Objective: We develop a scalable pipeline leveraging existing tools to determine local ancestry for all individuals in the Global Parkinson’s Genetics Program (GP2), aiming to enrich the understanding and statistical analysis of genetic data across both admixed and non-admixed populations and accurately determining individual level risk.

Background: PD is a multifaceted neurological disorder with a genetic basis that is not fully understood. Both common and rare genetic variants play roles in its etiology, with local ancestry providing a novel angle for examining genetic complexities, especially in admixed populations.

Method: Our methodological framework involves: (1) Creating a phasing reference dataset, enhancing a 1KG dataset to 30x coverage for phasing. (2) Normalizing reference files, extracting biallelic variants, converting PLINK files to VCF, and compressing and indexing these files. Similar steps are taken for target files. (3) Merging reference and target files, phasing with the enhanced 1KG dataset, and extracting relevant data. (4) Analyzing phased data to calculate principal components, create clusters for efficient RFMix v1 analysis, and generate VCFs reflecting rephased alleles for each sample. (5) Visualization of local ancestry per individual.

Results: Expected outcomes include the identification of ancestry-specific variants associated with PD, integrating these findings into a polygenic risk score panel for PD, making this available as a part of GP2 resources. This methodology aims to address heterogeneity in genetic analyses, especially for admixed individuals, enhancing the statistical robustness of our findings.

Conclusion: By focusing on local ancestry, our research seeks to deepen our understanding of its genetic architecture across diverse populations as well as increase the statistical power in analyses looking at admixed populations. The development and application of our comprehensive analysis pipeline offer a blueprint for future genetic studies, leveraging this approach to understanding complex neurological diseases.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/determining-and-leveraging-local-ancestry-to-assess-individual-level-risk-from-the-global-parkinsons-genetics-program/