Combined effect of low-penetrant SNPs on breast cancer risk View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-11-01

AUTHORS

S Harlid, M I L Ivarsson, S Butt, E Grzybowska, J E Eyfjörd, P Lenner, A Försti, K Hemminki, J Manjer, J Dillner, J Carlson

ABSTRACT

Background:Although many low-penetrant genetic risk factors for breast cancer have been discovered, knowledge about the effect of multiple risk alleles is limited, especially in women <50 years. We therefore investigated the association between multiple risk alleles and breast cancer risk as well as individual effects according to age-approximated pre- and post-menopausal status.Methods:Ten previously described breast cancer-associated single-nucleotide polymorphisms (SNPs) were analysed in a joint European biobank-based study comprising 3584 breast cancer cases and 5063 cancer-free controls. Genotyping was performed using MALDI-TOF mass spectrometry, and odds ratios were estimated using logistic regression.Results:Significant associations with breast cancer were confirmed for 7 of the 10 SNPs. Analysis of the joint effect of the original 10 as well as the statistically significant 7 SNPs (rs2981582, rs3803662, rs889312, rs13387042, rs13281615, rs3817198 and rs981782) found a highly significant trend for increasing breast cancer risk with increasing number of risk alleles (P-trend 5.6 × 10−20 and 1.5 × 10−25, respectively). Odds ratio for breast cancer of 1.84 (95% confidence interval (CI): 1.59–2.14; 10 SNPs) and 2.12 (95% CI: 1.80–2.50; 7 SNPs) was seen for the maximum vs the minimum number of risk alleles. Additionally, one of the examined SNPs (rs981782 in HCN1) had a protective effect that was significantly stronger in premenopausal women (P-value: 7.9 × 10−4).Conclusion:The strongly increasing risk seen when combining many low-penetrant risk alleles supports the polygenic inheritance model of breast cancer. More... »

PAGES

389-396

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/bjc.2011.461

DOI

http://dx.doi.org/10.1038/bjc.2011.461

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https://app.dimensions.ai/details/publication/pub.1001060523

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22045194


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31 schema:description Background:Although many low-penetrant genetic risk factors for breast cancer have been discovered, knowledge about the effect of multiple risk alleles is limited, especially in women <50 years. We therefore investigated the association between multiple risk alleles and breast cancer risk as well as individual effects according to age-approximated pre- and post-menopausal status.Methods:Ten previously described breast cancer-associated single-nucleotide polymorphisms (SNPs) were analysed in a joint European biobank-based study comprising 3584 breast cancer cases and 5063 cancer-free controls. Genotyping was performed using MALDI-TOF mass spectrometry, and odds ratios were estimated using logistic regression.Results:Significant associations with breast cancer were confirmed for 7 of the 10 SNPs. Analysis of the joint effect of the original 10 as well as the statistically significant 7 SNPs (rs2981582, rs3803662, rs889312, rs13387042, rs13281615, rs3817198 and rs981782) found a highly significant trend for increasing breast cancer risk with increasing number of risk alleles (P-trend 5.6 × 10−20 and 1.5 × 10−25, respectively). Odds ratio for breast cancer of 1.84 (95% confidence interval (CI): 1.59–2.14; 10 SNPs) and 2.12 (95% CI: 1.80–2.50; 7 SNPs) was seen for the maximum vs the minimum number of risk alleles. Additionally, one of the examined SNPs (rs981782 in HCN1) had a protective effect that was significantly stronger in premenopausal women (P-value: 7.9 × 10−4).Conclusion:The strongly increasing risk seen when combining many low-penetrant risk alleles supports the polygenic inheritance model of breast cancer.
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37 schema:keywords MALDI-TOF mass spectrometry
38 alleles
39 analysis
40 association
41 biobank-based studies
42 breast cancer
43 breast cancer cases
44 breast cancer risk
45 breast cancer-associated single nucleotide polymorphisms
46 cancer
47 cancer cases
48 cancer risk
49 cancer-associated single nucleotide polymorphisms
50 cancer-free controls
51 cases
52 combined effect
53 control
54 effect
55 factors
56 genetic risk factors
57 genotyping
58 individual effects
59 inheritance model
60 joint effects
61 knowledge
62 logistic regression
63 low penetrant single nucleotide polymorphisms
64 mass spectrometry
65 maximum
66 minimum number
67 model
68 multiple risk alleles
69 number
70 odds
71 odds ratio
72 polygenic inheritance model
73 polymorphism
74 post-menopausal status
75 pre
76 premenopausal women
77 protective effect
78 ratio
79 regression
80 risk
81 risk alleles
82 risk factors
83 significant association
84 significant trend
85 single nucleotide polymorphisms
86 spectrometry
87 status
88 study
89 trends
90 women
91 years
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