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Causal associations between risk factors and common diseases inferred from GWAS summary data

Author

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  • Zhihong Zhu

    (The University of Queensland)

  • Zhili Zheng

    (The University of Queensland
    Wenzhou Medical University)

  • Futao Zhang

    (The University of Queensland)

  • Yang Wu

    (The University of Queensland)

  • Maciej Trzaskowski

    (The University of Queensland)

  • Robert Maier

    (The University of Queensland)

  • Matthew R. Robinson

    (The University of Queensland)

  • John J. McGrath

    (The University of Queensland
    The Park Centre for Mental Health
    Aarhus University)

  • Peter M. Visscher

    (The University of Queensland
    The University of Queensland)

  • Naomi R. Wray

    (The University of Queensland
    The University of Queensland)

  • Jian Yang

    (The University of Queensland
    The University of Queensland)

Abstract

Health risk factors such as body mass index (BMI) and serum cholesterol are associated with many common diseases. It often remains unclear whether the risk factors are cause or consequence of disease, or whether the associations are the result of confounding. We develop and apply a method (called GSMR) that performs a multi-SNP Mendelian randomization analysis using summary-level data from genome-wide association studies to test the causal associations of BMI, waist-to-hip ratio, serum cholesterols, blood pressures, height, and years of schooling (EduYears) with common diseases (sample sizes of up to 405,072). We identify a number of causal associations including a protective effect of LDL-cholesterol against type-2 diabetes (T2D) that might explain the side effects of statins on T2D, a protective effect of EduYears against Alzheimer’s disease, and bidirectional associations with opposite effects (e.g., higher BMI increases the risk of T2D but the effect of T2D on BMI is negative).

Suggested Citation

  • Zhihong Zhu & Zhili Zheng & Futao Zhang & Yang Wu & Maciej Trzaskowski & Robert Maier & Matthew R. Robinson & John J. McGrath & Peter M. Visscher & Naomi R. Wray & Jian Yang, 2018. "Causal associations between risk factors and common diseases inferred from GWAS summary data," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-017-02317-2
    DOI: 10.1038/s41467-017-02317-2
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    Cited by:

    1. Qing Cheng & Xiao Zhang & Lin S. Chen & Jin Liu, 2022. "Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. M d Mesbah Uddin & Ngoc Quynh H. Nguyen & Bing Yu & Jennifer A. Brody & Akhil Pampana & Tetsushi Nakao & Myriam Fornage & Jan Bressler & Nona Sotoodehnia & Joshua S. Weinstock & Michael C. Honigberg &, 2022. "Clonal hematopoiesis of indeterminate potential, DNA methylation, and risk for coronary artery disease," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    3. Matthew T. Patrick & Qinmengge Li & Rachael Wasikowski & Nehal Mehta & Johann E. Gudjonsson & James T. Elder & Xiang Zhou & Lam C. Tsoi, 2022. "Shared genetic risk factors and causal association between psoriasis and coronary artery disease," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Marie C. Sadler & Chiara Auwerx & Kaido Lepik & Eleonora Porcu & Zoltán Kutalik, 2022. "Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    5. Siqi Xu & Peng Wang & Wing Kam Fung & Zhonghua Liu, 2023. "A novel penalized inverse‐variance weighted estimator for Mendelian randomization with applications to COVID‐19 outcomes," Biometrics, The International Biometric Society, vol. 79(3), pages 2184-2195, September.
    6. Wenhan Chen & Yang Wu & Zhili Zheng & Ting Qi & Peter M. Visscher & Zhihong Zhu & Jian Yang, 2021. "Improved analyses of GWAS summary statistics by reducing data heterogeneity and errors," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    7. Charley Xia & Sarah J. Pickett & David C. M. Liewald & Alexander Weiss & Gavin Hudson & W. David Hill, 2023. "The contributions of mitochondrial and nuclear mitochondrial genetic variation to neuroticism," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    8. Gemma Cadby & Corey Giles & Phillip E. Melton & Kevin Huynh & Natalie A. Mellett & Thy Duong & Anh Nguyen & Michelle Cinel & Alex Smith & Gavriel Olshansky & Tingting Wang & Marta Brozynska & Mike Ino, 2022. "Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    9. William R. Reay & Michael P. Geaghan & Murray J. Cairns, 2022. "The genetic architecture of pneumonia susceptibility implicates mucin biology and a relationship with psychiatric illness," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    10. Zipeng Liu & Yiming Qin & Tian Wu & Justin D. Tubbs & Larry Baum & Timothy Shin Heng Mak & Miaoxin Li & Yan Dora Zhang & Pak Chung Sham, 2023. "Reciprocal causation mixture model for robust Mendelian randomization analysis using genome-scale summary data," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    11. Haoran Xue & Wei Pan, 2020. "Inferring causal direction between two traits in the presence of horizontal pleiotropy with GWAS summary data," PLOS Genetics, Public Library of Science, vol. 16(11), pages 1-30, November.
    12. Zhen Qiao & Julia Sidorenko & Joana A. Revez & Angli Xue & Xueling Lu & Katri Pärna & Harold Snieder & Peter M. Visscher & Naomi R. Wray & Loic Yengo, 2023. "Estimation and implications of the genetic architecture of fasting and non-fasting blood glucose," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    13. Jessica M B Rees & Angela M Wood & Frank Dudbridge & Stephen Burgess, 2019. "Robust methods in Mendelian randomization via penalization of heterogeneous causal estimates," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-24, September.
    14. Clara Albiñana & Zhihong Zhu & Nis Borbye-Lorenzen & Sanne Grundvad Boelt & Arieh S. Cohen & Kristin Skogstrand & Naomi R. Wray & Joana A. Revez & Florian Privé & Liselotte V. Petersen & Cynthia M. Bu, 2023. "Genetic correlates of vitamin D-binding protein and 25-hydroxyvitamin D in neonatal dried blood spots," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    15. Zhaotong Lin & Yangqing Deng & Wei Pan, 2021. "Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model," PLOS Genetics, Public Library of Science, vol. 17(11), pages 1-25, November.
    16. Yi-Qian Sun & Rebecca C Richmond & Yue Chen & Xiao-Mei Mai, 2020. "Mixed evidence for the relationship between periodontitis and Alzheimer’s disease: A bidirectional Mendelian randomization study," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-9, January.
    17. Adrien Georges & Min-Lee Yang & Takiy-Eddine Berrandou & Mark K. Bakker & Ozan Dikilitas & Soto Romuald Kiando & Lijiang Ma & Benjamin A. Satterfield & Sebanti Sengupta & Mengyao Yu & Jean-François De, 2021. "Genetic investigation of fibromuscular dysplasia identifies risk loci and shared genetics with common cardiovascular diseases," Nature Communications, Nature, vol. 12(1), pages 1-16, December.
    18. Fengzhe Xu & Evan Yi-Wen Yu & Xue Cai & Liang Yue & Li-peng Jing & Xinxiu Liang & Yuanqing Fu & Zelei Miao & Min Yang & Menglei Shuai & Wanglong Gou & Congmei Xiao & Zhangzhi Xue & Yuting Xie & Sainan, 2023. "Genome-wide genotype-serum proteome mapping provides insights into the cross-ancestry differences in cardiometabolic disease susceptibility," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    19. Jayshree Advani & Puja A. Mehta & Andrew R. Hamel & Sudeep Mehrotra & Christina Kiel & Tobias Strunz & Ximena Corso-Díaz & Madeline Kwicklis & Freekje Asten & Rinki Ratnapriya & Emily Y. Chew & Dena G, 2024. "QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration," Nature Communications, Nature, vol. 15(1), pages 1-20, December.

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