scholarly journals A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46 450 cases and 42 461 controls from the breast cancer association consortium

2013 ◽  
Vol 23 (7) ◽  
pp. 1934-1946 ◽  
Author(s):  
Roger L. Milne ◽  
Jesús Herranz ◽  
Kyriaki Michailidou ◽  
Joe Dennis ◽  
Jonathan P. Tyrer ◽  
...  
2014 ◽  
Vol 23 (22) ◽  
pp. 6096-6111 ◽  
Author(s):  
Roger L. Milne ◽  
Barbara Burwinkel ◽  
Kyriaki Michailidou ◽  
Jose-Ignacio Arias-Perez ◽  
M. Pilar Zamora ◽  
...  

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e2815 ◽  
Author(s):  
Zhiming Dai ◽  
Tian Tian ◽  
Meng Wang ◽  
Xinghan Liu ◽  
Shuai Lin ◽  
...  

Previous studies have investigated the association between cytotoxic T-lymphocyte antigen-4 (CTLA-4) polymorphisms and breast cancer susceptibility, but the results remained inconsistent. Therefore, we evaluated the relationship between four common CTLA-4 polymorphisms and breast cancer risk by a meta-analysis, aiming to derive a comprehensive and precise conclusion. We searched EMBASE, Pubmed, Web of Science, CNKI, and Wanfang databases until July 18th, 2016. Finally, ten eligible studies involving 4,544 breast cancer patients and 4,515 cancer-free controls were included; all these studies were from Asia. Odds ratio (OR) and 95% confidence interval (CI) were used to evaluate the breast cancer risk in five genetic models. The results indicated that the CTLA-4 +49A>G (rs231775) polymorphism had a significant association with decreased breast cancer risk in allelic, homozygous, dominant and recessive models. Also, the +6230G>A (rs3087243) polymorphism reduced breast cancer risk especially in the Chinese population under homozygous and recessive models. In contrast, the −1661A>G (rs4553808) polymorphism increased breast cancer risk in allelic, heterozygous and dominant models, whereas −1722 T>C (rs733618) did not relate to breast cancer risk. In conclusion, CTLA-4 polymorphisms significantly associate with breast cancer susceptibility in Asian populations, and different gene loci may have different effects on breast cancer development. Further large-scale studies including multi-racial populations are required to confirm our findings.


2007 ◽  
Vol 67 (19) ◽  
pp. 9584-9590 ◽  
Author(s):  
Marjanka K. Schmidt ◽  
Scarlett Reincke ◽  
Annegien Broeks ◽  
Linde M. Braaf ◽  
Frans B.L. Hogervorst ◽  
...  

2015 ◽  
Vol 47 (11) ◽  
pp. 1294-1303 ◽  
Author(s):  
Felix R Day ◽  
◽  
Katherine S Ruth ◽  
Deborah J Thompson ◽  
Kathryn L Lunetta ◽  
...  

2015 ◽  
Vol 70 (12) ◽  
pp. 758-762
Author(s):  
Felix R. Day ◽  
Katherine S. Ruth ◽  
Deborah J. Thompson ◽  
Kathryn L. Lunetta ◽  
Natalia Pervjakova ◽  
...  

2019 ◽  
Vol 49 (1) ◽  
pp. 216-232 ◽  
Author(s):  
Pooja Middha Kapoor ◽  
Sara Lindström ◽  
Sabine Behrens ◽  
Xiaoliang Wang ◽  
Kyriaki Michailidou ◽  
...  

Abstract Background Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions. Methods Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions. Results Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10–4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10–5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth. Conclusions Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.


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