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Self-report data as a tool for subtype identification in genetically-defined Parkinson’s Disease

Through a targeted recruitment 23andMe has collected DNA and patient-reported symptoms from more than 10,000 subjects reporting a physician-verified diagnosis of PD. This study evaluated the potential of self-report, web-based questionnaires to rapidly assess disease natural history and symptomology...

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Autores principales: Winslow, Ashley R., Hyde, Craig L., Wilk, Jemma B., Eriksson, Nicholas, Cannon, Paul, Miller, Melissa R., Hirst, Warren D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6113219/
https://www.ncbi.nlm.nih.gov/pubmed/30154511
http://dx.doi.org/10.1038/s41598-018-30843-6
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author Winslow, Ashley R.
Hyde, Craig L.
Wilk, Jemma B.
Eriksson, Nicholas
Cannon, Paul
Miller, Melissa R.
Hirst, Warren D.
author_facet Winslow, Ashley R.
Hyde, Craig L.
Wilk, Jemma B.
Eriksson, Nicholas
Cannon, Paul
Miller, Melissa R.
Hirst, Warren D.
author_sort Winslow, Ashley R.
collection PubMed
description Through a targeted recruitment 23andMe has collected DNA and patient-reported symptoms from more than 10,000 subjects reporting a physician-verified diagnosis of PD. This study evaluated the potential of self-report, web-based questionnaires to rapidly assess disease natural history and symptomology in genetically-defined PD populations. While average age-at-diagnosis was significantly lower in GBA mutation carriers compared to idiopathic PD, or iPD (idiopathic PD, defined as no GBA mutations and no LRRK2 G2019S mutation), there were no significant differences in symptoms. Conversely, LRRK2 G2019S carrier status significantly associated with reporting of milder daily symptoms of lightheadedness and several differences were observed at a false discovery rate < 0.1, including increased reporting of changes in walking as an initial symptom of disease, decreased reporting of lightheadedness upon standing, and milder symptoms related to daily functioning. The subclinical differences in symptoms reported by LRRK2 G2019S carriers suggest differences in underlying pathophysiology and/or disease progression in LRRK2 carriers compared to iPD. Importantly, we confirm previous findings in PD genetic subsets where disease characteristics were ascertained through clinical exam. Overall, these data support the effective use of self-report and genetic data to rapidly analyze information from a large disease population or difficult to identify genetic subgroups.
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spelling pubmed-61132192018-08-30 Self-report data as a tool for subtype identification in genetically-defined Parkinson’s Disease Winslow, Ashley R. Hyde, Craig L. Wilk, Jemma B. Eriksson, Nicholas Cannon, Paul Miller, Melissa R. Hirst, Warren D. Sci Rep Article Through a targeted recruitment 23andMe has collected DNA and patient-reported symptoms from more than 10,000 subjects reporting a physician-verified diagnosis of PD. This study evaluated the potential of self-report, web-based questionnaires to rapidly assess disease natural history and symptomology in genetically-defined PD populations. While average age-at-diagnosis was significantly lower in GBA mutation carriers compared to idiopathic PD, or iPD (idiopathic PD, defined as no GBA mutations and no LRRK2 G2019S mutation), there were no significant differences in symptoms. Conversely, LRRK2 G2019S carrier status significantly associated with reporting of milder daily symptoms of lightheadedness and several differences were observed at a false discovery rate < 0.1, including increased reporting of changes in walking as an initial symptom of disease, decreased reporting of lightheadedness upon standing, and milder symptoms related to daily functioning. The subclinical differences in symptoms reported by LRRK2 G2019S carriers suggest differences in underlying pathophysiology and/or disease progression in LRRK2 carriers compared to iPD. Importantly, we confirm previous findings in PD genetic subsets where disease characteristics were ascertained through clinical exam. Overall, these data support the effective use of self-report and genetic data to rapidly analyze information from a large disease population or difficult to identify genetic subgroups. Nature Publishing Group UK 2018-08-28 /pmc/articles/PMC6113219/ /pubmed/30154511 http://dx.doi.org/10.1038/s41598-018-30843-6 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Winslow, Ashley R.
Hyde, Craig L.
Wilk, Jemma B.
Eriksson, Nicholas
Cannon, Paul
Miller, Melissa R.
Hirst, Warren D.
Self-report data as a tool for subtype identification in genetically-defined Parkinson’s Disease
title Self-report data as a tool for subtype identification in genetically-defined Parkinson’s Disease
title_full Self-report data as a tool for subtype identification in genetically-defined Parkinson’s Disease
title_fullStr Self-report data as a tool for subtype identification in genetically-defined Parkinson’s Disease
title_full_unstemmed Self-report data as a tool for subtype identification in genetically-defined Parkinson’s Disease
title_short Self-report data as a tool for subtype identification in genetically-defined Parkinson’s Disease
title_sort self-report data as a tool for subtype identification in genetically-defined parkinson’s disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6113219/
https://www.ncbi.nlm.nih.gov/pubmed/30154511
http://dx.doi.org/10.1038/s41598-018-30843-6
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