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Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

  • Stavroula Kanoni (Contributor)
  • Sarah E. Graham (Contributor)
  • Yuxuan Wang (Boston University) (Contributor)
  • Ida Surakka (Contributor)
  • Shweta Ramdas (Contributor)
  • Xiang Zhu (Stanford University, Pennsylvania State University) (Contributor)
  • Shoa L. Clarke (Contributor)
  • Konain Fatima Bhatti (Contributor)
  • Sailaja L. Vedantam (Contributor)
  • Thomas W. Winkler (Contributor)
  • Adam E. Locke (Contributor)
  • Eirini Marouli (Contributor)
  • Greg J.M. Zajac (Contributor)
  • Kuan Han H. Wu (Contributor)
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  • Qin Hui (Contributor)
  • Derek Klarin (Contributor)
  • Austin T. Hilliard (Contributor)
  • Zeyuan Wang (Contributor)
  • Chao Xue (Contributor)
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  • Isleifur Olafsson (Contributor)
  • Mi Yeong Hwang (Contributor)
  • Sohee Han (Contributor)
  • Masato Akiyama (Contributor)
  • Saori Sakaue (Contributor)
  • Chikashi Terao (Contributor)
  • Masahiro Kanai (Contributor)
  • Wei Zhou (University of Michigan, Massachusetts General Hospital, Broad Institute) (Contributor)
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  • Wei Zhao (Contributor)
  • David R. Weir (University of Michigan) (Contributor)
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  • Michael R. Brown (The University of Texas Health Science Center at Houston) (Contributor)
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Dataset

Description

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
Date made available13 Apr 2023
PublisherFigshare
  • Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

    Kanoni, S., Graham, S. E., Wang, Y., Surakka, I., Ramdas, S., Zhu, X., Clarke, S. L., Bhatti, K. F., Vedantam, S., Winkler, T. W., Locke, A. E., Marouli, E., Zajac, G. J. M., Wu, K. H. H., Ntalla, I., Hui, Q., Klarin, D., Hilliard, A. T., Wang, Z. & Xue, C. & 519 others, Thorleifsson, G., Helgadottir, A., Gudbjartsson, D. F., Holm, H., Olafsson, I., Hwang, M. Y., Han, S., Akiyama, M., Sakaue, S., Terao, C., Kanai, M., Zhou, W., Brumpton, B. M., Rasheed, H., Havulinna, A. S., Veturi, Y., Pacheco, J. A., Rosenthal, E. A., Lingren, T., Feng, Q. P., Kullo, I. J., Narita, A., Takayama, J., Martin, H. C., Hunt, K. A., Trivedi, B., Haessler, J., Giulianini, F., Bradford, Y., Miller, J. E., Campbell, A., Lin, K., Millwood, I. Y., Rasheed, A., Hindy, G., Faul, J. D., Zhao, W., Weir, D. R., Turman, C., Huang, H., Graff, M., Choudhury, A., Sengupta, D., Mahajan, A., Brown, M. R., Zhang, W., Yu, K., Schmidt, E. M., Pandit, A., Gustafsson, S., Yin, X., Luan, J., Zhao, J. 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