Protective Effects of Lovastatin in a Population-Based ALS Study and Mouse Model.

OBJECTIVE: The objective of this study was to use a novel combined pharmacoepidemiologic and amyotrophic lateral sclerosis (ALS) mouse model approach to identify potential motor neuron protective medications. METHODS: We constructed a large, population-based case-control study to investigate motor neuron disease (MND) among US Medicare beneficiaries aged 66 to 90 in 2009. We included 1,128 incident MND cases and 56,400 age, sex, race, and ethnicity matched controls. We calculated MND relative risk for >1,000 active ingredients represented in Part D (pharmacy) claims in 2006 to 2007 (>1 year before diagnosis/reference). We then applied a comprehensive screening approach to select medications for testing in SOD1G93A mice: sulfasalazine, telmisartan, and lovastatin. We treated mice with the human dose equivalent of the medication or vehicle via subcutaneous osmotic pump before onset of weakness. We then assessed weight, gait, and survival. In additional mice, we conducted histological studies. RESULTS: We observed previously established medical associations for MND and an inverse dose-response association between lovastatin and MND, with 28% reduced risk at 40 mg/day. In SOD1G93A mouse studies, sulfasalazine and telmisartan conferred no benefit, whereas lovastatin treatment delayed onset and prolonged survival. Lovastatin treated mice also had less microgliosis, misfolded SOD1, and spinal motor neuron loss in the ventral horn. INTERPRETATION: Lovastatin reduced the risk of ALS in humans, which was confirmed in an ALS mouse model by delayed symptom onset, prolonged survival, and preservation of motor neurons. Although further studies to understand the mechanism are required, lovastatin may represent a potential neuroprotective therapy for patients with ALS. These data demonstrate the utility of a combined pharmacoepidemiologic and mouse model approach. ANN NEUROL 2023;93:881-892.

Incidence of amyotrophic lateral sclerosis in older adults.

INTRODUCTION/AIMS: We investigated the age- and sex-specific incidence and survival of Medicare beneficiaries with amyotrophic lateral sclerosis (ALS) in patients 66 to 90 years of age. METHODS: We identified all incident ALS cases within a population-based sample of Medicare beneficiaries in 2009 (total: 22 000 177 person-years at risk for ALS). We calculated age- and sex-specific incidence in 2009 according to multiple, progressively more stringent case definitions. Our most inclusive definition required one ALS code, whereas the most restrictive definition required at least one additional ALS code more than 6 months after the first code, including one from a neurologist. We identified associated imaging studies and electrodiagnostic testing and followed all cases through the end of 2014 to determine survival. RESULTS: The overall incidence for our most inclusive definition was 22.84 per 100 000 person-years for men and 16.05 per 100 000 person-years for women. The overall incidence was 5.72 per 100 000 person-years for men and 3.99 per 100 000 person-years for women for our most restrictive definition. For our most inclusive definition, fewer than 39.7% of cases ever had an ALS diagnosis from a neurologist, more than 50% had an electrodiagnostic test or imaging study, and 40.1% survived less than 1 year after diagnosis, with 25.5% of these cases surviving no more than 6 months. Cases not meeting the most restrictive definition were more likely than those who did meet the restrictive definition to be older, black, or Asian. DISCUSSION: The oldest and marginalized Medicare beneficiaries diagnosed with ALS are less likely to be included in epidemiological studies with restrictive definitions, but future studies will need to assess the accuracy of diagnosis.

A genome-wide association study on medulloblastoma.

INTRODUCTION: Medulloblastoma is a malignant embryonal tumor of the cerebellum that occurs predominantly in children. To find germline genetic variants associated with medulloblastoma risk, we conducted a genome-wide association study (GWAS) including 244 medulloblastoma cases and 247 control subjects from Sweden and Denmark. METHODS: Genotyping was performed using Illumina BeadChips, and untyped variants were imputed using IMPUTE2. RESULTS: Fifty-nine variants in 11 loci were associated with increased medulloblastoma risk (p < 1 × 10-5), but none were statistically significant after adjusting for multiple testing (p < 5 × 10-8). Thirteen of these variants were genotyped, whereas 46 were imputed. Genotyped variants were further investigated in a validation study comprising 249 medulloblastoma cases and 629 control subjects. In the validation study, rs78021424 (18p11.23, PTPRM) was associated with medulloblastoma risk with OR in the same direction as in the discovery cohort (ORT = 1.59, pvalidation = 0.02). We also selected seven medulloblastoma predisposition genes for investigation using a candidate gene approach: APC, BRCA2, PALB2, PTCH1, SUFU, TP53, and GPR161. The strongest evidence for association was found for rs201458864 (PALB2, ORT = 3.76, p = 3.2 × 10-4) and rs79036813 (PTCH1, ORA = 0.42, p = 2.6 × 10-3). CONCLUSION: The results of this study, including a novel potential medulloblastoma risk loci at 18p11.23, are suggestive but need further validation in independent cohorts.

Herpesvirus Infections and Risk of Parkinson's Disease.

INTRODUCTION: Herpesviruses might play a role in the pathogenesis of neurodegenerative disorders. We sought to examine a possible association between alpha herpesvirus infections and Parkinson's disease. METHODS: We conducted a population-based case-control study of incident Parkinson's disease in 2009 Medicare beneficiaries age 66-90 years (89,790 cases, 118,095 randomly selected comparable controls). We classified beneficiaries with any diagnosis code for "herpes simplex" and/or "herpes zoster" in the previous 5 years as having had the respective alpha herpesviruses. In beneficiaries with Part D prescription coverage, we also identified those prescribed anti-herpetic medications. We calculated odds ratios (OR) and 95% CI between alpha herpesvirus diagnosis/treatment and Parkinson's disease with logistic regression, with adjustment for age, sex, race/ethnicity, smoking, and use of medical care. RESULTS: Parkinson's disease risk was inversely associated with herpes simplex (OR 0.79, 95% CI 0.74-0.84), herpes zoster (OR 0.88, 95% CI 0.85-0.91), and anti-herpetic medications (OR 0.87, 95% CI 0.80-0.96). CONCLUSION: Herpesvirus infection or treatment might reduce risk of Parkinson's disease, but future studies will be required to explore whether this inverse association is causal.

ß2-adrenoreceptor medications and risk of Parkinson disease.

OBJECTIVE: A recent study observed a 2-fold greater risk of Parkinson disease (PD) in relation to the ß2-adrenoreceptor antagonist propranolol and a markedly lower risk of PD for the ß2-adrenoreceptor agonist salbutamol. We examined whether confounding by clinical indication for these medications, that is, tremor and smoking-related pulmonary conditions, explained these associations. METHODS: In a large, population-based case-control study of United States Medicare beneficiaries in 2009 with diagnosis codes, procedure codes, and prescription data (48,295 incident PD cases, 52,324 controls), we examined the risk of PD in relation to use of selected ß antagonists (propranolol, carvedilol, metoprolol), the ß2 agonist salbutamol, and other medications used for the same clinical indications (primidone, inhaled corticosteroids). We adjusted for demographics, smoking, and overall use of medical care. We then examined the effect of also adjusting for clinical indication and applying medication exposure lagging. RESULTS: Propranolol appeared to increase PD risk (odds ratio [OR] = 3.62, 95% confidence interval [CI] = 3.31-3.96). When we adjusted for tremor or abnormal involuntary movement prior to the PD diagnosis/reference date and lagged propranolol exposure, the association was 0.97 (95% CI = 0.80-1.18). Primidone, also used for tremor, was similarly sensitive to this adjustment and lagging. ß Antagonists not indicated for tremor appeared to reduce PD risk (carvedilol: OR = 0.77, 95% CI = 0.73-0.81; metoprolol: OR = 0.94, 95% CI = 0.91-0.97) and were insensitive to adjustment for indications and lagging. Neither salbutamol nor inhaled corticosteroids were consistently associated with PD risk. INTERPRETATION: ß2-adrenoreceptor agonists and antagonists do not appear to alter PD risk. Ann Neurol 2018;84:691-701.

Traumatic brain injury in the prodromal period of Parkinson's disease: A large epidemiological study using medicare data.

OBJECTIVE: Studies suggest a greater risk of Parkinson's disease (PD) after traumatic brain injury (TBI), but it is possible that the risk of TBI is greater in the prodromal period of PD. We aimed to examine the time-to-TBI in PD patients in their prodromal period compared to population-based controls. METHODS: We identified 89,790 incident PD cases and 118,095 comparable controls aged > 65 years in 2009 using Medicare claims data. Using data from the preceding 5 years, we compared time-to-TBI in PD patients in their prodromal period to controls. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for TBI in a Cox regression, while adjusting for age, sex, race/ethnicity, modified Charlson comorbidity index, smoking, and alcohol use. RESULTS: Risk of TBI was greater in PD patients in their prodromal period across all age and sex groups, with HRs consistently increasing with proximity to PD diagnosis. HRs ranged from 1.64 (95% CI, 1.52, 1.77) 5 years preceding diagnosis to 3.93 (95% CI, 3.74, 4.13) in the year before. The interaction between PD, TBI, and time was primarily observed for TBI attributed to falls. Motor dysfunction and cognitive impairment, suggested by corresponding International Classification of Diseases, Ninth Revision codes, partially mediated the PD-TBI association. INTERPRETATION: There is a strong association between PD and a recent TBI in the prodromal period of PD. This association strengthens as PD diagnosis approaches and may be a result of undetected nonmotor and motor symptoms, but confirmation will be required. Ann Neurol 2017;82:744-754.

Blood α-synuclein in agricultural pesticide handlers in central Washington State.

Epidemiologic studies suggest that occupational exposure to pesticides might increase Parkinson disease risk. Some pesticides, such as the organophosphorus insecticide chlorpyrifos, appear to increase the expression of α-synuclein, a protein critically involved in Parkinson disease. Therefore, we assessed total blood cell α-synuclein in 90 specimens from 63 agricultural pesticide handlers, mainly Hispanic men from central Washington State, who participated in the state's cholinesterase monitoring program in 2007-2010. Additionally, in age-adjusted linear regression models for repeated measures, we assessed whether α-synuclein levels were associated with butyrylcholinesterase-chlorpyrifos adducts or cholinesterase inhibition measured in peripheral blood, or with self-reported pesticide exposure or paraoxonase (PON1) genotype. There was no evidence by any of those indicators that exposure to chlorpyrifos was associated with greater blood α-synuclein. We observed somewhat greater α-synuclein with the PON1-108T (lower paraoxonase enzyme) allele, and with ≥ 10 h of exposure to cholinesterase inhibiting insecticides in the preceding 30 days, but neither of these associations followed a clear dose-response pattern. These results suggest that selected genetic and environmental factors may affect α-synuclein blood levels. However, longitudinal studies with larger numbers of pesticide handlers will be required to confirm and elucidate the possible associations observed in this exploratory cross-sectional study.

Enhancing case ascertainment of Parkinson's disease using Medicare claims data in a population-based cohort: the Cardiovascular Health Study.

PURPOSE: We sought to improve a previous algorithm to ascertain Parkinson's disease (PD) in the Cardiovascular Health Study by incorporating additional data from Medicare outpatient claims. We compared our results to the previous algorithm in terms of baseline prevalence and incidence of PD, as well as associations with baseline smoking characteristics. METHODS: Our original case ascertainment used self-reported diagnosis, antiparkinsonian medication, and hospitalization discharge International Classification of Diseases-Ninth version code. In this study, we incorporated additional data from fee-for-service Medicare claims, extended follow-up time, review of hospitalization records, and adjudicated cause of death. Two movement disorders specialists adjudicated final PD status. We used logistic regression models and controlled for age, sex, African American race, and education. RESULTS: We identified 75 additional cases but reclassified 80 previously identified cases as not having PD. We observed significant inverse association with smoking status (odds ratio = 0.42; 95% confidence interval (CI) = 0.22, 0.79), and inverse linear trends with pack-years (p = 0.005), and cigarettes per day (p = 0.019) with incident PD. All estimates were stronger than those from the previous algorithm. CONCLUSIONS: Our enhanced method did not alter prevalence and incidence estimates compared with our previous algorithm. However, our enhanced method provided stronger estimates of association, potentially due to reduced level of disease misclassification.

Fine Particulate Matter and Parkinson Disease Risk Among Medicare Beneficiaries.

BACKGROUND AND OBJECTIVES: Numerous studies suggest that environmental exposures play a critical role in Parkinson disease (PD) pathogenesis, and large, population-based studies have the potential to advance substantially the identification of novel PD risk factors. We sought to study the nationwide geographic relationship between PD and air pollution, specifically PM2.5 (particulate matter with a diameter <2.5 micrometers), using population-based US Medicare data. METHODS: We conducted a population-based geographic study of Medicare beneficiaries aged 66-90 years geocoded to US counties and zip+4. We used integrated nested Laplace approximation to create age, sex, race, smoking, and health care utilization-adjusted relative risk (RR) at the county level for geographic analyses with PM2.5 as the primary exposure of interest. We also performed an individual-level analysis using logistic regression with cases and controls with zip+4 centroid PM2.5. We adjusted a priori for the same covariates and verified no confounding by indicators of socioeconomic status or neurologist density. RESULTS: Among 21,639,190 Medicare beneficiaries, 89,390 had incident PD in 2009. There was a nationwide association between average annual PM2.5 and PD risk whereby the RR of PD was 56% (95% CI 47%-66%) greater for those exposed to the median level of PM2.5 compared with those with the lowest level of PM2.5. This association was linear up to 13 µg/m3 corresponding to a 4.2% (95% CI 3.7%-4.8%) greater risk of PD for each additional µg/m3 of PM2.5 (p trend < 0.0001). We identified a region with high PD risk in the Mississippi-Ohio River Valley, where the risk of PD was 19% greater compared with the rest of the nation. The strongest association between PM2.5 and PD was found in a region with low PD risk in the Rocky Mountains. PM2.5 was also associated with PD in the Mississippi-Ohio River Valley where the association was relatively weaker, due to a possible ceiling effect at average annual PM2.5 levels of ∼13 µg/m3. DISCUSSION: State-of-the-art geographic analytic techniques revealed an association between PM2.5 and PD that varied in strength by region. A deeper investigation into the specific subfractions of PM2.5 may provide additional insight into regional variability in the PM2.5-PD association.

Biologic targets of prescription medications and risk of neurodegenerative disease in United States Medicare beneficiaries.

OBJECTIVE: To identify prescription medications associated with a lower risk of three neurodegenerative diseases: Parkinson disease, Alzheimer disease, and amyotrophic lateral sclerosis. METHODS: We conducted a population-based, case-control study of U.S. Medicare beneficiaries in 2009 (42,885 incident neurodegenerative disease cases, 334,387 randomly selected controls). Using medication data from 2006-2007, we categorized all filled medications according to their biological targets and mechanisms of action on those targets. We used multinomial logistic regression models, while accounting for demographics, indicators of smoking, and health care utilization, to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for 141 target-action pairs and each neurodegenerative disease. For target-action pairs inversely associated with all three diseases, we attempted replication in a cohort study that included an active comparator group. We constructed the cohort by following controls forward for incident neurodegenerative disease from the beginning of 2010 until death or end of 2014, i.e., up to five years after the two-year exposure lag. We used Cox proportional hazards regression while accounting for the same covariates. RESULTS: The most consistent inverse association across both studies and all three neurodegenerative diseases was for xanthine dehydrogenase/oxidase blockers, represented by the gout medication, allopurinol. Allopurinol was associated with a 13-34% lower risk for each neurodegenerative disease group in multinomial regression, and a mean reduction of 23% overall, as compared to individuals who did not use allopurinol. In the replication cohort we observed a significant 23% reduction for neurodegenerative disease in the fifth year of follow-up, when comparing allopurinol users to non-users, and more marked associations with an active comparator group. We observed parallel associations for a related target-action pair unique to carvedilol. DISCUSSION/CONCLUSION: Xanthine dehydrogenase/oxidase blockade might reduce risk of neurodegenerative disease. However, further research will be necessary to confirm that the associations related to this pathway are causal or to examine whether this mechanism slows progression.

A predictive algorithm to identify ever smoking in medical claims-based epidemiologic studies.

PURPOSE: To develop and validate an algorithm to estimate probability of ever smoking using administrative claims. METHODS: Using population-based samples of Medicare-aged individuals (121,278 Behavioral Risk Factor Surveillance System survey respondents and 207,885 Medicare beneficiaries), we developed a logistic regression model to predict probability of ever smoking from demographic and claims data. We applied the model in 1,657,266 additional Medicare beneficiaries and calculated area under the receiver operating characteristic curve (AUC) using presence or absence of a tobacco-specific diagnosis or procedure code as our "gold standard." We used these "gold standard" and lung/laryngeal cancer codes to over-ride predicted probability as 100%. We calculated Spearman's rho between probability from this full algorithm and smoking assessed in prior Parkinson disease studies, by substituting our observed and prior ("true") smoking-Parkinson disease odds ratios into the attenuation equation. RESULTS: The predictive model contained 23 variables, including basic demographics, high alcohol consumption, asthma, cardiovascular disease and associated risk factors, selected cancers, and indicators of routine medical usage. The AUC was 67.6% (95% confidence interval 67.5%-67.7%) comparing smoking probability to tobacco-specific diagnosis or procedure codes. Spearman's rho for the full algorithm was 0.82. CONCLUSIONS: Ever smoking might be approximated in administrative data for use as a continuous, probabilistic variable in epidemiologic analyses.

Environmental tobacco smoke and Parkinson's disease.

BACKGROUND: Parkinson's disease is inversely associated with cigarette smoking, but its relation with passive smoking or environmental tobacco smoke exposure is rarely examined. METHODS: Within a case-control study, we assessed the association between Parkinson's disease and living or working with active smokers. Cases were newly diagnosed with idiopathic Parkinson's disease (n = 154) from western Washington State in 2002-2008. Age- and sex-matched controls (n = 173) were neurologically normal and unrelated to cases. RESULTS: Compared with never active or passive tobacco smokers, we observed reduced Parkinson's disease risks for ever passive only smokers (OR, 0.34; 95% CI, 0.16-0.73), similar to those for ever active smokers (OR, 0.35; 95% CI, 0.17-0.73). Among persons whose only tobacco smoke exposure was passive smoking at home, risk was inversely associated with years exposed. CONCLUSIONS: These observations parallel those well established for active smoking. However, it remains unresolved whether a true protective effect of tobacco smoke, generally detrimental to health, underlies these associations.

Environmental manganese exposure and cognitive control in a South African population.

OBJECTIVE: To characterize the association between environmental (residential air) manganese (Mn) exposure and cognitive performance, focusing on cognitive control, in a Black African population. METHODS: We administered the Go-No-Go, Digit Span, and Matrix Reasoning tests to population-based samples age ≥40 from a high Mn (smelter) exposed community, Meyerton (N = 629), and a demographically comparable low (background levels) non-exposed community, Ethembalethu, (N = 96) in Gauteng province, South Africa. We investigated the associations between community and performance on the cognitive tests, using linear regression. We adjusted a priori for age and sex, and examined the effect of adjustment for education, nonverbal IQ, smoking, and alcohol consumption. We measured airborne PM2.5-Mn to confirm community exposure differences. RESULTS: Compared to Ethembalethu residents, Meyerton residents' test scores were lower (poorer) for all tests: 0.55 (95 % confidence interval [CI] 0.08, 1.03) lower scores for Matrix Reasoning, 0.34 (95 % CI -0.07, 0.75) lower for Digit Span, and 0.15 (95 % CI 0.09, 0.21) lower for Go-No-Go (high frequency discriminability index [probability]). The latter represented the most marked difference in terms of z-scores (0.50, 95 % CI 0.30, 0.71 standard deviations lower). The mean of the z-score of each of the three tests was also lower (0.34, 95 % CI 0.18, 0.50 standard deviations lower). These associations were similar in men and women, but attenuated with adjustment for education. Differences for Matrix Reasoning and Digit Span between the two communities were observed only among those who had lived in Meyerton ≥10 years, whereas for Go-No-Go, differences were also apparent among those who had lived in Meyerton <10 years. Mean PM2.5-Mn at a long-term fixed site in Meyerton was 203 ng/m3 and 10 ng/m3 in Ethembalethu. CONCLUSION: Residence in a community near a high Mn emission source is associated with cognitive dysfunction, including aspects of cognitive control as assessed by the Go-No-Go test.

A comparison of prediction approaches for identifying prodromal Parkinson disease.

Identifying people with Parkinson disease during the prodromal period, including via algorithms in administrative claims data, is an important research and clinical priority. We sought to improve upon an existing penalized logistic regression model, based on diagnosis and procedure codes, by adding prescription medication data or using machine learning. Using Medicare Part D beneficiaries age 66-90 from a population-based case-control study of incident Parkinson disease, we fit a penalized logistic regression both with and without Part D data. We also built a predictive algorithm using a random forest classifier for comparison. In a combined approach, we introduced the probability of Parkinson disease from the random forest, as a predictor in the penalized regression model. We calculated the receiver operator characteristic area under the curve (AUC) for each model. All models performed well, with AUCs ranging from 0.824 (simplest model) to 0.835 (combined approach). We conclude that medication data and random forests improve Parkinson disease prediction, but are not essential.

Depression and anxiety in a manganese-exposed community.

OBJECTIVE: To characterize the association between residential environmental manganese (Mn) exposure and depression and anxiety, given prior associations among occupationally-exposed workers. METHODS: We administered the Beck Depression Inventory (BDI) and the State-Trait Anxiety Inventory (STAI) to 697 study participants in their preferred languages. These participants represented a population-based sample of residents aged ≥40 from two predominantly Black African communities in Gauteng province, South Africa: 605 in Meyerton, adjacent to a large Mn smelter, and 92 in Ethembalethu, a comparable non-exposed community. We investigated the associations between community (Meyerton vs. Ethembalethu) and severity of depression and anxiety, using linear regression, adjusting for age and sex. To document community-level differences in Mn exposure, we measured airborne PM2.5-Mn. RESULTS: Meyerton residents had BDI scores 5.63 points (95 % CI 3.07, 8.20) higher than Ethembalethu residents, with all questions contributing to this significant difference. STAI-state scores were marginally higher in Meyerton than Ethembalethu residents [2.12 (95 % CI -0.17, 4.41)], whereas STAI-trait scores were more similar between the communities [1.26 (95 % CI -0.82, 3.35)]. Mean PM2.5-Mn concentration was 203 ng/m3 at a long-term fixed site in Meyerton and 10 ng/m3 in Ethembalethu. CONCLUSION: Residence near Mn emission sources may be associated with greater depression symptomatology, and possibly current, but not lifetime, anxiety.

Principal Component Analysis of Striatal and Extrastriatal D2 Dopamine Receptor Positron Emission Tomography in Manganese-Exposed Workers.

The relationships between the neurotoxicant manganese (Mn), dopaminergic pathology, and parkinsonism remain unclear. Therefore, we used [11C](N-methyl)benperidol (NMB) positron emission tomography to investigate the associations between Mn exposure, striatal and extrastriatal D2 dopamine receptors (D2R), and motor function in 54 workers with a range of Mn exposure. Cumulative Mn exposure was estimated from work histories, and all workers were examined by a movement specialist and completed a Grooved Pegboard test (GPT). NMB D2R nondisplaceable binding potentials (BPND) were calculated for brain regions of interest. We identified 2 principal components (PCs) in a PC analysis which explained 66.8% of the regional NMB BPND variance (PC1 = 55.4%; PC2 = 11.4%). PC1 was positively correlated with NMB binding in all regions and inversely correlated with age. PC2 was driven by NMB binding in 7 brain regions (all p < .05), positively in the substantia nigra, thalamus, amygdala, and medial orbital frontal gyrus and negatively in the nucleus accumbens, anterior putamen, and caudate. PC2 was associated with both Mn exposure status and exposure duration (years). In addition, PC2 was associated with higher Unified Parkinson's Disease Rating Scale motor subsection 3 (UPDRS3) scores and slower GPT performance. We conclude Mn exposure is associated with both striatal and extrastriatal D2R binding. Multifocal alterations in D2R expression are also associated with motor dysfunction as measured by both the GPT and UPDRS3, demonstrating a link between Mn exposure, striatal and extrastriatal D2R expression, and clinical neurotoxicity.

Water quality monitoring records for estimating tap water arsenic and nitrate: a validation study.

BACKGROUND: Tap water may be an important source of exposure to arsenic and nitrate. Obtaining and analyzing samples in the context of large studies of health effects can be expensive. As an alternative, studies might estimate contaminant levels in individual homes by using publicly available water quality monitoring records, either alone or in combination with geographic information systems (GIS). METHODS: We examined the validity of records-based methods in Washington State, where arsenic and nitrate contamination is prevalent but generally observed at modest levels. Laboratory analysis of samples from 107 homes (median 0.6 microg/L arsenic, median 0.4 mg/L nitrate as nitrogen) served as our "gold standard." Using Spearman's rho we compared these measures to estimates obtained using only the homes' street addresses and recent and/or historical measures from publicly monitored water sources within specified distances (radii) ranging from one half mile to 10 miles. RESULTS: Agreement improved as distance decreased, but the proportion of homes for which we could estimate summary measures also decreased. When including all homes, agreement was 0.05-0.24 for arsenic (8 miles), and 0.31-0.33 for nitrate (6 miles). Focusing on the closest source yielded little improvement. Agreement was greatest among homes with private wells. For homes on a water system, agreement improved considerably if we included only sources serving the relevant system (rho = 0.29 for arsenic, rho = 0.60 for nitrate). CONCLUSIONS: Historical water quality databases show some promise for categorizing epidemiologic study participants in terms of relative tap water nitrate levels. Nonetheless, such records-based methods must be used with caution, and their use for arsenic may be limited.

Validation of a Parkinson Disease Predictive Model in a Population-Based Study.

Parkinson disease (PD) has a relatively long prodromal period that may permit early identification to reduce diagnostic testing for other conditions when patients are simply presenting with early PD symptoms, as well as to reduce morbidity from fall-related trauma. Earlier identification also could prove critical to the development of neuroprotective therapies. We previously developed a PD predictive model using demographic and Medicare claims data in a population-based case-control study. The area under the receiver-operating characteristic curve (AUC) indicated good performance. We sought to further validate this PD predictive model. In a randomly selected, population-based cohort of 115,492 Medicare beneficiaries aged 66-90 and without PD in 2009, we applied the predictive model to claims data from the prior five years to estimate the probability of future PD diagnosis. During five years of follow-up, we used 2010-2014 Medicare data to determine PD and vital status and then Cox regression to investigate whether PD probability at baseline was associated with time to PD diagnosis. Within a nested case-control sample, we calculated the AUC, sensitivity, and specificity. A total of 2,326 beneficiaries developed PD. Probability of PD was associated with time to PD diagnosis (p < 0.001, hazard ratio = 13.5, 95% confidence interval (CI) 10.6-17.3 for the highest vs. lowest decile of probability). The AUC was 83.3% (95% CI 82.5%-84.1%). At the cut point that balanced sensitivity and specificity, sensitivity was 76.7% and specificity was 76.2%. In an independent sample of additional Medicare beneficiaries, we again applied the model and observed good performance (AUC = 82.2%, 95% CI 81.1%-83.3%). Administrative claims data can facilitate PD identification within Medicare and Medicare-aged samples.