Common variants in ZNF365 are associated with both mammographic density and breast cancer risk.
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ABSTRACT:
SUBMITTER: Lindstrom S
PROVIDER: S-EPMC3076615 | biostudies-literature | 2011 Mar
REPOSITORIES: biostudies-literature
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Common variants in ZNF365 are associated with both mammographic density and breast cancer risk.
Lindström Sara S Vachon Celine M CM Li Jingmei J Varghese Jajini J Thompson Deborah D Warren Ruth R Brown Judith J Leyland Jean J Audley Tina T Wareham Nicholas J NJ Loos Ruth J F RJ Paterson Andrew D AD Rommens Johanna J Waggott Darryl D Martin Lisa J LJ Scott Christopher G CG Pankratz V Shane VS Hankinson Susan E SE Hazra Aditi A Hunter David J DJ Hopper John L JL Southey Melissa C MC Chanock Stephen J SJ Silva Isabel dos Santos Idos S Liu JianJun J Eriksson Louise L Couch Fergus J FJ Stone Jennifer J Apicella Carmel C Czene Kamila K Kraft Peter P Hall Per P Easton Douglas F DF Boyd Norman F NF Tamimi Rulla M RM
Nature genetics 20110130 3
High-percent mammographic density adjusted for age and body mass index is one of the strongest risk factors for breast cancer. We conducted a meta analysis of five genome-wide association studies of percent mammographic density and report an association with rs10995190 in ZNF365 (combined P = 9.6 × 10(-10)). Common variants in ZNF365 have also recently been associated with susceptibility to breast cancer. ...[more]
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Project description:IntroductionKnown prediction models for breast cancer can potentially by improved by the addition of mammographic density and common genetic variants identified in genome-wide associations studies known to be associated with risk of the disease. We evaluated the benefit of including mammographic density and the cumulative effect of genetic variants in breast cancer risk prediction among women in a Singapore population.MethodsWe estimated the risk of breast cancer using a prospective cohort of 24,161 women aged 50 to 64 from Singapore with available mammograms and known risk factors for breast cancer who were recruited between 1994 and 1997. We measured mammographic density using the medio-lateral oblique views of both breasts. Each woman's genotype for 75 SNPs was simulated based on the genotype frequency obtained from the Breast Cancer Association Consortium data and the cumulative effect was summarized by a genetic risk score (GRS). Any improvement in the performance of our proposed prediction model versus one containing only variables from the Gail model was assessed by changes in receiver-operating characteristic and predictive values.ResultsDuring 17 years of follow-up, 680 breast cancer cases were diagnosed. The multivariate-adjusted hazard ratios (95% confidence intervals) were 1.60 (1.22-2.10), 2.20 (1.65-2.92), 2.33 (1.71-3.20), 2.12 (1.43-3.14), and 3.27 (2.24-4.76) for the corresponding mammographic density categories: 11-20cm2, 21-30cm2, 31-40cm2, 41-50cm2, 51-60cm2, and 1.10 (1.03-1.16) for GRS. At the predicted absolute 10-year risk thresholds of 2.5% and 3.0%, a model with mammographic density and GRS could correctly identify 0.9% and 0.5% more women who would develop the disease compared to a model using only the Gail variables, respectively.ConclusionMammographic density and common genetic variants can improve the discriminatory power of an established breast cancer risk prediction model among females in Singapore.
| S-EPMC4581713 | biostudies-literature
Project description:BackgroundMammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biologic mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to interindividual differences in mammographic density measures.MethodsWe established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and nondense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, BMI, and menopausal status.ResultsConsistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (P = 0.00005) and adjusted percent density (P = 0.001), whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (P = 0.003), but not with adjusted dense area (P = 0.07).ConclusionWe identified two common breast cancer susceptibility variants associated with mammographic measures of radiodense tissue in the breast gland.ImpactWe examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association.
| S-EPMC3569092 | biostudies-literature
Project description:Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.
| S-EPMC4470785 | biostudies-literature
Project description:Mammographic density reflects the amount of stromal and epithelial tissues in relation to adipose tissue in the breast and is a strong risk factor for breast cancer. Here we report the results from meta-analysis of genome-wide association studies (GWAS) of three mammographic density phenotypes: dense area, non-dense area and percent density in up to 7,916 women in stage 1 and an additional 10,379 women in stage 2. We identify genome-wide significant (P<5 × 10(-8)) loci for dense area (AREG, ESR1, ZNF365, LSP1/TNNT3, IGF1, TMEM184B and SGSM3/MKL1), non-dense area (8p11.23) and percent density (PRDM6, 8p11.23 and TMEM184B). Four of these regions are known breast cancer susceptibility loci, and four additional regions were found to be associated with breast cancer (P<0.05) in a large meta-analysis. These results provide further evidence of a shared genetic basis between mammographic density and breast cancer and illustrate the power of studying intermediate quantitative phenotypes to identify putative disease-susceptibility loci.
| S-EPMC4320806 | biostudies-literature
Project description:Cumulus, Altocumulus, and Cirrocumulus are measures of mammographic density defined at increasing pixel brightness thresholds, which, when converted to mammogram risk scores (MRSs), predict breast cancer risk. Twin and family studies suggest substantial variance in the MRSs could be explained by genetic factors. For 2559 women aged 30 to 80 years (mean 54 years), we measured the MRSs from digitized film mammograms and estimated the associations of the MRSs with a 313-SNP breast cancer polygenic risk score (PRS) and 202 individual SNPs associated with breast cancer risk. The PRS was weakly positively correlated (correlation coefficients ranged 0.05−0.08; all p < 0.04) with all the MRSs except the Cumulus-white MRS based on the “white but not bright area” (correlation coefficient = 0.04; p = 0.06). After adjusting for its association with the Altocumulus MRS, the PRS was not associated with the Cumulus MRS. There were MRS associations (Bonferroni-adjusted p < 0.04) with one SNP in the ATXN1 gene and nominally with some ESR1 SNPs. Less than 1% of the variance of the MRSs is explained by the genetic markers currently known to be associated with breast cancer risk. Discovering the genetic determinants of the bright, not white, regions of the mammogram could reveal substantial new genetic causes of breast cancer.
| S-EPMC9179294 | biostudies-literature
Project description:PurposeTo improve breast cancer risk stratification to enable more targeted early detection/prevention strategies that will better balance risks and benefits of population screening programmes.Methods9362 of 57,902 women in the Predicting-Risk-Of-Cancer-At-Screening (PROCAS) study who were unaffected by breast cancer at study entry and provided DNA for a polygenic risk score (PRS). The PRS was analysed alongside mammographic density (density-residual-DR) and standard risk factors (Tyrer-Cuzick-model) to assess future risk of breast cancer based on tumour stage receptor expression and pathology.Results195 prospective incident breast cancers had a prediction based on TC/DR/PRS which was informative for subsequent breast cancer overall [IQ-OR 2.25 (95% CI 1.89-2.68)] with excellent calibration-(0.99). The model performed particularly well in predicting higher stage stage 2+ IQ-OR 2.69 (95% CI 2.02-3.60) and ER + BCs (IQ-OR 2.36 (95% CI 1.93-2.89)). DR was most predictive for HER2+ and stage 2+ cancers but did not discriminate as well between poor and extremely good prognosis BC as either Tyrer-Cuzick or PRS. In contrast, PRS gave the highest OR for incident stage 2+ cancers, [IQR-OR 1.79 (95% CI 1.30-2.46)].ConclusionsA combined approach using Tyrer-Cuzick/DR/PRS provides accurate risk stratification, particularly for poor prognosis cancers. This provides support for reducing the screening interval in high-risk women and increasing the screening interval in low-risk women defined by this model.
| S-EPMC6548748 | biostudies-literature
Project description:IntroductionSeveral common alleles have been shown to be associated with breast and/or ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. Recent genome-wide association studies of breast cancer have identified eight additional breast cancer susceptibility loci: rs1011970 (9p21, CDKN2A/B), rs10995190 (ZNF365), rs704010 (ZMIZ1), rs2380205 (10p15), rs614367 (11q13), rs1292011 (12q24), rs10771399 (12p11 near PTHLH) and rs865686 (9q31.2).MethodsTo evaluate whether these single nucleotide polymorphisms (SNPs) are associated with breast cancer risk for BRCA1 and BRCA2 carriers, we genotyped these SNPs in 12,599 BRCA1 and 7,132 BRCA2 mutation carriers and analysed the associations with breast cancer risk within a retrospective likelihood framework.ResultsOnly SNP rs10771399 near PTHLH was associated with breast cancer risk for BRCA1 mutation carriers (per-allele hazard ratio (HR) = 0.87, 95% CI: 0.81 to 0.94, P-trend = 3 × 10-4). The association was restricted to mutations proven or predicted to lead to absence of protein expression (HR = 0.82, 95% CI: 0.74 to 0.90, P-trend = 3.1 × 10-5, P-difference = 0.03). Four SNPs were associated with the risk of breast cancer for BRCA2 mutation carriers: rs10995190, P-trend = 0.015; rs1011970, P-trend = 0.048; rs865686, 2df-P = 0.007; rs1292011 2df-P = 0.03. rs10771399 (PTHLH) was predominantly associated with estrogen receptor (ER)-negative breast cancer for BRCA1 mutation carriers (HR = 0.81, 95% CI: 0.74 to 0.90, P-trend = 4 × 10-5) and there was marginal evidence of association with ER-negative breast cancer for BRCA2 mutation carriers (HR = 0.78, 95% CI: 0.62 to 1.00, P-trend = 0.049).ConclusionsThe present findings, in combination with previously identified modifiers of risk, will ultimately lead to more accurate risk prediction and an improved understanding of the disease etiology in BRCA1 and BRCA2 mutation carriers.
| S-EPMC3496151 | biostudies-literature
Project description:BackgroundBenign breast disease and high breast density are prevalent, strong risk factors for breast cancer. Women with both risk factors may be at very high risk.MethodsWe included 42818 women participating in the Breast Cancer Surveillance Consortium who had no prior diagnosis of breast cancer and had undergone at least one benign breast biopsy and mammogram; 1359 women developed incident breast cancer in 6.1 years of follow-up (78.1% invasive, 21.9% ductal carcinoma in situ). We calculated hazard ratios (HRs) using Cox regression analysis. The referent group was women with nonproliferative changes and average density. All P values are two-sided.ResultsBenign breast disease and breast density were independently associated with breast cancer. The combination of atypical hyperplasia and very high density was uncommon (0.6% of biopsies) but was associated with the highest risk for breast cancer (HR = 5.34; 95% confidence interval [CI] = 3.52 to 8.09, P < .001). Proliferative disease without atypia (25.6% of biopsies) was associated with elevated risk that varied little across levels of density: average (HR = 1.37; 95% CI = 1.11 to 1.69, P = .003), high (HR = 2.02; 95% CI = 1.68 to 2.44, P < .001), or very high (HR = 2.05; 95% CI = 1.54 to 2.72, P < .001). Low breast density (4.5% of biopsies) was associated with low risk (HRs <1) for all benign pathology diagnoses.ConclusionsWomen with high breast density and proliferative benign breast disease are at very high risk for future breast cancer. Women with low breast density are at low risk, regardless of their benign pathologic diagnosis.
| S-EPMC3714021 | biostudies-literature
Project description:BackgroundAttention in the 2000s on the importance of mammographic density led us to study screening sensitivity, breast cancer incidence, and associations with risk factors by mammographic density in Danish breast cancer screening programs. Here, we summarise our approaches and findings.MethodsDichotomized density codes: fatty, equal to BI-RADS density code 1 and part of 2, and other mixed/dense data from the 1990s-were available from two counties, and BI-RADS density codes from one region were available from 2012/13. Density data were linked with data on vital status, incident breast cancer, and potential risk factors. We calculated screening sensitivity by combining data on screen-detected and interval cancers. We used cohorts to study high density as a predictor of breast cancer risk; cross-sectional data to study the association between life style factors and density, adjusting for age and body mass index (BMI); and time trends to study the prevalence of high density across birth cohorts.ResultsSensitivity decreased with increasing density from 78% in women with BI-RADS 1 to 47% in those with BI-RADS 4. For women with mixed/dense compared with those with fatty breasts, the rate ratio of incident breast cancer was 2.45 (95% CI 2.14-2.81). The percentage of women with mixed/dense breasts decreased with age, but at a higher rate the later the women were born. Among users of postmenopausal hormone therapy, the percentage of women with mixed/dense breasts was higher than in non-users, but the patterns across birth cohorts were similar. The occurrence of mixed/dense breast at screening age decreased by a z-score unit of BMI at age 13-odds ratio (OR) 0.56 (95% CI 0.53-0.58)-and so did breast cancer risk and hazard ratio (HR) 0.92 (95% CI 0.84-1.00), but it changed to HR 1.01 (95% CI 0.93-1.11) when controlled for density. Age and BMI adjusted associations between life style factors and density were largely close to unity; physical activity OR 1.06 (95% CI 0.93-1.21); alcohol consumption OR 1.01 (95% CI 0.81-1.27); air pollution OR 0.96 (95% 0.93-1.01) per 20 ?g/m3; and traffic noise OR 0.94 (95% CI 0.86-1.03) per 10 dB. Weak negative associations were seen for diabetes OR 0.61 (95% CI 0.40-0.92) and cigarette smoking OR 0.86 (95% CI 0.75-0.99), and a positive association was found with hormone therapy OR 1.24 (95% 1.14-1.35).ConclusionOur data indicate that breast tissue in middle-aged women is highly dependent on childhood body constitution while adult life-style plays a modest role, underlying the need for a long-term perspective in primary prevention of breast cancer.
| S-EPMC6912479 | biostudies-literature
Project description:BACKGROUND:Genome-wide association studies (GWAS) identified variants at 19p13.1 and ZNF365 (10q21.2) as risk factors for breast cancer among BRCA1 and BRCA2 mutation carriers, respectively. We explored associations with ovarian cancer and with breast cancer by tumor histopathology for these variants in mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). METHODS:Genotyping data for 12,599 BRCA1 and 7,132 BRCA2 mutation carriers from 40 studies were combined. RESULTS:We confirmed associations between rs8170 at 19p13.1 and breast cancer risk for BRCA1 mutation carriers [HR, 1.17; 95% confidence interval (CI), 1.07-1.27; P = 7.42 × 10(-4)] and between rs16917302 at ZNF365 (HR, 0.84; 95% CI, 0.73-0.97; P = 0.017) but not rs311499 at 20q13.3 (HR, 1.11; 95% CI, 0.94-1.31; P = 0.22) and breast cancer risk for BRCA2 mutation carriers. Analyses based on tumor histopathology showed that 19p13 variants were predominantly associated with estrogen receptor (ER)-negative breast cancer for both BRCA1 and BRCA2 mutation carriers, whereas rs16917302 at ZNF365 was mainly associated with ER-positive breast cancer for both BRCA1 and BRCA2 mutation carriers. We also found for the first time that rs67397200 at 19p13.1 was associated with an increased risk of ovarian cancer for BRCA1 (HR, 1.16; 95% CI, 1.05-1.29; P = 3.8 × 10(-4)) and BRCA2 mutation carriers (HR, 1.30; 95% CI, 1.10-1.52; P = 1.8 × 10(-3)). CONCLUSIONS:19p13.1 and ZNF365 are susceptibility loci for ovarian cancer and ER subtypes of breast cancer among BRCA1 and BRCA2 mutation carriers. IMPACT:These findings can lead to an improved understanding of tumor development and may prove useful for breast and ovarian cancer risk prediction for BRCA1 and BRCA2 mutation carriers.
| S-EPMC3319317 | biostudies-literature