Parkinson’s Disease Pathogenic Variants: Cross-Ancestry Analysis and Microarray Data Validation

Background
Known pathogenic variants in Parkinson’s disease (PD) contribute to disease development but have yet to be fully explored by arrays at scale.

Objectives
This study evaluated genotyping success of the NeuroBooster array (NBA) and determined the frequencies of pathogenic variants across ancestries.

Method
We analyzed the presence and allele frequency of 34 pathogenic variants in 28,710 PD cases, 9,614 other neurodegenerative disorder cases, and 15,821 controls across 11 ancestries within the Global Parkinson’s Genetics Program dataset. Of these, 25 were genotyped on NBA and cluster plots were used to assess their quality.

Results
Genes previously predicted to have high or very high confidence of causing PD tend to have more pathogenic variants and are present across ancestry groups. Twenty-five of the 34 pathogenic variants were typed by the NBA array and classified “good” (n=12), “medium” (n=4), and “bad” (n=9) variants.

Conclusion
Our results confirm the likelihood that established PD genes are pathogenic and highlight the importance of ancestrally diverse research in PD. We also show the usefulness of the NBA as a reliable tool for genotyping of rare variants for PD.

Training and Networking Working Group

The Training and Networking working group promotes training and networking throughout the GP2 project.
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Complex Disease - Data Analysis Working Group

The Data Analysis working group manages the maintenance, democratization, and acceleration of analyses, and provides analytical support for investigators with approved projects.
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Meet the authors

Data and Software Engineer

Mathew Koretsky, BSc

National Institutes of Health | WA, USA

Lead of Collaborative Research

Hampton Leonard

National Institute on Aging/National Institutes of Health | USA