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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.

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.

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.

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.

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

Background Objectives Methods Results Conclusions Electronic medical record (EMR)–based studies hold great potential for epidemiologic investigations of Parkinson's disease (PD) causal factors and phenomenology, but diagnostic misclassification may obscure or bias inferences.The aims were to determine the validity of PD diagnostic codes in the Veterans Administration (VA) national electronic medical databases and develop recommendations for maximizing ascertainment accuracy.We investigated a cohort of 146,776 veterans who utilized VA healthcare between 1999 and 2021. We reviewed the medical records of individuals with a PD International Classification of Diseases (ICD) code in outpatient, inpatient, or community care encounters to assign a gold‐standard diagnosis. We determined diagnostic accuracy based on provider type, coding frequency, medications, and potentially exclusionary ICD codes overall and by race.A total of 377 of 810 (46.5%) with a PD ICD code had PD. Veterans whose PD was coded by a PD‐specialist neurologist were most likely to have PD (83.6%), but sensitivity was low (15.0%). Diagnostic accuracy decreased for PD coded by any neurologist (66.9%), but sensitivity improved (69.4%). Requiring two or more PD codes in combination with two or more levodopa prescriptions improved accuracy, particularly among nonneurologists. Neuroleptic‐induced parkinsonism was the most frequent diagnosis in those without PD (15.6%). Accuracy was lower in Black (29.0%) than White (50.5%) veterans regardless of provider type (miscoding odds ratio 2.5, 95% confidence interval 1.7–3.6).These results highlight the limitations of EMR‐based PD ascertainment. Researchers can maximize accuracy by considering provider specialty, coding frequency, pharmacy data, and exclusionary diagnoses, but some degree of record review is required to ensure high accuracy. Higher miscoding among Black veterans warrants further study. © 2024 The Author(s). 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. [ABSTRACT FROM AUTHOR]

Background: We recently reported an increased risk of Parkinson's disease (PD) in service members who resided at Marine Base Camp Lejeune, North Carolina, when water supplies were contaminated with trichloroethylene and other volatile organic compounds (VOCs). Prior studies suggest that environmental exposures may affect PD phenotype or progression, but this has not been reported for VOCs. Objective: The objective of this study was to test whether PD progression is faster in individuals exposed to VOCs in water at Camp Lejeune. Methods: A cohort of 172,128 marines residing at Camp Lejeune between 1975 and 1985 was previously assembled. We identified individuals with PD in Veterans Health Administration and Medicare databases between 2000 and 2021. Using estimates derived by the US Agency for Toxic Substances and Disease Registry, we classified individuals as exposed or unexposed to VOCs in residential water. We used Kaplan–Meier and Cox regression models to test differences between exposed and unexposed groups in the time from PD diagnosis until psychosis, fracture, fall, or death. Results: Among 270 persons with PD, 177 (65.6%) were exposed to VOCs in residential water. Median cumulative exposure was 4970 μg/L‐months, >50‐fold the permissible level. Time until psychosis, fracture, and fall were all shorter in the exposed group, with adjusted hazard ratios (HRs) exceeding 2: psychosis HR, 2.19 (95% confidence interval [CI]: 0.99–4.83); fracture HR, 2.44 (95% CI: 0.91–6.55); and fall HR, 2.64 (95% CI: 0.97–7.21). A significant dose response was observed for time to fall (P trend, 0.032). No differences were observed for time until death. Conclusions: PD progression may be faster in persons exposed to trichloroethylene and other VOCs in water decades earlier. © 2024 The Author(s). 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. [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.

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]

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.

Background: Environmental exposure to trichloroethylene (TCE), a carcinogenic dry‐cleaning chemical, may be linked to Parkinson's disease (PD). Objective: The objective of this study was to determine whether PD and cancer were elevated among attorneys who worked near a contaminated site. Methods: We surveyed and evaluated attorneys with possible exposure and assessed a comparison group. Results: Seventy‐nine of 82 attorneys (96.3%; mean [SD] age: 69.5 [11.4] years; 89.9% men) completed at least one phase of the study. For comparison, 75 lawyers (64.9 [10.2] years; 65.3% men) underwent clinical evaluations. Four (5.1%) of them who worked near the polluted site reported PD, more than expected based on age and sex (1.7%; P = 0.01) but not significantly higher than the comparison group (n = 1 [1.3%]; P = 0.37). Fifteen (19.0%), compared to four in the comparison group (5.3%; P = 0.049), had a TCE‐related cancer. Conclusions: In a retrospective study, diagnoses of PD and TCE‐related cancers appeared to be elevated among attorneys who worked next to a contaminated dry‐cleaning site. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Little is known about electrocardiogram (ECG) markers of Parkinson's disease (PD) during the prodromal stage. The aim of the study was to build a generalizable ECG-based fully automatic artificial intelligence (AI) model to predict PD risk during the prodromal stage, up to 5 years before disease diagnosis. This case–control study included samples from Loyola University Chicago (LUC) and University of Tennessee-Methodist Le Bonheur Healthcare (MLH). Cases and controls were matched according to specific characteristics (date, age, sex and race). Clinical data were available from May, 2014 onward at LUC and from January, 2015 onward at MLH, while the ECG data were available as early as 1990 in both institutes. PD was denoted by at least two primary diagnostic codes (ICD9 332.0; ICD10 G20) at least 30 days apart. PD incidence date was defined as the earliest of first PD diagnostic code or PD-related medication prescription. ECGs obtained at least 6 months before PD incidence date were modeled to predict a subsequent diagnosis of PD within three time windows: 6 months–1 year, 6 months–3 years, and 6 months–5 years. We applied a novel deep neural network using standard 10-s 12-lead ECGs to predict PD risk at the prodromal phase. This model was compared to multiple feature engineering-based models. Subgroup analyses for sex, race and age were also performed. Our primary prediction model was a one-dimensional convolutional neural network (1D-CNN) that was built using 131 cases and 1058 controls from MLH, and externally validated on 29 cases and 165 controls from LUC. The model was trained on 90% of the MLH data, internally validated on the remaining 10% and externally validated on LUC data. The best performing model resulted in an external validation AUC of 0.67 when predicting future PD at any time between 6 months and 5 years after the ECG. Accuracy increased when restricted to ECGs obtained within 6 months to 3 years before PD diagnosis (AUC 0.69) and was highest when predicting future PD within 6 months to 1 year (AUC 0.74). The 1D-CNN model based on raw ECG data outperformed multiple models built using more standard ECG feature engineering approaches. These results demonstrate that a predictive model developed in one cohort using only raw 10-s ECGs can effectively classify individuals with prodromal PD in an independent cohort, particularly closer to disease diagnosis. Standard ECGs may help identify individuals with prodromal PD for cost-effective population-level early detection and inclusion in disease-modifying therapeutic trials. [ABSTRACT FROM AUTHOR]

Fueled by aging populations and continued environmental contamination, the global burden of Parkinson's disease (PD) is increasing. The disease, or more appropriately diseases, have multiple environmental and genetic influences but no approved disease modifying therapy. Additionally, efforts to prevent this debilitating disease have been limited. As numerous environmental contaminants (e.g., pesticides, metals, industrial chemicals) are implicated in PD, disease prevention is possible. To reduce the burden of PD, we have compiled preclinical and clinical research priorities that highlight both disease prediction and primary prevention. Though not exhaustive, the "PD prevention agenda" builds upon many years of research by our colleagues and proposes next steps through the lens of modifiable risk factors. The agenda identifies ten specific areas of further inquiry and considers the funding and policy changes that will be necessary to help prevent the world's fastest growing brain disease. [ABSTRACT FROM AUTHOR]

Purpose: Cardiac autonomic dysfunction in idiopathic Parkinson's disease (PD) manifests as reduced heart rate variability (HRV). In the present study, we explored the deceleration capacity of heart rate (DC) in patients with idiopathic PD, an advanced HRV marker that has proven clinical utility. Methods: Standard and advanced HRV measures derived from 7-min electrocardiograms in 20 idiopathic PD patients and 27 healthy controls were analyzed. HRV measures were compared using regression analysis, controlling for age, sex, and mean heart rate. Results: Significantly reduced HRV was found only in the subcohort of PD patients older than 60 years. Low- frequency power and global HRV measures were lower in patients than in controls, but standard beat-to-beat HRV markers (i.e., rMSSD and high-frequency power) were not significantly different between groups. DC was significantly reduced in the subcohort of PD patients older than 60 years compared to controls. Conclusions: Deceleration-related oscillations of HRV were significantly reduced in the older PD patients compared to healthy controls, suggesting that short-term DC may be a sensitive marker of cardiac autonomic dysfunction in PD. DC may be complementary to traditional markers of short-term HRV for the evaluation of autonomic modulation in PD. Further study to examine the association between DC and cardiac adverse events in PD is needed to clarify the clinical relevance of DC in this population. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

There is evidence from observational studies for a role of a number of environmental exposures and lifestyle habits in modulating the risk for Parkinson's disease. Environmental and lifestyle associations, if causal, represent opportunities for Parkinson's disease prevention or disease modification at individual and population levels. In the past decade, additional evidence has been published that improves causal inference and/or enhances our understanding of the complexity of these associations. A number of gene-environment interactions have been elucidated, and our understanding of the roles of physical activity, pesticide and other chemical exposures, dietary habits, emotional stress, head injury, and smoking has been refined. In the next decade, better techniques will help us to close the gaps in our knowledge, including taking into account Parkinson's disease heterogeneity and gene and risk factor interactions in observational studies. To do this, larger datasets, global consortia, genomewide environment interaction studies, prospective studies throughout the lifespan, and improvements in the methodology of clinical trials of physical activity will be key. Despite the caveats of observational studies, a number of low-risk and potentially high-yield recommendations for lifestyle modification could be made to minimize the individual and societal burdens of Parkinson's disease, including dietary modifications, increasing physical activity, and head injury avoidance. Furthermore, a reduction in pesticide use could have a major impact on global health related to and beyond Parkinson's disease. Given the increasing prevalence of this disorder, formulating and promoting these recommendations should be a high priority. © 2019 International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

During the 1990s, we estimated the genetic contribution to Parkinson's disease risk in a large, population-based twin registry. Because many unaffected twins were still alive, previous concordance estimates were based on incomplete information. Ninety-five percent of twins are now deceased. Here, we update concordance and heritability through 2015 using National Death Index data. In total, we identified 30 concordant and 193 discordant pairs. Proband-wise concordance was 0.20 in monozygotic and 0.13 in dizygotic pairs. Heritability was 0.27 overall, 0.83 in pairs diagnosed ≤50, and 0.19 in pairs diagnosed >50. High concordance in dizygotic twins suggests shared effects of early childhood environment. Ann Neurol 2019;85:600-605. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a chronic, progressive, disabling neurodegenerative disorder that begins in mid to late life and is characterized by motor impairment, autonomic dysfunction, and, in many, psychological and cognitive changes. Recent advances have helped delineate pathogenetic mechanisms, yet the cause of PD in most individuals is unknown. Although at least 15 genes and genetic loci have been associated with PD, identified genetic causes are responsible for only a few percent of cases. Epidemiologic studies have found increased risk of PD associated with exposure to environmental toxicants such as pesticides, solvents, metals, and other pollutants, and many of these compounds recapitulate PD pathology in animal models. This review summarizes the environmental toxicology of PD, highlighting the consistency of observations across cellular, animal, and human studies of PD pathogenesis. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a chronic, progressive, disabling neurodegenerative disorder that begins in mid to late life and is characterized by motor impairment, autonomic dysfunction, and, in many, psychological and cognitive changes. Recent advances have helped delineate pathogenetic mechanisms, yet the cause of PD in most individuals is unknown. Although at least 15 genes and genetic loci have been associated with PD, identified genetic causes are responsible for only a few percent of cases. Epidemiologic studies have found increased risk of PD associated with exposure to environmental toxicants such as pesticides, solvents, metals, and other pollutants, and many of these compounds recapitulate PD pathology in animal models. This review summarizes the environmental toxicology of PD, highlighting the consistency of observations across cellular, animal, and human studies of PD pathogenesis. [ABSTRACT FROM AUTHOR]

Background: Mitochondrial dysfunction and oxidative stress are pathophysiologic mechanisms implicated in experimental models and genetic forms of Parkinson's disease (PD). Certain pesticides may affect these mechanisms, but no pesticide has been definitively associated with PD in humans. oBjectives: Our goal was to determine whether pesticides that cause mitochondrial dysfunction or oxidative stress are associated with PD or clinical features of parkinsonism in humans. Methods: We assessed lifetime use of pesticides selected by mechanism in a case-control study nested in the Agricultural Health Study (AHS). PD was diagnosed by movement disorders special­ists. Controls were a stratified random sample of all AHS participants frequency-matched to cases by age, sex, and state at approximately three controls:one case. results: In 110 PD cases and 358 controls, PD was associated with use of a group of pesticides that inhibit mitochondrial complex I [odds ratio (OR) = 1.7; 95% confidence interval (CI), 1.0-2.8] including rotenone (OR = 2.5; 95% CI, 1.3-4.7) and with use of a group of pesticides that cause oxidative stress (OR = 2.0; 95% CI, 1.2-3.6), including paraquat (OR = 2.5; 95% CI, 1.4-4.7). conclusions: PD was positively associated with two groups of pesticides defined by mechanisms implicated experimentally-those that impair mitochondrial function and those that increase oxida­tive stress-supporting a role for these mechanisms in PD pathophysiology. [ABSTRACT FROM AUTHOR]

Context: The cause of Parkinson disease (PD) is unknown. Genetic linkages have been identified in families with PD, but whether most PD is inherited has not been determined.Objective: To assess genetic inheritance of PD by studying monozygotic (MZ) and dizygotic (DZ) twin pairs.Design: Twin study comparing concordance rates of PD in MZ and DZ twin pairs.Setting and Participants: A total of 19842 white male twins enrolled in the National Academy of Sciences/National Research Council World War II Veteran Twins Registry were screened for PD and standard diagnostic criteria for PD were applied. Zygosity was determined by polymerase chain reaction or questionnaire.Main Outcome Measure: Parkinson disease concordance in twin pairs, stratified by zygosity and age at diagnosis.Results: Of 268 twins with suspected parkinsonism and 250 presumed unaffected twin brothers, 193 twins with PD were identified (concordance-adjusted prevalence, 8.67/1000). In 71 MZ and 90 DZ pairs with complete diagnoses, pairwise concordance was similar (0.129 overall, 0.155 MZ, 0.111 DZ; relative risk, 1.39; 95% confidence interval, 0.63-3.1). In 16 pairs with diagnosis at or before age 50 years in at least 1 twin, MZ concordance was 1.0 (4 pairs), and DZ was 0.167 (relative risk, 6.0; 95% confidence interval, 1.69-21.26).Conclusions: The similarity in concordance overall indicates that genetic factors do not play a major role in causing typical PD. No genetic component is evident when the disease begins after age 50 years. However, genetic factors appear to be important when disease begins at or before age 50 years. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Head injury, α-synuclein genetic variability and Parkinson's disease" that was published in the same issue.

Alzheimer's disease, Parkinson's disease, and motor neuron disease, the most common of the late-life neurodegenerative disorders, are in most cases thought to have complex etiologies. Common features among these disorders include insidious onset, pathological findings of protein aggregates and selected neuronal degeneration, and resulting characteristic clinical syndromes. The number of elders in the United States, including aging veterans, is increasing. Investigation of causes and preventive interventions for neurodegenerative disorders is increasingly relevant. Recent epidemiological and laboratory studies suggest that exposures years or decades before diagnosis can trigger the processes that ultimately result in a neurodegenerative disease. If this is correct, preventive measures may be needed in midlife or earlier. This article will focus on putative risk factors relevant to military service. [ABSTRACT FROM AUTHOR]