A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis.
<h4>Objective</h4>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 stronge...
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| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2014-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0101488 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Sajjad Rafiq |
| collection | DOAJ |
| description | <h4>Objective</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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. |
| format | Article |
| id | doaj-art-75b5ef61c65741d4a2105cb78f057939 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-75b5ef61c65741d4a2105cb78f0579392025-08-20T03:46:13ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-01912e10148810.1371/journal.pone.0101488A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis.Sajjad RafiqSofia KhanWilliam TapperAndrew CollinsRosanna Upstill-GoddardSusan GertyCarl BlomqvistKristiina AittomäkiFergus J CouchJianjun LiuHeli NevanlinnaDiana Eccles<h4>Objective</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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.https://doi.org/10.1371/journal.pone.0101488 |
| spellingShingle | 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 A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis. PLoS ONE |
| title | A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis. |
| title_full | A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis. |
| title_fullStr | A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis. |
| title_full_unstemmed | A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis. |
| title_short | A genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis. |
| title_sort | genome wide meta analysis study for identification of common variation associated with breast cancer prognosis |
| url | https://doi.org/10.1371/journal.pone.0101488 |
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