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Prioritizing Parkinson’s disease genes using population-scale transcriptomic data

Author

Listed:
  • Yang I. Li

    (University of Chicago)

  • Garrett Wong

    (Icahn School of Medicine at Mount Sinai)

  • Jack Humphrey

    (UCL Genetics Institute
    UCL Institute of Neurology)

  • Towfique Raj

    (Icahn School of Medicine at Mount Sinai)

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.

Suggested Citation

  • Yang I. Li & Garrett Wong & Jack Humphrey & Towfique Raj, 2019. "Prioritizing Parkinson’s disease genes using population-scale transcriptomic data," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-08912-9
    DOI: 10.1038/s41467-019-08912-9
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    1. Salim Megat & Natalia Mora & Jason Sanogo & Olga Roman & Alberto Catanese & Najwa Ouali Alami & Axel Freischmidt & Xhuljana Mingaj & Hortense Calbiac & François Muratet & Sylvie Dirrig-Grosch & Stépha, 2023. "Integrative genetic analysis illuminates ALS heritability and identifies risk genes," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    2. Xiaoguang Xu & Chachrit Khunsriraksakul & James M. Eales & Sebastien Rubin & David Scannali & Sushant Saluja & David Talavera & Havell Markus & Lida Wang & Maciej Drzal & Akhlaq Maan & Abigail C. Lay , 2024. "Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets," Nature Communications, Nature, vol. 15(1), pages 1-29, December.
    3. Hui Chen & Zeyang Wang & Lihai Gong & Qixuan Wang & Wenyan Chen & Jia Wang & Xuelian Ma & Ruofan Ding & Xing Li & Xudong Zou & Mireya Plass & Cheng Lian & Ting Ni & Gong-Hong Wei & Wei Li & Lin Deng &, 2024. "A distinct class of pan-cancer susceptibility genes revealed by an alternative polyadenylation transcriptome-wide association study," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    4. Ya Cui & Frederick J. Arnold & Fanglue Peng & Dan Wang & Jason Sheng Li & Sebastian Michels & Eric J. Wagner & Albert R. Spada & Wei Li, 2023. "Alternative polyadenylation transcriptome-wide association study identifies APA-linked susceptibility genes in brain disorders," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    5. Gemma Shireby & Emma L. Dempster & Stefania Policicchio & Rebecca G. Smith & Ehsan Pishva & Barry Chioza & Jonathan P. Davies & Joe Burrage & Katie Lunnon & Dorothea Seiler Vellame & Seth Love & Alan , 2022. "DNA methylation signatures of Alzheimer’s disease neuropathology in the cortex are primarily driven by variation in non-neuronal cell-types," Nature Communications, Nature, vol. 13(1), pages 1-14, December.

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