IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0181038.html
   My bibliography  Save this article

Approaches to detect genetic effects that differ between two strata in genome-wide meta-analyses: Recommendations based on a systematic evaluation

Author

Listed:
  • Thomas W Winkler
  • Anne E Justice
  • L Adrienne Cupples
  • Florian Kronenberg
  • Zoltán Kutalik
  • Iris M Heid
  • the GIANT consortium

Abstract

Genome-wide association meta-analyses (GWAMAs) conducted separately by two strata have identified differences in genetic effects between strata, such as sex-differences for body fat distribution. However, there are several approaches to identify such differences and an uncertainty which approach to use. Assuming the availability of stratified GWAMA results, we compare various approaches to identify between-strata differences in genetic effects. We evaluate type I error and power via simulations and analytical comparisons for different scenarios of strata designs and for different types of between-strata differences. For strata of equal size, we find that the genome-wide test for difference without any filtering is the best approach to detect stratum-specific genetic effects with opposite directions, while filtering for overall association followed by the difference test is best to identify effects that are predominant in one stratum. When there is no a priori hypothesis on the type of difference, a combination of both approaches can be recommended. Some approaches violate type I error control when conducted in the same data set. For strata of unequal size, the best approach depends on whether the genetic effect is predominant in the larger or in the smaller stratum. Based on real data from GIANT (>175 000 individuals), we exemplify the impact of the approaches on the detection of sex-differences for body fat distribution (identifying up to 10 loci). Our recommendations provide tangible guidelines for future GWAMAs that aim at identifying between-strata differences. A better understanding of such effects will help pinpoint the underlying mechanisms.

Suggested Citation

  • Thomas W Winkler & Anne E Justice & L Adrienne Cupples & Florian Kronenberg & Zoltán Kutalik & Iris M Heid & the GIANT consortium, 2017. "Approaches to detect genetic effects that differ between two strata in genome-wide meta-analyses: Recommendations based on a systematic evaluation," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
  • Handle: RePEc:plo:pone00:0181038
    DOI: 10.1371/journal.pone.0181038
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0181038
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0181038&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0181038?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. James Y. Dai & Charles Kooperberg & Michael Leblanc & Ross L. Prentice, 2012. "Two-stage testing procedures with independent filtering for genome-wide gene-environment interaction," Biometrika, Biometrika Trust, vol. 99(4), pages 929-944.
    2. B. Devlin & Kathryn Roeder, 1999. "Genomic Control for Association Studies," Biometrics, The International Biometric Society, vol. 55(4), pages 997-1004, December.
    3. Bhramar Mukherjee & Jaeil Ahn & Stephen B. Gruber & Malay Ghosh & Nilanjan Chatterjee, 2010. "Case–Control Studies of Gene–Environment Interaction: Bayesian Design and Analysis," Biometrics, The International Biometric Society, vol. 66(3), pages 934-948, September.
    4. Dana B Hancock & María Soler Artigas & Sina A Gharib & Amanda Henry & Ani Manichaikul & Adaikalavan Ramasamy & Daan W Loth & Medea Imboden & Beate Koch & Wendy L McArdle & Albert V Smith & Joanna Smol, 2012. "Genome-Wide Joint Meta-Analysis of SNP and SNP-by-Smoking Interaction Identifies Novel Loci for Pulmonary Function," PLOS Genetics, Public Library of Science, vol. 8(12), pages 1-1, 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. Kenneth E. Westerman & Timothy D. Majarian & Franco Giulianini & Dong-Keun Jang & Jenkai Miao & Jose C. Florez & Han Chen & Daniel I. Chasman & Miriam S. Udler & Alisa K. Manning & Joanne B. Cole, 2022. "Variance-quantitative trait loci enable systematic discovery of gene-environment interactions for cardiometabolic serum biomarkers," Nature Communications, Nature, vol. 13(1), pages 1-11, December.

    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. Lei Zhang & Yu-Fang Pei & Jian Li & Christopher J Papasian & Hong-Wen Deng, 2009. "Univariate/Multivariate Genome-Wide Association Scans Using Data from Families and Unrelated Samples," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-12, August.
    2. Vincent Michaud & Eulalie Lasseaux & David J. Green & Dave T. Gerrard & Claudio Plaisant & Tomas Fitzgerald & Ewan Birney & Benoît Arveiler & Graeme C. Black & Panagiotis I. Sergouniotis, 2022. "The contribution of common regulatory and protein-coding TYR variants to the genetic architecture of albinism," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    3. Natalie DeForest & Yuqi Wang & Zhiyi Zhu & Jacqueline S. Dron & Ryan Koesterer & Pradeep Natarajan & Jason Flannick & Tiffany Amariuta & Gina M. Peloso & Amit R. Majithia, 2024. "Genome-wide discovery and integrative genomic characterization of insulin resistance loci using serum triglycerides to HDL-cholesterol ratio as a proxy," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    4. Parsa Akbari & Dragana Vuckovic & Luca Stefanucci & Tao Jiang & Kousik Kundu & Roman Kreuzhuber & Erik L. Bao & Janine H. Collins & Kate Downes & Luigi Grassi & Jose A. Guerrero & Stephen Kaptoge & Ju, 2023. "A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    5. Gang Zheng & Zhaohai Li & Mitchell H. Gail & Joseph L. Gastwirth, 2010. "Impact of Population Substructure on Trend Tests for Genetic Case–Control Association Studies," Biometrics, The International Biometric Society, vol. 66(1), pages 196-204, March.
    6. Jakris Eu-ahsunthornwattana & E Nancy Miller & Michaela Fakiola & Wellcome Trust Case Control Consortium 2 & Selma M B Jeronimo & Jenefer M Blackwell & Heather J Cordell, 2014. "Comparison of Methods to Account for Relatedness in Genome-Wide Association Studies with Family-Based Data," PLOS Genetics, Public Library of Science, vol. 10(7), pages 1-20, July.
    7. Matthieu Bouaziz & Christophe Ambroise & Mickael Guedj, 2011. "Accounting for Population Stratification in Practice: A Comparison of the Main Strategies Dedicated to Genome-Wide Association Studies," PLOS ONE, Public Library of Science, vol. 6(12), pages 1-13, December.
    8. Aditi Shendre & Howard W Wiener & Marguerite R Irvin & Bradley E Aouizerat & Edgar T Overton & Jason Lazar & Chenglong Liu & Howard N Hodis & Nita A Limdi & Kathleen M Weber & Stephen J Gange & Degui , 2017. "Genome-wide admixture and association study of subclinical atherosclerosis in the Women’s Interagency HIV Study (WIHS)," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-23, December.
    9. Li Shaoyu & Lu Qing & Fu Wenjiang & Romero Roberto & Cui Yuehua, 2009. "A Regularized Regression Approach for Dissecting Genetic Conflicts that Increase Disease Risk in Pregnancy," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-30, October.
    10. Ilja M Nolte & Chris Wallace & Stephen J Newhouse & Daryl Waggott & Jingyuan Fu & Nicole Soranzo & Rhian Gwilliam & Panos Deloukas & Irina Savelieva & Dongling Zheng & Chrysoula Dalageorgou & Martin F, 2009. "Common Genetic Variation Near the Phospholamban Gene Is Associated with Cardiac Repolarisation: Meta-Analysis of Three Genome-Wide Association Studies," PLOS ONE, Public Library of Science, vol. 4(7), pages 1-10, July.
    11. Nick Patterson & Alkes L Price & David Reich, 2006. "Population Structure and Eigenanalysis," PLOS Genetics, Public Library of Science, vol. 2(12), pages 1-20, December.
    12. Ferguson John P. & Palejev Dean, 2014. "P-value calibration for multiple testing problems in genomics," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(6), pages 659-673, December.
    13. Tiago C. Silva & Juan I. Young & Lanyu Zhang & Lissette Gomez & Michael A. Schmidt & Achintya Varma & X. Steven Chen & Eden R. Martin & Lily Wang, 2022. "Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    14. Takeshi Nishiyama & Hirohisa Kishino & Sadao Suzuki & Ryosuke Ando & Hideshi Niimura & Hirokazu Uemura & Mikako Horita & Keizo Ohnaka & Nagato Kuriyama & Haruo Mikami & Naoyuki Takashima & Keitaro Mas, 2012. "Detailed Analysis of Japanese Population Substructure with a Focus on the Southwest Islands of Japan," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-7, April.
    15. Zhao Huaqing & Rebbeck Timothy R. & Mitra Nandita, 2012. "Analyzing Genetic Association Studies with an Extended Propensity Score Approach," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(5), pages 1-24, October.
    16. Sophie A. Riesmeijer & Zoha Kamali & Michael Ng & Dmitriy Drichel & Bram Piersma & Kerstin Becker & Thomas B. Layton & Jagdeep Nanchahal & Michael Nothnagel & Ahmad Vaez & Hans Christian Hennies & Pau, 2024. "A genome-wide association meta-analysis implicates Hedgehog and Notch signaling in Dupuytren’s disease," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    17. repec:jss:jstsof:23:i08 is not listed on IDEAS
    18. Peng Chen & Rick Twee-Hee Ong & Wan-Ting Tay & Xueling Sim & Mohammad Ali & Haiyan Xu & Chen Suo & Jianjun Liu & Kee-Seng Chia & Eranga Vithana & Terri L Young & Tin Aung & Wei-Yen Lim & Chiea-Chuen K, 2013. "A Study Assessing the Association of Glycated Hemoglobin A1C (HbA1C) Associated Variants with HbA1C, Chronic Kidney Disease and Diabetic Retinopathy in Populations of Asian Ancestry," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-1, November.
    19. Dan E Arking & M Juhani Junttila & Philippe Goyette & Adriana Huertas-Vazquez & Mark Eijgelsheim & Marieke T Blom & Christopher Newton-Cheh & Kyndaron Reinier & Carmen Teodorescu & Audrey Uy-Evanado &, 2011. "Identification of a Sudden Cardiac Death Susceptibility Locus at 2q24.2 through Genome-Wide Association in European Ancestry Individuals," PLOS Genetics, Public Library of Science, vol. 7(6), pages 1-9, June.
    20. Feng Zhang & Yuping Wang & Hong-Wen Deng, 2008. "Comparison of Population-Based Association Study Methods Correcting for Population Stratification," PLOS ONE, Public Library of Science, vol. 3(10), pages 1-7, October.
    21. Robert C. Elston & Elizabeth A. Thompson, 2000. "A Century of Biometrical Genetics," Biometrics, The International Biometric Society, vol. 56(3), pages 659-666, September.

    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:plo:pone00:0181038. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.