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Sex differences in disease risk from reported genome-wide association study findings

Abstract

Men and women differ in susceptibility to many diseases and in responses to treatment. Recent advances in genome-wide association studies (GWAS) provide a wealth of data for associating genetic profiles with disease risk; however, in general, these data have not been systematically probed for sex differences in gene-disease associations. Incorporating sex into the analysis of GWAS results can elucidate new relationships between single nucleotide polymorphisms (SNPs) and human disease. In this study, we performed a sex-differentiated analysis on significant SNPs from GWAS data of the seven common diseases studied by the Wellcome Trust Case Control Consortium. We employed and compared three methods: logistic regression, Woolf’s test of heterogeneity, and a novel statistical metric that we developed called permutation method to assess sex effects (PMASE). After correction for false discovery, PMASE finds SNPs that are significantly associated with disease in only one sex. These sexually dimorphic SNP-disease associations occur in Coronary Artery Disease and Crohn’s Disease. GWAS analyses that fail to consider sex-specific effects may miss discovering sexual dimorphism in SNP-disease associations that give new insights into differences in disease mechanism between men and women.

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Acknowledgments

We acknowledge the following individuals and funding sources for their contribution to this work: Joel Dudley, Rong Chen, Alex Morgan, Michael Walker, Rita Popat, Rob Tibshirani, and Daniel Newburger. We thank Alex Skrenchuk and Boris Oskotsky from Stanford University for computer support. We acknowledge the Hewlett Packard Foundation and Lucile Packard Foundation for Children’s Health for financial support. We also thank the reviewers for their helpful comments. This study makes use of data generated by the Wellcome Trust Case–Control Consortium. A full list of the investigators who contributed to the generation of the data is available from www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 076113. This work was supported by the US National Institute of General Medical Sciences [R01 GM079719 to A.J.B.]; Hewlett Family Stanford Graduate Fellowship to L.Y.L.; National Science Foundation Graduate Research Fellowship to L.Y.L.; Richard and Naomi Horowitz Stanford Graduate Fellowship to M.A.S.; and US National Library of Medicine [T15 LM007033 to M.S.].

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The authors declare that there are no conflicts of interest related to this manuscript.

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Correspondence to Atul J. Butte.

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Liu, L.Y., Schaub, M.A., Sirota, M. et al. Sex differences in disease risk from reported genome-wide association study findings. Hum Genet 131, 353–364 (2012). https://doi.org/10.1007/s00439-011-1081-y

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Keywords

  • Disease Association
  • Wellcome Trust Case Control Consortium
  • False Discovery Rate Calculation
  • Common Control Group
  • Gene ATG16L1