| 31. |
- Middha, Pooja K., et al.
(författare)
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A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry
- 2023
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Ingår i: Breast Cancer Research. - : BioMed Central (BMC). - 1465-5411 .- 1465-542X. ; 25:1
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Tidskriftsartikel (refereegranskat)abstract
- Background Genome-wide studies of gene-environment interactions (GxE) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide GxE analysis of similar to 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer. Methods Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs. Results Assuming a 1 x 10(-5) prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94). Conclusions Overall, the contribution of GxE interactions to the heritability of breast cancer is very small. At the population level, multiplicative GxE interactions do not make an important contribution to risk prediction in breast cancer.
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| 32. |
- Orr, Nick, et al.
(författare)
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Genome-wide association study identifies a common variant in RAD51B associated with male breast cancer risk
- 2012
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 44:11, s. 1182-1184
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Tidskriftsartikel (refereegranskat)abstract
- We conducted a genome-wide association study of male breast cancer comprising 823 cases and 2,795 controls of European ancestry, with validation in independent sample sets totaling 438 cases and 474 controls. A SNP in RAD51B at 14q24.1 was significantly associated with male breast cancer risk (P = 3.02 x 10(-13); odds ratio (OR) = 1.57). We also refine association at 16q12.1 to a SNP within TOX3 (P = 3.87 x 10(-15); OR = 1.50).
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| 33. |
- Shu, Xiang, et al.
(författare)
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Associations of obesity and circulating insulin and glucose with breast cancer risk : a Mendelian randomization analysis
- 2019
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Ingår i: International Journal of Epidemiology. - : OXFORD UNIV PRESS. - 0300-5771 .- 1464-3685. ; 48:3, s. 795-806
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Tidskriftsartikel (refereegranskat)abstract
- Background: In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear. Methods: We conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium. Results: All sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p = 5.09 x 10(-4)], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p = 4.02 x 10(-4)), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p = 5.05 x 10(-19)) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p = 9.22 x 10(-6)). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer. Conclusions: We confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer.
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| 34. |
- Shu, Xiang, et al.
(författare)
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Evaluation of associations between genetically predicted circulating protein biomarkers and breast cancer risk
- 2020
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Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 146:8, s. 2130-2138
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Tidskriftsartikel (refereegranskat)abstract
- A small number of circulating proteins have been reported to be associated with breast cancer risk, with inconsistent results. Herein, we attempted to identify novel protein biomarkers for breast cancer via the integration of genomics and proteomics data. In the Breast Cancer Association Consortium (BCAC), with 122,977 cases and 105,974 controls of European descendants, we evaluated the associations of the genetically predicted concentrations of >1,400 circulating proteins with breast cancer risk. We used data from a large-scale protein quantitative trait loci (pQTL) analysis as our study instrument. Summary statistics for these pQTL variants related to breast cancer risk were obtained from the BCAC and used to estimate odds ratios (OR) for each protein using the inverse-variance weighted method. We identified 56 proteins significantly associated with breast cancer risk by instrumental analysis (false discovery rate <0.05). Of these, the concentrations of 32 were influenced by variants close to a breast cancer susceptibility locus (ABO, 9q34.2). Many of these proteins, such as insulin receptor, insulin-like growth factor receptor 1 and other membrane receptors (OR: 0.82–1.18, p values: 6.96 × 10−4–3.28 × 10−8), are linked to insulin resistance and estrogen receptor signaling pathways. Proteins identified at other loci include those involved in biological processes such as alcohol and lipid metabolism, proteolysis, apoptosis, immune regulation and cell motility and proliferation. Consistent associations were observed for 22 proteins in the UK Biobank data (p < 0.05). The study identifies potential novel biomarkers for breast cancer, but further investigation is needed to replicate our findings.
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| 35. |
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| 36. |
- Stevens, Kristen N, et al.
(författare)
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19p13.1 is a triple negative-specific breast cancer susceptibility locus
- 2012
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Ingår i: Cancer Research. - 0008-5472 .- 1538-7445. ; 72, s. 1795-
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Tidskriftsartikel (refereegranskat)abstract
- The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with risk of ovarian cancer. Here we investigated 19p13.1 variation and risk of breast cancer subtypes, defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status, using 48,869 breast cancer cases and 49,787 controls from the Breast Cancer Association Consortium (BCAC). Variants from 19p13.1 were not associated with breast cancer overall or with ER-positive breast cancer but were significantly associated with ER-negative breast cancer risk [rs8170 Odds Ratio (OR)=1.10, 95% Confidence Interval (CI) 1.05 - 1.15, p=3.49 x 10-5] and triple negative (TN) (ER, PR and HER2 negative) breast cancer [rs8170 OR=1.22, 95% CI 1.13 - 1.31, p=2.22 x 10-7]. However, rs8170 was no longer associated with ER-negative breast cancer risk when TN cases were excluded [OR=0.98, 95% CI 0.89 - 1.07, p=0.62]. In addition, a combined analysis of TN cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC) (n=3,566) identified a genome-wide significant association between rs8170 and TN breast cancer risk [OR=1.25, 95% CI 1.18 - 1.33, p=3.31 x 10-13]. Thus, 19p13.1 is the first triple negative-specific breast cancer risk locus and the first locus specific to a histological subtype defined by ER, PR, and HER2 to be identified. These findings provide convincing evidence that genetic susceptibility to breast cancer varies by tumor subtype and that triple negative tumors and other subtypes likely arise through distinct etiologic pathways.
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| 37. |
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| 38. |
- Zeng, Chenjie, et al.
(författare)
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Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus
- 2016
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Background: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. Method: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. Results: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 x 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 x 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 x 10(-4)) identified in the general populations, and rs113824616 (P = 7 x 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. Conclusion: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.
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