IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v9y2018i1d10.1038_s41467-018-04558-1.html
   My bibliography  Save this article

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Author

Listed:
  • Ting Qi

    (The University of Queensland)

  • Yang Wu

    (The University of Queensland)

  • Jian Zeng

    (The University of Queensland)

  • Futao Zhang

    (The University of Queensland
    The University of Queensland)

  • Angli Xue

    (The University of Queensland)

  • Longda Jiang

    (The University of Queensland)

  • Zhihong Zhu

    (The University of Queensland)

  • Kathryn Kemper

    (The University of Queensland)

  • Loic Yengo

    (The University of Queensland)

  • Zhili Zheng

    (The University of Queensland
    Wenzhou Medical University)

  • Riccardo E. Marioni

    (University of Edinburgh
    University of Edinburgh)

  • Grant W. Montgomery

    (The University of Queensland)

  • Ian J. Deary

    (University of Edinburgh)

  • Naomi R. Wray

    (The University of Queensland
    The University of Queensland)

  • Peter M. Visscher

    (The University of Queensland
    The University of Queensland)

  • Allan F. McRae

    (The University of Queensland)

  • Jian Yang

    (The University of Queensland
    The University of Queensland
    Wenzhou Medical University)

Abstract

Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes for brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top-associated cis-expression or -DNA methylation (DNAm) quantitative trait loci (cis-eQTLs or cis-mQTLs) between brain and blood (r b ). Using publicly available data, we find that genetic effects at the top cis-eQTLs or mQTLs are highly correlated between independent brain and blood samples ( $$\hat r_b = 0.70$$ r ^ b = 0.70 for cis-eQTLs and $$\hat r_ b = 0.78$$ r ^ b = 0.78 for cis-mQTLs). Using meta-analyzed brain cis-eQTL/mQTL data (n = 526 to 1194), we identify 61 genes and 167 DNAm sites associated with four brain-related phenotypes, most of which are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = 1980 to 14,115). Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL/mQTL data with large sample sizes.

Suggested Citation

  • Ting Qi & Yang Wu & Jian Zeng & Futao Zhang & Angli Xue & Longda Jiang & Zhihong Zhu & Kathryn Kemper & Loic Yengo & Zhili Zheng & Riccardo E. Marioni & Grant W. Montgomery & Ian J. Deary & Naomi R. W, 2018. "Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-04558-1
    DOI: 10.1038/s41467-018-04558-1
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-018-04558-1
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-018-04558-1?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
    ---><---

    Citations

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


    Cited by:

    1. Sophie A. Riesmeijer & Zoha Kamali & Michael Ng & Dmitriy Drichel & Bram Piersma & Kerstin Becker & Thomas B. Layton & Jagdeep Nanchahal & Michael Nothnagel & Ahmad Vaez & Hans Christian Hennies & Pau, 2024. "A genome-wide association meta-analysis implicates Hedgehog and Notch signaling in Dupuytren’s disease," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Yihao Lu & Meritxell Oliva & Brandon L. Pierce & Jin Liu & Lin S. Chen, 2024. "Integrative cross-omics and cross-context analysis elucidates molecular links underlying genetic effects on complex traits," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    3. Lasse Pihlstrøm & Gemma Shireby & Hanneke Geut & Sandra Pilar Henriksen & Annemieke J. M. Rozemuller & Jon-Anders Tunold & Eilis Hannon & Paul Francis & Alan J. Thomas & Seth Love & Jonathan Mill & Wi, 2022. "Epigenome-wide association study of human frontal cortex identifies differential methylation in Lewy body pathology," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    4. Max Lam & Chia-Yen Chen & W. David Hill & Charley Xia & Ruoyu Tian & Daniel F. Levey & Joel Gelernter & Murray B. Stein & Alexander S. Hatoum & Hailiang Huang & Anil K. Malhotra & Heiko Runz & Tian Ge, 2022. "Collective genomic segments with differential pleiotropic patterns between cognitive dimensions and psychopathology," Nature Communications, Nature, vol. 13(1), pages 1-22, December.
    5. Yordi J. Vegte & Ruben N. Eppinga & M. Yldau Ende & Yanick P. Hagemeijer & Yuvaraj Mahendran & Elias Salfati & Albert V. Smith & Vanessa Y. Tan & Dan E. Arking & Ioanna Ntalla & Emil V. Appel & Claudi, 2023. "Genetic insights into resting heart rate and its role in cardiovascular disease," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    6. Alesha A. Hatton & Fei-Fei Cheng & Tian Lin & Ren-Juan Shen & Jie Chen & Zhili Zheng & Jia Qu & Fan Lyu & Sarah E. Harris & Simon R. Cox & Zi-Bing Jin & Nicholas G. Martin & Dongsheng Fan & Grant W. M, 2024. "Genetic control of DNA methylation is largely shared across European and East Asian populations," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

    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:9:y:2018:i:1:d:10.1038_s41467-018-04558-1. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.