IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-32095-5.html
   My bibliography  Save this article

Transferability of genetic loci and polygenic scores for cardiometabolic traits in British Pakistani and Bangladeshi individuals

Author

Listed:
  • Qin Qin Huang

    (Wellcome Sanger Institute)

  • Neneh Sallah

    (University College London
    University College London)

  • Diana Dunca

    (University College London
    University College London)

  • Bhavi Trivedi

    (Queen Mary University of London)

  • Karen A. Hunt

    (Queen Mary University of London)

  • Sam Hodgson

    (University of Southampton)

  • Samuel A. Lambert

    (University of Cambridge
    University of Cambridge
    Wellcome Genome Campus and University of Cambridge)

  • Elena Arciero

    (Wellcome Sanger Institute)

  • John Wright

    (Bradford Teaching Hospitals National Health Service (NHS) Foundation Trust)

  • Chris Griffiths

    (Queen Mary University of London)

  • Richard C. Trembath

    (King’s College London)

  • Harry Hemingway

    (University College London
    University College London
    University College London Hospitals Biomedical Research Centre (UCLH BRC))

  • Michael Inouye

    (University of Cambridge
    University of Cambridge
    Wellcome Genome Campus and University of Cambridge
    University of Cambridge)

  • Sarah Finer

    (Queen Mary University of London)

  • David A. Heel

    (Queen Mary University of London)

  • R. Thomas Lumbers

    (University College London
    University College London Hospitals Biomedical Research Centre (UCLH BRC)
    University College London)

  • Hilary C. Martin

    (Wellcome Sanger Institute)

  • Karoline Kuchenbaecker

    (University College London
    University College London)

Abstract

Individuals with South Asian ancestry have a higher risk of heart disease than other groups but have been largely excluded from genetic research. Using data from 22,000 British Pakistani and Bangladeshi individuals with linked electronic health records from the Genes & Health cohort, we conducted genome-wide association studies of coronary artery disease and its key risk factors. Using power-adjusted transferability ratios, we found evidence for transferability for the majority of cardiometabolic loci powered to replicate. The performance of polygenic scores was high for lipids and blood pressure, but lower for BMI and coronary artery disease. Adding a polygenic score for coronary artery disease to clinical risk factors showed significant improvement in reclassification. In Mendelian randomisation using transferable loci as instruments, our findings were consistent with results in European-ancestry individuals. Taken together, trait-specific transferability of trait loci between populations is an important consideration with implications for risk prediction and causal inference.

Suggested Citation

  • Qin Qin Huang & Neneh Sallah & Diana Dunca & Bhavi Trivedi & Karen A. Hunt & Sam Hodgson & Samuel A. Lambert & Elena Arciero & John Wright & Chris Griffiths & Richard C. Trembath & Harry Hemingway & M, 2022. "Transferability of genetic loci and polygenic scores for cardiometabolic traits in British Pakistani and Bangladeshi individuals," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32095-5
    DOI: 10.1038/s41467-022-32095-5
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-32095-5
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-32095-5?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
    ---><---

    References listed on IDEAS

    as
    1. Timothy R Braun & Latonya F Been & Akhil Singhal & Jacob Worsham & Sarju Ralhan & Gurpreet S Wander & John C Chambers & Jaspal S Kooner & Christopher E Aston & Dharambir K Sanghera, 2012. "A Replication Study of GWAS-Derived Lipid Genes in Asian Indians: The Chromosomal Region 11q23.3 Harbors Loci Contributing to Triglycerides," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-12, May.
    2. Karoline Kuchenbaecker & Nikita Telkar & Theresa Reiker & Robin G. Walters & Kuang Lin & Anders Eriksson & Deepti Gurdasani & Arthur Gilly & Lorraine Southam & Emmanouil Tsafantakis & Maria Karalefthe, 2019. "The transferability of lipid loci across African, Asian and European cohorts," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    3. Ying Wang & Jing Guo & Guiyan Ni & Jian Yang & Peter M. Visscher & Loic Yengo, 2020. "Theoretical and empirical quantification of the accuracy of polygenic scores in ancestry divergent populations," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    4. Sarah E. Graham & Shoa L. Clarke & Kuan-Han H. Wu & Stavroula Kanoni & Greg J. M. Zajac & Shweta Ramdas & Ida Surakka & Ioanna Ntalla & Sailaja Vedantam & Thomas W. Winkler & Adam E. Locke & Eirini Ma, 2021. "The power of genetic diversity in genome-wide association studies of lipids," Nature, Nature, vol. 600(7890), pages 675-679, December.
    5. L. Duncan & H. Shen & B. Gelaye & J. Meijsen & K. Ressler & M. Feldman & R. Peterson & B. Domingue, 2019. "Analysis of polygenic risk score usage and performance in diverse human populations," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Tzu-Ting Chen & Jaeyoung Kim & Max Lam & Yi-Fang Chuang & Yen-Ling Chiu & Shu-Chin Lin & Sang-Hyuk Jung & Beomsu Kim & Soyeon Kim & Chamlee Cho & Injeong Shim & Sanghyeon Park & Yeeun Ahn & Aysu Okbay, 2024. "Shared genetic architectures of educational attainment in East Asian and European populations," Nature Human Behaviour, Nature, vol. 8(3), pages 562-575, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ananyo Choudhury & Jean-Tristan Brandenburg & Tinashe Chikowore & Dhriti Sengupta & Palwende Romuald Boua & Nigel J. Crowther & Godfred Agongo & Gershim Asiki & F. Xavier Gómez-Olivé & Isaac Kisiangan, 2022. "Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Carla Márquez-Luna & Steven Gazal & Po-Ru Loh & Samuel S. Kim & Nicholas Furlotte & Adam Auton & Alkes L. Price, 2021. "Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    3. Jingning Zhang & Jianan Zhan & Jin Jin & Cheng Ma & Ruzhang Zhao & Jared O’Connell & Yunxuan Jiang & Bertram L. Koelsch & Haoyu Zhang & Nilanjan Chatterjee, 2024. "An ensemble penalized regression method for multi-ancestry polygenic risk prediction," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    4. Abram Bunya Kamiza & Sounkou M. Touré & Feng Zhou & Opeyemi Soremekun & Cheickna Cissé & Mamadou Wélé & Aboubacrine M. Touré & Oyekanmi Nashiru & Manuel Corpas & Moffat Nyirenda & Amelia Crampin & Jef, 2023. "Multi-trait discovery and fine-mapping of lipid loci in 125,000 individuals of African ancestry," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    5. Pereira, Rita & Biroli, Pietro & von hinke, stephanie & Van Kippersluis, Hans & Galama, Titus & Rietveld, Niels & Thom, Kevin, 2022. "Gene-Environment Interplay in the Social Sciences," OSF Preprints d96z3, Center for Open Science.
    6. Brieuc Lehmann & Maxine Mackintosh & Gil McVean & Chris Holmes, 2023. "Optimal strategies for learning multi-ancestry polygenic scores vary across traits," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    7. Jun Wang & Qihui Chen & Gang Chen & Yingxiang Li & Guoshu Kong & Chen Zhu, 2020. "What is creating the height premium? New evidence from a Mendelian randomization analysis in China," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-20, April.
    8. Michael G. Levin & Noah L. Tsao & Pankhuri Singhal & Chang Liu & Ha My T. Vy & Ishan Paranjpe & Joshua D. Backman & Tiffany R. Bellomo & William P. Bone & Kiran J. Biddinger & Qin Hui & Ozan Dikilitas, 2022. "Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    9. Nicole Deflaux & Margaret Sunitha Selvaraj & Henry Robert Condon & Kelsey Mayo & Sara Haidermota & Melissa A. Basford & Chris Lunt & Anthony A. Philippakis & Dan M. Roden & Joshua C. Denny & Anjene Mu, 2023. "Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    10. Isabelle Austin-Zimmerman & Daniel F. Levey & Olga Giannakopoulou & Joseph D. Deak & Marco Galimberti & Keyrun Adhikari & Hang Zhou & Spiros Denaxas & Haritz Irizar & Karoline Kuchenbaecker & Andrew M, 2023. "Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    11. Xiaofeng Zhu & Yihe Yang & Noah Lorincz-Comi & Gen Li & Amy R. Bentley & Paul S. de Vries & Michael Brown & Alanna C. Morrison & Charles N. Rotimi & W. James Gauderman & Dabeeru C. Rao & Hugues Aschar, 2024. "An approach to identify gene-environment interactions and reveal new biological insight in complex traits," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    12. Injeong Shim & Hiroyuki Kuwahara & NingNing Chen & Mais O. Hashem & Lama AlAbdi & Mohamed Abouelhoda & Hong-Hee Won & Pradeep Natarajan & Patrick T. Ellinor & Amit V. Khera & Xin Gao & Fowzan S. Alkur, 2023. "Clinical utility of polygenic scores for cardiometabolic disease in Arabs," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    13. H. Serhat Tetikol & Deniz Turgut & Kubra Narci & Gungor Budak & Ozem Kalay & Elif Arslan & Sinem Demirkaya-Budak & Alexey Dolgoborodov & Duygu Kabakci-Zorlu & Vladimir Semenyuk & Amit Jain & Brandi N., 2022. "Pan-African genome demonstrates how population-specific genome graphs improve high-throughput sequencing data analysis," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    14. Danielle Rasooly & Gina M. Peloso & Alexandre C. Pereira & Hesam Dashti & Claudia Giambartolomei & Eleanor Wheeler & Nay Aung & Brian R. Ferolito & Maik Pietzner & Eric H. Farber-Eger & Quinn Stanton , 2023. "Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    15. Mingxuan Cai & Zhiwei Wang & Jiashun Xiao & Xianghong Hu & Gang Chen & Can Yang, 2023. "XMAP: Cross-population fine-mapping by leveraging genetic diversity and accounting for confounding bias," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    16. Linda Ottensmann & Rubina Tabassum & Sanni E. Ruotsalainen & Mathias J. Gerl & Christian Klose & Elisabeth Widén & Kai Simons & Samuli Ripatti & Matti Pirinen, 2023. "Genome-wide association analysis of plasma lipidome identifies 495 genetic associations," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    17. Trejo, Sam, 2020. "Exploring Genetic Influences on Birth Weight," SocArXiv 7j59q, Center for Open Science.
    18. Tzu-Ting Chen & Jaeyoung Kim & Max Lam & Yi-Fang Chuang & Yen-Ling Chiu & Shu-Chin Lin & Sang-Hyuk Jung & Beomsu Kim & Soyeon Kim & Chamlee Cho & Injeong Shim & Sanghyeon Park & Yeeun Ahn & Aysu Okbay, 2024. "Shared genetic architectures of educational attainment in East Asian and European populations," Nature Human Behaviour, Nature, vol. 8(3), pages 562-575, March.
    19. Kaname Kojima & Shu Tadaka & Fumiki Katsuoka & Gen Tamiya & Masayuki Yamamoto & Kengo Kinoshita, 2020. "A genotype imputation method for de-identified haplotype reference information by using recurrent neural network," PLOS Computational Biology, Public Library of Science, vol. 16(10), pages 1-21, October.
    20. Sebastian Hendrix & Jenina Kingma & Roelof Ottenhoff & Masoud Valiloo & Monika Svecla & Lobke F. Zijlstra & Vinay Sachdev & Kristina Kovac & Johannes H. M. Levels & Aldo Jongejan & Jan F. Boer & Folke, 2023. "Hepatic SREBP signaling requires SPRING to govern systemic lipid metabolism in mice and humans," Nature Communications, Nature, vol. 14(1), pages 1-15, 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:13:y:2022:i:1:d:10.1038_s41467-022-32095-5. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.