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  • Review Article
  • Published:

The role of sex in the genomics of human complex traits

An Author Correction to this article was published on 28 June 2019

This article has been updated

Abstract

Nearly all human complex traits and disease phenotypes exhibit some degree of sex differences, including differences in prevalence, age of onset, severity or disease progression. Until recently, the underlying genetic mechanisms of such sex differences have been largely unexplored. Advances in genomic technologies and analytical approaches are now enabling a deeper investigation into the effect of sex on human health traits. In this Review, we discuss recent insights into the genetic models and mechanisms that lead to sex differences in complex traits. This knowledge is critical for developing deeper insight into the fundamental biology of sex differences and disease processes, thus facilitating precision medicine.

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Fig. 1: Factors contributing to phenotypic sex differences.
Fig. 2: Epidemiological insights into sex-biased disease prevalence and heritability from biobank and insurance claims data.
Fig. 3: GWAS loci identified on autosomes and the X chromosome.

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Change history

  • 28 June 2019

    In Box 4 of the originally published article, the text describing the Miami plot in part c of the figure contained some minor errors. Specifically, during pre-publication revision of the article, the authors updated the illustrative Miami plot (shown in figure part c) from that of reference 80 (Randall et al. PLoS Genet. (2013)) to a more recent study in reference 82 (Winkler et al. PLoS Genet. (2015)). The box text has now been updated to reflect that change. In paragraph 2, the trait has been updated from “hip circumference adjusted for body mass index” to “waist-to-hip ratio adjusted for body mass index (under 50 years old)” and it has been clarified that female GWAS data are shown on the top half of the plot with male data at the bottom. The original two citations of reference 80 in the Box 4 text have been updated to reference 82. Finally, a typographical artefact was corrected on the Y axis of the Miami plot, whereby the labels ‘14’ and ‘16’ in the top half of the plot we originally both shown as ‘12’. None of these corrections alter the overall illustrative point that genetic architectures for traits can differ between males and females, which was a conclusion of both reference 80 and reference 82.

References

  1. Centers for Disease Control and Prevention. CDC health disparities and inequalities report — United States, 2013. MMWR Suppl. 62, 1–189 (2013).

    Google Scholar 

  2. Clayton, J. A. Applying the new SABV (sex as a biological variable) policy to research and clinical care. Physiol. Behav. 187, 2–5 (2017). This seminal paper outlines the US National Institutes of Health policies for considering SABV in biomedical research, presents general guidelines on how to adhere to the policy and provides examples of how SABV impacts clinical care.

    PubMed  Google Scholar 

  3. Gao, F. et al. XWAS: a software toolset for genetic data analysis and association studies of the X chromosome. J. Hered. 106, 666–671 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Wise, A. L., Gyi, L. & Manolio, T. A. eXclusion: toward integrating the X chromosome in genome-wide association analyses. Am. J. Hum. Genet. 92, 643–647 (2013). This commentary explores the reasons underlying the relative lack of reported genetic associations on human ChrX, highlighting technical challenges, many of which are still relevant today.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Heidari, S., Babor, T. F., Castro, P. D., Tort, S. & Curno, M. Sex and gender equity in research: rationale for the SAGER guidelines and recommended use. Epidemiol. Serv. Saude 26, 665–675 (2017). Developed by a panel of experts representing nine countries, this paper outlines comprehensive guidelines for reporting of sex and gender information in study design, data analyses, results and interpretation of findings.

    PubMed  Google Scholar 

  6. [No authors listed.] Accounting for sex in the genome. Nat. Med 23, 1243 (2017).

  7. König, I. R., Loley, C., Erdmann, J. & Ziegler, A. How to include chromosome x in your genome-wide association study. Genet. Epidemiol. 38, 97–103 (2014).

    PubMed  Google Scholar 

  8. Wang, J., Talluri, R. & Shete, S. Selection of X-chromosome Inactivation Model. Cancer Inform. 16, 1176935117747272 (2017).

    PubMed  PubMed Central  Google Scholar 

  9. Webster, T. H. et al. Identifying, understanding, and correcting technical biases on the sex chromosomes in next-generation sequencing data Preprint at bioRxiv. https://doi.org/10.1101/346940 (2018).

    Article  Google Scholar 

  10. Arnold, A. P., Chen, X. & Itoh, Y. What a difference an X or Y makes: sex chromosomes, gene dose, and epigenetics in sexual differentiation. Handb. Exp. Pharmacol. 214, 67–88 (2012).

    CAS  Google Scholar 

  11. Arnold, A. P. Y chromosome’s roles in sex differences in disease. Proc. Natl Acad. Sci. USA 114, 3787–3789 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Zore, T., Palafox, M. & Reue, K. Sex differences in obesity, lipid metabolism, and inflammation — A role for the sex chromosomes? Mol. Metab. 15, 35–44 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Carter, C. O. & Evans, K. A. Inheritance of congenital pyloric stenosis. J. Med. Genet. 6, 233–254 (1969). This classic paper defines the sex-dependent liability threshold model based on evidence from patients with pyloric stenosis.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Carter, C. O. The inheritance of congenital pyloric stenosis. Br. Med. Bull 17, 251–254 (1961).

    CAS  PubMed  Google Scholar 

  15. Robinson, E. B., Lichtenstein, P., Anckarsäter, H., Happé, F. & Ronald, A. Examining and interpreting the female protective effect against autistic behavior. Proc. Natl Acad. Sci. USA 110, 5258–5262 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Rhee, S. H. & Waldman, I. D. Etiology of sex differences in the prevalence of ADHD: An examination of inattention and hyperactivity — impulsivity. Am. J. Med. Genet. B Neuropsychiatr. Genet. 127, 60–64 (2004).

    Google Scholar 

  17. Taylor, M. J. et al. Is there a female protective effect against attention-deficit/hyperactivity disorder? evidence from two representative twin samples. J. Am. Acad. Child Adolesc. Psychiatry 55, 504–512 (2016).

    PubMed  PubMed Central  Google Scholar 

  18. Kruse, L. M., Buchan, J. G., Gurnett, C. A. & Dobbs, M. B. Polygenic threshold model with sex dimorphism in adolescent idiopathic scoliosis: the Carter effect. J. Bone Joint Surg. Am. 94, 1485–1491 (2012).

    PubMed  Google Scholar 

  19. Kantarci, O. H. et al. Men transmit MS more often to their children vs women: the Carter effect. Neurology 67, 305–310 (2006).

    CAS  PubMed  Google Scholar 

  20. Ge, T., Chen, C.-Y., Neale, B. M., Sabuncu, M. R. & Smoller, J. W. Phenome-wide heritability analysis of the UK Biobank. PLOS Genet. 13, e1006711 (2017). This is one of the first studies analysing a large population-based cohort to estimate heritabilities of over 550 phenotypes and to identify traits for which heritabilities are moderated by age, sex and socio-economic status.

    PubMed  PubMed Central  Google Scholar 

  21. Wang, K., Gaitsch, H., Poon, H., Cox, N. J. & Rzhetsky, A. Classification of common human diseases derived from shared genetic and environmental determinants. Nat. Genet. 49, 1319–1325 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Stringer, S., Polderman, T. & Posthuma, D. Majority of human traits do not show evidence for sex-specific genetic and environmental effects. Sci. Rep. 7, 8688 (2017). This meta-analysis of 2,335,920 twin pairs and over 2,600 phenotypes reports that only a small portion of human traits exhibit significant sex differences in heritability.

    PubMed  PubMed Central  Google Scholar 

  23. Polderman, T. J. C. et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat. Genet. 47, 702–709 (2015).

    CAS  PubMed  Google Scholar 

  24. Traglia, M. et al. Genetic mechanisms leading to sex differences across common diseases and anthropometric traits. Genetics 205, 979–992 (2017). This is one of the first studies to comprehensively evaluate multiple genetic models for evidence of their contribution to sex differences in several diseases and anthropometric traits.

    CAS  PubMed  Google Scholar 

  25. Rawlik, K., Canela-Xandri, O. & Tenesa, A. Evidence for sex-specific genetic architectures across a spectrum of human complex traits. Genome Biol. 17, 166 (2016).

    PubMed  PubMed Central  Google Scholar 

  26. Vink, J. M. et al. Sex differences in genetic architecture of complex phenotypes? PLOS ONE 7, e47371 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Duncan, L. E. et al. Largest GWAS of PTSD (N = 20 070) yields genetic overlap with schizophrenia and sex differences in heritability. Mol. Psychiatry 23, 666–673 (2017).

    PubMed  PubMed Central  Google Scholar 

  28. Sartor, C. E. et al. Common genetic and environmental contributions to post-traumatic stress disorder and alcohol dependence in young women. Psychol. Med. 41, 1497–1505 (2011).

    CAS  PubMed  Google Scholar 

  29. Kalgotra, P., Sharda, R. & Croff, J. M. Examining health disparities by gender: a multimorbidity network analysis of electronic medical record. Int. J. Med. Inform. 108, 22–28 (2017).

    PubMed  Google Scholar 

  30. Martin, J. et al. A genetic investigation of sex bias in the prevalence of attention-deficit/hyperactivity disorder. Biol. Psychiatry 83, 1044–1053 (2017).

    PubMed  Google Scholar 

  31. Gilks, W. P., Abbott, J. K. & Morrow, E. H. Sex differences in disease genetics: evidence, evolution, and detection. Trends Genet. 30, 453–463 (2014).

    CAS  PubMed  Google Scholar 

  32. Davies, W. Genomic imprinting on the X chromosome: implications for brain and behavioral phenotypes. Ann. N.Y. Acad. Sci. 1204, E14–E19 (2010).

    PubMed  Google Scholar 

  33. Tukiainen, T. et al. Landscape of X chromosome inactivation across human tissues. Nature 550, 244–248 (2017). This important study demonstrates that both escape from XCI and incomplete XCI, which affect a portion of ChrX genes, result in sex-biased gene expression across human tissues.

    PubMed  PubMed Central  Google Scholar 

  34. Carrel, L. & Willard, H. F. X-inactivation profile reveals extensive variability in X-linked gene expression in females. Nature 434, 400–404 (2005).

    CAS  PubMed  Google Scholar 

  35. Raznahan, A. et al. Sex-chromosome dosage effects on gene expression in humans. Proc. Natl Acad. Sci. USA 115, 7398–7403 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Alvarez-Nava, F. et al. Effect of the parental origin of the X-chromosome on the clinical features, associated complications, the two-year-response to growth hormone (rhGH) and the biochemical profile in patients with turner syndrome. Int. J. Pediatr. Endocrinol. 2013, 10 (2013).

    PubMed  PubMed Central  Google Scholar 

  37. Sawalha, A. H., Harley, J. B. & Scofield, R. H. Autoimmunity and Klinefelter’s syndrome: when men have two X chromosomes. J. Autoimmun. 33, 31–34 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Burgoyne, P. S. & Arnold, A. P. A primer on the use of mouse models for identifying direct sex chromosome effects that cause sex differences in non-gonadal tissues. Biol. Sex. Differ. 7, 68 (2016).

    PubMed  PubMed Central  Google Scholar 

  39. Burdett, T. et al. GWAS catalog: the NHGRI-EBI catalog of published genome-wide association studies. EBI www.ebi.ac.uk/gwas (2016).

  40. MacArthur, J. et al. The new NHGRI-EBI catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res. 45, D896–D901 (2017).

    CAS  PubMed  Google Scholar 

  41. Chang, D. et al. Accounting for eXentricities: analysis of the X chromosome in GWAS reveals X-linked genes implicated in autoimmune diseases. PLOS ONE 9, e113684 (2014). This article reports a novel software package for XWAS and applies it to 16 autoimmune and related phenotypes.

    PubMed  PubMed Central  Google Scholar 

  42. Lee, J. J. et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat. Genet. 50, 1112–1121 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Tukiainen, T. et al. Chromosome X-wide association study identifies Loci for fasting insulin and height and evidence for incomplete dosage compensation. PLOS Genet. 10, e1004127 (2014).

    PubMed  PubMed Central  Google Scholar 

  44. Charchar, F. J. et al. Inheritance of coronary artery disease in men: an analysis of the role of the Y chromosome. Lancet 379, 915–922 (2012). Using ChrY phylogenetic tree analysis, this study reports a role of the Y haplogroup I in coronary artery disease in men.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Sezgin, E. et al. Association of Y chromosome haplogroup I with HIV progression, and HAART outcome. Hum. Genet. 125, 281–294 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Krementsov, D. N. et al. Genetic variation in chromosome Y regulates susceptibility to influenza A virus infection. Proc. Natl Acad. Sci. USA 114, 3491–3496 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Case, L. K. et al. Chromosome y regulates survival following murine coxsackievirus b3 infection. G3 (Bethesda) 2, 115–121 (2012).

    CAS  Google Scholar 

  48. Case, L. K. et al. The Y chromosome as a regulatory element shaping immune cell transcriptomes and susceptibility to autoimmune disease. Genome Res. 23, 1474–1485 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Eng, A. et al. Gender differences in occupational exposure patterns. Occup. Environ. Med. 68, 888–894 (2011).

    PubMed  Google Scholar 

  50. Allen, A. M., Scheuermann, T. S., Nollen, N., Hatsukami, D. & Ahluwalia, J. S. Gender differences in smoking behavior and dependence motives among daily and nondaily smokers. Nicotine Tob. Res. 18, 1408–1413 (2016).

    PubMed  Google Scholar 

  51. Campos-Serna, J., Ronda-Pérez, E., Artazcoz, L., Moen, B. E. & Benavides, F. G. Gender inequalities in occupational health related to the unequal distribution of working and employment conditions: a systematic review. Int. J. Equity Health 12, 57 (2013).

    PubMed  PubMed Central  Google Scholar 

  52. Moorman, J. E. et al. Vital and health statistics, series 3, number 35: national surveillance of asthma: United States, 2001-2010. CDC https://www.cdc.gov/nchs/data/series/sr_03/sr03_035.pdf (2012).

  53. Zein, J. G. & Erzurum, S. C. Asthma is different in women. Curr. Allergy Asthma Rep. 15, 28 (2015).

    PubMed  PubMed Central  Google Scholar 

  54. Haast, R. A. M., Gustafson, D. R. & Kiliaan, A. J. Sex differences in stroke. J. Cereb. Blood Flow Metab. 32, 2100–2107 (2012).

    PubMed  PubMed Central  Google Scholar 

  55. Murphy, V. E. & Gibson, P. G. Premenstrual asthma: prevalence, cycle-to-cycle variability and relationship to oral contraceptive use and menstrual symptoms. J. Asthma 45, 696–704 (2008).

    PubMed  Google Scholar 

  56. Murphy, V. E., Clifton, V. L. & Gibson, P. G. Asthma exacerbations during pregnancy: incidence and association with adverse pregnancy outcomes. Thorax 61, 169–176 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Forray, A., Focseneanu, M., Pittman, B., McDougle, C. J. & Epperson, C. N. Onset and exacerbation of obsessive-compulsive disorder in pregnancy and the postpartum period. J. Clin. Psychiatry 71, 1061–1068 (2010).

    PubMed  PubMed Central  Google Scholar 

  58. Guglielmi, V. et al. Obsessive-compulsive disorder and female reproductive cycle events: results from the OCD and reproduction collaborative study. Depress. Anxiety 31, 979–987 (2014).

    PubMed  Google Scholar 

  59. Soares, C. N. & Zitek, B. Reproductive hormone sensitivity and risk for depression across the female life cycle: a continuum of vulnerability? J. Psychiatry Neurosci. 33, 331–343 (2008).

    PubMed  PubMed Central  Google Scholar 

  60. Schiller, C. E., Meltzer-Brody, S. & Rubinow, D. R. The role of reproductive hormones in postpartum depression. CNS Spectr. 20, 48–59 (2015).

    PubMed  Google Scholar 

  61. Klein, S. L. & Flanagan, K. L. Sex differences in immune responses. Nat. Rev. Immunol. 16, 626–638 (2016).

    CAS  PubMed  Google Scholar 

  62. Cephus, J.-Y. et al. Testosterone attenuates group 2 innate lymphoid cell-mediated airway inflammation. Cell Rep. 21, 2487–2499 (2017). This study reports a mechanism by which testosterone regulates immune cells involved in the development of asthma and thus acts as a protective mechanism in males.

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Patsopoulos, N. A., Tatsioni, A. & Ioannidis, J. P. A. Claims of sex differences: an empirical assessment in genetic associations. JAMA 298, 880–893 (2007).

    CAS  PubMed  Google Scholar 

  64. Krohn, J. et al. Genetic interactions with sex make a relatively small contribution to the heritability of complex traits in mice. PLOS ONE 9, e96450 (2014).

    PubMed  PubMed Central  Google Scholar 

  65. Schaafsma, S. M. et al. Sex-specific gene–environment interactions underlying ASD-like behaviors. Proc. Natl Acad. Sci. USA 114, 1383–1388 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Havill, L. M., Mahaney, M. C. & Rogers, J. Genotype-by-sex and environment-by-sex interactions influence variation in serum levels of bone-specific alkaline phosphatase in adult baboons (Papio hamadryas). Bone 35, 198–203 (2004).

    CAS  PubMed  Google Scholar 

  67. Bearoff, F. et al. Identification of genetic determinants of the sexual dimorphism in CNS autoimmunity. PLOS ONE 10, e0117993 (2015).

    PubMed  PubMed Central  Google Scholar 

  68. Parks, B. W. et al. Genetic architecture of insulin resistance in the mouse. Cell Metab. 21, 334–346 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Nuzhdin, S. V., Pasyukova, E. G., Dilda, C. L., Zeng, Z. B. & Mackay, T. F. Sex-specific quantitative trait loci affecting longevity in Drosophila melanogaster. Proc. Natl Acad. Sci. USA 94, 9734–9739 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Boraska, V. et al. Genome-wide meta-analysis of common variant differences between men and women. Hum. Mol. Genet. 21, 4805–4815 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Desachy, G. et al. Increased female autosomal burden of rare copy number variants in human populations and in autism families. Mol. Psychiatry 20, 170–175 (2015).

    CAS  PubMed  Google Scholar 

  72. Han, J. et al. Gender differences in CNV burden do not confound schizophrenia CNV associations. Sci. Rep. 6, 25986 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Barson, N. J. et al. Sex-dependent dominance at a single locus maintains variation in age at maturity in salmon. Nature 528, 405–408 (2015).

    CAS  PubMed  Google Scholar 

  74. Hawkes, M. F. et al. Intralocus sexual conflict and insecticide resistance. Proc. Biol. Sci. 283, 20161429 (2016).

    PubMed  PubMed Central  Google Scholar 

  75. Foerster, K. et al. Sexually antagonistic genetic variation for fitness in red deer. Nature 447, 1107–1110 (2007).

    CAS  PubMed  Google Scholar 

  76. Johnston, S. E. et al. Life history trade-offs at a single locus maintain sexually selected genetic variation. Nature 502, 93–95 (2013).

    CAS  PubMed  Google Scholar 

  77. Mank, J. E. Population genetics of sexual conflict in the genomic era. Nat. Rev. Genet. 18, 721–730 (2017).

    CAS  PubMed  Google Scholar 

  78. Mitra, I. et al. Pleiotropic mechanisms indicated for sex differences in autism. PLOS Genet. 12, e1006425 (2016). This is one of the first studies to comprehensively test multiple genetic models that might contribute to sex differences in autism spectrum disorder.

    PubMed  PubMed Central  Google Scholar 

  79. Taylor, K. C. et al. Investigation of gene-by-sex interactions for lipid traits in diverse populations from the population architecture using genomics and epidemiology study. BMC Genet. 14, 33 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Randall, J. C. et al. Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits. PLOS Genet. 9, e1003500 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Myers, R. A. et al. Genome-wide interaction studies reveal sex-specific asthma risk alleles. Hum. Mol. Genet. 23, 5251–5259 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  82. Winkler, T. W. et al. The influence of age and sex on genetic associations with adult body size and shape: a large-scale genome-wide interaction study. PLOS Genet. 11, e1005378 (2015). As a follow-up to reference 80, this work is one of the first to provide evidence for sexually differentiated genetic architecture of anthropometric traits, specifically reporting cases of opposite effects at individual loci.

    PubMed  PubMed Central  Google Scholar 

  83. Pulit, S. L. et al. Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry. Hum. Mol. Genet. https://doi.org/10.1093/hmg/ddy327 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Liu, L. Y., Schaub, M. A., Sirota, M. & Butte, A. J. Sex differences in disease risk from reported genome-wide association study findings. Hum. Genet. 131, 353–364 (2012).

    PubMed  Google Scholar 

  85. Hartiala, J. A. et al. Genome-wide association study and targeted metabolomics identifies sex-specific association of CPS1 with coronary artery disease. Nat. Commun. 7, 10558 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Orozco, G., Ioannidis, J. P. A., Morris, A., Zeggini, E. & The DIAGRAM consortium. Sex-specific differences in effect size estimates at established complex trait loci. Int. J. Epidemiol. 41, 1376–1382 (2012).

    PubMed  PubMed Central  Google Scholar 

  87. Zhuang, J. J. & Morris, A. P. Assessment of sex-specific effects in a genome-wide association study of rheumatoid arthritis. BMC Proc. 3 (Suppl. 7), S90 (2009).

    PubMed  PubMed Central  Google Scholar 

  88. Singh, S. K. et al. A childhood acute lymphoblastic leukemia genome-wide association study identifies novel sex-specific risk variants. Medicine 95, e5300 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  89. Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Zheng, J. et al. LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics 33, 272–279 (2017).

    CAS  PubMed  Google Scholar 

  91. The Brainstorm Consortium. Analysis of shared heritability in common disorders of the brain. Science 360, eaap8757 (2018).

    PubMed Central  Google Scholar 

  92. Heid, I. M. et al. Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nat. Genet. 42, 949–960 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  93. Do, R. et al. Common variants associated with plasma triglycerides and risk for coronary artery disease. Nat. Genet. 45, 1345–1352 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Andreassen, O. A. et al. Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: differential involvement of immune-related gene loci. Mol. Psychiatry 20, 207–214 (2015).

    CAS  PubMed  Google Scholar 

  95. Rahmioglu, N. et al. Genome-wide enrichment analysis between endometriosis and obesity-related traits reveals novel susceptibility loci. Hum. Mol. Genet. 24, 1185–1199 (2015).

    CAS  PubMed  Google Scholar 

  96. Khramtsova, E. A. et al. Sex Differences in the Genetic Architecture of Obsessive-Compulsive Disorder. Am. J. Med. Genet. B Neuropsychiatr. Genet. https://doi.org/10.1002/ajmg.b.32687 (2018).

    Article  Google Scholar 

  97. Ayroles, J. F. et al. Systems genetics of complex traits in Drosophila melanogaster. Nat. Genet. 41, 299–307 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  98. Cheng, C. & Kirkpatrick, M. Environmental plasticity in the intersexual correlation and sex bias of gene expression. J. Hered. 108, 754–758 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  99. Seo, M. et al. Comprehensive identification of sexually dimorphic genes in diverse cattle tissues using RNA-seq. BMC Genomics 17, 81 (2016).

    PubMed  PubMed Central  Google Scholar 

  100. Mayne, B. T. et al. Large scale gene expression meta-analysis reveals tissue-specific, sex-biased gene expression in humans. Front. Genet. 7, 183 (2016). This is a large-scale meta-analysis of human sex-biased gene expression from 22 publicly available data sets including over 2,500 samples from 15 different tissues and 9 different organs.

    PubMed  PubMed Central  Google Scholar 

  101. Melé, M. et al. Human genomics. The human transcriptome across tissues and individuals. Science 348, 660–665 (2015).

    PubMed  Google Scholar 

  102. Chen, C. Y., Lopes-Ramos, C. M., Kuijjer, M. L. & Paulson, J. N. Sexual dimorphism in gene expression and regulatory networks across human tissues. Preprint at bioRxiv https://doi.org/10.1101/082289 (2016).

    Article  Google Scholar 

  103. Gershoni, M. & Pietrokovski, S. The landscape of sex-differential transcriptome and its consequent selection in human adults. BMC Biol. 15, 7 (2017).

    PubMed  PubMed Central  Google Scholar 

  104. Zhang, Y. et al. Transcriptional profiling of human liver identifies sex-biased genes associated with polygenic dyslipidemia and coronary artery disease. PLOS ONE 6, e23506 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  105. Welle, S., Tawil, R. & Thornton, C. A. Sex-related differences in gene expression in human skeletal muscle. PLOS ONE 3, e1385 (2008).

    PubMed  PubMed Central  Google Scholar 

  106. Trabzuni, D. et al. Widespread sex differences in gene expression and splicing in the adult human brain. Nat. Commun. 4, 2771 (2013). This study reports widespread sex-biased gene expression in 12 regions of the human brain.

    PubMed  Google Scholar 

  107. Jansen, R. et al. Sex differences in the human peripheral blood transcriptome. BMC Genomics 15, 33 (2014). This study describes sex differences in the whole-blood transcriptome of over 5,200 study participants, revealing differential expression of genes from both autosomes and sex chromosomes.

    PubMed  PubMed Central  Google Scholar 

  108. Ecker, S. et al. Genome-wide analysis of differential transcriptional and epigenetic variability across human immune cell types. Genome Biol. 18, 18 (2017).

    PubMed  PubMed Central  Google Scholar 

  109. Zhang, W., Bleibel, W. K., Roe, C. A., Cox, N. J. & Eileen Dolan, M. Gender-specific differences in expression in human lymphoblastoid cell lines. Pharmacogenet. Genomics 17, 447–450 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  110. McRae, A. F. et al. Replicated effects of sex and genotype on gene expression in human lymphoblastoid cell lines. Hum. Mol. Genet. 16, 364–373 (2007).

    CAS  PubMed  Google Scholar 

  111. Johnston, C. M. et al. Large-scale population study of human cell lines indicates that dosage compensation is virtually complete. PLOS Genet. 4, e9 (2008).

    PubMed  PubMed Central  Google Scholar 

  112. Shi, L., Zhang, Z. & Su, B. Sex biased gene expression profiling of human brains at major developmental stages. Sci. Rep. 6, 21181 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  113. Ma, J., Malladi, S. & Beck, A. H. Systematic analysis of sex-linked molecular alterations and therapies in cancer. Sci. Rep. 6, 19119 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  114. Labonté, B. et al. Sex-specific transcriptional signatures in human depression. Nat. Med. 23, 1102–1111 (2017). This study reports the remodelling of human brain transcriptional profiles in major depression, with little overlap in the alterations occurring in males and females.

    PubMed  PubMed Central  Google Scholar 

  115. Qin, W., Liu, C., Sodhi, M. & Lu, H. Meta-analysis of sex differences in gene expression in schizophrenia. BMC Syst. Biol. 10 (Suppl. 1), 9 (2016).

    PubMed  PubMed Central  Google Scholar 

  116. Mennecozzi, M., Landesmann, B., Palosaari, T., Harris, G. & Whelan, M. Sex differences in liver toxicity—do female and male human primary hepatocytes react differently to toxicants in vitro? PLOS ONE 10, e0122786 (2015).

    PubMed  PubMed Central  Google Scholar 

  117. Furman, D. et al. Systems analysis of sex differences reveals an immunosuppressive role for testosterone in the response to influenza vaccination. Proc. Natl Acad. Sci. USA 111, 869–874 (2014).

    CAS  PubMed  Google Scholar 

  118. Ngo, S. T., Steyn, F. J. & McCombe, P. A. Gender differences in autoimmune disease. Front. Neuroendocrinol. 35, 347–369 (2014).

    CAS  PubMed  Google Scholar 

  119. Yang, X. et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res. 16, 995–1004 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  120. Mank, J. E., Hultin-Rosenberg, L., Webster, M. T. & Ellegren, H. The unique genomic properties of sex-biased genes: insights from avian microarray data. BMC Genomics 9, 148 (2008).

    PubMed  PubMed Central  Google Scholar 

  121. Bouman, A., Heineman, M. J. & Faas, M. M. Sex hormones and the immune response in humans. Hum. Reprod. Update 11, 411–423 (2005).

    CAS  PubMed  Google Scholar 

  122. Manning, K. S. & Cooper, T. A. The roles of RNA processing in translating genotype to phenotype. Nat. Rev. Mol. Cell. Biol. 18, 102–114 (2017).

    CAS  PubMed  Google Scholar 

  123. Gamazon, E. R. & Stranger, B. E. Genomics of alternative splicing: evolution, development and pathophysiology. Hum. Genet. 133, 679–687 (2014).

    CAS  PubMed  Google Scholar 

  124. Li, Y. I. et al. RNA splicing is a primary link between genetic variation and disease. Science 352, 600–604 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  125. Lindholm, M. E. et al. The human skeletal muscle transcriptome: sex differences, alternative splicing, and tissue homogeneity assessed with RNA sequencing. FASEB J. 28, 4571–4581 (2014).

    CAS  PubMed  Google Scholar 

  126. Blekhman, R., Marioni, J. C., Zumbo, P., Stephens, M. & Gilad, Y. Sex-specific and lineage-specific alternative splicing in primates. Genome Res. 20, 180–189 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  127. The Johns Hopkins University School of Medicine. Online Mendelian Inheritance in Man®: an online catalog of human genes and genetic disorders. OMIM https://omim.org/ (2018).

  128. Nicolae, D. L. et al. Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLOS Genet. 6, e1000888 (2010).

    PubMed  PubMed Central  Google Scholar 

  129. Nica, A. C. et al. Candidate causal regulatory effects by integration of expression QTLs with complex trait genetic associations. PLOS Genet. 6, e1000895 (2010).

    PubMed  PubMed Central  Google Scholar 

  130. GTEx Consortium et al. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).

    PubMed Central  Google Scholar 

  131. Kasela, S. et al. Pathogenic implications for autoimmune mechanisms derived by comparative eQTL analysis of CD4+versus CD8+T cells. PLOS Genet. 13, e1006643 (2017).

    PubMed  PubMed Central  Google Scholar 

  132. Lee, M. N. et al. Common genetic variants modulate pathogen-sensing responses in human dendritic cells. Science 343, 1246980 (2014).

    PubMed  PubMed Central  Google Scholar 

  133. Takata, A., Matsumoto, N. & Kato, T. Genome-wide identification of splicing QTLs in the human brain and their enrichment among schizophrenia-associated loci. Nat. Commun. 8, 14519 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  134. Chen, L. et al. Genetic drivers of epigenetic and transcriptional variation in human immune cells. Cell 167, 1398–1414 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  135. Fairfax, B. P. et al. Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression. Science 343, 1246949 (2014).

    PubMed  PubMed Central  Google Scholar 

  136. Kim-Hellmuth, S. et al. Genetic regulatory effects modified by immune activation contribute to autoimmune disease associations. Nat. Commun. 8, 266 (2017).

    PubMed  PubMed Central  Google Scholar 

  137. Ye, C. J. et al. Intersection of population variation and autoimmunity genetics in human T cell activation. Science 345, 1254665 (2014).

    PubMed  PubMed Central  Google Scholar 

  138. Stranger, B. E. & Raj, T. Genetics of human gene expression. Curr. Opin. Genet. Dev. 23, 627–634 (2013).

    CAS  PubMed  Google Scholar 

  139. Raj, T. et al. Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes. Science 344, 519–523 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  140. Stranger, B. E. et al. Population genomics of human gene expression. Nat. Genet. 39, 1217–1224 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  141. Lappalainen, T. et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501, 506–511 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  142. Grundberg, E. et al. Mapping cis- and trans-regulatory effects across multiple tissues in twins. Nat. Genet. 44, 1084–1089 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  143. Nica, A. C. et al. The architecture of gene regulatory variation across multiple human tissues: the MuTHER study. PLOS Genet. 7, e1002003 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  144. Pala, M. et al. Population- and individual-specific regulatory variation in Sardinia. Nat. Genet. 49, 700–707 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  145. Kwan, T. et al. Tissue effect on genetic control of transcript isoform variation. PLOS Genet. 5, e1000608 (2009).

    PubMed  PubMed Central  Google Scholar 

  146. Gutierrez-Arcelus, M. et al. Tissue-specific effects of genetic and epigenetic variation on gene regulation and splicing. PLOS Genet. 11, e1004958 (2015).

    PubMed  PubMed Central  Google Scholar 

  147. Yao, C. et al. Sex- and age-interacting eQTLs in human complex diseases. Hum. Mol. Genet. 23, 1947–1956 (2014).

    CAS  PubMed  Google Scholar 

  148. Kukurba, K. R. et al. Impact of the X Chromosome and sex on regulatory variation. Genome Res. 26, 768–777 (2016). This study characterizes human whole blood cis-eQTLs and SNP-by-sex interaction eQTLs on ChrX and autosomes and the relationship to sex-biased chromatin accessibility.

    CAS  PubMed  PubMed Central  Google Scholar 

  149. Lindén, M. et al. Sex influences eQTL effects of SLE and Sjögren’s syndrome-associated genetic polymorphisms. Biol. Sex. Differ. 8, 34 (2017).

    PubMed  PubMed Central  Google Scholar 

  150. Dimas, A. S. et al. Sex-biased genetic effects on gene regulation in humans. Genome Res. 22, 2368–2375 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  151. Welter, D. et al. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res. 42, D1001–D1006 (2014).

    CAS  PubMed  Google Scholar 

  152. Awadalla, P. et al. Cohort profile of the CARTaGENE study: Quebec’s population-based biobank for public health and personalized genomics. Int. J. Epidemiol. 42, 1285–1299 (2013).

    PubMed  Google Scholar 

  153. Hussin, J. G. et al. Recombination affects accumulation of damaging and disease-associated mutations in human populations. Nat. Genet. 47, 400–404 (2015).

    CAS  PubMed  Google Scholar 

  154. Westra, H.-J. et al. Cell specific eQTL analysis without sorting cells. PLOS Genet. 11, e1005223 (2015).

    PubMed  PubMed Central  Google Scholar 

  155. Naranbhai, V. et al. Genomic modulators of gene expression in human neutrophils. Nat. Commun. 6, 7545 (2015).

    PubMed  Google Scholar 

  156. Chen, Y. et al. Difference in leukocyte composition between women before and after menopausal age, and distinct sexual dimorphism. PLOS ONE 11, e0162953 (2016).

    PubMed  PubMed Central  Google Scholar 

  157. Kassam, I. et al. Autosomal genetic control of human gene expression does not differ across the sexes. Genome Biol. 17, 248 (2016).

    PubMed  PubMed Central  Google Scholar 

  158. Xu, X. et al. Modular genetic control of sexually dimorphic behaviors. Cell 148, 596–607 (2012). In addition to demonstrating sex-biased gene expression in mouse brain, this study demonstrates that targeted disruption of sex-biased genes impacts sexually differentiated behaviours.

    CAS  PubMed  PubMed Central  Google Scholar 

  159. Quinn, M. A. & Cidlowski, J. A. Endogenous hepatic glucocorticoid receptor signaling coordinates sex-biased inflammatory gene expression. FASEB J. 30, 971–982 (2016).

    CAS  PubMed  Google Scholar 

  160. Gomez-Santos, C. et al. Profile of adipose tissue gene expression in premenopausal and postmenopausal women: site-specific differences. Menopause 18, 675–684 (2011).

    PubMed  Google Scholar 

  161. Kósa, J. P. et al. Effect of menopause on gene expression pattern in bone tissue of nonosteoporotic women. Menopause 16, 367–377 (2009).

    PubMed  Google Scholar 

  162. Zhu, M.-L. et al. Sex bias in CNS autoimmune disease mediated by androgen control of autoimmune regulator. Nat. Commun. 7, 11350 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  163. Boks, M. P. et al. The relationship of DNA methylation with age, gender and genotype in twins and healthy controls. PLOS ONE 4, e6767 (2009).

    PubMed  PubMed Central  Google Scholar 

  164. Tapp, H. S. et al. Nutritional factors and gender influence age-related DNA methylation in the human rectal mucosa. Aging Cell 12, 148–155 (2013).

    CAS  PubMed  Google Scholar 

  165. Liu, J., Morgan, M., Hutchison, K. & Calhoun, V. D. A study of the influence of sex on genome wide methylation. PLOS ONE 5, e10028 (2010).

    PubMed  PubMed Central  Google Scholar 

  166. Hall, E. et al. Sex differences in the genome-wide DNA methylation pattern and impact on gene expression, microRNA levels and insulin secretion in human pancreatic islets. Genome Biol. 15, 522 (2014).

    PubMed  PubMed Central  Google Scholar 

  167. McCormick, H. et al. Isogenic mice exhibit sexually-dimorphic DNA methylation patterns across multiple tissues. BMC Genomics 18, 966 (2017).

    PubMed  PubMed Central  Google Scholar 

  168. Singmann, P. et al. Characterization of whole-genome autosomal differences of DNA methylation between men and women. Epigenetics Chromatin 8, 43 (2015). Analysing whole blood, this important study reports thousands of sexually differentiated DNA methylation sites, which are enriched among imprinted genes.

    PubMed  PubMed Central  Google Scholar 

  169. van Dongen, J. et al. Genetic and environmental influences interact with age and sex in shaping the human methylome. Nat. Commun. 7, 11115 (2016).

    PubMed  PubMed Central  Google Scholar 

  170. VanderKraats, N. D., Hiken, J. F., Decker, K. F. & Edwards, J. R. Discovering high-resolution patterns of differential DNA methylation that correlate with gene expression changes. Nucleic Acids Res. 41, 6816–6827 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  171. Ling, G., Sugathan, A., Mazor, T., Fraenkel, E. & Waxman, D. J. Unbiased, genome-wide in vivo mapping of transcriptional regulatory elements reveals sex differences in chromatin structure associated with sex-specific liver gene expression. Mol. Cell. Biol. 30, 5531–5544 (2010). This study characterizes sex-biased DNase occupancy in mouse liver associated with sex-biased gene expression and shows how chromatin accessibility can be altered by sex hormones.

    CAS  PubMed  PubMed Central  Google Scholar 

  172. Sugathan, A. & Waxman, D. J. Genome-wide analysis of chromatin states reveals distinct mechanisms of sex-dependent gene regulation in male and female mouse liver. Mol. Cell. Biol. 33, 3594–3610 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  173. Thakur, M. K., Asaithambi, A. & Mukherjee, S. Sex-specific alterations in chromatin conformation of the brain of aging mouse. Mol. Biol. Rep. 26, 239–247 (1999).

    CAS  PubMed  Google Scholar 

  174. Arnold, A. P. & Lusis, A. J. Understanding the sexome: measuring and reporting sex differences in gene systems. Endocrinology 153, 2551–2555 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  175. de Vries, G. J. & Forger, N. G. Sex differences in the brain: a whole body perspective. Biol. Sex. Differ. 6, 15 (2015).

    PubMed  PubMed Central  Google Scholar 

  176. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014).

    PubMed Central  Google Scholar 

  177. Furtado, M. & Katzman, M. A. Neuroinflammatory pathways in anxiety, posttraumatic stress, and obsessive compulsive disorders. Psychiatry Res. 229, 37–48 (2015).

    CAS  PubMed  Google Scholar 

  178. Furtado, M. & Katzman, M. A. Examining the role of neuroinflammation in major depression. Psychiatry Res. 229, 27–36 (2015).

    CAS  PubMed  Google Scholar 

  179. Marsh, S. E. et al. The adaptive immune system restrains Alzheimer’s disease pathogenesis by modulating microglial function. Proc. Natl Acad. Sci. USA 113, E1316–E1325 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  180. Heneka, M. T., Golenbock, D. T. & Latz, E. Innate immunity in Alzheimer’s disease. Nat. Immunol. 16, 229–236 (2015).

    CAS  PubMed  Google Scholar 

  181. Sorge, R. E. et al. Different immune cells mediate mechanical pain hypersensitivity in male and female mice. Nat. Neurosci. 18, 1081–1083 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  182. Grassmann, F. et al. A candidate gene association study identifies DAPL1 as a female-specific susceptibility locus for age-related macular degeneration (AMD). Neuromolecular Med. 17, 111–120 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  183. Kim, S.-G. Gender differences in the genetic risk for alcohol dependence — the results of a pharmacogenetic study in Korean alcoholics. Nihon Arukoru Yakubutsu Igakkai Zasshi 44, 680–685 (2009).

    PubMed  Google Scholar 

  184. Yu, Y. et al. Systematic analysis of adverse event reports for sex differences in adverse drug events. Sci. Rep. 6, 24955 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  185. Rademaker, M. Do women have more adverse drug reactions? Am. J. Clin. Dermatol. 2, 349–351 (2001).

    CAS  PubMed  Google Scholar 

  186. Tharpe, N. Adverse drug reactions in women’s health care. J. Midwifery Womens Health 56, 205–213 (2011).

    PubMed  Google Scholar 

  187. Heinrich, J., Gahart, M. T., Rowe, E. J. & Bradley, L. Drug safety: most drugs withdrawn in recent years had greater health risks for women. GAO https://www.gao.gov/assets/100/90642.pdf (2001).

  188. Anderson, G. D. Sex and racial differences in pharmacological response: where is the evidence? Pharmacogenetics, pharmacokinetics, and pharmacodynamics. J. Womens Health 14, 19–29 (2005).

    Google Scholar 

  189. Kim, S.-G. et al. A micro opioid receptor gene polymorphism (A118G) and naltrexone treatment response in adherent Korean alcohol-dependent patients. Psychopharmacology 201, 611–618 (2009).

    CAS  PubMed  Google Scholar 

  190. Zhou, Q. et al. CYP2C9*3(1075 A>C), ABCB1 and SLCO1B1 genetic polymorphisms and gender are determinants of inter-subject variability in pitavastatin pharmacokinetics. Pharmazie 68, 187–194 (2013).

    CAS  PubMed  Google Scholar 

  191. Hubacek, J. A. et al. Possible gene-gender interaction between the SLCO1B1 polymorphism and statin treatment efficacy. Neuro Endocrinol. Lett. 33 (Suppl. 2), 22–25 (2012).

    CAS  PubMed  Google Scholar 

  192. McCullough, L. D., Zeng, Z., Blizzard, K. K., Debchoudhury, I. & Hurn, P. D. Ischemic nitric oxide and poly (ADP-ribose) polymerase-1 in cerebral ischemia: male toxicity, female protection. J. Cereb. Blood Flow Metab. 25, 502–512 (2005).

    CAS  PubMed  Google Scholar 

  193. U.S. Food and Drug Administration. Questions and answers: risk of next-morning impairment after use of insomnia drugs; FDA requires lower recommended doses for certain drugs containing zolpidem (Ambien, Ambien CR, Edluar, and Zolpimist). FDA https://www.fda.gov/drugs/drugsafety/ucm334041.htm (2018).

  194. Bogetto, F., Venturello, S., Albert, U., Maina, G. & Ravizza, L. Gender-related clinical differences in obsessive-compulsive disorder. Eur. Psychiatry 14, 434–441 (1999).

    CAS  PubMed  Google Scholar 

  195. Mancebo, M. C., Garcia, A. M. & Pinto, A. Juvenile-onset OCD: clinical features in children, adolescents and adults. Acta Psychiatr. Scand. 118, 149–159 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  196. Tükel, R. et al. Influence of age of onset on clinical features in obsessive–compulsive disorder. Depress. Anxiety 21, 112–117 (2005).

    PubMed  Google Scholar 

  197. Santangelo, S. L. et al. Tourette’s syndrome: what are the influences of gender and comorbid obsessive-compulsive disorder? J. Am. Acad. Child Adolesc. Psychiatry 33, 795–804 (1994).

    CAS  PubMed  Google Scholar 

  198. Mandy, W. et al. Sex differences in autism spectrum disorder: evidence from a large sample of children and adolescents. J. Autism Dev. Disord. 42, 1304–1313 (2012).

    PubMed  Google Scholar 

  199. Towbin, J. A. et al. X-linked dilated cardiomyopathy. Molecular genetic evidence of linkage to the Duchenne muscular dystrophy (dystrophin) gene at the Xp21 locus. Circulation 87, 1854–1865 (1993).

    CAS  PubMed  Google Scholar 

  200. The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature 526, 68–74 (2015).

    Google Scholar 

  201. McCarthy, S. et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 48, 1279–1283 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  202. Glas, R., Marshall Graves, J. A., Toder, R., Ferguson-Smith, M. & O’Brien, P. C. Cross-species chromosome painting between human and marsupial directly demonstrates the ancient region of the mammalian X. Mamm. Genome 10, 1115–1116 (1999).

    CAS  PubMed  Google Scholar 

  203. Ritchie, M. E., Liu, R., Carvalho, B. S. & Irizarry, R. A. & Australia and New Zealand Multiple Sclerosis Genetics Consortium (ANZgene). Comparing genotyping algorithms for Illumina’s Infinium whole-genome SNP BeadChips. BMC Bioinformatics 12, 68 (2011).

    PubMed  PubMed Central  Google Scholar 

  204. Loley, C., Ziegler, A. & König, I. R. Association tests for X-chromosomal markers—a comparison of different test statistics. Hum. Hered. 71, 23–36 (2011).

    PubMed  PubMed Central  Google Scholar 

  205. Clayton, D. Testing for association on the X chromosome. Biostatistics 9, 593–600 (2008).

    PubMed  PubMed Central  Google Scholar 

  206. Clayton, D. snpStats: SnpMatrix and XSnpMatrix classes and methods. bioconductor https://bioconductor.org/packages/release/bioc/html/snpStats.html (2018).

  207. Sultan, M. et al. A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science 321, 956–960 (2008).

    CAS  PubMed  Google Scholar 

  208. Castagné, R. et al. The choice of the filtering method in microarrays affects the inference regarding dosage compensation of the active X-chromosome. PLOS ONE 6, e23956 (2011).

    PubMed  PubMed Central  Google Scholar 

  209. Polderman, T. J. C. et al. The biological contributions to gender identity and gender diversity: bringing data to the table. Behav. Genet. 48, 95–108 (2018).

    PubMed  Google Scholar 

  210. Werling, D. M. & Geschwind, D. H. Sex differences in autism spectrum disorders. Curr. Opin. Neurol. 26, 146–153 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  211. Reich, R., Cloninger, C. R. & Guze, S. B. The multifactorial model of disease transmission: I. Description of the model and its use in psychiatry. Br. J. Psychiatry 127, 1–10 (1975).

    CAS  PubMed  Google Scholar 

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Acknowledgements

The authors thank A. Rzhetsky and I. Mayzus for providing the prevalence of male and female traits from Truven MarketScan insurance claims data. The authors also thank A. Skol for helpful comments on the manuscript and M. Oliva for contributing to Figure1 and for providing NOD2 observations. This work was supported in part by US National Institutes of Health (NIH) grants 3P50MH094267-04S1, 1R01MH101820-S1 and HG007598-S1.

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Nature Reviews Genetics thanks A. Keinan, K. Reue and the other, anonymous reviewer(s) for their contribution to the peer review of this work.

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Glossary

Sex differences

Significant differences in the means of a phenotype between males and females — also includes sexual dimorphism.

Genetic liability

The total contribution of the risk or trait-influencing alleles for a given trait.

Sexual dimorphism

Two distinct forms of a trait that differentiate members of the same species by their sex.

Heritability

The proportion of the total phenotypic variance in a population that can be attributed to genetic variance in the population.

Genetic architecture

The number, allele frequency and effect size of genetic variants that influence a trait.

Pseudoautosomal regions

(PARs). Homologous regions on the X and Y chromosomes that recombine and are not inherited in a sex-dependent manner.

Imprinting

An epigenetic mechanism of transcriptional silencing of a gene in a gamete inherited from the mother or the father, leading to a parent-of-origin specific imbalance in gene expression of the two inherited copies.

Dosage compensation

A process by which gene expression is balanced between two members of the same species (typically between two biological sexes). In humans, this is accomplished by silencing of one of the copies of the X chromosome in females.

Hemizygous

A haploid zygosity state in which only one copy of a gene is present, such as Y chromosome genes, which do not recombine with the X chromosome

X chromosome inactivation

(XCI). A process by which one of the copies of an X chromosome is silenced in each female cell through epigenetic modification, such as DNA methylation.

Sex-biased gene expression

A term that encompasses various gene regulatory phenomena that may differ between sexes, including differential expression and differential splicing.

Aneuploidy

Abnormal number of chromosomes in a cell.

Total liability

The combination of genetic and environmental factors that contribute to the development of a complex trait.

Missing heritability

The observation that for most complex traits, the sum of the identified trait-associated genetic variation contributes only a proportion of the estimated trait heritability.

Sexually differentiated

(Also known as sex-specific or sex-biased). A term used to describe a phenotype exhibiting a quantitative or qualitative sex difference.

ChrY haplogroups

Groups of haplotypes that map to the same common ancestor on the patriline.

Interaction

A phenomenon in which the effect of one variable depends on the value of another variable (for example, gene-by-environment interaction).

Type II error

A false negative finding, that is, a failure to reject a false null hypothesis.

Copy number variants

(CNVs). Regions of the genome that may be duplicated or deleted and for which the number of copies vary between individuals.

Sexually antagonistic selection

A situation in which selection on an allele acts in opposite directions in males and females because opposite phenotypes associated with the allele are optimal in each sex.

Genetic correlation

An estimate of the proportion of genetic variance shared by two traits, measured from 0 to 1, with 1 indicating complete genetic correlation.

Anthropometric traits

Physical properties of the human body including but not limited to secondary sex characteristics such as height, waist and hip measurements.

Pleiotropy

A phenomenon in which a single gene or genetic variant influences more than one phenotype.

Endophenotypes

Intermediate measurable phenotypes between an individual’s genotype and a phenotype, for example, characteristics of the transcriptome.

Sex differentially expressed

(sex-DE). A situation in which mean mRNA levels of a gene differ between tissues or cells derived from males or females.

Hormone response elements

Short segments of DNA in gene promoters to which hormone receptor complexes bind and regulate gene expression.

Sex-biased splicing

A situation in which different transcript splicing isoforms (or different ratios of them) are present in tissues or cells derived from males or females.

Expression quantitative trait loci

(eQTLs). Regions of the genome containing genetic variants associated with gene expression levels in a given tissue or cell type.

Sex-biased eQTLs

Expression quantitative trait loci (eQTLs) at which the allelic effect size differs between females and males.

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Khramtsova, E.A., Davis, L.K. & Stranger, B.E. The role of sex in the genomics of human complex traits. Nat Rev Genet 20, 173–190 (2019). https://doi.org/10.1038/s41576-018-0083-1

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