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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.

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

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.

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]

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]

Introduction Between 1953 and 1987, over one million Veterans were exposed to contaminated water at Marine Corps Base Camp Lejeune, North Carolina. We examined the relationship between toxicant exposure and subsequent disability ratings in female veterans. Materials and Methods Comparisons were made between females stationed at Camp Lejeune and from Marine Corps Base Camp Pendleton, California who were not known to have been exposed to these toxicants, between 1975 and 1985, using data from the Agency for Toxic Substances and Diseases Registry and VA data. Results A total of 4,491 (52%) females from Camp Lejeune and 2,811 (47%) from Camp Pendleton used VA health care between October 1, 1999 and February 17, 2021. Approximately 51% of Camp Lejeune females were exposed to toxicants. More than half (50.6% and 53.9% from Lejeune and Pendleton, respectively) had a disability rating ≥10%. Females who were Black, Hispanic, officers, or had longer duration in camp were more likely to have a disability rating, whereas females exposed to toxicants were less likely to have a disability rating. When the regression was redone examining the predictors of disability due to any of 8 presumptive conditions associated with toxicant exposure, the only significant variable was having been at Camp Lejeune (odds ratio [OR], 2.5, 95% CI, 1.3–4.7). Toxicant exposure was not significant when only Camp Lejeune females were included in the model. Conclusion Little attention has been given to female veterans exposed to toxicants at Camp Lejeune. Although we did not find an association between exposure and disability ratings, reliance on service-connected disability codes and small numbers were limitations. Further examination using international code of diseases diagnostic codes may be warranted. [ABSTRACT FROM AUTHOR]