. Initially, we use the 3D acceleration and orientation velocity signals from an off-the-shelf smartwatch to detect the bite moments and upwards wrist micromovements that occur during a meal session. Afterwards, we process the upwards hand micromovements that appear prior to every detected bite during the meal in order to estimate the bite’s PtM duration. Finally, we use a density-based scheme to estimate the PtM durations distribution and form the in-meal eating behavior profile of the subject. In the results section, we provide validation for every step of the process independently, as well as showcase our findings using a total of three datasets, one collected in a controlled clinical setting using standardized meals (with a total of 28 meal sessions from 7 Healthy Controls (HC) and 21 PD patients) and two collected in-the-wild under free living conditions (37 meals from 4 HC/10 PD patients and 629 meals from 3 HC/3 PD patients, respectively). Experimental results reveal an Area Under the Curve (AUC) of 0.748 for the clinical dataset and 0.775/1.000 for the in-the-wild datasets towards the classification of in-meal eating behavior profiles to the PD or HC group. This is the first work that attempts to use wearable Inertial Measurement Unit (IMU) sensor data, collected both in clinical and in-the-wild settings, towards the extraction of an objective eating behavior indicator for PD.

Diagnostic performance of loss of nigral hyperintensity on susceptibility-weighted imaging in parkinsonism: an updated meta-analysis

OBJECTIVES

To evaluate diagnostic performance of loss of nigral hyperintensity on SWI in differentiating idiopathic Parkinson's disease (IPD) or primary parkinsonism (including IPD and Parkinson-plus syndrome) from healthy/disease controls.

METHODS

MEDLINE/PubMed and EMBASE databases were searched to identify original articles investigating the diagnostic performance of loss of nigral hyperintensity for differentiating IPD or primary parkinsonism from healthy/disease control, up to April 3, 2020. Pooled sensitivity and specificity were calculated using a bivariate random-effects model. The proportion of nondiagnostic scan, inter- and intrareader agreement, and the proportion of concordance between clinical laterality and imaging asymmetry were also pooled.

RESULTS

Nineteen articles covering 2125 patients (1097 with primary parkinsonism, 1028 healthy/disease controls) were included. For discrimination between IPD and healthy/disease controls, pooled sensitivity and specificity were 0.96 (95% CI, 0.91-0.98) and 0.95 (95% CI, 0.92-0.97). For discrimination between primary parkinsonism and healthy/disease controls, pooled sensitivity and specificity were 0.87 (95% CI, 0.75-0.94) and 0.93 (95% CI, 0.85-0.97). The pooled proportion of non-diagnostic scans on random-effects modeling was 4.2% (95% CI, 2.5-6.9%). The inter- and intrareader agreements were almost perfect, with the pooled coefficients being 0.84 (95% CI, 0.78-0.89) and 0.96 (95% CI, 0.89-0.99), respectively. The pooled proportion of concordant cases was 69.3% (95% CI, 58.4-78.4%).

CONCLUSIONS

Loss of nigral hyperintensity on SWI can differentiate IPD or primary parkinsonism from a healthy/disease control group with high accuracy. However, the proportion of non-diagnostic scans is not negligible and must be taken into account.

KEY POINTS

• For discrimination between idiopathic Parkinson's disease and healthy/disease controls, pooled sensitivity and specificity of loss of nigral hyperintensity were 0.96 and 0.95. • For discrimination between primary parkinsonism and healthy/disease controls, pooled sensitivity and specificity of loss of nigral hyperintensity were 0.87 and 0.93. • The pooled proportion of non-diagnostic scans on random-effects modeling was 4.2%.

Psychiatric morbidity in patients with idiopathic Parkinson's disease: A cross-sectional study

OBJECTIVE

To evaluate the prevalence of psychiatric comorbidities in patients with idiopathic Parkinson's disease (IPD).

METHODOLOGY

Two hundred and thirty-nine patients with IPD were evaluated on Mini-International Neuropsychiatric Interview PLUS (MINI-PLUS). In addition, patients found to have depression as per the MINI-PLUS were evaluated on Beck Depression Inventory.

RESULTS

One hundred and thirty-five (56.5%) patients had a current psychiatric diagnosis and 59.8% had a lifetime psychiatric diagnosis. As per MINI-PLUS, about two-fifth (39.7%) of patients had suicidality. In 18.8% of patients, suicidality was present in the absence of axis-I psychiatric diagnosis. Among the various psychiatric disorders, the most common disorders included depressive disorders (current: 17.5%; lifetime: 23.8%), anxiety disorders (current: 17.5%; lifetime: 17.5%), and psychotic disorders (current: 11.3%; lifetime: 11.7%).

CONCLUSIONS

More than half of the patients with Parkinson's disease have psychiatric disorders. High prevalence of psychiatric morbidity calls for close liaison between the neurologist and the psychiatric disorders.

Clinical Features of Parkinson's Disease: The Evolution of Critical Symptoms

Parkinson’s disease (PD) is a multi-attribute neurodegenerative disorder combining motor and nonmotor symptoms without well-defined diagnostic clinical markers. The presence of primary motor features (bradykinesia, rest tremor, rigidity and loss of postural reflexes) are the most characteristic signs of PD that are also utilized to identify patients in current clinical practice. The successful implementation of levodopa treatment revealed that nonmotor features are the main contributors of patient disability in PD, and their occurrence might be earlier than motor symptoms during disease progression. Targeted detection of prodromal PD symptoms can open up new possibilities in the identification of PD patients and provide potential patient populations for developing novel neuroprotective therapies. In this review, the evolution of critical features in PD diagnosis is described with special attention to nonmotor symptoms and their possible detection.

Parkinson patients without tremor show changed patterns of mechanical muscle oscillations during a specific bilateral motor task compared to controls

The pathophysiology of Parkinson's disease (PD) is still not understood. There are investigations which show a changed oscillatory behaviour of brain circuits or changes in variability of, e.g., gait parameters in PD. The aim of this study was to investigate whether or not the motor output differs between PD patients and healthy controls. Thereby, patients without tremor are investigated in the medication off state performing a special bilateral isometric motor task. The force and accelerations (ACC) were recorded as well as the Mechanomyography (MMG) of the biceps brachii, the brachioradialis and of the pectoralis major muscles using piezoelectric-sensors during the bilateral motor task at 60% of the maximal isometric contraction. The frequency, a specific power ratio, the amplitude variation and the slope of amplitudes were analysed. The results indicate that the oscillatory behaviour of motor output in PD patients without tremor deviates from controls: thereby, the 95%-confidence-intervals of power ratio and of amplitude variation of all signals are disjoint between PD and controls and show significant differences in group comparisons (power ratio: p = 0.000-0.004, r = 0.441-0.579; amplitude variation: p = 0.000-0.001, r = 0.37-0.67). The mean frequency shows a significant difference for ACC (p = 0.009, r = 0.43), but not for MMG. It remains open, whether this muscular output reflects changes of brain circuits and whether the results are reproducible and specific for PD.

Neurotoxic and Neuroprotective Role of Exosomes in Parkinson’s Disease

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Exosomes are extracellular vesicles produced by eukaryotic cells that are also found in most biological fluids and tissues. While they were initially thought to act as compartments for removal of cellular debris, they are now recognized as important tools for cell-to-cell communication and for the transfer of pathogens between the cells. They have attracted particular interest in neurodegenerative diseases for their potential role in transferring prion-like proteins between neurons, and in Parkinson’s disease (PD), they have been shown to spread oligomers of α-synuclein in the brain accelerating the progression of this pathology. A potential neuroprotective role of exosomes has also been equally proposed in PD as they could limit the toxicity of α-synuclein by clearing them out of the cells. Exosomes have also attracted considerable attention for use as drug vehicles. Being nonimmunogenic in nature, they provide an unprecedented opportunity to enhance the delivery of incorporated drugs to target cells. In this review, we discuss current knowledge about the potential neurotoxic and neuroprotective role of exosomes and their potential application as drug delivery systems in PD.

Movement disorders: a themed collection

Movement disorders are a diverse and challenging group of neurological conditions. Geriatricians and allied health professionals play a key role in the care of patients living with these disorders. Age and Ageing is making freely available online a collection of 15 papers that highlight the breadth and depth of this field. Perhaps unsurprisingly papers on Parkinson's disease predominate, but rarer movement disorders, including those seen following stroke and Huntington's disease, are also represented. Difficulties in diagnosis are explored, together with innovative approaches to management of both motor and non-motor symptoms. The collection includes qualitative work, longitudinal studies and clinical trials, and both the individual patient perspective and the international perspective are considered. There are papers for generalists, papers for specialists, papers for clinical commissioners and papers for researchers. Comprehensive review articles provide clarity, guidance and pragmatism. Finally, a New Horizons article encourages us to look to the future of movement disorders, which lies not only in developing novel therapies and trials but also in recognising the enormous value of palliative care and the multidisciplinary approach.

Population-scale hand tremor analysis via anonymized mouse cursor signals

Tremors are a common movement disorder with a spectrum of benign and pathological causes, including neurodegenerative disease, alcohol withdrawal, and physical overexertion. Studies of tremors in clinical practice are limited in size and scope and depend on explicit tracking of tremor characteristics by clinicians. Data drawn from small numbers of patients observed in short-duration sessions pose challenges for understanding the nature and distribution of tremors over a large population. Methods are presented to estimate hand tremors based on anonymized computer mouse cursor movement data collected from millions of users of a web search engine. To determine the feasibility of using this signal for the estimation of the prevalence of tremors over a large population, the characteristics of tremor-like movements are computed and compared against user data that can be interpreted as self-reports, the findings of published clinical studies, and a target selection study where participants self-report hand tremors and known causes. The results demonstrate significant alignment between estimated tremors and both self-reports and clinical findings. Those with cursor tremor events are more likely to report tremor-related search interests. Variations in cursor tremor quantity and cursor tremor frequency with demographics mirror those from clinical studies. Distributions of cursor tremor frequencies vary as expected for different medical conditions. Overall, the study finds evidence for the validity of harnessing anonymized mouse cursor motion as a population-scale tremor sensor for epidemiologic studies. Feasible future applications include opt-in services for screening and for monitoring the progression of illness.

Association of the Polygenic Risk Score with the Incidence Risk of Parkinson's Disease and Cerebrospinal Fluid α-Synuclein in a Chinese Cohort

Parkinson's disease (PD) is attributed to interactions among genes and environmental and lifestyle factors, but the genetic architecture of PD is complex and not completely understood. To evaluate whether the genetic profile modifies PD development and cerebrospinal fluid (CSF) pathological biomarkers, we enrolled 418 PD patients and 426 age- and sex-matched normal controls. Forty-six single nucleotide polymorphisms (SNPs) that were reported to be significantly associated with PD in large-scale genome-wide association studies (GWASs) were genotyped and analysed. The alleles associated with PD were used to build polygenic risk score (PRS) models to represent polygenic risk. The Cox proportional hazards model and receiver operating characteristic (ROC) analyses were used to evaluate the prediction value of the PRS for PD risk and age at onset. The CSF α-synuclein levels were measured in a subgroup of control subjects (n = 262), and its relationship with the PRS was analysed. We found that some SNPs identified from other populations had significant correlations with PD in our Chinese cohort. The PRS we built had prediction value for PD risk and age at onset. The CSF α-synuclein level had no correlation with the PRS in normal subjects.

Accuracy of nigrosome-1 detection to discriminate patients with Parkinson's disease and essential tremor

PURPOSE

The use of susceptibility weighted imaging in high field magnetic resonance imaging scanners can detect the nigrosome-1 area located in the caudo-lateral region of the pars compacta in the substantia nigra. This structure comprises a significant amount of dopaminergic neurons and degenerates in the early stages of Parkinson's disease. Essential tremor is a neurological condition that in some cases could be confused with the early stages of Parkinson's disease with a possible error in clinical diagnosis. Our purpose is to evaluate the accuracy of nigrosome-1 detection by high resolution magnetic resonance imaging to discriminate Parkinson's disease from essential tremor.

METHODS

A case-control study compared patients with a clinical diagnosis of Parkinson's disease and essential tremor. Magnetic resonance imaging studies were performed using a 3T magnetic resonance imaging scanner. The susceptibility weighted imaging sequence was obtained in the axial plane with an isotropic voxel of 0.75 mm. Two independent neuroradiologists evaluated the images without access to clinical patient data.

RESULTS

Sixteen patients were included in each group (Parkinson's disease and essential tremor). Average age: Parkinson's disease group: 71.3 (SD 6.3) and essential tremor group: 68.3 (SD 12.3). For the first evaluator, the nigrosome-1 area was absent in 15 patients with Parkinson's disease and in two with essential tremor and for the second evaluator was absent in 15 patients with Parkinson's disease and four with essential tremor. The sensitivity/specificity for the diagnosis of Parkinson's disease was 93.75%/87.5% for the first evaluator and 93.75%/75% for the second evaluator.

CONCLUSION

The detection of the nigrosome-1 area is a useful tool in the differential diagnosis between Parkinson's disease and essential tremor, with high sensitivity and specificity.

Robust Detection of Parkinson's Disease Using Harvested Smartphone Voice Data: A Telemedicine Approach

Introduction: Parkinson's disease affects over 10 million people globally, and ∼20% of patients with Parkinson's disease have not been diagnosed as such. The clinical diagnosis is costly: there are no specific tests or biomarkers and it can take days to diagnose as it relies on a holistic evaluation of the individual's symptoms. Existing research either predicts a Unified Parkinson Disease Rating Scale rating, uses other key Parkinsonian features such as tapping, gait, and tremor to diagnose an individual, or focuses on different audio features. Methods: In this article, we present a classification approach implemented as an iOS App to detect whether an individual has Parkinson's using 10-s audio clips of the individual saying "aaah" into a smartphone. Results: The 1,000 voice samples analyzed were obtained from the mPower (mobile Parkinson Disease) study, which collected 65,022 voice samples from 5,826 unique participants. Conclusions: The experimental results comparing 12 different methods indicate that our approach achieves 99.0% accuracy in under a second, which significantly outperforms both prior diagnosis methods in the accuracy achieved and the efficiency of clinical diagnoses.

Identifying Parkinson's disease and parkinsonism cases using routinely collected healthcare data: A systematic review

Background

Population-based, prospective studies can provide important insights into Parkinson’s disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose.

Methods

We searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity.

Results

We identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56–90% in hospital datasets, 53–87% in prescription datasets, 81–90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36–88% in hospital datasets, 40–74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15–73% in single datasets for PD and 43–63% in single datasets for parkinsonism.

Conclusions

In many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity.

Diagnostic accuracy of imaging brain vesicular monoamine transporter type 2 (VMAT2) in clinically uncertain parkinsonian syndrome (CUPS): a 3-year follow-up study in community patients

OBJECTIVES

To further validate the diagnostic utility of ¹⁸F-AV-133 vesicular monoamine transporter type 2 (VMAT2) positron emission tomography (PET) in patients with clinically uncertain parkinsonian syndromes (CUPS) by comparison to clinical diagnosis at 3 years follow-up.

DESIGN, SETTING AND PARTICIPANTS

In a previous study, we reported that ¹⁸F-AV-133 PET in community patients with CUPS changed diagnosis and management and increased diagnostic confidence. The current diagnosis of this cohort was obtained from the patient and treating specialist and compared with the diagnosis suggested 3 years earlier by the ¹⁸F-AV-133 PET. A second ¹⁸F-AV-133 PET was available in those with a discordant or inconclusive final diagnosis.

STUDY OUTCOME MEASURES

The primary end point was the proportion of patients who had a follow-up clinical diagnosis, which was concordant with their initial ¹⁸F-AV-133 PET scan. Secondary end points were the proportion of patients who had the same diagnosis at follow-up as that reached after the initial scan and the stability of diagnostic changes made after the first scan.

RESULTS

81 of the 85 patients previously recruited to the CUPS study had follow-up of which 79 had a clinical diagnosis and 2 remained CUPS. The diagnosis was in agreement with the initial ¹⁸F-AV-133 PET scan result in 74 cases. Five patients had a discordant diagnosis; one patient with rubral tremor had a severely abnormal scan that had worsened when rescanned; four cases with normal initial and repeat scans had a clinical diagnosis of Parkinson's disease. Two patients with suspected genetic disorders remained classified as CUPS and both had normal scans. In the 24 CUPS cohort patients where ¹⁸F-AV-133 PET initially changed diagnosis, this change was supported by follow-up diagnosis in all but the one rubral tremor case.

CONCLUSION

¹⁸F-AV-133 PET is a useful tool in improving diagnostic accuracy in CUPS providing results and diagnostic changes that remain robust after 3 years follow-up.

Impact of DAT-SPECT on Management of Patients Suspected of Parkinsonism

OBJECTIVE

To evaluate the value of I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl) nortropane (I-FP-CIT) dopamine transporter single photon emission computed tomography (DAT-SPECT) to change management strategies of patients suspected of parkinsonism.

METHOD

This was an institutional review board-approved, retrospective study. DAT-SPECT scans ordered by movement disorder specialist and neurologists from 2011-2014 were reviewed. Clinical data and radiological reports of 173 patients suspected of parkinsonism were reviewed. The DAT-SPECT scan results were correlated with clinical assessment and treatment changes.

RESULTS

A total of 173 patients (104 male and 69 female subjects; age, 64.4 ± 12.6 years) suspected of parkinsonism were included. Median duration of symptoms was 36 months (range, 1-480 months). Scans were most often requested when there was diagnostic uncertainty in clinical features (59.6%, 103/173) or to differentiate one other disease from parkinsonism such as Parkinson disease (PD) versus essential tremor (23.7%, 41/173), PD versus drug-induced parkinsonism (8.7%, 15/173), or PD versus psychogenic (6.4%, 11/173) or vascular (1.7%, 3/173) disorders. Patients were classified, according to the DAT-SPECT scanning results, as those with abnormal DAT-SPECT findings (59%, 102/173) and those with normal DAT-SPECT findings (41%, 71/173). In patients with normal DAT-SPECT findings, follow-up management data were available in 76.1% (54/71). The management changed in 39.4% (28/54) after DAT scan with starting a new appropriate medications or supportive therapy in 4.2% (3/28), withholding inappropriate dopaminergic treatment in 11.3% (8/28), or continuing observation in 23.9% (17/28). In patients with abnormal DAT-SPECT findings, follow-up management data were available in 78.4% (80/102). There was change in management of 37.3% (38/80), a new PD treatment was started in 89.5% (34/38). The dose of medication was adjusted in 5.3% (2/38), although the original treatment was not changed. Parkinson disease treatment was stopped in 2.6% (1/38) and discontinued in 2.6% (1/38) based on clinical decision of neurologists despite abnormal DAT-SPECT findings.

CONCLUSIONS

DAT-SPECT findings impacted treatment decisions in 44.7% of patients suspected of Parkinsonism.

Recent Advances in Biomarkers for Parkinson's Disease

Parkinson's disease (PD) is one of the common progressive neurodegenerative disorders with several motor and non-motor symptoms. Most of the motor symptoms may appear at a late stage where most of the dopaminergic neurons have been already damaged. In order to provide better clinical intervention and treatment at the onset of disease, it is imperative to find accurate biomarkers for early diagnosis, including prodromal diagnosis and preclinical diagnosis. At the same time, these reliable biomarkers can also be utilized to monitor the progress of the disease. In this review article, we will discuss recent advances in the development of PD biomarkers from different aspects, including clinical, biochemical, neuroimaging and genetic aspects. Although various biomarkers for PD have been developed so far, their specificity and sensitivity are not ideal when applied individually. So, the combination of multimodal biomarkers will greatly improve the diagnostic accuracy and facilitate the implementation of personalized medicine.

Detecting neurodegenerative disorders from web search signals

Neurodegenerative disorders, such as Parkinson’s disease (PD) and Alzheimer’s disease (AD), are important public health problems warranting early detection. We trained machine-learned classifiers on the longitudinal search logs of 31,321,773 search engine users to automatically detect neurodegenerative disorders. Several digital phenotypes with high discriminatory weights for detecting these disorders are identified. Classifier sensitivities for PD detection are 94.2/83.1/42.0/34.6% at false positive rates (FPRs) of 20/10/1/0.1%, respectively. Preliminary analysis shows similar performance for AD detection. Subject to further refinement of accuracy and reproducibility, these findings show the promise of web search digital phenotypes as adjunctive screening tools for neurodegenerative disorders.

NFE2L2, PPARGC1α, and pesticides and Parkinson's disease risk and progression

OBJECTIVE

To investigate three expression-altering NFE2L2 SNPs and four PPARGC1α previously implicated SNPs and pesticides on Parkinson's disease (PD) risk and symptom progression.

METHODS

In 472 PD patients and 532 population-based controls, we examined variants and their interactions with maneb and paraquat (MB/PQ) pesticide exposure on PD onset (logistic regression) and progression of motor symptoms and cognitive decline (n = 192; linear repeated measures).

RESULTS

NFE2L2 rs6721961 T allele was associated with a reduced risk of PD (OR = 0.70, 95% CI = 0.53, 0.94) and slower cognitive decline (β = 0.095; p = 0.0004). None of the PPARGC1α SNPs were marginally associated with PD risk. We estimate statistical interactions between MB/PQ and PPARGC1α rs6821591 (interaction p = 0.009) and rs8192678 (interaction p = 0.05), such that those with high exposure and the variant allele were at an increased risk of PD (OR ≥ 1.30, p ≤ 0.05). PPARGC1α rs6821591 was also associated with faster motor symptom progression as measured with the UPDRS-III (β = 0.234; p = 0.001).

CONCLUSION

Our study provides support for the involvement of both NFE2L2 and PPARGC1α in PD susceptibility and progression, marginally and through pathways involving MB/PQ exposure.

ACR-ACNM Practice Parameter for the Performance of Dopamine Transporter (DaT) Single Photon Emission Computed Tomography (SPECT) Imaging for Movement Disorders

This American College of Radiology and American College of Nuclear Medicine joint clinical practice parameter is for performance of dopamine transporter single photon emission computed tomography (SPECT) imaging, for patients with movement disorders. Parkinsonian syndrome (PS) consists of a group of neurodegenerative diseases including Parkinson disease (PD), progressive supranuclear palsy (PSP), multiple system atrophy (MSA), corticobasal degeneration (CBD), and dementia with Lewy bodies (DLB). Accurate diagnosis of PS is critical for clinical management. An important diagnostic dilemma is the differentiation of PS and non-neurodegenerative disorders, such as essential tremor (ET) or drug-induced tremor, due to the overlap of clinical symptoms. The management approach to these conditions is distinctly different. An abnormal iodine-123 ioflupane SPECT scan suggests a decreased amount of dopamine transporter in the striatum, that is, a diagnosis of nigrostriatal neurodegenerative PS, whereas a normal scan suggests ET or other nondegenerative parkinsonism (drug-induced, vascular, or psychogenic).

Mortality and quality of death certification in a cohort of patients with Parkinson's disease and matched controls in North Wales, UK at 18 years: a community-based cohort study

OBJECTIVE

This investigation reports the cause and the quality of death certification in a community cohort of patients with Parkinson's disease (PD) and controls at 18 years.

SETTING

Denbighshire North Wales, UK.

PARTICIPANTS

The community-based cohorts consisted of 166 patients with PD and 102 matched controls.

PRIMARY OUTCOMES

All-cause mortality was ascertained at 18 years by review of hospitals' primary care records and examination of death certificates obtained from the UK General Register Office. Mortality HRs were estimated using Cox proportional regression, controlling for covariates including age at study entry, age at death, gender, motor function, mood, health-related quality of life (HRQoL) and cognitive function.

RESULTS

After 18 years, 158 (95%) of patients in the PD cohort and 34 (33%) in the control cohort had died. Compared with the general UK population, the PD cohort had a higher risk of mortality (standard mortality rate, 1.82, 95% CI 1.55 to 2.13). As the primary or underlying cause of death, PD was not reported in 75/158 (47%) of the death certificates. In addition, although 144/158 (91%) of the PD cohort had a diagnosis of dementia, this was reported in less than 10% of death certificates. The main cause of death reported in the PD cohort was pneumonia (53%), followed by cardiac-related deaths (21%). Compared with controls, patients with PD had a greater risk of pneumonia (2.03, 95% CI 1.34 to 3.6), poorer HRQoL and more likely to reside in institutional care at death (P<0.01).

CONCLUSION

This investigation found that PD was associated with an excess risk of mortality compared with the general population. However, PD as a primary or underlying cause of death recorded on certificates was found to be suboptimal. This suggests that the quality of mortality statistics drawn from death certificates alone is not a valid or reliable source of data.

Sex disparities in health and health care utilization after Parkinson diagnosis: Rethinking PD associated disability

OBJECTIVE

To examine sex differences and trends in comorbid disease and health care utilization in individuals with newly diagnosed Parkinson disease (PD).

DESIGN

Retrospective cohort study.

PARTICIPANTS

Over 133,000 Medicare beneficiaries with a new PD diagnosis in 2002 followed through 2008.

METHODS

We compared the prevalence and cumulative incidence of common medical conditions, trends in survival and health care utilization between men and women with PD.

RESULTS

Female PD patients had higher adjusted incidence rate ratio (IRR) of depression (IRR: 1.28, 1.25-1.31), hip fracture (IRR: 1.51, 1.45-1.56), osteoporosis (3.01, 2.92-3.1), and rheumatoid/osteoarthritis (IRR: 1.47, 1.43-1.51) than men. In spite of greater survival, women with PD used home health and skilled nursing facility care more often, and had less outpatient physician contact than men throughout the study period.

CONCLUSIONS

Women experience a unique health trajectory after PD diagnosis as suggested by differing comorbid disease burden and health care utilization compared to men. Future studies of sex differences in care needs, care quality, comorbidity related disability, PD progression, and non-clinical factors associated with disability are needed to inform research agendas and clinical guidelines that may improve quality survival for women with PD.

Parkinson's disease in Germany: prevalence and incidence based on health claims data

BACKGROUND

In Germany, epidemiological information on Parkinson's disease (PD) is rare and outdated. Considering aging populations, current prevalences and incidence rates about this age-related disease would be important for adequate public health planning.

METHODS

We used newly available health claims data sets from the largest German health insurer dating 2004-2007 and 2007-2010 with an analysis population in the base years of 491 038 persons aged 50 and older. Quarter-specific information about ICD-10 diagnoses and PD drug prescriptions from the inpatient and outpatient sectors was used to validate PD cases. Estimations were presented for two validation strategies relying on repeated PD diagnoses (SIa) and on one PD diagnosis followed by at least one PD drug prescription (SIb).

RESULTS

The standardized prevalence was 797 (SIb) to 961/100 000 persons (SIa), showing an age-specific increase up to category 85-89 and a decline thereafter. The standardized incidence rate was 192 to 229/100 000 person-years with a similar age-specific shape. Prevalences and incidences rates were higher for men compared to women in regard to age.

CONCLUSIONS

Health claims data are found to be suitable for PD assessment using the repeated diagnoses or PD drug prescriptions as necessary criteria.

Magnetic resonance imaging for the diagnosis of Parkinson's disease

The differential diagnosis of parkinsonian syndromes is considered one of the most challenging in neurology and error rates in the clinical diagnosis can be high even at specialized centres. Despite several limitations, magnetic resonance imaging (MRI) has undoubtedly enhanced the diagnostic accuracy in the differential diagnosis of neurodegenerative parkinsonism over the last three decades. This review aims to summarize research findings regarding the value of the different MRI techniques, including advanced sequences at high- and ultra-high-field MRI and modern image analysis algorithms, in the diagnostic work-up of Parkinson's disease. This includes not only the exclusion of alternative diagnoses for Parkinson's disease such as symptomatic parkinsonism and atypical parkinsonism, but also the diagnosis of early, new onset, and even prodromal Parkinson's disease.

Editor's Highlight: Base Excision Repair Variants and Pesticide Exposure Increase Parkinson's Disease Risk

Exposure to certain pesticides induces oxidative stress and increases Parkinson's disease (PD) risk. Mitochondrial DNA (mtDNA) damage is found in dopaminergic neurons in idiopathic PD and following pesticide exposure in experimental models thereof. Base excision repair (BER) is the major pathway responsible for repairing oxidative DNA damage in cells. Whether single nucleotide polymorphisms (SNPs) in BER genes alone or in combination with pesticide exposure influence PD risk is unknown. We investigated the contributions of functional SNPs in 2 BER genes (APEX1 and OGG1) and mitochondrial dysfunction- or oxidative stress-related pesticide exposure, including paraquat, to PD risk. We also studied the effect of paraquat on levels of mtDNA damage and mitochondrial bioenergetics. 619 PD patients and 854 population-based controls were analyzed for the 2 SNPs, APEX1 rs1130409 and OGG1 rs1052133. Ambient pesticide exposures were assessed with a geographic information system. Individually, or in combination, the BER SNPs did not influence PD risk. Mitochondrial-inhibiting (OR = 1.79, 95% CI [1.32, 2.42]), oxidative stress-inducing pesticides (OR = 1.61, 95% CI [1.22, 2.11]), and paraquat (OR = 1.54, 95% CI [1.23, 1.93]) were associated with PD. Statistical interactions were detected, including for a genetic risk score based on rs1130409 and rs1052133 and oxidative stress inducing pesticides, where highly exposed carriers of both risk genotypes were at the highest risk of PD (OR = 2.21, 95% CI [1.25, 3.86]); similar interactions were estimated for mitochondrial-inhibiting pesticides and paraquat alone. Additionally, paraquat exposure was found to impair mitochondrial respiration and increase mtDNA damage in in vivo and in vitro systems. Our findings provide insight into possible mechanisms involved in increased PD risk due to pesticide exposure in the context of BER genotype variants.

Challenges and opportunities for brainstem neuroimaging with ultrahigh field MRI

The human brainstem plays a central role in connecting the cerebrum, the cerebellum and the spinal cord to one another, hosting relay nuclei for afferent and efferent signaling, and providing source nuclei for several neuromodulatory systems that impact central nervous system function. While the investigation of the brainstem with functional or structural magnetic resonance imaging has been hampered for years due to this brain structure's physiological and anatomical characteristics, the field has seen significant advances in recent years thanks to the broader adoption of ultrahigh-field (UHF) MRI scanning. In the present review, we focus on the advantages offered by UHF in the context of brainstem imaging, as well as the challenges posed by the investigation of this complex brain structure in terms of data acquisition and analysis. We also illustrate how UHF MRI can shed new light on the neuroanatomy and neurophysiology underlying different brainstem-based circuitries, such as the central autonomic network and neurotransmitter/neuromodulator systems, discuss existing and foreseeable clinical applications to better understand diseases such as chronic pain and Parkinson's disease, and explore promising future directions for further improvements in brainstem imaging using UHF MRI techniques.

Proteomic studies associated with Parkinson's disease

INTRODUCTION

Parkinson's disease (PD) is an insidious disorder affecting more than 1-2% of the population over the age of 65. Understanding the etiology of PD may create opportunities for developing new treatments. Genomic and transcriptomic studies are useful, but do not provide evidence for the actual status of the disease. Conversely, proteomic studies deal with proteins, which are real time players, and can hence provide information on the dynamic nature of the affected cells. The number of publications relating to the proteomics of PD is vast. Therefore, there is a need to evaluate the current proteomics literature and establish the connections between the past and the present to foresee the future. Areas covered: PubMed and Web of Science were used to retrieve the literature associated with PD proteomics. Studies using human samples, model organisms and cell lines were selected and reviewed to highlight their contributions to PD. Expert commentary: The proteomic studies associated with PD achieved only limited success in facilitating disease diagnosis, monitoring and progression. A global system biology approach using new models is needed. Future research should integrate the findings of proteomics with other omics data to facilitate both early diagnosis and the treatment of PD.

Reliability of functional gait assessment in patients with Parkinson disease: Interrater and intrarater reliability and internal consistency

To determine the reliability of the functional gait assessment (FGA) as a measure of balance and gait in patients with Parkinson disease (PD).This study involved121 inpatients with PD (mean age 61.9 years). The participants were scored using the FGA by 2 raters, and the testing procedure was videotaped. One of the raters re-assessed the same FGA test via review of the videotaped test 4 weeks later.The interrater and intrarater reliability of the total FGA score was found to be excellent, with an intraclass correlation coefficient of 0.99. The reliability of single items of the FGA ranged from 0.49 to 0.99. The internal consistency of the FGA scores was 0.94.The FGA has high inter-rater and intrarater reliability, and internal consistency for evaluating balance and gait disorders in patients with PD.

Recent advances in biomarkers for Parkinson's disease focusing on biochemicals, omics and neuroimaging

Parkinson's disease (PD) is one of the most common neurodegenerative disorders, involving progressive loss of the nigro-striatal dopaminergic neurons. Cardinal symptoms including tremors, muscle rigidity, drooping posture, drooping, walking difficulty, and autonomic symptoms appear when a significant number of nigrostriatal dopaminergic neurons have already been destroyed. Hence, reliable biomarkers are needed for early and accurate diagnosis to measure disease progression and response to therapy. We review the current status of protein and small molecule biomarkers involved in oxidative stress, protein aggregation and inflammation etc. which are present in cerebrospinal fluid, human blood, urine or saliva. In recent years, advances in genomics, proteomics, metabolomics, and functional brain imaging techniques have led to new insights into the pathoetiology of PD. Further studies in the novel discovery of PD biomarkers will provide avenues to treat PD patients more effectively with few or no side effects.

Diagnostic errors in older patients: a systematic review of incidence and potential causes in seven prevalent diseases

Background

Misdiagnosis, either over- or underdiagnosis, exposes older patients to increased risk of inappropriate or omitted investigations and treatments, psychological distress, and financial burden.

Objective

To evaluate the frequency and nature of diagnostic errors in 16 conditions prevalent in older patients by undertaking a systematic literature review.

Data sources and study selection

Cohort studies, cross-sectional studies, or systematic reviews of such studies published in Medline between September 1993 and May 2014 were searched using key search terms of “diagnostic error”, “misdiagnosis”, “accuracy”, “validity”, or “diagnosis” and terms relating to each disease.

Data synthesis

A total of 938 articles were retrieved. Diagnostic error rates of >10% for both over- and underdiagnosis were seen in chronic obstructive pulmonary disease, dementia, Parkinson’s disease, heart failure, stroke/transient ischemic attack, and acute myocardial infarction. Diabetes was overdiagnosed in <5% of cases.

Conclusion

Over- and underdiagnosis are common in older patients. Explanations for over-diagnosis include subjective diagnostic criteria and the use of criteria not validated in older patients. Underdiagnosis was associated with long preclinical phases of disease or lack of sensitive diagnostic criteria. Factors that predispose to misdiagnosis in older patients must be emphasized in education and clinical guidelines.

Organophosphate Pesticide Exposures, Nitric Oxide Synthase Gene Variants, and Gene-Pesticide Interactions in a Case-Control Study of Parkinson's Disease, California (USA)

BACKGROUND

Nitric oxide synthase (NOS) genes are candidates for Parkinson's disease (PD) because NOS enzymes produce nitric oxide (NO), a pro-oxidant that can damage neurons. Widely used organophosphate (OP) pesticides can induce oxidative stress and are reported to increase PD risk. Additionally, two single nucleotide polymorphisms (SNPs) from the PON1 (paraoxonase 1) gene influence the ability to metabolize OPs.

OBJECTIVE

Here, we investigated contributions of NOS genes and OP pesticides to PD risk, controlling for PON1 status.

METHODS

In 357 incident PD cases and 495 population controls, we investigated eight NOS SNPs and interactions with both household and ambient agricultural OP exposures assessed with geographic information system (GIS).

RESULTS

In comparing PD in homozygous variant carriers of NOS2A rs1060826 versus homozygous wild-type or heterozygotes, we estimate an adjusted odds ratio (OR) of 1.51 (95% CI: 0.95, 2.41). When considering interactions between NOS1 rs2682826 and OP exposure from household use, the OR for frequent OP use alone was 1.30 (95% CI: 0.72, 2.34) and for the CT+TT genotype alone was 0.89 (95% CI: 0.58, 1.39), and for frequent OP use combined with the CT+TT genotype the OR was 2.84 (95% CI: 1.49, 5.40) (interaction p-value 0.04). Similar results were seen for ambient OP exposure. Interactions between OP exposure and three other NOS1 SNPs and a genetic risk score combining all NOS1 SNPs reached statistical significance.

CONCLUSIONS

We found that OP pesticides were more strongly associated with PD among participants with variant genotypes in NOS1, consistent with the importance of oxidative stress-inducing mechanisms. Our data provide evidence for NOS1 modifying PD risk in OP exposed populations.

CITATION

Paul KC, Sinsheimer JS, Rhodes SL, Cockburn M, Bronstein J, Ritz B. 2016. Organophosphate pesticide exposures, nitric oxide synthase gene variants, and gene-pesticide interactions in a case-control study of Parkinson's disease, California (USA). Environ Health Perspect 124:570-577; http://dx.doi.org/10.1289/ehp.1408976.

Computational approaches for understanding the diagnosis and treatment of Parkinson's disease

This study describes how the application of evolutionary algorithms (EAs) can be used to study motor function in humans with Parkinson's disease (PD) and in animal models of PD. Human data is obtained using commercially available sensors via a range of non-invasive procedures that follow conventional clinical practice. EAs can then be used to classify human data for a range of uses, including diagnosis and disease monitoring. New results are presented that demonstrate how EAs can also be used to classify fruit flies with and without genetic mutations that cause Parkinson's by using measurements of the proboscis extension reflex. The case is made for a computational approach that can be applied across human and animal studies of PD and lays the way for evaluation of existing and new drug therapies in a truly objective way.

What do patients with scans without evidence of dopaminergic deficit (SWEDD) have? New evidence and continuing controversies

The term SWEDD (scans without evidence for dopaminergic deficit) refers to the absence, rather than the presence, of an imaging abnormality in patients clinically presumed to have Parkinson's disease (PD). However, such a term has since been widely used in the medical literature, even as a diagnostic label. While many authors have suggested that different disorders of PD lookalikes may account for a proportion of SWEDD cases, others have claimed that some of them may have a benign subtype of PD. Thus, there has been ensuing controversy and confusion and the use of this term continues without clarity of what it represents. We have systematically reviewed all the studies involving patients with SWEDD with the aim of shedding light on what these patients actually have. It becomes clear from this systematic review that while most 'SWEDD' cases are due to a clinical misdiagnosis of PD, there exists a small proportion of patients with SWEDD who may have PD on the basis of a positive levodopa response, clinical progression, imaging and/or genetic evidence. The latter challenge the seemingly incontrovertible relationship between dopaminergic tracer binding and the diagnosis of nigrostriatal parkinsonism, particularly PD. Patients with SWEDD are unlikely to reflect a single clinical entity and we suggest that the term SWEDD should be abandoned.

Accuracy of clinical diagnosis of Parkinson disease: A systematic review and meta-analysis

OBJECTIVE

To evaluate the diagnostic accuracy of clinical diagnosis of Parkinson disease (PD) reported in the last 25 years by a systematic review and meta-analysis.

METHODS

We searched for articles published between 1988 and August 2014. Studies were included if reporting diagnostic parameters regarding clinical diagnosis of PD or crude data. The selected studies were subclassified based on different study setting, type of test diagnosis, and gold standard. Bayesian meta-analyses of available data were performed.

RESULTS

We selected 20 studies, including 11 using pathologic examination as gold standard. Considering only these 11 studies, the pooled diagnostic accuracy was 80.6% (95% credible interval [CrI] 75.2%-85.3%). Accuracy was 73.8% (95% CrI 67.8%-79.6%) for clinical diagnosis performed mainly by nonexperts. Accuracy of clinical diagnosis performed by movement disorders experts rose from 79.6% (95% CrI 46%-95.1%) of initial assessment to 83.9% (95% CrI 69.7%-92.6%) of refined diagnosis after follow-up. Using UK Parkinson's Disease Society Brain Bank Research Center criteria, the pooled diagnostic accuracy was 82.7% (95% CrI 62.6%-93%).

CONCLUSION

The overall validity of clinical diagnosis of PD is not satisfying. The accuracy did not significantly improve in the last 25 years, particularly in the early stages of disease, where response to dopaminergic treatment is less defined and hallmarks of alternative diagnoses such as atypical parkinsonism may not have emerged. Misclassification rate should be considered to calculate the sample size both in observational studies and randomized controlled trials. Imaging and biomarkers are urgently needed to improve the accuracy of clinical diagnosis in vivo.

Temporal fluctuations of tremor signals from inertial sensor: a preliminary study in differentiating Parkinson's disease from essential tremor

BACKGROUND

Parkinson's disease (PD) and essential tremor (ET) are the two most common movement disorders but the rate of misdiagnosis rate in these disorders is high due to similar characteristics of tremor. The purpose of the study is to present: (a) a solution to identify PD and ET patients by using the novel measurement of tremor signal variations while performing the resting task, (b) the improvement of the differentiation of PD from ET patients can be obtained by using the ratio of the novel measurement while performing two specific tasks.

METHODS

35 PD and 22 ET patients were asked to participate in the study. They were asked to wear a 6-axis inertial sensor on his/her index finger of the tremor dominant hand and perform three tasks including kinetic, postural and resting tasks. Each task required 10 s to complete. The angular rate signal measured during the performance of these tasks was band-pass filtered and transformed into a two-dimensional representation. The ratio of the ellipse area covering 95 % of this two-dimensional representation of different tasks was investigated and the two best tasks were selected for the purpose of differentiation.

RESULTS

The ellipse area of two-dimensional representation of the resting task of PD and ET subjects are statistically significantly different (p < 0.05). Furthermore, the fluctuation ratio, defined as a ratio of the ellipse area of two-dimensional representation of resting to kinetic tremor, of PD subjects were statistically significantly higher than ET subjects in all axes (p = 0.0014, 0.0011 and 0.0001 for x, y and z-axis, respectively). The validation shows that the proposed method provides 100 % sensitivity, specificity and accuracy of the discrimination in the 5 subjects in the validation group. While the method would have to be validated with a larger number of subjects, these preliminary results show the feasibility of the approach.

CONCLUSIONS

This study provides the novel measurement of tremor variation in time domain termed 'temporal fluctuation'. The temporal fluctuation of the resting task can be used to discriminate PD from ET subjects. The ratio of the temporal fluctuation of the resting task to the kinetic task improves the reliability of the discrimination. While the method is powerful, it is also simple so it could be applied on low resource platforms such as smart phones and watches which are commonly equipped with inertial sensors.

The Natural Progression of Parkinson's Disease in a Small Cohort with 15 Drug-naïve Patients

BACKGROUND

The studies of the natural progression of Parkinson's disease (PD) in Chinese populations have been lacking. To address this issue and obtain a preliminary data, we conducted a PD progression assessment in 15 adults with de novo PD from a nutritional intervention trial (NIT) cohort in Lin County China.

METHODS

Using the Copiah County screening questionnaire and United Kingdom Parkinson's Disease Society Brain Bank diagnostic criteria, we surveyed the available NIT cohort members in 2000 and diagnosed 86 patients as PD. In 2010, we resurveyed all PD patients and confirmed definite PD diagnosis in 15 cases with the rest of them being dead (54); having probable (10) PD or vascular Parkinsonism (3); refusing to participate (2); or being away (2). In both surveys, we used Hoehn and Yahr (HY) scale and assessed the disease progression. Unified Parkinson's Disease Rating Scale (UPDRS) was added to the second survey.

RESULTS

In 2010, the average disease duration for 15 definite PD patients was 13.6 ± 7.3 years. Over a 10-year time span, 9 out of 15 patients remained at the same HY stage while the remaining 6 progressed. Rigidity (47% vs. 100%; P = 0.002) and postural instability (7% vs. 47%; P = 0.005) worsened significantly. The mean UPDRS motor scores in 2010 were 39.4 ± 23.7.

CONCLUSIONS

Overall worsening of motor function in PD seems to be the rule in this untreated cohort, and their rate of progression seemed to be slower than those reported in the western populations.