Search

BackgroundThe penetrance of common genetic risk variants for Parkinson's disease (PD) is low. Pesticide exposure increases PD risk, but how exposure affects penetrance is not well understood.ObjectiveTo determine the relationship between occupational pesticide exposure and PD in people with LRRK2 and GBA risk variants.MethodsParticipants of the Parkinson's Progression Markers Initiative (PPMI) with a LRRK2-G2019 S or GBA risk variant provided information about occupational pesticide exposure. We compared exposure in carriers with and without PD. Among carriers with PD, we used Cox proportional hazard models to compare time-to impairment in balance, cognition, and activities of daily living (ADLs) between participants with and without prior occupational pesticide exposure.Results378 participants with a risk variant provided exposure information; 176 with LRRK2-G2019 S (54 with and 122 without PD) and 202 with GBA variants (47 with and 155 without PD). Twenty-six participants reported pesticide exposure. People with a GBA variant and occupational pesticide exposure had much higher odds of PD (aOR: 5.4, 95% CI 1.7-18.5, p

IntroductionEarly diagnosis of Parkinson's disease (PD) is important to identify treatments to slow neurodegeneration. People who develop PD often have symptoms before the disease manifests and may be coded as diagnoses in the electronic health record (EHR).MethodsTo predict PD diagnosis, we embedded EHR data of patients onto a biomedical knowledge graph called Scalable Precision medicine Open Knowledge Engine (SPOKE) and created patient embedding vectors. We trained and validated a classifier using these vectors from 3,004 PD patients, restricting records to 1, 3, and 5 years before diagnosis, and 457,197 non-PD group.ResultsThe classifier predicted PD diagnosis with moderate accuracy (AUC = 0.77 ± 0.06, 0.74 ± 0.05, 0.72 ± 0.05 at 1, 3, and 5 years) and performed better than other benchmark methods. Nodes in the SPOKE graph, among cases, revealed novel associations, while SPOKE patient vectors revealed the basis for individual risk classification.DiscussionThe proposed method was able to explain the clinical predictions using the knowledge graph, thereby making the predictions clinically interpretable. Through enriching EHR data with biomedical associations, SPOKE may be a cost-efficient and personalized way to predict PD diagnosis years before its occurrence.

The etiologies of Parkinson's disease (PD) remain unclear. Some, such as certain genetic mutations and head trauma, are widely known or easily identified. However, these causes or risk factors do not account for the majority of cases. Other, less visible factors must be at play. Among these is a widely used industrial solvent and common environmental contaminant little recognized for its likely role in PD: trichloroethylene (TCE). TCE is a simple, six-atom molecule that can decaffeinate coffee, degrease metal parts, and dry clean clothes. The colorless chemical was first linked to parkinsonism in 1969. Since then, four case studies involving eight individuals have linked occupational exposure to TCE to PD. In addition, a small epidemiological study found that occupational or hobby exposure to the solvent was associated with a 500% increased risk of developing PD. In multiple animal studies, the chemical reproduces the pathological features of PD.Exposure is not confined to those who work with the chemical. TCE pollutes outdoor air, taints groundwater, and contaminates indoor air. The molecule, like radon, evaporates from underlying soil and groundwater and enters homes, workplaces, or schools, often undetected. Despite widespread contamination and increasing industrial, commercial, and military use, clinical investigations of TCE and PD have been limited. Here, through a literature review and seven illustrative cases, we postulate that this ubiquitous chemical is contributing to the global rise of PD and that TCE is one of its invisible and highly preventable causes. Further research is now necessary to examine this hypothesis.

BackgroundParkinson's disease (PD) is a chronic, disabling neurodegenerative disorder.ObjectiveTo predict a future diagnosis of PD using questionnaires and simple non-invasive clinical tests.MethodsParticipants in the prospective Kuakini Honolulu-Asia Aging Study (HAAS) were evaluated biannually between 1995-2017 by PD experts using standard diagnostic criteria. Autopsies were sought on all deaths. We input simple clinical and risk factor variables into an ensemble-tree based machine learning algorithm and derived models to predict the probability of developing PD. We also investigated relationships of predictive models and neuropathologic features such as nigral neuron density.ResultsThe study sample included 292 subjects, 25 of whom developed PD within 3 years and 41 by 5 years. 116 (46%) of 251 subjects not diagnosed with PD underwent autopsy. Light Gradient Boosting Machine modeling of 12 predictors correctly classified a high proportion of individuals who developed PD within 3 years (area under the curve (AUC) 0.82, 95%CI 0.76-0.89) or 5 years (AUC 0.77, 95%CI 0.71-0.84). A large proportion of controls who were misclassified as PD had Lewy pathology at autopsy, including 79%of those who died within 3 years. PD probability estimates correlated inversely with nigral neuron density and were strongest in autopsies conducted within 3 years of index date (r = -0.57, p

The Trial of Parkinson's And Zoledronic acid (TOPAZ, https://clinicaltrials.gov/ct2/show/NCT03924414 ) is a unique collaboration between experts in movement disorders and osteoporosis to test the efficacy of zoledronic acid, an FDA-approved parenteral treatment for osteoporosis, for fracture prevention in people with neurodegenerative parkinsonism. Aiming to enroll 3,500 participants age 65 years or older, TOPAZ is one of the largest randomized, placebo-controlled clinical trials ever attempted in parkinsonism. The feasibility of TOPAZ is enhanced by its design as a U.S.- wide home-based trial without geographical limits. Participants receive information from multiple sources, including specialty practices, support groups and websites. Conducting TOPAZ in participants' homes takes advantage of online consent technology, the capacity to confirm diagnosis using telemedicine and the availability of research nursing to provide screening and parenteral therapy in homes. Home-based clinical research may provide an efficient, convenient, less expensive method that opens participation in clinical trials to almost anyone with parkinsonism.

The gastrointestinal microbiome is altered in Parkinson's disease and likely plays a key role in its pathophysiology, affecting symptoms and response to therapy and perhaps modifying progression or even disease initiation. Gut dysbiosis therefore has a significant potential as a therapeutic target in Parkinson's disease, a condition elusive to disease-modifying therapy thus far. The gastrointestinal environment hosts a complex ecology, and efforts to modulate the relative abundance or function of established microorganisms are still in their infancy. Still, these techniques are being rapidly developed and have important implications for our understanding of Parkinson's disease. Currently, modulation of the microbiome can be achieved through non-pharmacologic means such as diet, pharmacologically through probiotic, prebiotic, or antibiotic use and procedurally through fecal transplant. Novel techniques being explored include the use of small molecules or genetically engineered organisms, with vast potential. Here, we review how some of these approaches have been used to date, important areas of ongoing research, and how microbiome modulation may play a role in the clinical management of Parkinson's disease in the future.

BackgroundThe penetrance of leucine rich repeat kinase 2 (LRRK2) mutations is incomplete and may be influenced by environmental and/or other genetic factors. Nonsteroidal anti-inflammatory drugs (NSAIDs) are known to reduce inflammation and may lower Parkinson's disease (PD) risk, but their role in LRRK2-associated PD is unknown.ObjectivesThe objective of this study is to evaluate the association of regular NSAID use and LRRK2-associated PD.MethodsSymptomatic ("LRRK2-PD") and asymptomatic ("LRRK2-non-PD") participants with LRRK2 G2019S, R1441X, or I2020T variants (definitely pathogenic variant carriers) or G2385R or R1628P variants (risk variant carriers) from 2 international cohorts provided information on regular ibuprofen and/or aspirin use (≥2 pills/week for ≥6 months) prior to the index date (diagnosis date for PD, interview date for non-PD). Multivariate logistic regression was used to evaluate the relationship between regular NSAID use and PD for any NSAID, separately for ibuprofen and aspirin in all carriers and separately in pathogenic and risk variant groups.ResultsA total of 259 LRRK2-PD and 318 LRRK2-non-PD participants were enrolled. Regular NSAID use was associated with reduced odds of PD in the overall cohort (odds ratio [OR], 0.34; 95% confidence interval [CI], 0.21-0.57) and in both pathogenic and risk variant carriers (ORPathogenic , 0.38; 95% CI, 0.21-0.67 and ORRiskVariant , 0.19; 95% CI, 0.04-0.99). Similar associations were observed for ibuprofen and aspirin separately (ORIbuprofen , 0.19; 95% CI, 0.07-0.50 and ORAspirin , 0.51; 95% CI, 0.28-0.91).ConclusionsRegular NSAID use may be associated with reduced penetrance in LRRK2-associated PD. The LRRK2 protein is involved in inflammatory pathways and appears to be modulated by regular anti-inflammatory use. Longitudinal observational and interventional studies of NSAID exposure and LRRK2-PD are needed to confirm this association. © 2020 International Parkinson and Movement Disorder Society.

Autonomic nervous system involvement precedes the motor features of Parkinson's disease (PD). Our goal was to develop a proof-of-concept model for identifying subjects at high risk of developing PD by analysis of cardiac electrical activity. We used standard 10-s electrocardiogram (ECG) recordings of 60 subjects from the Honolulu Asia Aging Study including 10 with prevalent PD, 25 with prodromal PD, and 25 controls who never developed PD. Various methods were implemented to extract features from ECGs including simple heart rate variability (HRV) metrics, commonly used signal processing methods, and a Probabilistic Symbolic Pattern Recognition (PSPR) method. Extracted features were analyzed via stepwise logistic regression to distinguish between prodromal cases and controls. Stepwise logistic regression selected four features from PSPR as predictors of PD. The final regression model built on the entire dataset provided an area under receiver operating characteristics curve (AUC) with 95% confidence interval of 0.90 [0.80, 0.99]. The five-fold cross-validation process produced an average AUC of 0.835 [0.831, 0.839]. We conclude that cardiac electrical activity provides important information about the likelihood of future PD not captured by classical HRV metrics. Machine learning applied to ECGs may help identify subjects at high risk of having prodromal PD.

BackgroundThe effect of the COVID-19 pandemic on people with Parkinson's disease (PD) is poorly understood.ObjectiveTo rapidly identify areas of need and improve care in people with PD during the COVID-19 pandemic, we deployed a survey to assess COVID-19 symptoms and the pandemic's effect among those with and without COVID-19.MethodsPeople with and without PD participating in the online study Fox Insight (FI) were invited to complete a survey between April 23 and May 23, 2020. Among people reporting COVID-19 diagnoses, we compared symptoms and outcomes in people with and without PD. Among people not reporting COVID-19, we assessed access to healthcare and services and PD symptoms.Results7,209/9,762 active FI users responded (approximately 74% response rate), 5,429 people with PD and 1,452 without PD. COVID-19 diagnoses were reported by 51 people with and 26 without PD. Complications were more frequent in people with longer PD duration. People with PD and COVID-19 experienced new or worsening motor (63%) and nonmotor (75%) symptoms. People with PD not diagnosed with COVID-19 reported disrupted medical care (64%), exercise (21%), and social activities (57%), and worsened motor (43%) and non-motor (52%) symptoms. Disruptions were more common for those living alone, with lower income and non-White race.ConclusionsThe COVID-19 pandemic is associated with wide-ranging effects on people with PD, and certain groups may be at particular risk. FI provides a rapid, patient-centered means to assess these effects and identify needs that can be used to improve the health of people with PD.

PurposeCardiac autonomic dysfunction manifests as reduced heart rate variability (HRV) in idiopathic Parkinson's disease (PD), but no significant reduction has been found in PD patients who carry the LRRK2 mutation. Novel HRV features have not been investigated in these individuals. We aimed to assess cardiac autonomic modulation through standard and novel approaches to HRV analysis in individuals who carry the LRRK2 G2019S mutation.MethodsShort-term electrocardiograms were recorded in 14 LRRK2-associated PD patients, 25 LRRK2-non-manifesting carriers, 32 related non-carriers, 20 idiopathic PD patients, and 27 healthy controls. HRV measures were compared using regression modeling, controlling for age, sex, mean heart rate, and disease duration. Discriminant analysis highlighted the feature combination that best distinguished LRRK2-associated PD from controls.ResultsBeat-to-beat and global HRV measures were significantly increased in LRRK2-associated PD patients compared with controls (e.g., deceleration capacity of heart rate: p = 0.006) and idiopathic PD patients (e.g., 8th standardized moment of the interbeat interval distribution: p = 0.0003), respectively. LRRK2-associated PD patients also showed significantly increased irregularity of heart rate dynamics, as quantified by Rényi entropy, when compared with controls (p = 0.002) and idiopathic PD patients (p = 0.0004). Ordinal pattern statistics permitted the identification of LRRK2-associated PD individuals with 93% sensitivity and 93% specificity. Consistent results were found in a subgroup of LRRK2-non-manifesting carriers when compared with controls.ConclusionsIncreased beat-to-beat HRV in LRRK2 G2019S mutation carriers compared with controls and idiopathic PD patients may indicate augmented cardiac autonomic cholinergic activity, suggesting early impairment of central vagal feedback loops in LRRK2-associated PD.

The National Academy of Sciences-National Research Council (NAS-NRC) Twin Registry is one of the oldest, national population-based twin registries in the USA. It comprises 15,924 White male twin pairs born in the years 1917-1927 (N = 31.848), both of whom served in the armed forces, chiefly during World War II. This article updates activities in this registry since the most recent report in Twin Research and Human Genetics (Page, 2006). Records-based data include information from enlistment charts and Veterans Administration data linkages. There have been three major epidemiologic questionnaires and an education and earnings survey. Separate data collection efforts with the NAS-NRC registry include the National Heart, Lung, and Blood Institute (NHLBI) subsample, the Duke Twins Study of Memory in Aging and a clinically based study of Parkinson's disease. Progress has been made on consolidating the various data holdings of the NAS-NRC Twin Registry. Data that had been available through the National Academy of Sciences are now freely available through National Archive of Computerized Data on Aging (NACDA).

Background:It is unknown whether subjective daytime sleepiness or objective napping could precede the risk of Parkinson's disease (PD) in the long term. Methods:We studied 2920 men (mean age 76 years) without a history of PD and followed them for 11 years. Excessive daytime sleepiness (EDS) was defined as having an Epworth Sleepiness Scale score >10. Objective naps were defined as ≥5 consecutive minutes of inactivity as measured by actigraphy, and napping duration was the accumulated time of naps outside the main sleep period. We used logistic regression to compare PD risk across four groups: no EDS& napping

Post-traumatic stress disorder (PTSD) may be a risk factor for Parkinson's disease (PD). We examined the relation between PTSD and PD in a cohort of 158,122 Veterans who had any Veterans Health Administration (VHA) or Medicare health care utilization between 10/1/1999– 2/17/2021. Using a nested case-control design we matched 10 controls to each Veteran with PD by sex, race, and rank. In conditional logistic regression models adjusted for camp and smoking, a PTSD diagnosis was significantly associated with PD (OR = 1.35; p = 0.0002); odds were higher if PTSD was coded before PD (OR = 1.53, p < 0.0001). PTSD may be a risk factor for PD. [ABSTRACT FROM AUTHOR]

ObjectiveTo minimize pathologic heterogeneity in genetic studies of Parkinson disease (PD), the Autopsy-Confirmed Parkinson Disease Genetics Consortium conducted a genome-wide association study using both patients with neuropathologically confirmed PD and controls.MethodsFour hundred eighty-four cases and 1,145 controls met neuropathologic diagnostic criteria, were genotyped, and then imputed to 3,922,209 variants for genome-wide association study analysis.ResultsA small region on chromosome 1 was strongly associated with PD (rs10788972; p = 6.2 × 10(-8)). The association peak lies within and very close to the maximum linkage peaks of 2 prior positive linkage studies defining the PARK10 locus. We demonstrate that rs10788972 is in strong linkage disequilibrium with rs914722, the single nucleotide polymorphism defining the PARK10 haplotype previously shown to be significantly associated with age at onset in PD. The region containing the PARK10 locus was significantly reduced from 10.6 megabases to 100 kilobases and contains 4 known genes: TCEANC2, TMEM59, miR-4781, and LDLRAD1.ConclusionsWe confirm the association of a PARK10 haplotype with the risk of developing idiopathic PD. Furthermore, we significantly reduce the size of the PARK10 region. None of the candidate genes in the new PARK10 region have been previously implicated in the biology of PD, suggesting new areas of potential research. This study strongly suggests that reducing pathologic heterogeneity may enhance the application of genetic association studies to PD.

Pesticides have been associated with Parkinson's disease (PD), and protective gloves and workplace hygiene can reduce pesticide exposure. We assessed whether use of gloves and workplace hygiene modified associations between pesticides and PD. The Farming and Movement Evaluation (FAME) study is a nested case-control study within the Agricultural Health Study. Use of protective gloves, other PPE, and hygiene practices were determined by questionnaire (69 cases and 237 controls were included). We considered interactions of gloves and hygiene with ever-use of pesticides for all pesticides with ≥5 exposed and unexposed cases and controls in each glove-use stratum (paraquat, permethrin, rotenone, and trifluralin). 61% of respondents consistently used protective gloves and 87% consistently used ≥2 hygiene practices. Protective glove use modified the associations of paraquat and permethrin with PD: neither pesticide was associated with PD among protective glove users, while both pesticides were associated with PD among non-users (paraquat OR 3.9 [95% CI 1.3, 11.7], interaction p=0.15; permethrin OR 4.3 [95% CI 1.2, 15.6] interaction p=0.05). Rotenone was associated with PD regardless of glove use. Trifluralin was associated with PD among participants who used

Increased gut permeability, inflammation, and colonic α-synuclein pathology are present in early Parkinson's disease (PD) and have been proposed to contribute to PD pathogenesis. Peptidoglycan is a structural component of the bacterial cell wall. Peptidoglycan recognition proteins (PGRPs) maintain healthy gut microbial flora by regulating the immune response to both commensal and harmful bacteria. We tested the hypothesis that variants in genes that encode PGRPs are associated with PD risk. Participants in two independent case-control studies were genotyped for 30 single-nucleotide polymorphisms (SNPs) in the four PGLYRP genes. Using logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusted for potential confounding variables, we conducted analyses in each study, separately and pooled. One SNP failed the assay, and three had little to no variation. The ORs were similar in both study populations. In pooled analyses, three of seven PGLYRP2 SNPs (rs3813135, rs733731, rs892145), one of five PGLYRP3 SNPs (rs2987763), and six of nine PGLYRP4 SNPs (rs10888557, rs12063091, rs3006440, rs3006448, rs3006458, and rs3014864) were significantly associated with PD risk. Association was strongest for PGLYRP4 5'untranslated region (UTR) SNP rs10888557 (GG reference, CG OR 0.6 [95%CI 0.4-0.9], CC OR 0.15 [95%CI 0.04-0.6]; log-additive P-trend, 0.0004). Common variants in PGLYRP genes are associated with PD risk in two independent studies. These results require replication, but they are consistent with hypotheses of a causative role for the gut microbiota and gastrointestinal immune response in PD.

BackgroundDietary fat intake may modify Parkinson's disease (PD) risk directly or by altering the response to environmental neurotoxicants including pesticides.MethodsWe conducted a case-control study of PD nested in the Agricultural Health Study (AHS), a cohort of pesticide applicators and spouses. We evaluated diet and pesticide use before diagnosis in 89 PD cases, confirmed by movement disorder specialists, or a corresponding date in 336 frequency-matched controls. Associations were evaluated using multivariate logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs).ResultsIn the AHS, PD was inversely associated with N-3 polyunsaturated fatty acids (PUFAs) (OR 0.4, 95% CI 0.2-0.8 for highest vs. lowest tertile) and the N-3 precursor α-linolenic acid (0.4, 0.2-0.8). In a meta-analysis of nine studies, including the present one, PD was inversely associated with α-linolenic acid (0.81, 0.68-0.96). In the AHS, associations of PD with the pesticides paraquat and rotenone were modified by fat intake. The OR for paraquat was 4.2 (1.5-12) in individuals with PUFA intake below the median but 1.2 (0.4-3.4) in those with higher intake (p-interaction = 0.10). The OR for rotenone was 5.8 (2.3-15) in those with saturated fat intake above the median but 1.5 (0.5-4.2) in those with lower intake (p-interaction = 0.02).ConclusionsPUFA intake was consistently associated with lower PD risk, and dietary fats modified the association of PD risk with pesticide exposure. If confirmed, these findings suggest that a diet high in PUFAs and low in saturated fats might reduce risk of PD.

Paraquat is one of the most widely used herbicides worldwide. It produces a Parkinson's disease (PD) model in rodents through redox cycling and oxidative stress (OS) and is associated with PD risk in humans. Glutathione transferases provide cellular protection against OS and could potentially modulate paraquat toxicity. We investigated PD risk associated with paraquat use in individuals with homozygous deletions of the genes encoding glutathione S-transferase M1 (GSTM1) or T1 (GSTT1). Eighty-seven PD subjects and 343 matched controls were recruited from the Agricultural Health Study, a study of licensed pesticide applicators and spouses in Iowa and North Carolina. PD was confirmed by in-person examination. Paraquat use and covariates were determined by interview. We genotyped subjects for homozygous deletions of GSTM1 (GSTM1*0) and GSTT1 (GSTT1*0) and tested interaction between paraquat use and genotype using logistic regression. Two hundred and twenty-three (52%) subjects had GSTM1*0, 95 (22%) had GSTT1*0, and 73 (17%; all men) used paraquat. After adjustment for potential confounders, there was no interaction with GSTM1. In contrast, GSTT1 genotype significantly modified the association between paraquat and PD. In men with functional GSTT1, the odds ratio (OR) for association of PD with paraquat use was 1.5 (95% confidence interval [CI]: 0.6-3.6); in men with GSTT1*0, the OR was 11.1 (95% CI: 3.0-44.6; P interaction: 0.027). Although replication is needed, our results suggest that PD risk from paraquat exposure might be particularly high in individuals lacking GSTT1. GSTT1*0 is common and could potentially identify a large subpopulation at high risk of PD from oxidative stressors such as paraquat.

Although the causes of Parkinson's disease (PD) are thought to be primarily environmental, recent studies suggest that a number of genes influence susceptibility. Using targeted case recruitment and online survey instruments, we conducted the largest case-control genome-wide association study (GWAS) of PD based on a single collection of individuals to date (3,426 cases and 29,624 controls). We discovered two novel, genome-wide significant associations with PD-rs6812193 near SCARB2 (p = 7.6 × 10(-10), OR = 0.84) and rs11868035 near SREBF1/RAI1 (p = 5.6 × 10(-8), OR = 0.85)-both replicated in an independent cohort. We also replicated 20 previously discovered genetic associations (including LRRK2, GBA, SNCA, MAPT, GAK, and the HLA region), providing support for our novel study design. Relying on a recently proposed method based on genome-wide sharing estimates between distantly related individuals, we estimated the heritability of PD to be at least 0.27. Finally, using sparse regression techniques, we constructed predictive models that account for 6%-7% of the total variance in liability and that suggest the presence of true associations just beyond genome-wide significance, as confirmed through both internal and external cross-validation. These results indicate a substantial, but by no means total, contribution of genetics underlying susceptibility to both early-onset and late-onset PD, suggesting that, despite the novel associations discovered here and elsewhere, the majority of the genetic component for Parkinson's disease remains to be discovered.

Although the causes of Parkinson's disease (PD) are thought to be primarily environmental, recent studies suggest that a number of genes influence susceptibility. Using targeted case recruitment and online survey instruments, we conducted the largest case-control genome-wide association study (GWAS) of PD based on a single collection of individuals to date (3,426 cases and 29,624 controls). We discovered two novel, genome-wide significant associations with PD-rs6812193 near SCARB2 (p = 7.6 × 10(-10), OR = 0.84) and rs11868035 near SREBF1/RAI1 (p = 5.6 × 10(-8), OR = 0.85)-both replicated in an independent cohort. We also replicated 20 previously discovered genetic associations (including LRRK2, GBA, SNCA, MAPT, GAK, and the HLA region), providing support for our novel study design. Relying on a recently proposed method based on genome-wide sharing estimates between distantly related individuals, we estimated the heritability of PD to be at least 0.27. Finally, using sparse regression techniques, we constructed predictive models that account for 6%-7% of the total variance in liability and that suggest the presence of true associations just beyond genome-wide significance, as confirmed through both internal and external cross-validation. These results indicate a substantial, but by no means total, contribution of genetics underlying susceptibility to both early-onset and late-onset PD, suggesting that, despite the novel associations discovered here and elsewhere, the majority of the genetic component for Parkinson's disease remains to be discovered.