Bloem, Bastiaan R.

Levodopa is the most widely used medication for the symptomatic treatment of Parkinson’s disease and, despite being an “old” drug, is still considered the gold standard for offering symptomatic relief. The pharmacokinetic and pharmacodynamics of levodopa have been studied extensively. Our review explores the molecular mechanisms that affect the absorption of this drug, focusing on the large intra- and interindividual variability of absorption that is commonly encountered in daily clinical practice, and on the interaction with other medications. In addition, we will explore the clinical implications of levodopa absorption variability and address current and future strategies for researchers and clinicians.

Abstract Background Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. Objective We used results from genome‐wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. Methods We used individual data for participants of European ancestry from the Courage‐PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta‐Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross‐phenotypes polygenic risk score (PRS) analyses. Results We confirmed a previously reported positive genetic correlation of PD with melanoma (G corr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (G corr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31). Conclusions We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

AbstractBackgroundTwo studies that examined the interaction between HLA‐DRB1 and smoking in Parkinson's disease (PD) yielded findings in opposite directions.ObjectiveTo perform a large‐scale independent replication of the HLA‐DRB1 × smoking interaction.MethodsWe genotyped 182 single nucleotide polymorphism (SNPs) associated with smoking initiation in 12 424 cases and 9480 controls to perform a Mendelian randomization (MR) analysis in strata defined by HLA‐DRB1.ResultsAt the amino acid level, a valine at position 11 (V11) in HLA‐DRB1 displayed the strongest association with PD. MR showed an inverse association between genetically predicted smoking initiation and PD only in absence of V11 (odds ratio, 0.74, 95% confidence interval, 0.59–0.93, PInteraction = 0.028). In silico predictions of the influence of V11 and smoking‐induced modifications of α‐synuclein on binding affinity showed findings consistent with this interaction pattern.ConclusionsDespite being one of the most robust findings in PD research, the mechanisms underlying the inverse association between smoking and PD remain unknown. Our findings may help better understand this association. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Background: Previous studies showed that lifestyle behaviors (cigarette smoking, alcohol, coffee) are inversely associated with Parkinson’s disease (PD). The prodromal phase of PD raises the possibility that these associations may be explained by reverse causation. Objective: To examine associations of lifestyle behaviors with PD using two-sample Mendelian randomisation (MR) and the potential for survival and incidence-prevalence biases. Methods: We used summary statistics from publicly available studies to estimate the association of genetic polymorphisms with lifestyle behaviors, and from Courage-PD (7,369 cases, 7,018 controls; European ancestry) to estimate the association of these variants with PD. We used the inverse-variance weighted method to compute odds ratios (ORIVW) of PD and 95%confidence intervals (CI). Significance was determined using a Bonferroni-corrected significance threshold (p = 0.017). Results: We found a significant inverse association between smoking initiation and PD (ORIVW per 1-SD increase in the prevalence of ever smoking = 0.74, 95%CI = 0.60–0.93, p = 0.009) without significant directional pleiotropy. Associations in participants ≤67 years old and cases with disease duration ≤7 years were of a similar size. No significant associations were observed for alcohol and coffee drinking. In reverse MR, genetic liability toward PD was not associated with smoking or coffee drinking but was positively associated with alcohol drinking. Conclusion: Our findings are in favor of an inverse association between smoking and PD that is not explained by reverse causation, confounding, and survival or incidence-prevalence biases. Genetic liability toward PD was positively associated with alcohol drinking. Conclusions on the association of alcohol and coffee drinking with PD are hampered by insufficient statistical power.

ABSTRACTBackground: In 2015, the International Parkinson and Movement Disorder Society published clinical diagnostic criteria for Parkinson's disease (PD). Although recent validation studies suggest high accuracy, one unmet need is for highly specific criteria for clinical trials in early/de novo PD.Objectives: The objective of this study was to generate and test a PD diagnostic criteria termed “clinically established early PD.”Methods: We modified the Movement Disorder Society criteria to increase specificity for early PD by removing all disease duration components and changing red flags to absolute exclusions. We then estimated the sensitivity/specificity of clinically established early PD criteria in patients with disease duration <5 years, selected from a 626‐patient validation study.Results: After documentation of parkinsonism, 18 individual exclusion criteria are assessed that preclude the diagnosis of “clinically established early PD.” Among 212 PD and 152 non‐PD patients, the estimated specificity was 95.4%, with 69.8% sensitivity.Conclusions: We describe high‐specificity criteria for de novo PD, which are freely available for use in clinical trials. © 2018 International Parkinson and Movement Disorder Society

Background: Telemedicine is increasingly used to care for patients with movement disorders, but data regarding its global use are limited. Introduction: To obtain baseline international data about telemedicine use among movement disorder clinicians. Methods: An online survey was sent to all 6,056 Movement Disorder Society members in 2015. Scope, reimbursement, and perceived quality of telemedicine were assessed. Results: There were 549 respondents (9.1% overall response rate) from 83 countries. Most (85.8%) were physicians, and most (70.9%) worked in an academic or university practice. Half of respondents ( n = 287, from 57 countries) used telemedicine for clinical care; activities included e-mail (63.2%), video visits (follow-up [39.7%] and new [35.2%]), and video-based education (35.2%). One hundred five respondents personally conducted video visits, most frequently to outpatient clinics (53.5%), patient homes (30.8%), and hospital inpatients (30.3%). The most common challenges were a limited neurological examination (58.9%) and technological difficulties (53.3%), and the most common benefits were reduced travel time (92.9%) and patient costs (60.1%). The most frequent reimbursements were none (39.0%), public insurance (24.5%), and patient payment (9.3%). Half of respondents planned to use telemedicine in the future, and three-quarters were interested in telemedicine education. Conclusions: More than 250 respondents around the world engage in telemedicine for movement disorders; most perceived benefit for patients, despite challenges and reimbursement for clinicians. Formal instruction on telemedicine is highly desired. Although the survey response was low and possibly biased to over represent those with telemedicine experience, the study provides baseline data for future comparison and to improve telemedicine delivery.

ABSTRACT This article describes research criteria and probability methodology for the diagnosis of prodromal PD. Prodromal disease refers to the stage wherein early symptoms or signs of PD neurodegeneration are present, but classic clinical diagnosis based on fully evolved motor parkinsonism is not yet possible. Given the lack of clear neuroprotective/disease‐modifying therapy for prodromal PD, these criteria were developed for research purposes only. The criteria are based upon the likelihood of prodromal disease being present with probable prodromal PD defined as ≥80% certainty. Certainty estimates rely upon calculation of an individual's risk of having prodromal PD, using a Bayesian naïve classifier. In this methodology, a previous probability of prodromal disease is delineated based upon age. Then, the probability of prodromal PD is calculated by adding diagnostic information, expressed as likelihood ratios. This diagnostic information combines estimates of background risk (from environmental risk factors and genetic findings) and results of diagnostic marker testing. In order to be included, diagnostic markers had to have prospective evidence documenting ability to predict clinical PD. They include motor and nonmotor clinical symptoms, clinical signs, and ancillary diagnostic tests. These criteria represent a first step in the formal delineation of early stages of PD and will require constant updating as more information becomes available. © 2015 International Parkinson and Movement Disorder Society