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A combined analysis of genome-wide association studies in breast cancer

  • Epidemiology
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

In an attempt to identify common disease susceptibility alleles for breast cancer, we performed a combined analysis of three genome-wide association studies (GWAS), involving 2,702 women of European ancestry with invasive breast cancer and 5,726 controls. Tests for association were performed for 285,984 SNPs. Evidence for association with SNPs in genes in specific pathways was assessed using a permutation-based approach. We confirmed associations with loci reported by previous GWAS on 1p11.2, 2q35, 3p, 5p12, 8q24, 10q23.13, 14q24.1 and 16q. Six SNPs with the strongest signals of association with breast cancer, and which have not been reported previously, were typed in two further studies; however, none of the associations could be confirmed. Suggestive evidence for an excess of associations was found for genes involved in the regulation of actin cytoskeleton, glycan degradation, alpha-linolenic acid metabolism, circadian rhythm, hematopoietic cell lineage and drug metabolism. Androgen and oestrogen metabolism, a pathway previously found to be associated with the development of postmenopausal breast cancer, was marginally significant (P = 0.051 [unadjusted]). These results suggest that further analysis of SNPs in these pathways may identify associations that would be difficult to detect through agnostic single SNP analyses. More effort focused in these aspects of oncology can potentially open up promising avenues for the understanding of breast cancer and its prevention.

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Abbreviations

CGEMS:

Cancer Genetic Markers of Susceptibility

CI:

Confidence interval

EIRA:

Epidemiological Investigation of Rheumatoid Arthritis

FPRP:

False positive report probability

GWAS:

Genome-wide association study

OR:

Odds ratio

RBCS:

Rotterdam Breast Cancer Study

SEARCH:

Study of Epidemiology and Risk factors in Cancer Heredity

SNP:

Single nucleotide polymorphism

λGC :

Genomic inflation factor λ

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Acknowledgments

This work was supported by National Institutes of Health [RO1 CA58427], the Agency for Science, Technology and Research (A*STAR; Singapore), the Nordic Cancer Society, and Märit and Hans Rausing’s Initiative against Breast Cancer. J Li is a recipient of an A*STAR Graduate Scholarship (Overseas) award. KH was supported by the Swedish Research Council [523-2006-972]. KC was supported by the Swedish Cancer Society [5128-B07-01PAF]. The Helsinki study was supported by the Helsinki University Central Hospital Research Fund, Academy of Finland, the Finnish Cancer Society and the Sigrid Juselius Foundation. We thank Dr. Kirsimari Aaltonen and RN Hanna Jäntti for their help with the patient data. The SEARCH study was funded by Cancer Research UK. DFE is a Principal Research Fellow of Cancer Research UK. We thank the SEARCH team and Eastern Cancer Registry and Information Centre (ECRIC) for recruitment of the SEARCH cases. The RBCS was supported by the Dutch Cancer Society (Grant DDHK 2004-3124). We acknowledge the clinicians from the Rotterdam Family Cancer Clinic who were involved in collecting the RBCS samples: C. Seynaeve, J. Klijn, J. Collee, and R. Oldenburg. The sponsors took no role in the study design, the collection or analysis of the data, the interpretation of the results, the preparation of the manuscript, or the decision to submit the manuscript for publication.

Conflict of interest

The authors declare that they have no competing interests.

Author information

Authors and Affiliations

  1. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, P.O. Box 281, 17177, Stockholm, Sweden

    Jingmei Li, Keith Humphreys, Kamila Czene & Per Hall

  2. Human Genetics, Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore, 138672, Singapore

    Jingmei Li, Astrid Irwanto, Hui Qi Low, Garrett H. K. Teoh, Anbupalam Thalamuthu & Jianjun Liu

  3. Department of Obstetrics and Gynecology, Helsinki University Central Hospital, P.O. Box 700, 00029 HUS, Helsinki, Finland

    Tuomas Heikkinen & Heli Nevanlinna

  4. Department of Clinical Genetics, Helsinki University Central Hospital, P.O. Box 140, 00029 HUS, Helsinki, Finland

    Kristiina Aittomäki

  5. Department of Oncology, Helsinki University Central Hospital, P.O. Box 180, 00029 HUS, Helsinki, Finland

    Carl Blomqvist

  6. Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK

    Paul D. P. Pharoah & Douglas F. Easton

  7. Department of Oncology, University of Cambridge, Cambridge, CB1 8RN, UK

    Paul D. P. Pharoah, Alison M. Dunning, Shahana Ahmed & Douglas F. Easton

  8. Department of Medical Oncology, Rotterdam Family Cancer Clinic, Erasmus University Medical Center, Rotterdam, Netherlands

    Maartje J. Hooning & John W. M. Martens

  9. Department of Clinical Genetics, Rotterdam Family Cancer Clinic, Erasmus University Medical Center, Rotterdam, Netherlands

    Ans M. W. van den Ouweland

  10. Institute of Environmental Medicine, Karolinska Institutet, P.O. Box 281, Stockholm, 17177, Sweden

    Lars Alfredsson

  11. Institute for Molecular Medicine Finland, FIMM, University of Helsinki, P.O. Box 20, 00014, Helsinki, Finland

    Aarno Palotie & Leena Peltonen-Palotie

  12. Public Health Genomics Unit, National Institute for Health and Welfare, P.O. Box 30, 00271, Helsinki, Finland

    Aarno Palotie & Leena Peltonen-Palotie

  13. Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK

    Aarno Palotie & Leena Peltonen-Palotie

  14. Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, 02142, USA

    Aarno Palotie & Leena Peltonen-Palotie

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  1. Jingmei Li
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  2. Keith Humphreys
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  3. Tuomas Heikkinen
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  4. Kristiina Aittomäki
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Corresponding authors

Correspondence to Jianjun Liu or Per Hall.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 45 kb)

Supplementary File 1

Full description of methods (DOC 147 kb)

Supplementary File 2

Full description of combined results, including results of analysis carried out under recessive and dominant models. Results of corresponding meta-analyses of the three sample populations (Swedish, Finnish, CGEMS) are also presented (XLS 294 kb)

Supplementary File 3

Scatter plots of principal component analysis (PCA) within the Swedish, Finnish and CGEMS populations (PDF 601 kb)

Supplementary File 4

Full description of results for previously known SNPs, including analyses performed for dominant and recessive models (XLS 39 kb)

Supplementary File 5

Full description of results for single SNP association results for SNPs within top-ranking pathways (XLS 1210 kb)

Supplementary File 6

Full description of results for pathway analysis. Empirical p-values for 212 KEGG pathways are presented (XLS 36 kb)

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Li, J., Humphreys, K., Heikkinen, T. et al. A combined analysis of genome-wide association studies in breast cancer. Breast Cancer Res Treat 126, 717–727 (2011). https://doi.org/10.1007/s10549-010-1172-9

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  • DOI: https://doi.org/10.1007/s10549-010-1172-9

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