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

自我报告数据作为基因定义的帕金森病亚型识别的工具

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Abstract

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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