Parkinson's Disease Case Ascertainment in the EPIC Cohort: The NeuroEPIC4PD Study

A Delphi consensus to identify the key screening tests/questions for a digital neurological examination for epidemiological research

BACKGROUND

Most neurological diseases have no curative treatment; therefore, focusing on prevention is key. Continuous research to uncover the protective and risk factors associated with different neurological diseases is crucial to successfully inform prevention strategies. eHealth has been showing promising advantages in healthcare and public health and may therefore be relevant to facilitate epidemiological studies.

OBJECTIVE

In this study, we performed a Delphi consensus exercise to identify the key screening tests to inform the development of a digital neurological examination tool for epidemiological research.

METHODS

Twelve panellists (six experts in neurological examination, five experts in data collection-two were also experts in the neurological examination, and three experts in participant experience) of different nationalities joined the Delphi exercise. Experts in the neurological examination provided a selection of items that allow ruling out neurological impairment and can be performed by trained health workers. The items were then rated by them and other experts in terms of their feasibility and acceptability.

RESULTS

Ten tests and seven anamnestic questions were included in the final set of screening items for the digital neurological examination. Three tests and five anamnestic questions were excluded from the final selection due to their low ratings on feasibility.

CONCLUSION

This work identifies the key feasible and acceptable screening tests and anamnestic questions to build an electronic tool for performing the neurological examination, in the absence of a neurologist.

Association of Coffee Consumption and Prediagnostic Caffeine Metabolites With Incident Parkinson Disease in a Population-Based Cohort

BACKGROUND AND OBJECTIVES

Inverse associations between caffeine intake and Parkinson disease (PD) have been frequently implicated in human studies. However, no studies have quantified biomarkers of caffeine intake years before PD onset and investigated whether and which caffeine metabolites are related to PD.

METHODS

Associations between self-reported total coffee consumption and future PD risk were examined in the EPIC4PD study, a prospective population-based cohort including 6 European countries. Cases with PD were identified through medical records and reviewed by expert neurologists. Hazard ratios (HRs) and 95% CIs for coffee consumption and PD incidence were estimated using Cox proportional hazards models. A case-control study nested within the EPIC4PD was conducted, recruiting cases with incident PD and matching each case with a control by age, sex, study center, and fasting status at blood collection. Caffeine metabolites were quantified by high-resolution mass spectrometry in baseline collected plasma samples. Using conditional logistic regression models, odds ratios (ORs) and 95% CIs were estimated for caffeine metabolites and PD risk.

RESULTS

In the EPIC4PD cohort (comprising 184,024 individuals), the multivariable-adjusted HR comparing the highest coffee intake with nonconsumers was 0.63 (95% CI 0.46-0.88, p = 0.006). In the nested case-control study, which included 351 cases with incident PD and 351 matched controls, prediagnostic caffeine and its primary metabolites, paraxanthine and theophylline, were inversely associated with PD risk. The ORs were 0.80 (95% CI 0.67-0.95, p = 0.009), 0.82 (95% CI 0.69-0.96, p = 0.015), and 0.78 (95% CI 0.65-0.93, p = 0.005), respectively. Adjusting for smoking and alcohol consumption did not substantially change these results.

DISCUSSION

This study demonstrates that the neuroprotection of coffee on PD is attributed to caffeine and its metabolites by detailed quantification of plasma caffeine and its metabolites years before diagnosis.

Prediagnostic Blood Metal Levels and the Risk of Parkinson's Disease: A Large European Prospective Cohort

BACKGROUND

Metals have been postulated as environmental concerns in the etiology of Parkinson's disease (PD), but metal levels are typically measured after diagnosis, which might be subject to reverse causality.

OBJECTIVE

The aim of this study was to investigate the association between prediagnostic blood metal levels and PD risk.

METHODS

A case-control study was nested in a prospective European cohort, using erythrocyte samples collected before PD diagnosis.

RESULTS

Most assessed metals were not associated with PD risk. Cadmium has a suggestive negative association with PD (odds ratio [95% confidence interval] for the highest quartile, 0.70 [0.42-1.17]), which diminished among never smokers. Among current smokers only, lead was associated with decreased PD risk (0.06 [0.01-0.35]), whereas arsenic showed associations toward an increased PD risk (1.85 [0.45-7.93]).

CONCLUSIONS

We observe no strong evidence to support a role of metals in the development of PD. In particular, smoking may confound the association with tobacco-derived metals. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Lipopolysaccharide-binding protein and future Parkinson's disease risk: a European prospective cohort

INTRODUCTION

Lipopolysaccharide (LPS) is the outer membrane component of Gram-negative bacteria. LPS-binding protein (LBP) is an acute-phase reactant that mediates immune responses triggered by LPS and has been used as a blood marker for LPS. LBP has recently been indicated to be associated with Parkinson's disease (PD) in small-scale retrospective case-control studies. We aimed to investigate the association between LBP blood levels with PD risk in a nested case-control study within a large European prospective cohort.

METHODS

A total of 352 incident PD cases (55% males) were identified and one control per case was selected, matched by age at recruitment, sex and study center. LBP levels in plasma collected at recruitment, which was on average 7.8 years before diagnosis of the cases, were analyzed by enzyme linked immunosorbent assay. Odds ratios (ORs) were estimated for one unit increase of the natural log of LBP levels and PD incidence by conditional logistic regression.

RESULTS

Plasma LBP levels were higher in prospective PD cases compared to controls (median (interquartile range) 26.9 (18.1-41.0) vs. 24.7 (16.6-38.4) µg/ml). The OR for PD incidence per one unit increase of log LBP was elevated (1.46, 95% CI 0.98-2.19). This association was more pronounced among women (OR 2.68, 95% CI 1.40-5.13) and overweight/obese subjects (OR 1.54, 95% CI 1.09-2.18).

CONCLUSION

The findings suggest that higher plasma LBP levels may be associated with an increased risk of PD and may thus pinpoint to a potential role of endotoxemia in the pathogenesis of PD, particularly in women and overweight/obese individuals.

Parkinson's Disease Case Ascertainment in the Sister Study: A Cohort for Environmental Health Research

BACKGROUND

Large prospective studies are essential for investigating the environmental causes of Parkinson's disease (PD), but PD diagnosis via clinical exams is often infeasible in such studies.

OBJECTIVE

To present case ascertainment strategy and data collection in a US cohort of women.

METHODS

In the Sister Study (n = 50,884, baseline ages 55.6±9.0), physician-made PD diagnoses were first reported by participants or their proxies. Cohort-wide follow-up surveys collected data on subsequent diagnoses, medication usage and PD-relevant motor and nonmotor symptoms. We contacted self-reported PD cases and their treating physicians to obtain relevant diagnostic and treatment history. Diagnostic adjudication was made via expert review of all available data, except nonmotor symptoms. We examined associations of nonmotor symptoms with incident PD, using multivariable logistic regression models and reported odds ratio (OR) and 95% confidence intervals (CI).

RESULTS

Of the 371 potential PD cases identified, 242 diagnoses were confirmed. Compared with unconfirmed cases, confirmed cases were more likely to report PD diagnosis from multiple sources, medication usage, and motor and nonmotor features consistently during the follow-up. PD polygenic risk score was associated with confirmed PD (ORinter-quartile range = 1.74, 95% CI: 1.45-2.10), but not with unconfirmed cases (corresponding OR = 1.05). Hyposmia, dream-enacting behaviors, constipation, depression, unexplained weight loss, dry eyes, dry mouth, and fatigue were significantly related to PD risk, with ORs from 1.71 to 4.88. Only one of the eight negative control symptoms was associated with incident PD.

CONCLUSION

Findings support our PD case ascertainment approach in this large cohort of women. PD prodromal presentation is likely beyond its well-documented profile.

Comparison of risk factors for Parkinson’s disease, coronary events and ischemic stroke

Parkinson’s disease (PD) and cardiovascular disease share many important risk factors, but some associations differ. However, there are no studies that have compared their shared and specific risk factors. The present study aimed to compare risk factors for PD, coronary events, or ischemic stroke. We prospectively analyzed data from 26,210 participants with lifestyle factors aged 45–73 years enrolled between 1991 and 1996. The Cox proportional hazards model was used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) of PD, coronary events, or ischemic stroke in relation to each factor. A modified Lunn-McNeil competing risk analysis was performed to compare the HR strength of the three outcomes. A total of 486 incident PD cases, 3288 coronary events cases and 2,972 ischemic stroke cases occurred during a mean follow-up of 21 years. In multivariable models, age (per additional year: HR = 1.08; 95% CI: 1.06, 1.09), diabetes (HR = 1.52; 95% CI: 1.02, 2.26), neutrophil–lymphocyte ratio (per SD increase: HR = 1.09; 95% CI: 1.00, 1.19), and fasting blood glucose (per SD increase: HR = 1.18; 95% CI: 1.03, 1.36) are the risk factors for PD, whereas female sex (HR = 0.54; 95% CI: 0.43, 0.67), smoking (current smoker [HR = 0.57; 95% CI: 0.43, 0.74] and former smoker [HR = 0.81; 95% CI: 0.66, 0.99]), HDL (per SD increase: HR = 0.74; 95% CI: 0.57, 0.95), and LDL (per SD increase: HR = 0.77; 95% CI: 0.61, 0.96) are the protective factors. A comparison of risk factors for PD, coronary events, and ischemic stroke showed the three outcomes had concordant and discordant risk factors. Our results indicated the risk factor profiles for PD, coronary events, or ischemic stroke had many similarities, but also significant differences.

A Set of Reliable Samples for the Study of Biomarkers for the Early Diagnosis of Parkinson's Disease

Background

Parkinson's disease (PD) is a progressive neurodegenerative disorder, diagnosed according to the clinical criteria that occur in already advanced stages of PD. The definition of biomarkers for the early diagnosis of PD represents a challenge that might improve treatment and avoid complications in this disease. Therefore, we propose a set of reliable samples for the identification of altered metabolites to find potential prognostic biomarkers for early PD.

Methods

This case–control study included plasma samples of 12 patients with PD and 21 control subjects, from the Spanish European Prospective Investigation into Cancer and Nutrition (EPIC)-Navarra cohort, part of the EPIC-Spain study. All the case samples were provided by healthy volunteers who were followed-up for 15.9 (±4.1) years and developed PD disease later on, after the sample collection. Liquid chromatography coupled to tandem mass spectrometry was used for the analysis of samples.

Results

Out of 40 that were selected and studied due to their involvement in established cases of PD, seven significantly different metabolites between PD cases and healthy control subjects were obtained in this study (benzoic acid, palmitic acid, oleic acid, stearic acid, myo-inositol, sorbitol, and quinolinic acid). These metabolites are related to mitochondrial dysfunction, the oxidative stress, and the mechanisms of energy production.

Conclusion

We propose the samples from the EPIC study as reliable and invaluable samples for the search of early biomarkers of PD. Likewise, this study might also be a starting point in the establishment of a well-founded panel of metabolites that can be used for the early detection of this disease.

Parkinson's disease case ascertainment in a large prospective cohort

Background

In epidemiologic studies where physician-based case adjudication is not feasible, Parkinson’s disease (PD) case ascertainment is often limited to self-reports which may not be accurate. We evaluated strategies to identify PD cases in the Agricultural Health Study (AHS).

Methods

Doctor-diagnosed PD was self-reported on all cohort-wide surveys; potential cases were also identified from death certificates. Follow-up surveys asked about PD-related motor and non-motor symptoms. For PD confirmation, we collected additional diagnosis, symptom, and treatment data from 510 potential PD cases or their proxy (65% of those contacted) in a supplemental screener and obtained medical records for a subset (n = 65). We classified PD cases using established criteria and screener data.

Results

Of 510 potential PD cases, 75% were considered “probable” or “possible”; this proportion increased among participants diagnosed by a specialist (81.2%), taking PD medication (85.2%), or reporting ≥5 motor symptoms (86.8%) in a regular AHS survey. Of those with medical records, 93% (57 of 61) of probable or possible PD was confirmed. Never-smoking and non-motor and motor symptoms reported in prior AHS surveys were more common with probable/possible PD than unconfirmed PD.

Conclusion

In this retrospective PD case ascertainment effort, we found that PD self-report with information on motor symptoms or medications may be a reasonable alternative for identifying PD cases when physician exam is not feasible. Because of intervening mortality, screeners could not be obtained from about one-third of those contacted. Thus, findings warrant replication.

Parkinson's disease case ascertainment in prospective cohort studies through combining multiple health information resources

Epidemiological evidence from prospective cohort studies on risk factors of Parkinson's disease (PD) is limited as case ascertainment is challenging due to a lack of registries and the disease course of PD. The objective of this study was to create a case ascertainment method for PD within two prospective Dutch cohorts based on multiple sources of PD information. This method was validated using clinical records from the general practitioners (GPs). Face validity of the case ascertainment was tested for three etiological factors (smoking, sex and family history of PD). In total 54825 participants were included from the cohorts AMIGO and EPIC-NL. Sources of PD information included self-reported PD, self-reported PD medication, a 9 item screening questionnaire (Tanner), electronical medical records, hospital discharge data and mortality records. Based on these sources we developed a likelihood score with 4 categories (no PD, unlikely PD, possible PD, likely PD). For the different sources of PD information and for the likelihood score we present the agreement with GP-validated cases. Risk of PD for established factors was studied by logistic regression as exact diagnose dates were not always available. Based on the algorithm, we assigned 346 participants to the likely PD category. GP validation confirmed 67% of these participants in EPIC-NL, but only 12% in AMIGO. PD was confirmed in only 3% of the participants with a possible PD classification. PD case ascertainment by mortality records (91%), EMR ICPC (82%) and self-reported information (62-69%) had the highest confirmation rates. The Tanner PD screening questionnaire had a lower agreement (18%). Risk estimates for smoking, family history and sex using all likely PD cases were comparable to the literature for EPIC-NL, but not for smoking in AMIGO. Using multiple sources of PD evidence in cohorts remains important but challenging as performance of sources varied in validity.

Alcohol Consumption and Risk of Parkinson's Disease: Data From a Large Prospective European Cohort

BACKGROUND

Parkinson's disease (PD) etiology is not well understood. Reported inverse associations with smoking and coffee consumption prompted the investigation of alcohol consumption as a risk factor, for which evidence is inconclusive.

OBJECTIVE

To assess the associations between alcohol consumption and PD risk.

METHODS

Within NeuroEPIC4PD, a prospective European population-based cohort, 694 incident PD cases were ascertained from 209,998 PD-free participants. Average alcohol consumption at different time points was self-reported at recruitment. Cox regression hazard ratios were estimated for alcohol consumption and PD occurrence.

RESULTS

No associations between baseline or lifetime total alcohol consumption and PD risk were observed. Men with moderate lifetime consumption (5-29.9 g/day) were at ~50% higher risk compared with light consumption (0.1-4.9 g/day), but no linear exposure-response trend was observed. Analyses by beverage type also revealed no associations with PD.

CONCLUSION

Our data reinforce previous findings from prospective studies showing no association between alcohol consumption and PD risk. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Exploring causality of the association between smoking and Parkinson's disease

BACKGROUND

The aim of this paper is to investigate the causality of the inverse association between cigarette smoking and Parkinson's disease (PD). The main suggested alternatives include a delaying effect of smoking, reverse causality or an unmeasured confounding related to a low-risk-taking personality trait.

METHODS

A total of 715 incident PD cases were ascertained in a cohort of 220 494 individuals from NeuroEPIC4PD, a prospective European population-based cohort study including 13 centres in eight countries. Smoking habits were recorded at recruitment. We analysed smoking status, duration, and intensity and exposure to passive smoking in relation to PD onset.

RESULTS

Former smokers had a 20% decreased risk and current smokers a halved risk of developing PD compared with never smokers. Strong dose-response relationships with smoking intensity and duration were found. Hazard ratios (HRs) for smoking <20 years were 0.84 [95% confidence interval (CI) 0.67-1.07], 20-29 years 0.73 (95% CI 0.56-0.96) and >30 years 0.54 (95% CI 0.43-0.36) compared with never smokers. The proportional hazard assumption was verified, showing no change of risk over time, arguing against a delaying effect. Reverse causality was disproved by the consistency of dose-response relationships among former and current smokers. The inverse association between passive smoking and PD, HR 0.70 (95% CI 0.49-0.99) ruled out the effect of unmeasured confounding.

CONCLUSIONS

These results are highly suggestive of a true causal link between smoking and PD, although it is not clear which is the chemical compound in cigarette smoking responsible for the biological effect.

General and abdominal adiposity and the risk of Parkinson's disease: A prospective cohort study

INTRODUCTION

Due to demographic change, an increase in the frequency of Parkinson's disease (PD) patients is expected in the future and, thus, the identification of modifiable risk factors is urgently needed. We aimed to examine the associations of body mass index (BMI) and waist circumference (WC) with incident PD.

METHODS

In 13 of the 23 centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) study, a total of 734 incident cases of PD were identified between 1992 and 2012 with a mean follow-up of 12 years. Cox proportional hazards regression was used to calculate hazard ratios (HR) with 95% confidence intervals (CI). We modelled anthropometric variables as continuous and categorical exposures and performed subgroup analyses by potential effect modifiers including sex and smoking.

RESULTS

We found no association between BMI, WC and incident PD, neither among men nor among women. Among never and former smokers, BMI and waist circumference were also not associated with PD risk. For male smokers, however, we observed a statistically significant inverse association between BMI and PD risk (HR 0.51, 95%CI: 0.30, 0.84) and the opposite for women, i.e. a significant direct association of BMI (HR 1.79, 95%CI: 1.04, 3.08) and waist circumference (HR 1.64, 95%CI: 1.03, 2.61) with risk of PD.

CONCLUSION

Our data revealed no association between excess weight and PD risk but a possible interaction between anthropometry, sex and smoking.

Identifying Parkinson's disease and parkinsonism cases using routinely collected healthcare data: A systematic review

Background

Population-based, prospective studies can provide important insights into Parkinson’s disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose.

Methods

We searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity.

Results

We identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56–90% in hospital datasets, 53–87% in prescription datasets, 81–90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36–88% in hospital datasets, 40–74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15–73% in single datasets for PD and 43–63% in single datasets for parkinsonism.

Conclusions

In many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity.