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Prioritizing Parkinson’s disease genes using population-scale transcriptomic data
Yang Li, Garrett Wong, Jack Humphrey, Towfique Raj
Nature Communications · 2019 · ▲ 168 citations
Abstract
Genome-wide association studies (GWAS) have identified over 41 susceptibility loci associated with Parkinson's Disease (PD) but identifying putative causal genes and the underlying mechanisms remains challenging. Here, we leverage large-scale transcriptomic datasets to prioritize genes that are likely to affect PD by using a transcriptome-wide association study (TWAS) approach. Using this approach, we identify 66 gene associations whose predicted expression or splicing levels in dorsolateral prefrontal cortex (DLFPC) and peripheral monocytes are significantly associated with PD risk. We uncover many novel genes associated with PD but also novel mechanisms for known associations such as MAPT, for which we find that variation in exon 3 splicing explains the common genetic association. Genes identified in our analyses belong to the same or related pathways including lysosomal and innate immune function. Overall, our study provides a strong foundation for further mechanistic studies that will elucidate the molecular drivers of PD.
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- 10.1038/s41467-019-08912-9
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- 2026-07-25 MST
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APA
Li, Y., Wong, G., Humphrey, J., & Raj, T. (2019). Prioritizing Parkinson’s disease genes using population-scale transcriptomic data. <em>Nature Communications</em>. https://doi.org/10.1038/s41467-019-08912-9
Vancouver
Li Y, Wong G, Humphrey J, Raj T. Prioritizing Parkinson’s disease genes using population-scale transcriptomic data. Nature Communications. 2019. doi:10.1038/s41467-019-08912-9.
BibTeX
@article{yang2019Priori,
title = {Prioritizing Parkinson’s disease genes using population-scale transcriptomic data},
author = {Yang Li and Garrett Wong and Jack Humphrey and Towfique Raj},
journal = {Nature Communications},
year = {2019},
doi = {10.1038/s41467-019-08912-9},
}
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