IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v12y2021i1d10.1038_s41467-021-26280-1.html
   My bibliography  Save this article

Finding genetically-supported drug targets for Parkinson’s disease using Mendelian randomization of the druggable genome

Author

Listed:
  • Catherine S. Storm

    (University College London Queen Square Institute of Neurology)

  • Demis A. Kia

    (University College London Queen Square Institute of Neurology)

  • Mona M. Almramhi

    (University College London Queen Square Institute of Neurology
    King Abdulaziz University)

  • Sara Bandres-Ciga

    (National Institute on Aging)

  • Chris Finan

    (University College London
    University College London British Heart Foundation Research Accelerator Centre
    University Medical Center Utrecht, Heidelberglaan 100)

  • Aroon D. Hingorani

    (University College London
    University College London British Heart Foundation Research Accelerator Centre
    Health Data Research UK)

  • Nicholas W. Wood

    (University College London Queen Square Institute of Neurology)

Abstract

Parkinson’s disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson’s disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson’s disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson’s disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson’s disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson’s disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson’s disease drug development.

Suggested Citation

  • Catherine S. Storm & Demis A. Kia & Mona M. Almramhi & Sara Bandres-Ciga & Chris Finan & Aroon D. Hingorani & Nicholas W. Wood, 2021. "Finding genetically-supported drug targets for Parkinson’s disease using Mendelian randomization of the druggable genome," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26280-1
    DOI: 10.1038/s41467-021-26280-1
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-021-26280-1
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-021-26280-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Paul T E Cusack, 2020. "The Human Brain," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 31(3), pages 24261-24266, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Abolfazl Doostparast Torshizi & Dongnhu T. Truong & Liping Hou & Bart Smets & Christopher D. Whelan & Shuwei Li, 2024. "Proteogenomic network analysis reveals dysregulated mechanisms and potential mediators in Parkinson’s disease," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    2. Randy L. Parrish & Aron S. Buchman & Shinya Tasaki & Yanling Wang & Denis Avey & Jishu Xu & Philip L. De Jager & David A. Bennett & Michael P. Epstein & Jingjing Yang, 2024. "SR-TWAS: leveraging multiple reference panels to improve transcriptome-wide association study power by ensemble machine learning," Nature Communications, Nature, vol. 15(1), pages 1-16, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abigail B. Schneider & Bridget Leonard, 2022. "From anxiety to control: Mask‐wearing, perceived marketplace influence, and emotional well‐being during the COVID‐19 pandemic," Journal of Consumer Affairs, Wiley Blackwell, vol. 56(1), pages 97-119, March.
    2. Odelaisy León-Triana & Julián Pérez-Beteta & David Albillo & Ana Ortiz de Mendivil & Luis Pérez-Romasanta & Elisabet González-Del Portillo & Manuel Llorente & Natalia Carballo & Estanislao Arana & Víc, 2021. "Brain Metastasis Response to Stereotactic Radio Surgery: A Mathematical Approach," Mathematics, MDPI, vol. 9(7), pages 1-19, March.
    3. Mirren Charnley & Saba Islam & Guneet K. Bindra & Jeremy Engwirda & Julian Ratcliffe & Jiangtao Zhou & Raffaele Mezzenga & Mark D. Hulett & Kyunghoon Han & Joshua T. Berryman & Nicholas P. Reynolds, 2022. "Neurotoxic amyloidogenic peptides in the proteome of SARS-COV2: potential implications for neurological symptoms in COVID-19," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Hamed Nili & Alexander Walther & Arjen Alink & Nikolaus Kriegeskorte, 2020. "Inferring exemplar discriminability in brain representations," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-28, June.
    5. Linzmajer, Marc & Hubert, Mirja & Hubert, Marco, 2021. "It’s about the process, not the result: An fMRI approach to explore the encoding of explicit and implicit price information," Journal of Economic Psychology, Elsevier, vol. 86(C).
    6. Natalie J Shook & Barış Sevi & Jerin Lee & Benjamin Oosterhoff & Holly N Fitzgerald, 2020. "Disease avoidance in the time of COVID-19: The behavioral immune system is associated with concern and preventative health behaviors," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-15, August.
    7. Cristina Lázaro-Pérez & José Ángel Martínez-López & José Gómez-Galán, 2020. "Addictions in Spanish College Students in Confinement Times: Preventive and Social Perspective," Social Sciences, MDPI, vol. 9(11), pages 1-21, October.
    8. Yashika Arora & Pushpinder Walia & Mitsuhiro Hayashibe & Makii Muthalib & Shubhajit Roy Chowdhury & Stephane Perrey & Anirban Dutta, 2021. "Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans," PLOS Computational Biology, Public Library of Science, vol. 17(10), pages 1-38, October.
    9. Elvisa Drishti & Bresena Kopliku & Drini Imami, 2022. "Active political engagement, political patronage and local labour markets – The example of Shkoder," International Journal of Manpower, Emerald Group Publishing Limited, vol. 44(6), pages 1118-1142, April.
    10. Nguyen, Ha Trong & Brinkman, Sally & Le, Huong Thu & Zubrick, Stephen R. & Mitrou, Francis, 2022. "Gender differences in time allocation contribute to differences in developmental outcomes in children and adolescents," Economics of Education Review, Elsevier, vol. 89(C).
    11. Gricelda Herrera-Franco & Néstor Montalván-Burbano & Carlos Mora-Frank & Lady Bravo-Montero, 2021. "Scientific Research in Ecuador: A Bibliometric Analysis," Publications, MDPI, vol. 9(4), pages 1-34, December.
    12. Sofie L. Valk & Ting Xu & Casey Paquola & Bo-yong Park & Richard A. I. Bethlehem & Reinder Vos de Wael & Jessica Royer & Shahrzad Kharabian Masouleh & Şeyma Bayrak & Peter Kochunov & B. T. Thomas Yeo , 2022. "Genetic and phylogenetic uncoupling of structure and function in human transmodal cortex," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    13. Rosen Valchev & Cosmin Ilut, 2017. "Economic Agents as Imperfect Problem Solvers," 2017 Meeting Papers 1285, Society for Economic Dynamics.
    14. Florent Meyniel, 2020. "Brain dynamics for confidence-weighted learning," PLOS Computational Biology, Public Library of Science, vol. 16(6), pages 1-27, June.
    15. Virgilio Pérez & Cristina Aybar & Jose M. Pavía, 2021. "COVID-19 and Changes in Social Habits. Restaurant Terraces, a Booming Space in Cities. The Case of Madrid," Mathematics, MDPI, vol. 9(17), pages 1-18, September.
    16. Ana-Madalina Potcovaru, 2020. "The Impact Of Organizational Stress On The Human Resources From The Health System During Covid-19 Pandemic," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 10(5), pages 88-97, October.
    17. Bastien Berret & Frédéric Jean, 2020. "Stochastic optimal open-loop control as a theory of force and impedance planning via muscle co-contraction," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-28, February.
    18. Florencia Barreto-Zarza & Enrique B. Arranz-Freijo, 2022. "Family Context, Parenting and Child Development: An Epigenetic Approach," Social Sciences, MDPI, vol. 11(3), pages 1-13, March.
    19. Alberto Micheletti, 2020. "Modelling cultural selection on biological fitness to integrate social transmission and adaptive explanations for human behaviour," Post-Print hal-02563204, HAL.
    20. Sai Li & T. Tony Cai & Hongzhe Li, 2022. "Transfer learning for high‐dimensional linear regression: Prediction, estimation and minimax optimality," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(1), pages 149-173, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26280-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.