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Genome-wide association analysis of left ventricular imaging-derived phenotypes identifies 72 risk loci and yields genetic insights into hypertrophic cardiomyopathy

Author

Listed:
  • Caibo Ning

    (Wuhan University
    Renmin Hospital of Wuhan University
    Zhongnan Hospital of Wuhan University)

  • Linyun Fan

    (Wuhan University
    Renmin Hospital of Wuhan University
    Zhongnan Hospital of Wuhan University)

  • Meng Jin

    (Huazhong University of Science and Technology)

  • Wenji Wang

    (SenseTime Research)

  • Zhiqiang Hu

    (SenseTime Research)

  • Yimin Cai

    (Wuhan University)

  • Liangkai Chen

    (Huazhong University of Science and Technology)

  • Zequn Lu

    (Wuhan University)

  • Ming Zhang

    (Wuhan University)

  • Can Chen

    (Wuhan University)

  • Yanmin Li

    (Wuhan University)

  • Fuwei Zhang

    (Wuhan University)

  • Wenzhuo Wang

    (Wuhan University)

  • Yizhuo Liu

    (Wuhan University)

  • Shuoni Chen

    (Wuhan University)

  • Yuan Jiang

    (Wuhan University)

  • Chunyi He

    (Wuhan University)

  • Zhuo Wang

    (Wuhan University)

  • Xu Chen

    (Wuhan University)

  • Hanting Li

    (Wuhan University)

  • Gaoyuan Li

    (Wuhan University)

  • Qianying Ma

    (Wuhan University)

  • Hui Geng

    (Wuhan University)

  • Wen Tian

    (Wuhan University)

  • Heng Zhang

    (Wuhan University)

  • Bo Liu

    (Huazhong University of Science and Technology)

  • Qing Xia

    (SenseTime Research)

  • Xiaojun Yang

    (Zhongnan Hospital of Wuhan University, Wuhan University)

  • Zhongchun Liu

    (Renmin Hospital of Wuhan University)

  • Bin Li

    (Wuhan University)

  • Ying Zhu

    (Wuhan University
    Renmin Hospital of Wuhan University
    Zhongnan Hospital of Wuhan University
    Wuhan University)

  • Xiangpan Li

    (Renmin Hospital of Wuhan University)

  • Shaoting Zhang

    (SenseTime Research
    Shanghai Artificial Intelligence Laboratory)

  • Jianbo Tian

    (Wuhan University
    Renmin Hospital of Wuhan University
    Zhongnan Hospital of Wuhan University
    Wuhan University)

  • Xiaoping Miao

    (Wuhan University
    Renmin Hospital of Wuhan University
    Zhongnan Hospital of Wuhan University
    Wuhan University)

Abstract

Left ventricular regional wall thickness (LVRWT) is an independent predictor of morbidity and mortality in cardiovascular diseases (CVDs). To identify specific genetic influences on individual LVRWT, we established a novel deep learning algorithm to calculate 12 LVRWTs accurately in 42,194 individuals from the UK Biobank with cardiac magnetic resonance (CMR) imaging. Genome-wide association studies of CMR-derived 12 LVRWTs identified 72 significant genetic loci associated with at least one LVRWT phenotype (P

Suggested Citation

  • Caibo Ning & Linyun Fan & Meng Jin & Wenji Wang & Zhiqiang Hu & Yimin Cai & Liangkai Chen & Zequn Lu & Ming Zhang & Can Chen & Yanmin Li & Fuwei Zhang & Wenzhuo Wang & Yizhuo Liu & Shuoni Chen & Yuan , 2023. "Genome-wide association analysis of left ventricular imaging-derived phenotypes identifies 72 risk loci and yields genetic insights into hypertrophic cardiomyopathy," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43771-5
    DOI: 10.1038/s41467-023-43771-5
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    References listed on IDEAS

    as
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