Oral contraceptives modify the effect of GATA3 polymorphisms on the risk of asthma at the age of 18 years via DNA methylation

Clinical Epigenetics

Wilfried Karmaus²  Gabrielle A Lockett⁵  John W Holloway⁵  Veeresh Patil⁴  Hasan S Arshad⁴  Susan Ewart³  Ali H Ziyab¹  Nelís Soto-Ramírez²  Vikki G Nolan²  Hongmei Zhang²  Kranthi Guthikonda² 

[1] Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA;Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA;Department of Large Animal Clinical Sciences, Michigan State University, East Lansing, MI, USA;The David Hide Asthma and Allergy Research Centre, Isle of Wight, UK;Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK

关键词: CpG;    single nucleotide polymorphism;    adolescence;    puberty;    asthma;    age at menarche;    oral contraceptives;    epigenetics;    genetic variants;    DNA methylation;    GATA3 gene;   

Others  :  1092828
DOI  :  10.1186/1868-7083-6-17

 received in 2014-06-18, accepted in 2014-09-10,  发布年份 2014

【 摘 要 】

Background

The prevalence of asthma in girls increases after puberty. Previous studies have detected associations between sex hormones and asthma, as well as between sex hormones and T helper 2 (Th2) asthma-typical immune responses. Therefore, we hypothesized that exogenous or endogenous sex hormone exposure (represented by oral contraceptive pill (OCP) use and early menarche, respectively) are associated with DNA methylation (DNA-M) of the Th2 transcription factor gene, GATA3, in turn affecting the risk of asthma in girls, possibly in interaction with genetic variants.

Blood samples were collected from 245 female participants aged 18 years randomly selected for methylation analysis from the Isle of Wight birth cohort, UK. Information on use of OCPs, age at menarche, and concurrent asthma were assessed by questionnaire. Genome-wide DNA-M was determined using the Illumina Infinium HumanMethylation450 beadchip. In a first stage, we tested the interaction between sex hormone exposure and genetic variants on DNA-M of specific cytosine-phosphate-guanine (CpG) sites. In a second stage, we determined whether these CpG sites interact with genetic variants in GATA3 to explain the risk of asthma.

Results

Interactions between OCP use and seven single nucleotide polymorphisms (SNPs) of GATA3 were analyzed for 14 CpG sites (stage 1). The interaction between OCP use and SNP rs1269486 was found to be associated with the methylation level of cg17124583 (P = 0.002, false discovery rate (FDR) adjusted P = 0.04). DNA-M of this same CpG site was also influenced by the interaction between age at menarche and rs1269486 (P = 0.0017). In stage 2, we found that cg17124583 modified the association of SNP rs422628 with asthma risk at the age of 18 years (P = 0.006, FDR adjusted P = 0.04). Subjects with genotype AG showed an increase in average risk ratio (RR) from 0.31 (95% CI: 0.10 to 0.8) to 11.65 (95% CI: 1.71 to 79.5) when methylation level increased from 0.02 to 0.12, relative to genotype AA.

Conclusion

A two-stage model consisting of genetic variants in the GATA3 gene, OCP use, age at menarche, and DNA-M may explain how sex hormones in women can increase the asthma prevalence after puberty.

【 授权许可】

   
2014 Guthikonda et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

【 参考文献 】

• [1]Tollefsen E, Langhammer A, Romundstad P, Bjermer L, Johnsen R, Holmen TL: Female gender is associated with higher incidence and more stable respiratory symptoms during adolescence. Respir Med 2007, 101:896-902.
• [2]Wada K, Okuyama K, Ohkawara Y, Takayanagi M, Ohno I: Gender differences in transcriptional regulation of IL-5 expression by bronchial lymph node cells in a mouse model of asthma. Respirology 2010, 15:629-635.
• [3]Soto-Ramirez N, Ziyab AH, Karmaus W, Zhang H, Kurukulaaratchy RJ, Ewart S, Arshad SH: Epidemiologic methods of assessing asthma and wheezing episodes in longitudinal studies: measures of change and stability. J Epidemiol 2013, 23:399-410.
• [4]Postma DS: Gender differences in asthma development and progression. Gender Medicine 2007, 4:S133-S146.
• [5]Tam A, Morrish D, Wadsworth S, Dorscheid D, Man SF, Sin DD: The role of female hormones on lung function in chronic lung diseases. BMC Womens Health 2011, 11:24.
• [6]Siroux V, Curt F, Oryszczyn MP, Maccario J, Kauffmann F: Role of gender and hormone-related events on IgE, atopy, and eosinophils in the Epidemiological Study on the Genetics and Environment of Asthma, bronchial hyperresponsiveness and atopy. J Allergy Clin Immunol 2004, 114:491-498.
• [7]Balzano G, Fuschillo S, Melillo G, Bonini S: Asthma and sex hormones. Allergy 2001, 56:13-20.
• [8]Salam MT, Wenten M, Gilliland FD: Endogenous and exogenous sex steroid hormones and asthma and wheeze in young women. J Allergy Clin Immunol 2006, 117:1001-1007.
• [9]Haggerty CL, Ness RB, Kelsey S, Waterer GW: The impact of estrogen and progesterone on asthma. Ann Allergy Asthma Immunol 2003, 90:284-291. quiz 291-283, 347
• [10]Piccinni MP, Giudizi MG, Biagiotti R, Beloni L, Giannarini L, Sampognaro S, Parronchi P, Manetti R, Annunziato F, Livi C: Progesterone favors the development of human T helper cells producing Th2-type cytokines and promotes both IL-4 production and membrane CD30 expression in established Th1 cell clones. J Immunol 1995, 155:128-133.
• [11]de Oliveira AP, Domingos HV, Cavriani G, Damazo AS, Dos Santos Franco AL, Oliani SM, Oliveira-Filho RM, Vargaftig BB: Cellular recruitment and cytokine generation in a rat model of allergic lung inflammation are differentially modulated by progesterone and estradiol. Am J Physiol Cell Physiol 2007, 293:C1120-C1128.
• [12]Arruvito L, Sanz M, Banham AH, Fainboim L: Expansion of CD4(+)CD25(+) and FOXP3(+) regulatory T cells during the follicular phase of the menstrual cycle: Implications for human reproduction. Journal of Immunology 2007, 178:2572-2578.
• [13]Cai Y, Zhou J, Webb DC: Estrogen stimulates Th2 cytokine production and regulates the compartmentalisation of eosinophils during allergen challenge in a mouse model of asthma. Int Arch Allergy Immunol 2012, 158:252-260.
• [14]Uemura Y, Liu TY, Narita Y, Suzuki M, Matsushita S: 17 beta-Estradiol (E2) plus tumor necrosis factor-alpha induces a distorted maturation of human monocyte-derived dendritic cells and promotes their capacity to initiate T-helper 2 responses. Human Immunology 2008, 69:149-157.
• [15]Macsali F, Real FG, Plana E, Sunyer J, Anto J, Dratva J, Janson C, Jarvis D, Omenaas ER, Zemp E, Wjst M, Leynaert B, Svanes C: Early age at menarche, lung function, and adult asthma. Am J Respir Crit Care Med 2011, 183:8-14.
• [16]Al-Sahab B, Hamadeh MJ, Ardern CI, Tamim H: Early Menarche Predicts Incidence of Asthma in Early Adulthood. American Journal of Epidemiology 2011, 173:S293-S293.
• [17]Jartti T, Saarikoski L, Jartti L, Lisinen I, Jula A, Huupponen R, Viikari J, Raitakari OT: Obesity, adipokines and asthma. Allergy 2009, 64:770-777.
• [18]Burgess JA, Walters EH, Byrnes GB, Giles GG, Jenkins MA, Abramson MJ, Hopper JL, Dharmage SC: Childhood adiposity predicts adult-onset current asthma in females: a 25-yr prospective study. Eur Respir J 2007, 29:668-675.
• [19]Zheng WP, Flavell RA: The transcription factor GATA-3 is necessary and sufficient for Th2 cytokine gene expression in CD4 T cells. Cell 1997, 89:587-596.
• [20]Zhu J, Min B, Hu-Li J, Watson CJ, Grinberg A, Wang Q, Killeen N, Urban JF Jr, Guo L, Paul WE: Conditional deletion of Gata3 shows its essential function in T(H)1-T(H)2 responses. Nat Immunol 2004, 5:1157-1165.
• [21]Lee HJ, Takemoto N, Kurata H, Kamogawa Y, Miyatake S, O'Garra A, Arai N: GATA-3 induces T helper cell type 2 (Th2) cytokine expression and chromatin remodeling in committed Th1 cells. J Exp Med 2000, 192:105-115.
• [22]Egger G, Liang GN, Aparicio A, Jones PA: Epigenetics in human disease and prospects for epigenetic therapy. Nature 2004, 429:457-463.
• [23]Runyon RS, Cachola LM, Rajeshuni N, Hunter T, Garcia M, Ahn R, Lurmann F, Krasnow R, Jack LM, Miller RL, Swan GE, Kohli A, Jacobson AC, Nadeau KC: Asthma discordance in twins is linked to epigenetic modifications of T cells. Plos One 2012, 7:e48796.
• [24]Kumar RK, Hitchins MP, Foster PS: Epigenetic changes in childhood asthma. Dis Model Mech 2009, 2:549-553.
• [25]Kim EG, Shin HJ, Lee CG, Park HY, Kim YK, Park HW, Cho SH, Min KU, Cho ML, Park SH, Lee CW: DNA methylation and not allelic variation regulates STAT6 expression in human T cells. Clin Exp Med 2010, 10:143-152.
• [26]Shoemaker R, Deng J, Wang W, Zhang K: Allele-specific methylation is prevalent and is contributed by CpG-SNPs in the human genome. Genome Research 2010, 20:883-889.
• [27]Bell JT, Pai AA, Pickrell JK, Gaffney DJ, Pique-Regi R, Degner JF, Gilad Y, Pritchard JK: DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol 2011, 12:R10.
• [28]Hellman A, Chess A: Extensive sequence-influenced DNA methylation polymorphism in the human genome. Epigenetics Chromatin 2010, 3:11.
• [29]Karmaus W, Ziyab AH, Everson T, Holloway JW: Epigenetic mechanisms and models in the origins of asthma. Curr Opin Allergy Clin Immunol 2013, 13:63-69.
• [30]Malousi A, Kouidou S: DNA hypermethylation of alternatively spliced and repeat sequences in humans. Molecular Genetics and Genomics 2012, 287:631-642.
• [31]Oberdoerffer S: A conserved role for intragenic DNA methylation in alternative pre-mRNA splicing. Transcription 2012, 3:106-109.
• [32]Grundberg E, Meduri E, Ling JKS, Hedman AK, Keildson S, Buil A, Busche S, Yuan W, Nisbet J, Sekowska M, Wilk A, Barrett A, Small KS, Ge B, Caron M, Shin SY, Lathrop M, Dermitzakis ET, McCarthy MI, Spector TD, Bell JT, Deloukas P, Multiple Tissue Human Expression Resource Consortium: Global analysis of DNA methylation variation in adipose tissue from twins reveals links to disease-associated variants in distal regulatory elements (vol 93, pg 876, 2013). Am J Hum Genet 2013, 93:1158-1158.
• [33]Bean JA, Leeper JD, Wallace RB, Sherman BM, Jagger H: Variations in the reporting of menstrual histories. Am J Epidemiol 1979, 109:181-185.
• [34]Norell SE, Boethius G, Persson I: Oral contraceptive use: interview data versus pharmacy records. International Journal of Epidemiology 1998, 27:1033-1037.
• [35]Must A, Phillips SM, Naumova EN, Blum M, Harris S, Dawson-Hughes B, Rand WM: Recall of early menstrual history and menarcheal body size: After 30 years, how well do women remember? American Journal of Epidemiology 2002, 155:672-679.
• [36]Bibikova M, Barnes B, Tsan C, Ho V, Klotzle B, Le JM, Delano D, Zhang L, Schroth GP, Gunderson KL, Fan JB, Shen R: High density DNA methylation array with single CpG site resolution. Genomics 2011, 98:288-295.
• [37]Talens RPBD, Tobi EW, Kremer D, Jukema JW, Willemsen G, Putter HSP, Heijmans BT: Variation, patterns, and temporal stability of DNA methylation: considerations for epigenetic epidemiology. FASEB J 2010, 24:3135-3144.
• [38]Terry MB, Delgado-Cruzata L, Vin-Raviv N, Wu HC, Santella RM: DNA methylation in white blood cells Association with risk factors in epidemiologic studies. Epigenetics 2011, 6:828-837.
• [39]Heijmans BT, Mill J: Commentary: The seven plagues of epigenetic epidemiology. International Journal of Epidemiology 2012, 41:74-78.
• [40]Ma B, Wilker EH, Willis-Owen SA, Byun HM, Wong KC, Motta V, Baccarelli AA, Schwartz J, Cookson WO, Khabbaz K, Mittleman MA, Moffatt MF, Liang L: Predicting DNA methylation level across human tissues. Nucleic Acids Res 2014, 42:3515-3528.
• [41]Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, Wiencke JK, Kelsey KT: DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 2012, 13:86.
• [42]Cooper DN, Krawczak M, Polychronakos C, Tyler-Smith C, Kehrer-Sawatzki H: Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease. Hum Genet 2013, 132:1077-130.
• [43]Soto-Ramirez N, Arshad SH, Holloway J, Zhang H, Schauberger E, Ewart S, Patil V, Karmaus W: The interaction of genetic variants and DNA methylation of the interleukin-4 receptor gene increase the risk of asthma at age 18 years. Clinical Epigenetics 2013, 5:1.
• [44]Patil VK, Holloway JW, Zhang H, Soto-Ramirez N, Ewart S, Arshad SH, Karmaus W: Interaction of prenatal maternal smoking, interleukin 13 genetic variants and DNA methylation influencing airflow and airway reactivity. Clin Epigenetics 2013, 5:22.
• [45]Parikh P, Palazzo JP, Rose LJ, Daskalakis C, Weigel RJ: GATA-3 expression as a predictor of hormone response in breast cancer. J Am Coll Surg 2005, 200:705-710.
• [46]Salem ML: Estrogen, a double-edged sword: modulation of TH1- and TH2-mediated inflammations by differential regulation of TH1/TH2 cytokine production. Curr Drug Targets Inflamm Allergy 2004, 3:97-104.
• [47]Miyaura H, Iwata M: Direct and indirect inhibition of Th1 development by progesterone and glucocorticoids. Journal of Immunology 2002, 168:1087-1094.
• [48]Apter D, Reinila M, Vihko R: Some Endocrine Characteristics of Early Menarche, a Risk Factor for Breast-Cancer, Are Preserved into Adulthood. International Journal of Cancer 1989, 44:783-787.
• [49]Arshad SH, Hide DW: Effect of environmental factors on the development pf allergic disorders in infancy. J Allergy Clin Immun 1992, 90:235-241.
• [50]Brooks-Gunn J, Warren MP, Rosso J, Gargiulo J: Validity of self-report measures of girls' pubertal status. Child Dev 1987, 58:829-41.
• [51]Asher MI, Keil U, Anderson HR, Beasley R, Crane J, Martinez F, Mitchell EA, Pearce N, Sibbald B, Stewart AW, Strachan D, Weiland SK, Williams HC: International study of asthma and allergies in childhood (ISAAC): rationale and methods. Eur Respir J 1995, 8:483-491.
• [52]Barrett JC, Fry B, Maller J, Daly MJ: Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005, 21:263-265.
• [53]Bibikova MFJ: GoldenGate assay for DNA methylation profiling. Methods Mol Biology 2009, 507:149-163.
• [54]Ogbuanu IU, Karmaus W, Arshad SH, Kurukulaaratchy RJ, Ewart S: Effect of breastfeeding duration on lung function at age 10 years: a prospective birth cohort study. Thorax 2009, 64:62-66.
• [55]Wang DYL, Hu Q, Sucheston LE, Higgins MJ, Ambrosone CB: IMA: an R package for high-throughput analysis of Illumina's 450 K Infinium methylation data. Bioinformatics 2012, 28:729-730.
• [56]R: A language and environment for statistical computing. R Foundation for Statistical Computing [http://www.R-project.org/ webcite]
• [57]Hill WG, Robertson A: The effect of linkage on limits to artificial selection (Reprinted). Genet Res 2007, 89:311-336.
• [58]Kuan PFWS, Zhou X, Chu H: A statistical framework for Illumina DNA methylation arrays. Bioinformatics 2010, 26:2849-2855.
• [59]Du P, Zhang X, Huang CC, Jafari N, Kibbe WA, Hou L, Lin SM: Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics 2010, 11:587.
• [60]Benjamini Y, Hochberg Y: Controlling the False Discovery Rate - a Practical and Powerful Approach to Multiple Testing. J Roy Stat Soc B Met 1995, 57:289-300.