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Parkinson Disease: HELP
Articles by Alastair John Noyce
Based on 45 articles published since 2010
(Why 45 articles?)
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Between 2010 and 2020, A. Noyce wrote the following 45 articles about Parkinson Disease.
 
+ Citations + Abstracts
Pages: 1 · 2
1 Review The motor prodromes of parkinson's disease: from bedside observation to large-scale application. 2019

Simonet, C / Schrag, A / Lees, A J / Noyce, A J. ·Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK. · Department of Clinical and Movement Neurosciences, Institute of Neurology, University College London, London, UK. · Reta Lila Weston Institute of Neurological Studies, University College London, London, UK. · Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK. a.noyce@qmul.ac.uk. · Department of Clinical and Movement Neurosciences, Institute of Neurology, University College London, London, UK. a.noyce@qmul.ac.uk. ·J Neurol · Pubmed #31802219.

ABSTRACT: There is sufficient evidence that the pathological process that causes Parkinson's disease begins years before the clinical diagnosis is made. Over the last 15 years, there has been much interest in the existence of a prodrome in some patients, with a particular focus on non-motor symptoms such as reduced sense of smell, REM-sleep disorder, depression, and constipation. Given that the diagnostic criteria for Parkinson's disease depends on the presence of bradykinesia, it is somewhat surprising that there has been much less research into the possibility of subtle motor dysfunction as a pre-diagnostic pointer. This review will focus on early motor features and provide some advice on how to detect and measure them.

2 Review An early diagnosis is not the same as a timely diagnosis of Parkinson's disease. 2018

Rees, Richard Nathaniel / Acharya, Anita Prema / Schrag, Anette / Noyce, Alastair John. ·Department of Clinical Neuroscience, Institute of Neurology, UCL Hampstead Campus, London, UK. · Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK. · Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK. · Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK. ·F1000Res · Pubmed #30079229.

ABSTRACT: Parkinson's disease is a common neurodegenerative condition that has significant costs to the individual patient and to society. The pathology starts up to a decade before symptoms are severe enough to allow a diagnosis using current criteria. Although the search for disease-modifying treatment continues, it is vital to understand what the right time is for diagnosis. Diagnosis of Parkinson's disease is based on the classic clinical criteria, but the presence of other clinical features and disease biomarkers may allow earlier diagnosis, at least in a research setting. In this review, we identify the benefits of an early diagnosis, including before the classic clinical features occur. However, picking the right point for a "timely" diagnosis will vary depending on the preferences of the individual patient, efficacy (or existence) of disease-modifying treatment, and the ability for health systems to provide support and management for individuals at every stage of the disease. Good evidence for the quality-of-life benefits of existing symptomatic treatment supports the argument for earlier diagnosis at a time when symptoms are already present. This argument would be significantly bolstered by the development of disease-modifying treatments. Benefits of early diagnosis and treatment would affect not only the individual (and their families) but also the wider society and the research community. Ultimately, however, shared decision-making and the principles of autonomy, beneficence, and non-maleficence will need to be applied on an individual basis when considering a "timely" diagnosis.

3 Review Parkinson's Disease: Basic Pathomechanisms and a Clinical Overview. 2017

Noyce, Alastair / Bandopadhyay, Rina. ·Department of Molecular Neuroscience, Reta Lila Weston Institute of Neurological Studies, UCL Institute of Neurology, 1, Wakefield Street, London, WC1N 1PJ, UK. · Department of Molecular Neuroscience, Reta Lila Weston Institute of Neurological Studies, UCL Institute of Neurology, 1, Wakefield Street, London, WC1N 1PJ, UK. rina.bandopadhyay@ucl.ac.uk. ·Adv Neurobiol · Pubmed #28674978.

ABSTRACT: PD is a common and a debilitating degenerative movement disorder. The number of patients is increasing worldwide and as yet there is no cure for the disease. The majority of existing treatments target motor symptom control. Over the last two decades the impact of the genetic contribution to PD has been appreciated. Significant discoveries have been made, which have advanced our understanding of the pathophysiological and molecular basis of PD. In this chapter we outline current knowledge of the clinical aspects of PD and the basic mechanistic understanding.

4 Review Technologies Assessing Limb Bradykinesia in Parkinson's Disease. 2017

Hasan, Hasan / Athauda, Dilan S / Foltynie, Thomas / Noyce, Alastair J. ·UCL Institute of Neurology, Queen Square, London, UK. · Sobell Department of Motor Neuroscience and Movement Disorders, The National Hospital for Neurology and Neurosurgery, London, UK. · Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University London, London, UK. · Reta Lila Weston Institute of Neurological studies, UCL Institute of Neurology, London, UK. ·J Parkinsons Dis · Pubmed #28222539.

ABSTRACT: BACKGROUND: The MDS-UPDRS (Movement Disorders Society - Unified Parkinson's Disease Rating Scale) is the most widely used scale for rating impairment in PD. Subscores measuring bradykinesia have low reliability that can be subject to rater variability. Novel technological tools can be used to overcome such issues. OBJECTIVE: To systematically explore and describe the available technologies for measuring limb bradykinesia in PD that were published between 2006 and 2016. METHODS: A systematic literature search using PubMed (MEDLINE), IEEE Xplore, Web of Science, Scopus and Engineering Village (Compendex and Inspec) databases was performed to identify relevant technologies published until 18 October 2016. RESULTS: 47 technologies assessing bradykinesia in PD were identified, 17 of which offered home and clinic-based assessment whilst 30 provided clinic-based assessment only. Of the eligible studies, 7 were validated in a PD patient population only, whilst 40 were tested in both PD and healthy control groups. 19 of the 47 technologies assessed bradykinesia only, whereas 28 assessed other parkinsonian features as well. 33 technologies have been described in additional PD-related studies, whereas 14 are not known to have been tested beyond the pilot phase. CONCLUSION: Technology based tools offer advantages including objective motor assessment and home monitoring of symptoms, and can be used to assess response to intervention in clinical trials or routine care. This review provides an up-to-date repository and synthesis of the current literature regarding technology used for assessing limb bradykinesia in PD. The review also discusses the current trends with regards to technology and discusses future directions in development.

5 Review Challenges of modifying disease progression in prediagnostic Parkinson's disease. 2016

Salat, David / Noyce, Alastair J / Schrag, Anette / Tolosa, Eduardo. ·Neurology Service, Hospital Vall d'Hebron, Barcelona, Spain. · Reta Lila Weston Institute for Neurological Studies, UCL Institute of Neurology, London, UK. · Department of Clinical Neurosciences, UCL Institute of Neurology, London, UK. · Parkinson's Disease Research, August Pi i Sunyer Biomedical Research Institute, University of Barcelona, Barcelona, Spain; Parkinson Disease and Movement Disorder Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Universidad de Barcelona, Barcelona, Spain. Electronic address: etolosa@clinic.ub.es. ·Lancet Neurol · Pubmed #26993435.

ABSTRACT: Neurodegeneration in Parkinson's disease starts years before a clinical diagnosis can be reliably made. The prediagnostic phase of the disease offers a window of opportunity in which disease-modifying therapies-ie, those aimed at delaying or preventing the progression to overt disease and its many complications-could be most beneficial, but no such therapies are available at present. The unravelling of the mechanisms of neurodegeneration from the earliest stages, however, could lead to the development of new interventions whose therapeutic potential will need to be assessed in adequately designed clinical trials. Advances in the understanding of this prediagnostic phase of Parkinson's disease (for which the clinical diagnostic and prognostic markers used in more advanced disease stages are not applicable) will lead to the identification of biomarkers of neurodegeneration and its progression. These biomarkers will, in turn, help to identify the optimum population to be included and the most appropriate outcomes to be assessed in trials of disease-modifying drugs. Potential risks to minimally symptomatic participants, some of whom might not progress to manifest Parkinson's disease, and individuals who do not wish to know their mutation carrier status, could pose specific ethical dilemmas in the design of these trials.

6 Review The prediagnostic phase of Parkinson's disease. 2016

Noyce, Alastair John / Lees, Andrew John / Schrag, Anette-Eleonore. ·Department of Molecular Neuroscience, Reta Lila Weston Institute for Neurological Studies, UCL Institute of Neurology, London, UK. · Department of Clinical Neuroscience, UCL Institute of Neurology, London, UK. ·J Neurol Neurosurg Psychiatry · Pubmed #26848171.

ABSTRACT: The field of prediagnostic Parkinson's disease (PD) is fast moving with an expanding range of clinical and laboratory biomarkers, and multiple strategies seeking to discover those in the earliest stages or those 'at risk'. It is widely believed that the highest likelihood of securing neuroprotective benefit from drugs will be in these subjects, preceding current point of diagnosis of PD. In this review, we outline current knowledge of the prediagnostic phase of PD, including an up-to-date review of risk factors (genetic and environmental), their relative influence, and clinical features that occur prior to diagnosis. We discuss imaging markers across a range of modalities, and the emerging literature on fluid and peripheral tissue biomarkers. We then explore current initiatives to identify individuals at risk or in the earliest stages that might be candidates for future clinical trials, what we are learning from these initiatives, and how these studies will bring the field closer to realistically commencing primary or secondary preventive trials for PD. Further progress in this field hinges on greater clinical and biological description, and understanding of the prediagnostic, peridiagnostic and immediate postdiagnostic stages of PD. Identifying subjects 3-5 years before they are currently diagnosed may be an ideal group for neuroprotective trials. At the very least, these initiatives will help clarify the stage before and around diagnosis, enabling the field to push into unchartered territory at the earliest stages of disease.

7 Review Mendelian Randomization - the Key to Understanding Aspects of Parkinson's Disease Causation? 2016

Noyce, Alastair J / Nalls, Mike A. ·Reta Lila Weston Institute for Neurological Studies, UCL Institute of Neurology, London, UK. · Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA. ·Mov Disord · Pubmed #26695521.

ABSTRACT: Parkinson's disease has multiple determinants and is associated with a wide range of exposures that appear to modify risk in traditional observational studies, including numerous lifestyle and environmental factors. Across other fields of medicine, Mendelian randomization has emerged as a powerful method to examine whether associations between exposures and disease outcomes are causal. Here we discuss the concept of Mendelian randomization, its potential relevance to Parkinson's disease, and suggest avenues through which the method could be employed to further understanding of the causal basis of Parkinson's disease.

8 Review Constipation preceding Parkinson's disease: a systematic review and meta-analysis. 2016

Adams-Carr, Kerala L / Bestwick, Jonathan P / Shribman, Samuel / Lees, Andrew / Schrag, Anette / Noyce, Alastair J. ·Charing Cross Hospital, London, UK. · Wolfson Institute of Preventive Medicine, Barts and The London School of Medicine and Dentistry, London, UK. · National Hospital for Neurology and Neurosurgery, London, UK. · Institute of Neurology, University College London, London, UK. ·J Neurol Neurosurg Psychiatry · Pubmed #26345189.

ABSTRACT: OBJECTIVE: To systematically review published literature to estimate the magnitude of association between premorbid constipation and later diagnosis of Parkinson's disease. BACKGROUND: Constipation is a recognised non-motor feature of Parkinson's and has been reported to predate diagnosis in a number of observational studies. METHODS: A systematic review and meta-analysis was carried out following the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) criteria. A literature search was undertaken in December 2014 using PubMed and the search terms 'Parkinson's disease' and 'constipation'. Articles were screened for suitability and reviewed against inclusion and exclusion criteria. Studies were included if they assessed constipation by means of a structured questionnaire or if constipation/drugs used to treat constipation were coded in patient medical records. Data were extracted using a standardised template and effect size estimates combined using a fixed-effects model. Heterogeneity was explored with the I(2) statistic. RESULTS: 9 studies were included in the meta-analysis, with a combined sample size of 741 593 participants. Those with constipation had a pooled OR of 2.27 (95% CI 2.09 to 2.46) for developing subsequent Parkinson's disease compared with those without constipation. Weak evidence for heterogeneity was found (I(2)=18.9%, p=0.282). Restricting analysis to studies assessing constipation more than 10 years prior to Parkinson's disease gave a pooled OR of 2.13 (95% CI 1.78 to 2.56; I(2)=0.0%). CONCLUSIONS: This systematic review and meta-analysis demonstrates that people with constipation are at a higher risk of developing Parkinson's disease compared with those without and that constipation can predate Parkinson's diagnosis by over a decade.

9 Review Systematic review and meta-analysis of salivary protein concentration in Parkinson's disease. 2015

Masters, Joseph M / Bestwick, Jonathan / Warner, Thomas T / Giovannoni, Gavin / Proctor, Gordon B / Noyce, Alastair J. ·Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom. · Mucosal & Salivary Biology Division, King's College London Dental Institute, London, United Kingdom. · Reta Lila Weston Institute of Neurological Studies, UCL Institute of Neurology, London, United Kingdom. ·Mov Disord · Pubmed #26583568.

ABSTRACT: -- No abstract --

10 Review Bone health in Parkinson's disease: a systematic review and meta-analysis. 2014

Torsney, Kelli M / Noyce, Alastair J / Doherty, Karen M / Bestwick, Jonathan P / Dobson, Ruth / Lees, Andrew J. ·Emergency Department, West Middlesex Hospital, London, UK. · Reta Lila Weston Institute of Neurological Studies, UCL Institute of Neurology, London, UK. · Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK. · Blizard Institute, Centre for Neuroscience and Trauma, Queen Mary University of London, London, UK. ·J Neurol Neurosurg Psychiatry · Pubmed #24620034.

ABSTRACT: OBJECTIVE: Parkinson's disease (PD) and osteoporosis are chronic diseases associated with increasing age. Single studies have reported associations between them and the major consequence, namely, increased risk of fractures. The aim of this systematic review and meta-analysis was to evaluate the relationship of PD with osteoporosis, bone mineral density (BMD) and fracture risk. METHODS: A literature search was undertaken on 4 September 2012 using multiple indexing databases and relevant search terms. Articles were screened for suitability and data extracted where studies met inclusion criteria and were of sufficient quality. Data were combined using standard meta-analysis methods. RESULTS: 23 studies were used in the final analysis. PD patients were at higher risk of osteoporosis (OR 2.61; 95% CI 1.69 to 4.03) compared with healthy controls. Male patients had a lower risk for osteoporosis and osteopenia than female patients (OR 0.45; 95% CI 0.29 to 0.68). PD patients had lower hip, lumbar spine and femoral neck BMD levels compared with healthy controls; mean difference, -0.08, 95% CI -0.13 to -0.02 for femoral neck; -0.09, 95% CI -0.15 to -0.03 for lumbar spine; and -0.05, 95% CI -0.07 to -0.03 for total hip. PD patients were also at increased risk of fractures (OR 2.28; 95% CI 1.83 to 2.83). CONCLUSIONS: This systematic review and meta-analysis demonstrate that PD patients are at higher risk for both osteoporosis and osteopenia compared with healthy controls, and that female patients are at greater risk than male patients. Patients with PD also have lower BMD and are at increased risk of fractures.

11 Review Bone health in chronic neurological diseases: a focus on multiple sclerosis and parkinsonian syndromes. 2013

Dobson, Ruth / Yarnall, Alison / Noyce, Alastair John / Giovannoni, Gavin. ·Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University, London, UK. ruth.dobson@qmul.ac.uk ·Pract Neurol · Pubmed #23468558.

ABSTRACT: The importance of bone health is increasingly recognised, and there is mounting evidence that neurological conditions are associated with a significantly increased risk of osteoporosis and fractures. This increase in risk is likely to be multifactorial. Multiple sclerosis and Parkinson's disease were identified in the Global Longitudinal Study of Osteoporosis in Women study as significantly associated with osteoporosis. Here, we discuss the literature on bone health, falls and fractures in MS and akinetic-rigid syndromes, and suggest strategies to investigate and manage bone health in the neurology clinic.

12 Review Meta-analysis of early nonmotor features and risk factors for Parkinson disease. 2012

Noyce, Alastair J / Bestwick, Jonathan P / Silveira-Moriyama, Laura / Hawkes, Christopher H / Giovannoni, Gavin / Lees, Andrew J / Schrag, Anette. ·Institute of Neurology, University College London, London, United Kingdom. ·Ann Neurol · Pubmed #23071076.

ABSTRACT: OBJECTIVE: To evaluate the association between diagnosis of Parkinson disease (PD) and risk factors or early symptoms amenable to population-based screening. METHODS: A systematic review and meta-analysis of risk factors for PD. RESULTS: The strongest associations with later diagnosis of PD were found for having a first-degree or any relative with PD (odds ratio [OR], 3.23; 95% confidence interval [CI], 2.65-3.93 and OR, 4.45; 95% CI, 3.39-5.83) or any relative with tremor (OR, 2.74; 95% CI, 2.10-3.57), constipation (relative risk [RR], 2.34; 95% CI, 1.55-3.53), or lack of smoking history (current vs never: RR, 0.44; 95% CI, 0.39-0.50), each at least doubling the risk of PD. Further positive significant associations were found for history of anxiety or depression, pesticide exposure, head injury, rural living, beta-blockers, farming occupation, and well-water drinking, and negative significant associations were found for coffee drinking, hypertension, nonsteroidal anti-inflammatory drugs, calcium channel blockers, and alcohol, but not for diabetes mellitus, cancer, oral contraceptive pill use, surgical menopause, hormone replacement therapy, statins, acetaminophen/paracetamol, aspirin, tea drinking, history of general anesthesia, or gastric ulcers. In the systematic review, additional associations included negative associations with raised serum urate, and single studies or studies with conflicting results. INTERPRETATION: The strongest risk factors associated with later PD diagnosis are having a family history of PD or tremor, a history of constipation, and lack of smoking history. Further factors also but less strongly contribute to risk of PD diagnosis or, as some premotor symptoms, require further standardized studies to demonstrate the magnitude of risk associated with them.

13 Article Motor Dysfunction as a Prodrome of Parkinson's Disease. 2020

Alarcón, Fernando / Maldonado, Juan-Carlos / Cañizares, Miguel / Molina, José / Noyce, Alastair / Lees, Andrew J. ·Department of Neurology, Hospital Eugenio Espejo, Quito, Ecuador. · Faculty of Medicine, Universidad Central del Ecuador; and Universidad Regional Autónoma de los Andes, Quito, Ecuador. · Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK. · Reta Lila Weston, Institute of Neurology, London, UK. ·J Parkinsons Dis · Pubmed #32390641.

ABSTRACT: BACKGROUND: Recognition of motor signs in the prodromal stage could lead to best identify populations at risk for developing Parkinson's disease (PD). OBJECTIVE: This study identified motor symptoms and signs in individuals suspected of having PD but who did not have a progressive reduction in the speed and amplitude of finger tapping or other physical signs indicative of bradykinesia. METHODS: 146 patients, who had symptoms or signs suggestive of PD, were serially evaluated by a movement disorder specialist, using the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III and video recordings. If the patients 'converted' to PD during follow-up, they were categorized as cases and compared with those who did not meet PD criteria during follow-up (non-cases). RESULTS: The 82 cases were more likely to have action dystonia or postural/action/rest tremor of a limb (OR 2.8; 95% CI 1.10-7.09; p = 0.02), a reduced blink rate at rest (OR 2.32; 95% CI 1.18-4.55; p = 0.01), anxiety (OR 8.91; 95% CI 2.55-31.1; p <  0.001), depression (OR 7.03; 95% CI 2.86-17.2; p <  0.001), or a frozen shoulder (OR 3.14; 95% CI 1.58-6.21) than the 64 'non-cases'. A reduction of the fast blink rate was common in patients who met the criteria for PD (p <  0.001). CONCLUSIONS: This study emphasizes that motor dysfunction is a component of the clinical prodrome seen in some patients with PD.

14 Article Testing Shortened Versions of Smell Tests to Screen for Hyposmia in Parkinson's Disease. 2020

Auger, Stephen D / Kanavou, Sofia / Lawton, Michael / Ben-Shlomo, Yoav / Hu, Michele T / Schrag, Anette E / Morris, Huw R / Grosset, Donald G / Noyce, Alastair J. ·Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London London United Kingdom. · Population Health Sciences, University of Bristol Bristol United Kingdom. · Oxford Parkinson's Disease Centre University of Oxford Oxford United Kingdom. · Nuffield Department of Clinical Neurosciences University of Oxford Oxford United Kingdom. · Department of Clinical and Movement Neuroscience UCL Institute of Neurology, University College London London United Kingdom. · Department of Neurology Institute of Neurological Sciences, Queen Elizabeth University Hospital Glasgow United Kingdom. · Reta Lila Weston Institute and Department of Clinical and Movement Neuroscience UCL Institute of Neurology, University College London London United Kingdom. ·Mov Disord Clin Pract · Pubmed #32373655.

ABSTRACT: Background: Hyposmia is an early feature in neurodegenerative diseases, most notably Parkinson's disease (PD). Using abbreviated smell tests could provide a cost-effective means for large-scale hyposmia screening. It is unclear whether short smell tests can effectively detect hyposmia in patient populations. Objectives: To test the ability of short smell combinations to "prescreen" for probable hyposmia in people with PD and target administration of more extensive tests, such as the University of Pennsylvania Smell Identification Test. Methods: We assessed the screening performance of a short 4-smell combination previously derived from use of the 40-item University of Pennsylvania Smell Identification Test in healthy older people and its ability to detect hyposmia in a large cohort of PD patients. Results: The novel 4-smell combination included menthol, clove, onion, and orange and had a sensitivity of 87.1% (95% confidence interval, 84.9%-89.2%) and specificity of 69.7% (63.3%-75.5%) for detecting hyposmia in patients with PD. A different (also novel) 4-item combination developed using a data-driven approach in PD patients only achieved 81.3% (78.2%-84.4%) sensitivity for equivalent specificity. Conclusions: A short 4-smell combination derived from a healthy population demonstrated high sensitivity to detect those with hyposmia and PD.

15 Article The Association Between Type 2 Diabetes Mellitus and Parkinson's Disease. 2020

Cheong, Julia L Y / de Pablo-Fernandez, Eduardo / Foltynie, Thomas / Noyce, Alastair J. ·Barts and The London School of Medicine, Queen Mary University of London, London, UK. · Reta Lila Weston Institute of Neurological Studies, UCL Queen Square Institute of Neurology, London, UK. · Department of Clinical and Movement Neurosciences, University College London Institute of Neurology, London, UK. · Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK. ·J Parkinsons Dis · Pubmed #32333549.

ABSTRACT: In recent years, an emerging body of evidence has forged links between Parkinson's disease (PD) and type 2 diabetes mellitus (T2DM). In observational studies, those with T2DM appear to be at increased risk of developing PD, as well as experiencing faster progression and a more severe phenotype of PD, with the effects being potentially mediated by several common cellular pathways. The insulin signalling pathway, for example, may be responsible for neurodegeneration via affecting insulin dysregulation, aggregation of amyloids, neuroinflammation, mitochondrial dysfunction and altered synaptic plasticity. In light of these potential shared disease mechanisms, clinical trials are now investigating the use of established diabetes drugs targeting insulin resistance in the management of PD. This review will discuss the epidemiological links between T2DM and PD, the potential shared cellular mechanisms, and assess the relevant treatment options for disease modification of PD.

16 Article Ethnic Variation in the Manifestation of Parkinson's Disease: A Narrative Review. 2020

Ben-Joseph, Aaron / Marshall, Charles R / Lees, Andrew J / Noyce, Alastair J. ·Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK. · Reta Lila Weston Institute of Neurological Studies and Department of Clinical and Movement Neurosciences, University College London, London, UK. ·J Parkinsons Dis · Pubmed #31868680.

ABSTRACT: The global prevalence of Parkinson's disease is increasing, yet the characteristics, risk factors and genetics of PD in Black, Asian and Hispanic populations is little understood. In this paper we review the published literature on clinical variation in the symptoms and signs of Parkinson's disease in different ethnic groups and responses to treatment. We included any study that sampled patients with Parkinson's disease from distinct ethnic backgrounds. We conclude that whilst there is little published evidence for ethnic variation in the clinical features of Parkinson's disease, there are substantial limitations and gaps in the current literature, which mean that the evidence does necessarily not fit with clinical observation. Possible explanations for expected differences in manifestation include genetic determinants, the co-existence of cerebrovascular disease and/or Alzheimer's disease pathology, healthcare inequalities and socio-cultural factors.

17 Article Genetic modifiers of risk and age at onset in GBA associated Parkinson's disease and Lewy body dementia. 2020

Blauwendraat, Cornelis / Reed, Xylena / Krohn, Lynne / Heilbron, Karl / Bandres-Ciga, Sara / Tan, Manuela / Gibbs, J Raphael / Hernandez, Dena G / Kumaran, Ravindran / Langston, Rebekah / Bonet-Ponce, Luis / Alcalay, Roy N / Hassin-Baer, Sharon / Greenbaum, Lior / Iwaki, Hirotaka / Leonard, Hampton L / Grenn, Francis P / Ruskey, Jennifer A / Sabir, Marya / Ahmed, Sarah / Makarious, Mary B / Pihlstrøm, Lasse / Toft, Mathias / van Hilten, Jacobus J / Marinus, Johan / Schulte, Claudia / Brockmann, Kathrin / Sharma, Manu / Siitonen, Ari / Majamaa, Kari / Eerola-Rautio, Johanna / Tienari, Pentti J / Anonymous2491178 / Pantelyat, Alexander / Hillis, Argye E / Dawson, Ted M / Rosenthal, Liana S / Albert, Marilyn S / Resnick, Susan M / Ferrucci, Luigi / Morris, Christopher M / Pletnikova, Olga / Troncoso, Juan / Grosset, Donald / Lesage, Suzanne / Corvol, Jean-Christophe / Brice, Alexis / Noyce, Alastair J / Masliah, Eliezer / Wood, Nick / Hardy, John / Shulman, Lisa M / Jankovic, Joseph / Shulman, Joshua M / Heutink, Peter / Gasser, Thomas / Cannon, Paul / Scholz, Sonja W / Morris, Huw / Cookson, Mark R / Nalls, Mike A / Gan-Or, Ziv / Singleton, Andrew B. ·Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA. · Department of Human Genetics, McGill University, Montreal, Quebec, Canada. · Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada. · 23andMe, Inc., Mountain View, CA, USA. · Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK. · Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA. · Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA. · Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel. · Department of Neurology, Sheba Medical Center, Tel Hashomer, Israel. · Movement Disorders Institute, Sheba Medical Center, Tel Hashomer, Israel. · The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel. · The Danek Gertner Institute of Human Genetics, Sheba Medical Center, Tel Hashomer, Israel. · Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA. · Department of Neurology, Oslo University Hospital, Oslo, Norway. · Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands. · Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany. · German Center for Neurodegenerative Diseases (DZNE), Tuebingen, Germany. · Centre for Genetic Epidemiology, Institute for Clinical Epidemiology and Applied Biometry, University of Tubingen, Germany. · Institute of Clinical Medicine, Department of Neurology, University of Oulu, Oulu, Finland. · Department of Neurology and Medical Research Center, Oulu University Hospital, Oulu, Finland. · Department of Neurology, Helsinki University Hospital, and Molecular Neurology, Research Programs Unit, Biomedicum, University of Helsinki, Helsinki, Finland. · Neuroregeneration and Stem Cell Program, Institute for Cell Engineering, Johns Hopkins University Medical Center, Baltimore, MD, USA. · Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA. · Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA. · Longitudinal Studies Section, National Institute on Aging, Baltimore, MD, USA. · Newcastle Brain Tissue Resource, Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK. · Department of Pathology (Neuropathology, Johns Hopkins University Medical Center, Baltimore, MD, USA. · Department of Neurology, Institute of Neurological Sciences, Queen Elizabeth University Hospital, Glasgow, UK. · Inserm U1127, Sorbonne Universités, UPMC Univ Paris 06 UMR S1127, Institut du Cerveau et de la Moelle épinière, ICM, Paris, France. · Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK. · Department of Neurodegenerative Diseases, UCL Queen Square Institute of Neurology, London, UK. · Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA. · Department of Neurology, Baylor College of Medicine, Houston, USA. · Departments of Molecular and Human Genetics and Neuroscience, Baylor College of Medicine, Houston, USA. · Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, USA. · Data Tecnica International, Glen Echo, MD, USA. · Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada. ·Brain · Pubmed #31755958.

ABSTRACT: Parkinson's disease is a genetically complex disorder. Multiple genes have been shown to contribute to the risk of Parkinson's disease, and currently 90 independent risk variants have been identified by genome-wide association studies. Thus far, a number of genes (including SNCA, LRRK2, and GBA) have been shown to contain variability across a spectrum of frequency and effect, from rare, highly penetrant variants to common risk alleles with small effect sizes. Variants in GBA, encoding the enzyme glucocerebrosidase, are associated with Lewy body diseases such as Parkinson's disease and Lewy body dementia. These variants, which reduce or abolish enzymatic activity, confer a spectrum of disease risk, from 1.4- to >10-fold. An outstanding question in the field is what other genetic factors that influence GBA-associated risk for disease, and whether these overlap with known Parkinson's disease risk variants. Using multiple, large case-control datasets, totalling 217 165 individuals (22 757 Parkinson's disease cases, 13 431 Parkinson's disease proxy cases, 622 Lewy body dementia cases and 180 355 controls), we identified 1691 Parkinson's disease cases, 81 Lewy body dementia cases, 711 proxy cases and 7624 controls with a GBA variant (p.E326K, p.T369M or p.N370S). We performed a genome-wide association study and analysed the most recent Parkinson's disease-associated genetic risk score to detect genetic influences on GBA risk and age at onset. We attempted to replicate our findings in two independent datasets, including the personal genetics company 23andMe, Inc. and whole-genome sequencing data. Our analysis showed that the overall Parkinson's disease genetic risk score modifies risk for disease and decreases age at onset in carriers of GBA variants. Notably, this effect was consistent across all tested GBA risk variants. Dissecting this signal demonstrated that variants in close proximity to SNCA and CTSB (encoding cathepsin B) are the most significant contributors. Risk variants in the CTSB locus were identified to decrease mRNA expression of CTSB. Additional analyses suggest a possible genetic interaction between GBA and CTSB and GBA p.N370S induced pluripotent cell-derived neurons were shown to have decreased cathepsin B expression compared to controls. These data provide a genetic basis for modification of GBA-associated Parkinson's disease risk and age at onset, although the total contribution of common genetics variants is not large. We further demonstrate that common variability at genes implicated in lysosomal function exerts the largest effect on GBA associated risk for disease. Further, these results have implications for selection of GBA carriers for therapeutic interventions.

18 Article The Parkinson's Disease Mendelian Randomization Research Portal. 2019

Noyce, Alastair J / Bandres-Ciga, Sara / Kim, Jonggeol / Heilbron, Karl / Kia, Demis / Hemani, Gibran / Xue, Angli / Lawlor, Debbie A / Smith, George Davey / Duran, Raquel / Gan-Or, Ziv / Blauwendraat, Cornelis / Gibbs, J Raphael / Anonymous7311119 / Hinds, David A / Yang, Jian / Visscher, Peter / Cuzick, Jack / Morris, Huw / Hardy, John / Wood, Nicholas W / Nalls, Mike A / Singleton, Andrew B. ·Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom. · Department of Clinical and Movement Neurosciences, University College London, Institute of Neurology, London, United Kingdom. · Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA. · Instituto de Investigación Biosanitaria de Granada (ibs.GRANADA), Granada, Spain. · 23andMe, Inc., Mountain View, California, USA. · MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom. · Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia. · Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia. · Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom. · Centro de Investigacion Biomedica and Departamento de Fisiologia, Facultad de Medicina, Universidad de Granada, Granada, Spain. · Department of Neurology & Neurosurgery, McGill University, Montreal, Quebec, Canada. · Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada. · Department of Human Genetics, McGill University, Montreal, Quebec, Canada. · Institute for Advanced Research, Wenzhou Medical University, Wenzhou, Zhejiang, China. · Data Tecnica International, Glen Echo, Maryland, USA. ·Mov Disord · Pubmed #31659794.

ABSTRACT: BACKGROUND: Mendelian randomization is a method for exploring observational associations to find evidence of causality. OBJECTIVE: To apply Mendelian randomization between risk factors/phenotypic traits (exposures) and PD in a large, unbiased manner, and to create a public resource for research. METHODS: We used two-sample Mendelian randomization in which the summary statistics relating to single-nucleotide polymorphisms from 5,839 genome-wide association studies of exposures were used to assess causal relationships with PD. We selected the highest-quality exposure genome-wide association studies for this report (n = 401). For the disease outcome, summary statistics from the largest published PD genome-wide association studies were used. For each exposure, the causal effect on PD was assessed using the inverse variance weighted method, followed by a range of sensitivity analyses. We used a false discovery rate of 5% from the inverse variance weighted analysis to prioritize exposures of interest. RESULTS: We observed evidence for causal associations between 12 exposures and risk of PD. Of these, nine were effects related to increasing adiposity and decreasing risk of PD. The remaining top three exposures that affected PD risk were tea drinking, time spent watching television, and forced vital capacity, but these may have been biased and were less convincing. Other exposures at nominal statistical significance included inverse effects of smoking and alcohol. CONCLUSIONS: We present a new platform which offers Mendelian randomization analyses for a total of 5,839 genome-wide association studies versus the largest PD genome-wide association studies available (https://pdgenetics.shinyapps.io/MRportal/). Alongside, we report further evidence to support a causal role for adiposity on lowering the risk of PD. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

19 Article Genomewide association study of Parkinson's disease clinical biomarkers in 12 longitudinal patients' cohorts. 2019

Iwaki, Hirotaka / Blauwendraat, Cornelis / Leonard, Hampton L / Kim, Jonggeol J / Liu, Ganqiang / Maple-Grødem, Jodi / Corvol, Jean-Christophe / Pihlstrøm, Lasse / van Nimwegen, Marlies / Hutten, Samantha J / Nguyen, Khanh-Dung H / Rick, Jacqueline / Eberly, Shirley / Faghri, Faraz / Auinger, Peggy / Scott, Kirsten M / Wijeyekoon, Ruwani / Van Deerlin, Vivianna M / Hernandez, Dena G / Gibbs, J Raphael / Anonymous20211124 / Chitrala, Kumaraswamy Naidu / Day-Williams, Aaron G / Brice, Alexis / Alves, Guido / Noyce, Alastair J / Tysnes, Ole-Bjørn / Evans, Jonathan R / Breen, David P / Estrada, Karol / Wegel, Claire E / Danjou, Fabrice / Simon, David K / Andreassen, Ole / Ravina, Bernard / Toft, Mathias / Heutink, Peter / Bloem, Bastiaan R / Weintraub, Daniel / Barker, Roger A / Williams-Gray, Caroline H / van de Warrenburg, Bart P / Van Hilten, Jacobus J / Scherzer, Clemens R / Singleton, Andrew B / Nalls, Mike A. ·Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA. · Data Tecnica International, Glen Echo, Maryland, USA. · School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China. · Advanced Center for Parkinson's Disease Research, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA. · Precision Neurology Program, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts, USA. · The Norwegian Centre for Movement Disorders, Stavanger University Hospital, Stavanger, Norway. · Department of Chemistry, Bioscience and Environmental Engineering, University in Stavanger, Stavanger, Norway. · Assistance-Publique Hôpitaux de Paris, ICM, INSERM UMRS 1127, CNRS 7225, ICM, Department of Neurology and CIC Neurosciences, Pitié-Salpêtrière Hospital, Paris, France. · Department of Neurology, Oslo University Hospital, Oslo, Norway. · Radboud University Medical Centre, Donders Institute for Brain, Cognition, and Behaviour; Department of Neurology, Nijmegen, The Netherlands. · The Michael J. Fox Foundation for Parkinson's Research, New York, New York, USA. · Translational Genome Sciences, Biogen, Cambridge, Massachusetts, USA. · Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA. · Department of Biostatistics and Computational Biology, University of Rochester, Rochester, New York, USA. · Department of Computer Science, University of Illinois Urbana-Champaign, Champaign, Illinois, USA. · Department of Neurology, Center for Health + Technology, University of Rochester, Rochester, New York, USA. · Department of Clinical Neurosciences, University of Cambridge, John van Geest Centre for Brain Repair, Cambridge, United Kingdom. · Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Parelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA. · Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA. · Flagship Labs 60 Inc, Cambridge, Massachusetts, USA. · Statistical Genetics, Biogen, Cambridge, Massachusetts, USA. · Institut du cerveau et de la moelle épinière ICM, Paris, France. · Sorbonne Université SU, Paris, France. · INSERM UMR1127, Paris, France. · Department of Neurology, Stavanger University Hospital, Stavanger, Norway. · Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom. · Department of Clinical and Movement Neurosciences, UCL Institute of Neurology, London, United Kingdom. · Department of Neurology, Haukeland University Hospital, Bergen, Norway. · University of Bergen, Bergen, Norway. · Department of Neurology, Nottingham University NHS Trust, Nottingham, United Kingdom. · Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland. · Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, Scotland. · Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland. · Department of Medical and Molecular Genetics, Indiana University, Indianapolis, Indiana, USA. · Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA. · Harvard Medical School, Boston, Massachusetts, USA. · NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway, Norway. · Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway, Norway. · Voyager Therapeutics, Cambridge, Massachusetts, USA. · Department of Neurology, University of Rochester School of Medicine, Rochester, New York, USA. · Institute of Clinical Medicine, University of Oslo, Oslo, Norway. · German Center for Neurodegenerative Diseases-Tubingen, Tuebingen, Germany. · HIH Tuebingen, Tubingen, Tuebingen, Germany. · Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA. · Department of Veterans Affairs, Philadelphia, Pennsylvania, USA. · Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom. · Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands. ·Mov Disord · Pubmed #31505070.

ABSTRACT: BACKGROUND: Several reports have identified different patterns of Parkinson's disease progression in individuals carrying missense variants in GBA or LRRK2 genes. The overall contribution of genetic factors to the severity and progression of Parkinson's disease, however, has not been well studied. OBJECTIVES: To test the association between genetic variants and the clinical features of Parkinson's disease on a genomewide scale. METHODS: We accumulated individual data from 12 longitudinal cohorts in a total of 4093 patients with 22,307 observations for a median of 3.81 years. Genomewide associations were evaluated for 25 cross-sectional and longitudinal phenotypes. Specific variants of interest, including 90 recently identified disease-risk variants, were also investigated post hoc for candidate associations with these phenotypes. RESULTS: Two variants were genomewide significant. Rs382940(T>A), within the intron of SLC44A1, was associated with reaching Hoehn and Yahr stage 3 or higher faster (hazard ratio 2.04 [1.58-2.62]; P value = 3.46E-8). Rs61863020(G>A), an intergenic variant and expression quantitative trait loci for α-2A adrenergic receptor, was associated with a lower prevalence of insomnia at baseline (odds ratio 0.63 [0.52-0.75]; P value = 4.74E-8). In the targeted analysis, we found 9 associations between known Parkinson's risk variants and more severe motor/cognitive symptoms. Also, we replicated previous reports of GBA coding variants (rs2230288: p.E365K; rs75548401: p.T408M) being associated with greater motor and cognitive decline over time, and an APOE E4 tagging variant (rs429358) being associated with greater cognitive deficits in patients. CONCLUSIONS: We identified novel genetic factors associated with heterogeneity of Parkinson's disease. The results can be used for validation or hypothesis tests regarding Parkinson's disease. © 2019 International Parkinson and Movement Disorder Society.

20 Article The BRadykinesia Akinesia INcoordination (BRAIN) Tap Test: Capturing the Sequence Effect. 2019

Hasan, Hasan / Burrows, Maggie / Athauda, Dilan S / Hellman, Bruce / James, Ben / Warner, Thomas / Foltynie, Thomas / Giovannoni, Gavin / Lees, Andrew J / Noyce, Alastair J. ·Institute of Neurology Queen Square University College London, London UK. · Department of Clinical and Movement Neurosciences Institute of Neurology Queen Square, University College London, London UK. · Reta Lila Weston Institute of Neurological Studies Institute of Neurology, University College London London UK. · National Hospital for Neurology and Neurosurgery London UK. · uMotif Ltd London UK. · Blizard Institute Queen Mary University London, Barts and the London School of Medicine and Dentistry London UK. · Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. ·Mov Disord Clin Pract · Pubmed #31392247.

ABSTRACT: Background: The BRadykinesia Akinesia INcoordination (BRAIN) tap test is an online keyboard tapping task that has been previously validated to assess upper limb motor function in Parkinson's disease (PD). Objectives: To develop a new parameter that detects a sequence effect and to reliably distinguish between PD patients Methods: The BRAIN test scores in 61 patients with PD and 93 healthy controls were compared. A range of established parameters captured number and accuracy of alternate taps. The new velocity score recorded the intertap speed. Decrement in the velocity score was used as a marker for the sequence effect. In the validation phase, 19 PD patients and 19 controls were tested using different hardware including mobile devices. Results: Quantified slopes from the velocity score demonstrated bradykinesia (sequence effect) in PD patients (slope cut-off -0.002) with 58% sensitivity and 81% specificity (discovery phase of the study) and 65% sensitivity and 88% specificity (validation phase). All BRAIN test parameters differentiated between Conclusion: The BRAIN tap test is a simple, user-friendly, and free-to-use tool for the assessment of upper limb motor dysfunction in PD, which now includes a measure of bradykinesia.

21 Article Screening performance of abbreviated versions of the UPSIT smell test. 2019

Joseph, Theresita / Auger, Stephen D / Peress, Luisa / Rack, Daniel / Cuzick, Jack / Giovannoni, Gavin / Lees, Andrew / Schrag, Anette E / Noyce, Alastair J. ·University College London Medical School, London, UK. · Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK. · Barts and The London School of Medicine and Dentistry, London, UK. · Blizard Institute, Barts and the London Queen Mary University of London, London, UK. · Reta Lila Weston Institute, Department of Clinical and Movement Neurosciences, UCL Institute of Neurology, London, UK. · Department of Clinical and Movement Neurosciences, UCL Institute of Neurology, London, UK. · Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK. a.noyce@qmul.ac.uk. · Reta Lila Weston Institute, Department of Clinical and Movement Neurosciences, UCL Institute of Neurology, London, UK. a.noyce@qmul.ac.uk. ·J Neurol · Pubmed #31053960.

ABSTRACT: BACKGROUND: Hyposmia can develop with age and in neurodegenerative conditions, including Parkinson's disease (PD). The University of Pennsylvania Smell Identification Test (UPSIT) is a 40-item smell test widely used for assessing hyposmia. However, in a number of situations, such as identifying hyposmic individuals in large populations, shorter tests are preferable. METHODS: We assessed the ability of shorter UPSIT subsets to detect hyposmia in 891 healthy participants from the PREDICT-PD study. Shorter subsets included Versions A and B of the 4-item Pocket Smell Test (PST) and 12-item Brief Smell Identification Test (BSIT). Using a data-driven approach, we evaluated screening performances of 23,231,378 combinations of 1-7 smell items from the full UPSIT to derive "winning" subsets, and validated findings separately in another 191 healthy individuals. We then compared discriminatory UPSIT smells between PREDICT-PD participants and 40 PD patients, and assessed the performance of "winning" subsets containing discriminatory smells in PD patients. RESULTS: PST Versions A and B achieved sensitivity/specificity of 76.8%/64.9% and 86.6%/45.9%, respectively, while BSIT Versions A and B achieved 83.1%/79.5% and 96.5%/51.8%. From the data-driven analysis, 2 "winning" 7-item subsets surpassed the screening performance of 12-item BSITs (validation sensitivity/specificity of 88.2%/85.4% and 100%/53.5%), while a "winning" 4-item subset had higher sensitivity than PST-A, -B, and even BSIT-A (validation sensitivity 91.2%). Interestingly, several discriminatory smells featured within "winning" subsets, and demonstrated high-screening performances for identifying hyposmic PD patients. CONCLUSION: Using abbreviated smell tests could provide a cost-effective means of large-scale hyposmia screening, allowing more targeted UPSIT administration in general and PD-related settings.

22 Article Parkinson's disease age at onset genome-wide association study: Defining heritability, genetic loci, and α-synuclein mechanisms. 2019

Blauwendraat, Cornelis / Heilbron, Karl / Vallerga, Costanza L / Bandres-Ciga, Sara / von Coelln, Rainer / Pihlstrøm, Lasse / Simón-Sánchez, Javier / Schulte, Claudia / Sharma, Manu / Krohn, Lynne / Siitonen, Ari / Iwaki, Hirotaka / Leonard, Hampton / Noyce, Alastair J / Tan, Manuela / Gibbs, J Raphael / Hernandez, Dena G / Scholz, Sonja W / Jankovic, Joseph / Shulman, Lisa M / Lesage, Suzanne / Corvol, Jean-Christophe / Brice, Alexis / van Hilten, Jacobus J / Marinus, Johan / Anonymous861129 / Eerola-Rautio, Johanna / Tienari, Pentti / Majamaa, Kari / Toft, Mathias / Grosset, Donald G / Gasser, Thomas / Heutink, Peter / Shulman, Joshua M / Wood, Nicolas / Hardy, John / Morris, Huw R / Hinds, David A / Gratten, Jacob / Visscher, Peter M / Gan-Or, Ziv / Nalls, Mike A / Singleton, Andrew B / Anonymous871129. ·Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA. · Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA. · 23andMe, Inc., Mountain View, California, USA. · Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia. · Department of Neurology, University of Maryland School of Medicine, Baltimore, Maryland, USA. · Department of Neurology, Oslo University Hospital, Oslo, Norway. · Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany. · German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany. · Centre for Genetic Epidemiology, Institute for Clinical Epidemiology and Applied Biometry, University of Tubingen, Germany. · Department of Human Genetics, McGill University, Montreal, Quebec, Canada. · Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada. · Institute of Clinical Medicine, Department of Neurology, University of Oulu, Oulu, Finland. · Department of Neurology and Medical Research Center, Oulu University Hospital, Oulu, Finland. · The Michael J Fox Foundation for Parkinson's Research, New York, New York, USA. · Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom. · Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom. · Parkinson's Disease Center and Movement Disorders Clinic, Department of Neurology, Baylor College of Medicine, Houston, Texas, USA. · Inserm U1127, Sorbonne Universités, UPMC Univ Paris 06 UMR S1127, Institut du Cerveau et de la Moelle épinière, ICM, Paris, France. · Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands. · Department of Neurology, Helsinki University Hospital, and Molecular Neurology, Research Programs Unit, Biomedicum, University of Helsinki, Helsinki, Finland. · Institute of Clinical Medicine, University of Oslo, Oslo, Norway. · Department of Neurology, Institute of Neurological Sciences, Queen Elizabeth University Hospital, Glasgow, United Kingdom. · Institute of Neuroscience & Psychology, University of Glasgow, Glasgow, United Kingdom. · Departments of Molecular & Human Genetics and Neuroscience, Baylor College of Medicine, Houston, Texas, USA. · Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, Texas, USA. · Department of Neurodegenerative Diseases, UCL Queen Square Institute of Neurology, London, United Kingdom. · Mater Research, Translational Research Institute, Brisbane, Queensland, Australia. · Queensland Brain Institute, The University of Queensland, Brisbane, Australia. · Department of Neurology & Neurosurgery, McGill University, Montreal, Quebec, Canada. · Data Tecnica International, Glen Echo, Maryland, USA. ·Mov Disord · Pubmed #30957308.

ABSTRACT: BACKGROUND: Increasing evidence supports an extensive and complex genetic contribution to PD. Previous genome-wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age at onset are largely unknown. OBJECTIVES: To identify the genetic determinants of PD age at onset. METHODS: Using genetic data of 28,568 PD cases, we performed a genome-wide association study based on PD age at onset. RESULTS: We estimated that the heritability of PD age at onset attributed to common genetic variation was ∼0.11, lower than the overall heritability of risk for PD (∼0.27), likely, in part, because of the subjective nature of this measure. We found two genome-wide significant association signals, one at SNCA and the other a protein-coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni-corrected significant effect at other known PD risk loci, GBA, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. Notably, SNCA, TMEM175, SCARB2, BAG3, and GBA have all been shown to be implicated in α-synuclein aggregation pathways. Remarkably, other well-established PD risk loci, such as GCH1 and MAPT, did not show a significant effect on age at onset of PD. CONCLUSIONS: Overall, we have performed the largest age at onset of PD genome-wide association studies to date, and our results show that not all PD risk loci influence age at onset with significant differences between risk alleles for age at onset. This provides a compelling picture, both within the context of functional characterization of disease-linked genetic variability and in defining differences between risk alleles for age at onset, or frank risk for disease. © 2019 International Parkinson and Movement Disorder Society.

23 Article Predicting diagnosis of Parkinson's disease: A risk algorithm based on primary care presentations. 2019

Schrag, Anette / Anastasiou, Zacharias / Ambler, Gareth / Noyce, Alastair / Walters, Kate. ·University College London Institute of Neurology, University College London, London, UK. · University College London Department of Statistical Science, University College London, London, UK. · University College London Department of Primary Care & Population Health, University College London, London, UK. ·Mov Disord · Pubmed #30735573.

ABSTRACT: BACKGROUND: Diagnosis of Parkinson's disease (PD) is typically preceded by nonspecific presentations in primary care. OBJECTIVES: The objective of this study was to develop and validate a prediction model for diagnosis of PD based on presentations in primary care. SETTING: The settings were general practices providing data for The Health Improvement Network UK primary care database. METHODS: Data from 8,166 patients aged older than age 50 years with incident diagnosis of PD and 46,755 controls were analyzed. Likelihood ratios, sensitivity, specificity, and positive and negative predictive values for individual symptoms and combinations of presentations were calculated. An algorithm for risk of diagnosis of PD within 5 years was calculated using multivariate logistic regression analysis. Split sample analysis was used for model validation with a 70% development sample and a 30% validation sample. RESULTS: Presentations independently and significantly associated with later diagnosis of PD in multivariate analysis were tremor, constipation, depression or anxiety, fatigue, dizziness, urinary dysfunction, balance problems, memory problems and cognitive decline, hypotension, rigidity, and hypersalivation. The discrimination and calibration of the risk algorithm were good with an area under the curve of 0.80 (95% confidence interval 0.78-0.81). At a threshold of 5%, 37% of those classified as high risk would be diagnosed with PD within 5 years and 99% of those who were not classified as high risk would not be diagnosed with PD. CONCLUSION: This risk algorithm applied to routine primary care presentations can identify individuals at increased risk of diagnosis of PD within 5 years to allow for monitoring and earlier diagnosis of PD. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

24 Article Mendelian randomization study shows no causal relationship between circulating urate levels and Parkinson's disease. 2018

Kia, Demis A / Noyce, Alastair J / White, Jon / Speed, Doug / Nicolas, Aude / Anonymous7591112 / Burgess, Stephen / Lawlor, Debbie A / Davey Smith, George / Singleton, Andrew / Nalls, Mike A / Sofat, Reecha / Wood, Nicholas W. ·Department of Molecular Neuroscience, UCL Institute of Neurology, London, United Kingdom. · Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom. · UCL Genetics Institute, University College, London, United Kingdom. · Laboratory for Neurogenetics, National Institutes for Health, Bethesda, MD. · Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. · MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom. · Population Health Science, Bristol Medical School of Bristol, Bristol, United Kingdom. · Data Tecnica International, Glen Echo, MD. · Institute of Health Informatics, University College London, London, United Kingdom. ·Ann Neurol · Pubmed #30014513.

ABSTRACT: OBJECTIVE: Observational studies have shown that increased plasma urate is associated with lower risk of Parkinson's disease (PD), but these studies were not designed to test causality. If a causal relationship exists, then modulating plasma urate levels could be a potential preventive avenue for PD. We used a large two-sample Mendelian randomization (MR) design to assess for a causal relationship between plasma urate and PD risk. METHODS: We used a genetic instrument consisting of 31 independent loci for plasma urate on a case-control genome-wide association study data set, which included 13,708 PD cases and 95,282 controls. Individual effect estimates for each SNP were combined using the inverse-variance weighted (IVW) method. Two additional methods, MR-Egger and a penalized weighted median (PWM)-based approach, were used to assess potential bias attributed to pleiotropy or invalid instruments. RESULTS: We found no evidence for a causal relationship between urate and PD, with an effect estimate from the IVW method of odds ratio (OR) 1.03 (95% confidence interval [CI], 0.88-1.20) per 1-standard-deviation increase in plasma urate levels. MR Egger and PWM analyses yielded similar estimates (OR, 0.99 [95% CI, 0.83-1.17] and 0.99 [95% CI, 0.86-1.14], respectively). INTERPRETATION: We did not find evidence for a linear causal protective effect by urate on PD risk. The associations observed in previous observational studies may be, in part, attributed to confounding or reverse causality. In the context of the present findings, strategies to elevate circulating urate levels may not reduce overall PD risk. Ann Neurol 2018;84:191-199.

25 Article Association between diabetes and subsequent Parkinson disease: A record-linkage cohort study. 2018

De Pablo-Fernandez, Eduardo / Goldacre, Raph / Pakpoor, Julia / Noyce, Alastair J / Warner, Thomas T. ·From the Reta Lila Weston Institute of Neurological Studies, Department of Molecular Neurosciences (E.D.P.-F., A.J.N., T.T.W.), and Queen Square Brain Bank for Neurological Disorders (E.D.P.-F., T.T.W.), UCL Institute of Neurology, London · Unit of Health-Care Epidemiology (R.G., J.P.), Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford · and Preventive Neurology Unit (A.J.N.), Wolfson Institute of Preventive Medicine, Queen Mary University of London, UK. ·Neurology · Pubmed #29898968.

ABSTRACT: OBJECTIVE: To investigate the association between type 2 diabetes mellitus (T2DM) and subsequent Parkinson disease (PD). METHODS: Linked English national Hospital Episode Statistics and mortality data (1999-2011) were used to conduct a retrospective cohort study. A cohort of individuals admitted for hospital care with a coded diagnosis of T2DM was constructed, and compared to a reference cohort. Subsequent PD risk was estimated using Cox regression models. Individuals with a coded diagnosis of cerebrovascular disease, vascular parkinsonism, drug-induced parkinsonism, and normal pressure hydrocephalus were excluded from the analysis. RESULTS: A total of 2,017,115 individuals entered the T2DM cohort and 6,173,208 entered the reference cohort. There were significantly elevated rates of PD following T2DM (hazard ratio [HR] 1.32, 95% confidence interval [CI] 1.29-1.35; CONCLUSIONS: We report an increased rate of subsequent PD following T2DM in this large cohort study. These findings may reflect shared genetic predisposition and/or disrupted shared pathogenic pathways with potential clinical and therapeutic implications.

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