IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v626y2024i7999d10.1038_s41586-023-06988-4.html
   My bibliography  Save this article

The Born in Guangzhou Cohort Study enables generational genetic discoveries

Author

Listed:
  • Shujia Huang

    (Guangzhou Medical University)

  • Siyang Liu

    (Shenzhen Campus of Sun Yat-sen University)

  • Mingxi Huang

    (Guangzhou Medical University)

  • Jian-Rong He

    (Guangzhou Medical University
    Provincial Clinical Research Center for Child Health
    Guangzhou Medical University)

  • Chengrui Wang

    (Guangzhou Medical University)

  • Tianyi Wang

    (Chinese Academy of Sciences
    University of the Chinese Academy of Sciences)

  • Xiaotian Feng

    (Chinese Academy of Sciences
    University of the Chinese Academy of Sciences)

  • Yashu Kuang

    (Guangzhou Medical University
    Provincial Clinical Research Center for Child Health)

  • Jinhua Lu

    (Guangzhou Medical University
    Provincial Clinical Research Center for Child Health)

  • Yuqin Gu

    (Shenzhen Campus of Sun Yat-sen University)

  • Xiaoyan Xia

    (Guangzhou Medical University
    Guangzhou Medical University)

  • Shanshan Lin

    (Guangzhou Medical University
    Guangzhou Medical University)

  • Wenhao Zhou

    (Guangzhou Medical University)

  • Qiaomei Fu

    (Chinese Academy of Sciences
    University of the Chinese Academy of Sciences)

  • Huimin Xia

    (Provincial Clinical Research Center for Child Health
    Guangzhou Medical University
    Guangzhou Medical University)

  • Xiu Qiu

    (Guangzhou Medical University
    Provincial Clinical Research Center for Child Health
    Guangzhou Medical University)

Abstract

Genomic research that targets large-scale, prospective birth cohorts constitutes an essential strategy for understanding the influence of genetics and environment on human health1. Nonetheless, such studies remain scarce, particularly in Asia. Here we present the phase I genome study of the Born in Guangzhou Cohort Study2 (BIGCS), which encompasses the sequencing and analysis of 4,053 Chinese individuals, primarily composed of trios or mother–infant duos residing in South China. Our analysis reveals novel genetic variants, a high-quality reference panel, and fine-scale local genetic structure within BIGCS. Notably, we identify previously unreported East Asian-specific genetic associations with maternal total bile acid, gestational weight gain and infant cord blood traits. Additionally, we observe prevalent age-specific genetic effects on lipid levels in mothers and infants. In an exploratory intergenerational Mendelian randomization analysis, we estimate the maternal putatively causal and fetal genetic effects of seven adult phenotypes on seven fetal growth-related measurements. These findings illuminate the genetic links between maternal and early-life traits in an East Asian population and lay the groundwork for future research into the intricate interplay of genetics, intrauterine exposures and early-life experiences in shaping long-term health.

Suggested Citation

  • Shujia Huang & Siyang Liu & Mingxi Huang & Jian-Rong He & Chengrui Wang & Tianyi Wang & Xiaotian Feng & Yashu Kuang & Jinhua Lu & Yuqin Gu & Xiaoyan Xia & Shanshan Lin & Wenhao Zhou & Qiaomei Fu & Hui, 2024. "The Born in Guangzhou Cohort Study enables generational genetic discoveries," Nature, Nature, vol. 626(7999), pages 565-573, February.
  • Handle: RePEc:nat:nature:v:626:y:2024:i:7999:d:10.1038_s41586-023-06988-4
    DOI: 10.1038/s41586-023-06988-4
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41586-023-06988-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41586-023-06988-4?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Yuandan Wei & Jianxin Zhen & Liang Hu & Yuqin Gu & Yanhong Liu & Xinxin Guo & Zijing Yang & Hao Zheng & Shiyao Cheng & Fengxiang Wei & Likuan Xiong & Siyang Liu, 2024. "Genome-wide association studies of thyroid-related hormones, dysfunction, and autoimmunity among 85,421 Chinese pregnancies," Nature Communications, Nature, vol. 15(1), pages 1-17, 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:nature:v:626:y:2024:i:7999:d:10.1038_s41586-023-06988-4. 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.