A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis

Sajjad Rafiq, Sofia Khan, William Tapper, Andrew Collins, Rosanna Upstill-Goddard, Susan Gerty, Carl Blomqvist, Kristiina Aittomäki, Fergus J Couch, Jianjun Liu, Heli Nevanlinna, Diana Eccles

Research output: Contribution to journalArticle

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Abstract

Objective: Genome wide association studies (GWAs) of breast cancer mortality have identified few potential associations. The concordance between these studies is unclear. In this study, we used a meta-analysis of two prognostic GWAs and a replication cohort to identify the strongest associations and to evaluate the loci suggested in previous studies. We attempt to identify those SNPs which could impact overall survival irrespective of the age of onset. Methods: To facilitate the meta-analysis and to refine the association signals, SNPs were imputed using data from the 1000 genomes project. Cox-proportional hazard models were used to estimate hazard ratios (HR) in 536 patients from the POSH cohort (Prospective study of Outcomes in Sporadic versus Hereditary breast cancer) and 805 patients from the HEBCS cohort (Helsinki Breast Cancer Study). These hazard ratios were combined using a Mantel-Haenszel fixed effects meta-analysis and a p-value threshold of 5×10-8 was used to determine significance. Replication was performed in 1523 additional patients from the POSH study. Results: Although no SNPs achieved genome wide significance, three SNPs have significant association in the replication cohort and combined p-values less than 5.6×10-6. These SNPs are; rs421379 which is 556 kb upstream of ARRDC3 (HR = 1.49, 95% confidence interval (CI) = 1.27-1.75, P = 1.1×10-6), rs12358475 which is between ECHDC3 and PROSER2 (HR = 0.75, CI = 0.67-0.85, P = 1.8×10-6), and rs1728400 which is between LINC00917 and FOXF1. Conclusions: In a genome wide meta-analysis of two independent cohorts from UK and Finland, we identified potential associations at three distinct loci. Phenotypic heterogeneity and relatively small sample sizes may explain the lack of genome wide significant findings. However, the replication at three SNPs in the validation cohort shows promise for future studies in larger cohorts. We did not find strong evidence for concordance between the few associations highlighted by previous GWAs of breast cancer survival and this study.

Original languageEnglish (US)
Article numbere101488
JournalPLoS One
Volume9
Issue number12
DOIs
StatePublished - Dec 19 2014

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meta-analysis
breast neoplasms
prognosis
Single Nucleotide Polymorphism
Meta-Analysis
Hazards
Genes
Genome
Breast Neoplasms
genome
confidence interval
loci
prospective studies
Confidence Intervals
Finland
Survival
Genome-Wide Association Study
Age of Onset
Proportional Hazards Models
Sample Size

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Rafiq, S., Khan, S., Tapper, W., Collins, A., Upstill-Goddard, R., Gerty, S., ... Eccles, D. (2014). A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis. PLoS One, 9(12), [e101488]. https://doi.org/10.1371/journal.pone.0101488

A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis. / Rafiq, Sajjad; Khan, Sofia; Tapper, William; Collins, Andrew; Upstill-Goddard, Rosanna; Gerty, Susan; Blomqvist, Carl; Aittomäki, Kristiina; Couch, Fergus J; Liu, Jianjun; Nevanlinna, Heli; Eccles, Diana.

In: PLoS One, Vol. 9, No. 12, e101488, 19.12.2014.

Research output: Contribution to journalArticle

Rafiq, S, Khan, S, Tapper, W, Collins, A, Upstill-Goddard, R, Gerty, S, Blomqvist, C, Aittomäki, K, Couch, FJ, Liu, J, Nevanlinna, H & Eccles, D 2014, 'A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis', PLoS One, vol. 9, no. 12, e101488. https://doi.org/10.1371/journal.pone.0101488
Rafiq, Sajjad ; Khan, Sofia ; Tapper, William ; Collins, Andrew ; Upstill-Goddard, Rosanna ; Gerty, Susan ; Blomqvist, Carl ; Aittomäki, Kristiina ; Couch, Fergus J ; Liu, Jianjun ; Nevanlinna, Heli ; Eccles, Diana. / A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis. In: PLoS One. 2014 ; Vol. 9, No. 12.
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abstract = "Objective: Genome wide association studies (GWAs) of breast cancer mortality have identified few potential associations. The concordance between these studies is unclear. In this study, we used a meta-analysis of two prognostic GWAs and a replication cohort to identify the strongest associations and to evaluate the loci suggested in previous studies. We attempt to identify those SNPs which could impact overall survival irrespective of the age of onset. Methods: To facilitate the meta-analysis and to refine the association signals, SNPs were imputed using data from the 1000 genomes project. Cox-proportional hazard models were used to estimate hazard ratios (HR) in 536 patients from the POSH cohort (Prospective study of Outcomes in Sporadic versus Hereditary breast cancer) and 805 patients from the HEBCS cohort (Helsinki Breast Cancer Study). These hazard ratios were combined using a Mantel-Haenszel fixed effects meta-analysis and a p-value threshold of 5×10-8 was used to determine significance. Replication was performed in 1523 additional patients from the POSH study. Results: Although no SNPs achieved genome wide significance, three SNPs have significant association in the replication cohort and combined p-values less than 5.6×10-6. These SNPs are; rs421379 which is 556 kb upstream of ARRDC3 (HR = 1.49, 95{\%} confidence interval (CI) = 1.27-1.75, P = 1.1×10-6), rs12358475 which is between ECHDC3 and PROSER2 (HR = 0.75, CI = 0.67-0.85, P = 1.8×10-6), and rs1728400 which is between LINC00917 and FOXF1. Conclusions: In a genome wide meta-analysis of two independent cohorts from UK and Finland, we identified potential associations at three distinct loci. Phenotypic heterogeneity and relatively small sample sizes may explain the lack of genome wide significant findings. However, the replication at three SNPs in the validation cohort shows promise for future studies in larger cohorts. We did not find strong evidence for concordance between the few associations highlighted by previous GWAs of breast cancer survival and this study.",
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AU - Gerty, Susan

AU - Blomqvist, Carl

AU - Aittomäki, Kristiina

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N2 - Objective: Genome wide association studies (GWAs) of breast cancer mortality have identified few potential associations. The concordance between these studies is unclear. In this study, we used a meta-analysis of two prognostic GWAs and a replication cohort to identify the strongest associations and to evaluate the loci suggested in previous studies. We attempt to identify those SNPs which could impact overall survival irrespective of the age of onset. Methods: To facilitate the meta-analysis and to refine the association signals, SNPs were imputed using data from the 1000 genomes project. Cox-proportional hazard models were used to estimate hazard ratios (HR) in 536 patients from the POSH cohort (Prospective study of Outcomes in Sporadic versus Hereditary breast cancer) and 805 patients from the HEBCS cohort (Helsinki Breast Cancer Study). These hazard ratios were combined using a Mantel-Haenszel fixed effects meta-analysis and a p-value threshold of 5×10-8 was used to determine significance. Replication was performed in 1523 additional patients from the POSH study. Results: Although no SNPs achieved genome wide significance, three SNPs have significant association in the replication cohort and combined p-values less than 5.6×10-6. These SNPs are; rs421379 which is 556 kb upstream of ARRDC3 (HR = 1.49, 95% confidence interval (CI) = 1.27-1.75, P = 1.1×10-6), rs12358475 which is between ECHDC3 and PROSER2 (HR = 0.75, CI = 0.67-0.85, P = 1.8×10-6), and rs1728400 which is between LINC00917 and FOXF1. Conclusions: In a genome wide meta-analysis of two independent cohorts from UK and Finland, we identified potential associations at three distinct loci. Phenotypic heterogeneity and relatively small sample sizes may explain the lack of genome wide significant findings. However, the replication at three SNPs in the validation cohort shows promise for future studies in larger cohorts. We did not find strong evidence for concordance between the few associations highlighted by previous GWAs of breast cancer survival and this study.

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