Genetic risk of Parkinson’s disease in the general population

Darweesh, Sirwan K.L.; Verlinden, Vincentius J.A.; Adams, Hieab H.H.; Uitterlinden, André G.; Hofman, Albert; Stricker, Bruno H. Ch.; Duijn, Cornelia M. van; Koudstaal, Peter J.; Ikram, M. Arfan

doi:10.1016/j.parkreldis.2016.05.030

Cited by 13 publications

(12 citation statements)

References 37 publications

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“…Whilst individual risk estimates may not be particularly meaningful, this approach can be used to define a higher risk group for testing disease-modifying strategies 38 . The use of a PRS with and without other risk factors for PD has been previously validated in a large case-control setting 39 , but there are limited examples of application in a population setting such as we have done 40 . We anticipate that in a prospective setting in which there is information for the basic algorithm, data on smell, RBD and motor dysfunction, and polygenic risk, then performance may increase considerably.…”

Section: Discussionmentioning

confidence: 99%

Parkinson’s disease determinants, prediction and gene-environment interactions in the UK Biobank

Jacobs

Belete

Bestwick

et al. 2020

Preprint

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Section: Discussionmentioning

confidence: 99%

Parkinson’s disease determinants, prediction and gene-environment interactions in the UK Biobank

Jacobs

Belete

Bestwick

et al. 2020

Preprint

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“…Interestingly, using a different test we have already shown motor function to be a predictor of dementia onset over a 9 year period [ 248 ]. Moreover, we have also made several contributions towards understanding the etiology of Parkinson’s disease [ 249 – 251 ].…”

Section: Neurological Diseasesmentioning

confidence: 99%

The Rotterdam Study: 2018 update on objectives, design and main results

et al. 2017

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The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1500 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.

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“…While polygenic risk information appears to be unlikely to contribute significantly to the differentiation of PD from ET, there are a number of caveats and limitations of this study that may have limited our ability to detect a genetic signal. First, a relatively small proportion (<10%) of the heritability of PD has been explained by current GWAS findings ( Darweesh et al, 2016 ; Nalls et al, 2014 ; Pihlstrom et al, 2016 ), thus it is possible that more complete knowledge of common PD genetic risk factors could provide a predictive signature. Similarly, given the relatively small sample size of this study, a significant predictive genetic signal could have been detected in a larger study, though the discriminatory power of that signal would likely be weak.…”

Section: Discussionmentioning

confidence: 99%

“…Importantly, genetic risk is largely established at birth, and thus could potentially be an effective tool for predicting PD status at early disease stages when clinical signs are subtle. While only <10% of the heritability of PD has been explained by current genetic findings ( Darweesh et al, 2016 ; Nalls et al, 2014 ; Pihlstrom et al, 2016 ), and while the clinical utility of genetic testing for PD outside of early onset patient populations is limited ( Klein & Westenberger, 2012 ), genetic risk models have been shown to predict PD status from healthy controls, or correlate with aspects of PD severity or progression, with modest but statistically significant accuracy ( Hall et al, 2013 ). In addition, it is not known whether PD and ET share genetic risk factors that may interfere with genetic differentiation of the two conditions, nor how PD genetic factors interact with movement features to potentially improve discriminatory power.…”

Section: Introductionmentioning

confidence: 99%

Combined accelerometer and genetic analysis to differentiate essential tremor from Parkinson’s disease

Molparia

Schrader

Cohen

et al. 2018

PeerJ

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Essential tremor (ET) and Parkinson’s disease (PD) are among the most common adult-onset tremor disorders. Clinical and pathological studies suggest that misdiagnosis of PD for ET, and vice versa, occur in anywhere from 15% to 35% of cases. Complex diagnostic procedures, such as dopamine transporter imaging, can be powerful diagnostic aids but are lengthy and expensive procedures that are not widely available. Preliminary studies suggest that monitoring of tremor characteristics with consumer grade accelerometer devices could be a more accessible approach to the discrimination of PD from ET, but these studies have been performed in well-controlled clinical settings requiring multiple maneuvers and oversight from clinical or research staff, and thus may not be representative of at-home monitoring in the community setting. Therefore, we set out to determine whether discrimination of PD vs. ET diagnosis could be achieved by monitoring research subject movements at home using consumer grade devices, and whether discrimination could be improved with the addition of genetic profiling of the type that is readily available through direct-to-consumer genetic testing services. Forty subjects with PD and 27 patients with ET were genetically profiled and had their movements characterized three-times a day for two weeks through a simple procedure meant to induce rest tremors. We found that tremor characteristics could be used to predict diagnosis status (sensitivity = 76%, specificity = 65%, area under the curve (AUC) = 0.75), but that the addition of genetic risk information, via a PD polygenic risk score, did not improve discriminatory power (sensitivity = 80%, specificity = 65%, AUC = 0.73).

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Genetic risk of Parkinson’s disease in the general population

Cited by 13 publications

References 37 publications

Parkinson’s disease determinants, prediction and gene-environment interactions in the UK Biobank

Parkinson’s disease determinants, prediction and gene-environment interactions in the UK Biobank

The Rotterdam Study: 2018 update on objectives, design and main results

Combined accelerometer and genetic analysis to differentiate essential tremor from Parkinson’s disease

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