Breast Cancer Research and Treatment

, Volume 138, Issue 2, pp 529–542

A genome-wide association study to identify genetic susceptibility loci that modify ductal and lobular postmenopausal breast cancer risk associated with menopausal hormone therapy use: a two-stage design with replication

  • Rebecca Hein
  • Dieter Flesch-Janys
  • Norbert Dahmen
  • Lars Beckmann
  • Sara Lindström
  • Nils Schoof
  • Kamila Czene
  • Kirstin Mittelstraß
  • Thomas Illig
  • Petra Seibold
  • Sabine Behrens
  • Keith Humphreys
  • Jingmei Li
  • Jianjun Liu
  • Janet E. Olson
  • Xianshu Wang
  • Susan E. Hankinson
  • Thérèse Truong
  • Florence Menegaux
  • Isabel dos Santos Silva
  • Nichola Johnson
  • The GENICA Network
  • Shou-Tung Chen
  • Jyh-Cherng Yu
  • Argyrios Ziogas
  • Vesa Kataja
  • Veli-Matti Kosma
  • Arto Mannermaa
  • Hoda Anton-Culver
  • Chen-Yang Shen
  • Hiltrud Brauch
  • Julian Peto
  • Pascal Guénel
  • Peter Kraft
  • Fergus J. Couch
  • Douglas F. Easton
  • Per Hall
  • Jenny Chang-Claude
Epidemiology

DOI: 10.1007/s10549-013-2443-z

Cite this article as:
Hein, R., Flesch-Janys, D., Dahmen, N. et al. Breast Cancer Res Treat (2013) 138: 529. doi:10.1007/s10549-013-2443-z

Abstract

Menopausal hormone therapy (MHT) is associated with an elevated risk of breast cancer in postmenopausal women. To identify genetic loci that modify breast cancer risk related to MHT use in postmenopausal women, we conducted a two-stage genome-wide association study (GWAS) with replication. In stage I, we performed a case-only GWAS in 731 invasive breast cancer cases from the German case-control study Mammary Carcinoma Risk Factor Investigation (MARIE). The 1,200 single nucleotide polymorphisms (SNPs) showing the lowest P values for interaction with current MHT use (within 6 months prior to breast cancer diagnosis), were carried forward to stage II, involving pooled case-control analyses including additional MARIE subjects (1,375 cases, 1,974 controls) as well as 795 cases and 764 controls of a Swedish case-control study. A joint P value was calculated for a combined analysis of stages I and II. Replication of the most significant interaction of the combined stage I and II was performed using 5,795 cases and 5,390 controls from nine studies of the Breast Cancer Association Consortium (BCAC). The combined stage I and II yielded five SNPs on chromosomes 2, 7, and 18 with joint P values <6 × 10−6 for effect modification of current MHT use. The most significant interaction was observed for rs6707272 (P = 3 × 10−7) on chromosome 2 but was not replicated in the BCAC studies (P = 0.21). The potentially modifying SNPs are in strong linkage disequilibrium with SNPs in TRIP12 and DNER on chromosome 2 and SETBP1 on chromosome 18, previously linked to carcinogenesis. However, none of the interaction effects reached genome-wide significance. The inability to replicate the top SNP × MHT interaction may be due to limited power of the replication phase. Our study, however, suggests that there are unlikely to be SNPs that interact strongly enough with MHT use to be clinically significant in European women.

Keywords

Postmenopausal breast cancer riskMenopausal hormone therapyPolymorphismsGene-environment interactionGenome-wide association studyCase-only study

Abbreviations

ARF

Alternate reading frame of the INK4a/CDKN2A locus

BCAC

Breast Cancer Association Consortium

CGEMS

Cancer Genetic Markers of Susceptibility Project

CI

Confidence interval

DNE

Delta/notch-like epidermal growth factor-like repeat containing

EPT

Estrogen-progestagen combined therapy

ET

Estrogen-only therapy

FBXO36

F-box protein 36

HWE

Hardy-Weinberg equilibrium

IBS

Identical by state

LD

Linkage disequilibrium

MAF

Minor allele frequency

MALDI-TOF MS

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

MARIE

Mammary Carcinoma Risk Factor Investigation

MHT

Menopausal hormone therapy

OR

Odds ratio

QC

Quality control

SASBAC

Singapore and Sweden Breast Cancer Study

SET

Suppressor of variegation, enhancer of zeste, and Trithorax

SETBP1

SET binding protein

SNP

Single nucleotide polymorphism

TRIP12

Thyroid hormone receptor interactor 12

Supplementary material

10549_2013_2443_MOESM1_ESM.pdf (49 kb)
Supplementary material 1 (PDF 49 kb)
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Supplementary material 2 (PDF 29 kb)
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Supplementary material 3 (PDF 137 kb)
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Supplementary material 4 (PDF 76 kb)
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Supplementary material 5 (PDF 71 kb)
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Supplementary material 6 (PDF 153 kb)
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Supplementary material 7 (PDF 155 kb)
10549_2013_2443_MOESM8_ESM.tif (434 kb)
Supplementary Fig. 1: Linkage disequilibrium blocks on chromosome 7, position 71,000,000–71,600,000. Figure legend: Linkage disequilibrium (LD) in terms of D′ between rs2909969 and CALN1 on chromosome 7. LD blocks were generated using data from the HapMap project. The intensity of the colour is proportional to the strength of the LD for the SNP pair. Dark red indicates D‘=1. (TIFF 433 kb)
10549_2013_2443_MOESM9_ESM.tif (519 kb)
Supplementary Fig. 2: Linkage disequilibrium blocks on chromosome 18, position 40,850,000–41,000,000. Figure legend: Linkage disequilibrium (LD) in terms of D′ between rs1942574 and SETBP1 on chromosome 18. LD blocks were generated using data from the HapMap project. The intensity of the colour is proportional to the strength of the LD for the SNP pair. Dark red indicates D′=1. (TIFF 519 kb)

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Rebecca Hein
    • 1
    • 2
  • Dieter Flesch-Janys
    • 3
  • Norbert Dahmen
    • 4
  • Lars Beckmann
    • 1
    • 5
  • Sara Lindström
    • 6
    • 7
    • 8
  • Nils Schoof
    • 9
  • Kamila Czene
    • 9
  • Kirstin Mittelstraß
    • 10
  • Thomas Illig
    • 10
    • 11
  • Petra Seibold
    • 1
  • Sabine Behrens
    • 1
  • Keith Humphreys
    • 9
  • Jingmei Li
    • 12
  • Jianjun Liu
    • 12
  • Janet E. Olson
    • 13
  • Xianshu Wang
    • 13
  • Susan E. Hankinson
    • 7
  • Thérèse Truong
    • 14
    • 15
  • Florence Menegaux
    • 14
    • 15
  • Isabel dos Santos Silva
    • 16
  • Nichola Johnson
    • 17
  • The GENICA Network
    • 18
    • 19
    • 20
    • 21
    • 22
    • 23
  • Shou-Tung Chen
    • 24
  • Jyh-Cherng Yu
    • 25
  • Argyrios Ziogas
    • 26
  • Vesa Kataja
    • 27
    • 28
  • Veli-Matti Kosma
    • 29
    • 30
    • 31
  • Arto Mannermaa
    • 29
    • 30
    • 31
  • Hoda Anton-Culver
    • 32
  • Chen-Yang Shen
    • 33
    • 34
  • Hiltrud Brauch
    • 18
  • Julian Peto
    • 16
  • Pascal Guénel
    • 14
    • 15
  • Peter Kraft
    • 6
    • 7
    • 8
  • Fergus J. Couch
    • 13
  • Douglas F. Easton
    • 35
  • Per Hall
    • 9
  • Jenny Chang-Claude
    • 1
  1. 1.Unit of Genetic Epidemiology, Division of Cancer Epidemiology (C020)German Cancer Research Center (DKFZ)HeidelbergGermany
  2. 2.PMV Research Group at the Department of Child and Adolescent Psychiatry and PsychotherapyUniversity of CologneCologneGermany
  3. 3.Department of Cancer Epidemiology, Clinical Cancer RegistryUniversity Cancer Center and Institute for Medical Biometrics and Epidemiology, University Clinic Hamburg-EppendorfHamburgGermany
  4. 4.Congenics AGHamburgGermany
  5. 5.Foundation for Quality and Efficiency in Health Care (IQWIG)CologneGermany
  6. 6.Program in Molecular and Genetic EpidemiologyHarvard School of Public HealthBostonUSA
  7. 7.Department of EpidemiologyHarvard School Of Public HealthBostonUSA
  8. 8.Department of BiostatisticsHarvard School Of Public HealthBostonUSA
  9. 9.Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
  10. 10.Research Unit of Molecular EpidemiologyHelmholtz Center MunichMunichGermany
  11. 11.Hannover Unified BiobankHannover Medical SchoolHannoverGermany
  12. 12.Human GeneticsGenome Institute of SingaporeSingaporeSingapore
  13. 13.Department of Laboratory Medicine and PathologyMayo ClinicRochesterUSA
  14. 14.Inserm (National Institute of Health and Medical Research), CESP (Center for Research in Epidemiology and Population Health), U1018, Environmental Epidemiology of CancerVillejuifFrance
  15. 15.University Paris-SudVillejuifFrance
  16. 16.Department of Non-Communicable Disease EpidemiologyLondon School of Hygiene and Tropical MedicineLondonUK
  17. 17.Breakthrough Breast Cancer Research CentreThe Institute of Cancer ResearchLondonUK
  18. 18.Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, University of TübingenTübingenGermany
  19. 19.Molecular Genetics of Breast CancerGerman Cancer Research Center (DKFZ)HeidelbergGermany
  20. 20.Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA)BochumGermany
  21. 21.Institute and Outpatient Clinic of Occupational MedicineSaarland University Medical Center and Saarland University Faculty of MedicineHomburgGermany
  22. 22.Institute of PathologyMedical Faculty of the University of BonnBonnGermany
  23. 23.Department of Internal MedicineEvangelische Kliniken Bonn gGmbH, Johanniter KrankenhausBonnGermany
  24. 24.Department of SurgeryChanghua Christian HospitalChanghuaTaiwan
  25. 25.Department of SurgeryTri-Service General HospitalTaipeiTaiwan
  26. 26.Department of EpidemiologySchool of Medicine, University of CaliforniaIrvineUSA
  27. 27.School of Medicine, Institute of Clinical Medicine, Oncology, Biocenter Kuopio, Cancer Center of Eastern Finland, University of Eastern FinlandKuopioFinland
  28. 28.Cancer CenterKuopio University HospitalKuopioFinland
  29. 29.School of Medicine, Institute of Clinical Medicine, Pathology and Forensic MedicineUniversity of Eastern FinlandKuopioFinland
  30. 30.Biocenter Kuopio, Cancer Center of Eastern FinlandUniversity of Eastern FinlandKuopioFinland
  31. 31.Imaging Center, Department of Clinical PathologyKuopio University HospitalKuopioFinland
  32. 32.Department of EpidemiologyUniversity of California IrvineIrvineUSA
  33. 33.Institute of Biomedical SciencesAcademia SinicaTaipeiTaiwan
  34. 34.Taiwan BiobankTaipeiTaiwan
  35. 35.Centre for Cancer Genetic Epidemiology, Departments of Public Health and Primary Care and OncologyUniversity of CambridgeCambridgeUK