Title |
Oral contraceptives modify the effect of GATA3 polymorphisms on the risk of asthma at the age of 18 years via DNA methylation
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Published in |
Clinical Epigenetics, September 2014
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DOI | 10.1186/1868-7083-6-17 |
Pubmed ID | |
Authors |
Kranthi Guthikonda, Hongmei Zhang, Vikki G Nolan, Nelís Soto-Ramírez, Ali H Ziyab, Susan Ewart, Hasan S Arshad, Veeresh Patil, John W Holloway, Gabrielle A Lockett, Wilfried Karmaus |
Abstract |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 5 | 36% |
Australia | 1 | 7% |
Canada | 1 | 7% |
Argentina | 1 | 7% |
Taiwan | 1 | 7% |
Unknown | 5 | 36% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 9 | 64% |
Scientists | 4 | 29% |
Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 2% |
Spain | 1 | 2% |
Netherlands | 1 | 2% |
Unknown | 44 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 8 | 17% |
Researcher | 7 | 15% |
Student > Ph. D. Student | 5 | 11% |
Professor | 4 | 9% |
Student > Bachelor | 3 | 6% |
Other | 12 | 26% |
Unknown | 8 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 12 | 26% |
Agricultural and Biological Sciences | 8 | 17% |
Biochemistry, Genetics and Molecular Biology | 6 | 13% |
Nursing and Health Professions | 3 | 6% |
Computer Science | 2 | 4% |
Other | 5 | 11% |
Unknown | 11 | 23% |