CYP19A1 fine-mapping and Mendelian randomization: estradiol is causal for endometrial cancer

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Abstract

Candidate gene studies have reported CYP19A1 variants to be associated with endometrial cancer and with estradiol (E ₂) concentrations. We analyzed 2937 single nucleotide polymorphisms (SNPs) in 6608 endometrial cancer cases and 37 925 controls and report the first genome wide-significant association between endometrial cancer and a CYP19A1 SNP (rs727479 in intron 2, P=4.8×10 ⁻¹¹). SNP rs727479 was also among those most strongly associated with circulating E ₂ concentrations in 2767 post-menopausal controls ( P=7.4×10 ⁻⁸). The observed endometrial cancer odds ratio per rs727479 A-allele (1.15, CI=1.11–1.21) is compatible with that predicted by the observed effect on E ₂ concentrations (1.09, CI=1.03–1.21), consistent with the hypothesis that endometrial cancer risk is driven by E ₂. From 28 candidate-causal SNPs, 12 co-located with three putative gene-regulatory elements and their risk alleles associated with higher CYP19A1 expression in bioinformatical analyses. For both phenotypes, the associations with rs727479 were stronger among women with a higher BMI ( P _interaction=0.034 and 0.066 respectively), suggesting a biologically plausible gene-environment interaction.

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Most cited references 34

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Endogenous sex hormones and breast cancer in postmenopausal women: reanalysis of nine prospective studies.

T Key, P Appleby, I. Barnes … (2002)

Reproductive and hormonal factors are involved in the etiology of breast cancer, but there are only a few prospective studies on endogenous sex hormone levels and breast cancer risk. We reanalyzed the worldwide data from prospective studies to examine the relationship between the levels of endogenous sex hormones and breast cancer risk in postmenopausal women. We analyzed the individual data from nine prospective studies on 663 women who developed breast cancer and 1765 women who did not. None of the women was taking exogenous sex hormones when their blood was collected to determine hormone levels. The relative risks (RRs) for breast cancer associated with increasing hormone concentrations were estimated by conditional logistic regression on case-control sets matched within each study. Linear trends and heterogeneity of RRs were assessed by two-sided tests or chi-square tests, as appropriate. The risk for breast cancer increased statistically significantly with increasing concentrations of all sex hormones examined: total estradiol, free estradiol, non-sex hormone-binding globulin (SHBG)-bound estradiol (which comprises free and albumin-bound estradiol), estrone, estrone sulfate, androstenedione, dehydroepiandrosterone, dehydroepiandrosterone sulfate, and testosterone. The RRs for women with increasing quintiles of estradiol concentrations, relative to the lowest quintile, were 1.42 (95% confidence interval [CI] = 1.04 to 1.95), 1.21 (95% CI = 0.89 to 1.66), 1.80 (95% CI = 1.33 to 2.43), and 2.00 (95% CI = 1.47 to 2.71; P(trend)<.001); the RRs for women with increasing quintiles of free estradiol were 1.38 (95% CI = 0.94 to 2.03), 1.84 (95% CI = 1.24 to 2.74), 2.24 (95% CI = 1.53 to 3.27), and 2.58 (95% CI = 1.76 to 3.78; P(trend)<.001). The magnitudes of risk associated with the other estrogens and with the androgens were similar. SHBG was associated with a decrease in breast cancer risk (P(trend) =.041). The increases in risk associated with increased levels of all sex hormones remained after subjects who were diagnosed with breast cancer within 2 years of blood collection were excluded from the analysis. Levels of endogenous sex hormones are strongly associated with breast cancer risk in postmenopausal women.

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Endometrial cancers have long been divided into estrogen-dependent type I and the less common clinically aggressive estrogen-independent type II. Little is known about risk factors for type II tumors because most studies lack sufficient cases to study these much less common tumors separately. We examined whether so-called classical endometrial cancer risk factors also influence the risk of type II tumors. Individual-level data from 10 cohort and 14 case-control studies from the Epidemiology of Endometrial Cancer Consortium were pooled. A total of 14,069 endometrial cancer cases and 35,312 controls were included. We classified endometrioid (n = 7,246), adenocarcinoma not otherwise specified (n = 4,830), and adenocarcinoma with squamous differentiation (n = 777) as type I tumors and serous (n = 508) and mixed cell (n = 346) as type II tumors. Parity, oral contraceptive use, cigarette smoking, age at menarche, and diabetes were associated with type I and type II tumors to similar extents. Body mass index, however, had a greater effect on type I tumors than on type II tumors: odds ratio (OR) per 2 kg/m(2) increase was 1.20 (95% CI, 1.19 to 1.21) for type I and 1.12 (95% CI, 1.09 to 1.14) for type II tumors (P heterogeneity < .0001). Risk factor patterns for high-grade endometrioid tumors and type II tumors were similar. The results of this pooled analysis suggest that the two endometrial cancer types share many common etiologic factors. The etiology of type II tumors may, therefore, not be completely estrogen independent, as previously believed.

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Family-based association tests for genomewide association scans.

Wei-Min Chen, Gonçalo R Abecasis (2007)

With millions of single-nucleotide polymorphisms (SNPs) identified and characterized, genomewide association studies have begun to identify susceptibility genes for complex traits and diseases. These studies involve the characterization and analysis of very-high-resolution SNP genotype data for hundreds or thousands of individuals. We describe a computationally efficient approach to testing association between SNPs and quantitative phenotypes, which can be applied to whole-genome association scans. In addition to observed genotypes, our approach allows estimation of missing genotypes, resulting in substantial increases in power when genotyping resources are limited. We estimate missing genotypes probabilistically using the Lander-Green or Elston-Stewart algorithms and combine high-resolution SNP genotypes for a subset of individuals in each pedigree with sparser marker data for the remaining individuals. We show that power is increased whenever phenotype information for ungenotyped individuals is included in analyses and that high-density genotyping of just three carefully selected individuals in a nuclear family can recover >90% of the information available if every individual were genotyped, for a fraction of the cost and experimental effort. To aid in study design, we evaluate the power of strategies that genotype different subsets of individuals in each pedigree and make recommendations about which individuals should be genotyped at a high density. To illustrate our method, we performed genomewide association analysis for 27 gene-expression phenotypes in 3-generation families (Centre d'Etude du Polymorphisme Humain pedigrees), in which genotypes for ~860,000 SNPs in 90 grandparents and parents are complemented by genotypes for ~6,700 SNPs in a total of 168 individuals. In addition to increasing the evidence of association at 15 previously identified cis-acting associated alleles, our genotype-inference algorithm allowed us to identify associated alleles at 4 cis-acting loci that were missed when analysis was restricted to individuals with the high-density SNP data. Our genotype-inference algorithm and the proposed association tests are implemented in software that is available for free.

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Author and article information

Journal

Journal ID (nlm-ta): Endocr Relat Cancer

Journal ID (iso-abbrev): Endocr. Relat. Cancer

Journal ID (publisher-id): ERC

Title: Endocrine-Related Cancer

Publisher: Bioscientifica Ltd (Bristol )

ISSN (Print): 1351-0088

ISSN (Electronic): 1479-6821

Publication date (Print): February 2016

Publication date (Electronic preprint): 16 November 2015

Volume: 23

Issue: 2

Pages: 77-91

Affiliations

[1 ]Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Strangeways Research Laboratory , Worts Causeway, Cambridge, CB1 8RN, UK

[2 ]Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute , Brisbane, Queensland, 4006, Australia

[3 ]Wellcome Trust Centre for Human Genetics, University of Oxford , Oxford, OX3 7BN, UK

[4 ]Academic Department of Biochemistry, Royal Marsden Hospital , London, SW3 6JJ, UK

[5 ]Department of Clinical Genetics, St George's Hospital Medical School , London, SW17 0RE, UK

[6 ]Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge , Cambridge, CB1 8RN, UK

[7 ]Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, SE-171 77, Sweden

[8 ]Department of Medicine, Division of Hematology/Oncology, David Geffen School of Medicine, University of California at Los Angeles , Los Angeles, California, 90095, USA

[9 ]Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg , Erlangen, 91054, Germany

[10 ]Institute of Human Genetics, , University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg , Erlangen, 91054, Germany

[11 ]Gynaecology Research Unit, Hannover Medical School , Hannover, 30625, Germany

[12 ]Clinics of Gynaecology and Obstetrics, Hannover Medical School , Hannover, 30625, Germany

[13 ]Department of Gynaecology, Jena University Hospital – Friedrich Schiller University , Jena, 07743, Germany

[14 ]Vesalius Research Center , Leuven, 3000, Belgium

[15 ]Laboratory for Translational Genetics, Department of Oncology, University Hospitals Leuven , Leuven, 3000, Belgium

[16 ]Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University Hospitals, KU Leuven – University of Leuven , Leuven, 3000, Belgium

[17 ]Department of Health Sciences Research, Mayo Clinic , Rochester, Minnesota, 55905, USA

[18 ]Department of Biostatistics, University of Kansas Medical Center , Kansas City, Kansas, 66160, USA

[19 ]Department of Obstetrics and Gynecology Division of Gynecologic Oncology Mayo Clinic , Rochester, Minnesota, 55905, USA

[20 ]Department of Clinical Science, Centre for Cancerbiomarkers, The University of Bergen , Bergen, 5020, Norway

[21 ]Department of Obstetrics and Gynecology, Haukeland University Hospital , Bergen, 5021, Norway

[22 ]Hunter Medical Research Institute, John Hunter Hospital , Newcastle, New South Wales, 2305, Australia

[23 ]Centre for Information Based Medicine, University of Newcastle , Newcastle, New South Wales, 2308, Australia

[24 ]School of Biomedical Sciences and Pharmacy, , University of Newcastle Newcastle , Newcastle, New South Wales, 2308, Australia

[25 ]School of Medicine and Public Health, , University of Newcastle, Newcastle , Newcastle, New South Wales, 2308, Australia

[26 ]Grupo de investigación Citogenética, Filogenia y Evolución de Poblaciones, Universidad del Tolima , Ibagué, Tolima, Colombia

[27 ]Genome Center and Department of Biochemistry and Molecular Medicine, University of California , Davis, California, 95616, USA

[28 ]Department of Molecular Medicine and Surgery, Karolinska Institutet , Stockholm, SE-171 77, Sweden

[29 ]Department of Women's and Children's Health, Karolinska Institutet, Karolinska University Hospital , Stockholm, SE-171 77, Sweden

[30 ]Hunter Area Pathology Service, John Hunter Hospital , Newcastle, New South Wales, 2305, Australia

[31 ]Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle , Newcastle, New South Wales, 2305, Australia

[32 ]Institute of Health and Biomedical Innovation, Queensland University of Technology , Brisbane, 4006, Australia

[33 ]Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne victoria , Melbourne, Victoria, 3010, Australia

[34 ]PePeter MacCallum Cancer Center, The University of Melbourne , Melbourne, 3002, Australia

[35 ]Division of Genetics and Epidemiology, Institute of Cancer Research , London, SM2 5NG, UK

[36 ]Division of Breast Cancer Research, Institute of Cancer Research , London, SM2 5NG, UK

[37 ]Department of Gynecology and Obstetrics, Molecular Biology of Breast Cancer, University of Heidelberg , Heidelberg, 69117, Germany

[38 ]Division of Cancer Epidemiology, German Cancer Research Center , Heidelberg, 69120, Germany

[39 ]Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ) , Heidelberg, 69120, Germany

[40 ]Division of Preventive Oncology, German Cancer Research Center (DKFZ) , Heidelberg, 69120, Germany

[41 ]German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ) , Heidelberg, 69120, Germany

[42 ]Department of Obstetrics and Gynecology, Division of Tumor Genetics, Technical University of Munich , Munich, 80333, Germany

[43 ]Dr Margarete Fischer-Bosch-Institute of Clinical Pharmacology , Stuttgart, 70376, Germany

[44 ]University of Tübingen , Tübingen, 72074, Germany

[45 ]Department of Laboratory Medicine and Pathology, Mayo Clinic , Rochester, Minnesota, 55905, USA

[46 ]Cancer Epidemiology Centre, Cancer Council Victoria , Melbourne, Victoria, 3004, Australia

[47 ]Department of Epidemiology and Preventive Medicine, Monash University , Melbourne, Victoria, 3004, Australia

[48 ]Department of Genetics, Institute for Cancer Research, The Norwegian Radium Hospital , Oslo, 0310, Norway

[49 ]Faculty of Medicine, The K.G. Jebsen Center for Breast Cancer Research, Institute for Clinical Medicine, , University of Oslo , Oslo, 0316, Norway

[50 ]Department of Clinical Molecular Oncology, Division of Medicine, Akershus University Hospital , Lørenskog, 1478, Norway

[51 ]Department of Oncology, Sheffield Cancer Research, University of Sheffield , Sheffield, S10 2TN, UK

[52 ]Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen, 1165, Denmark

[53 ]Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital , Herlev, 2730, Denmark

[54 ]Department of Public Health and Primary Care, University of Cambridge , Cambridge, CB1 8RN, UK

[55 ]MRC Centre for Nutritional Epidemiology in Cancer Prevention and Survival (CNC), University of Cambridge , Cambridge, CB1 8RN, UK

Author notes

Correspondence should be addressed to D J Thompson djt25@ 123456medschl.cam.ac.uk

Article

Publisher ID: ERC150386

DOI: 10.1530/ERC-15-0386

PMC ID: 4697192

PubMed ID: 26574572

SO-VID: 5336ad23-7376-42ed-9a16-8db8768b6209

License:

This work is licensed under a Creative Commons Attribution 3.0 Unported License

History

Date revision received : 22 October 2015

Date accepted : 16 November 2015

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