scholarly journals Genome-wide association study of peripheral blood DNA methylation and conventional mammographic density measures

2018 ◽  
Author(s):  
Shuai Li ◽  
Pierre-Antoine Dugué ◽  
Laura Baglietto ◽  
Gianluca Severi ◽  
Ee Ming Wong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density ◽  
Peripheral Blood ◽  
Meta Analysis ◽  
Dense Area ◽  
Genome Wide ◽  
Density Measure

AbstractAge- and body mass index (BMI)-adjusted mammographie density is one the strongest breast cancer risk factors. DNA methylation is a molecular mechanism that could underlie interindividual variation in mammographic density. We aimed to investigate the association between breast cancer risk-predicting mammographic density measures and blood DNA methylation. For 436 women from the Australian Mammographic Density Twins and Sisters Study and 591 women from the Melbourne Collaborative Cohort Study, mammographic density (dense area, non-dense area and percentage dense area) defined by the conventional brightness threshold was measured using the CUMULUS software, and peripheral blood DNA methylation was measured using the HumanMethylation450 (HM450) BeadChip assay. Associations between DNA methylation at >400,000 sites and mammographic density measures adjusted for age and BMI were assessed within each cohort and pooled using fixed-effect meta-analysis. Associations with methylation at genetic loci known to be associated with mammographic density were also examined. We found no genome-wide significant(P<10−7)association for any mammographic density measure from the meta-analysis, or from the cohort-specific analyses. None of the 299 methylation sites located at genetic loci associated with mammographic density was associated with any mammographic density measure after adjusting for multiple testing (all P>0.05/299 = 1.7 × 10−4). In summary, our study did not detect associations between blood DNA methylation, as measured by the HM450 assay, and conventional mammographic density measures that predict breast cancer risk.

Abstract 3230: Genome-wide blood DNA methylation and breast cancer risk: A meta-analysis of four prospective studies

2018 ◽  
Author(s):  
Clara Bodelon ◽  
Srikant Ambatipudi ◽  
Pierre-Antoine Dugué ◽  
Annelie Johansson ◽  
Joshua N. Sampson ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Prospective Studies ◽  
Meta Analysis ◽  
Genome Wide

scholarly journals Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Weiva Sieh ◽  
Joseph H. Rothstein ◽  
Robert J. Klein ◽  
Stacey E. Alexeeff ◽  
Lori C. Sakoda ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density ◽  
Genetic Basis ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Biological Processes ◽  
Dense Area ◽  
Pathway Analyses

Abstract Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P < 5 × 10−8, tripling the number known to 46. Seventeen identified MD loci also are associated with breast cancer risk in an independent meta-analysis (P < 0.05). Mendelian randomization analyses show that genetic estimates of dense area (DA), nondense area (NDA), and percent density (PD) are all significantly associated with breast cancer risk (P < 0.05). Pathway analyses reveal distinct biological processes involving DA, NDA and PD loci. These findings provide additional insights into the genetic basis of MD phenotypes and their associations with breast cancer risk.

No association between night shiftwork and mammographic density

2020 ◽  
Vol 77 (8) ◽  
pp. 564-567
Author(s):  
Sonia El-Zaemey ◽  
Lin Fritschi ◽  
Jane Heyworth ◽  
Terry Boyle ◽  
Christobel Saunders ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Phase Shift ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density ◽  
Large Population ◽  
Cancer Case ◽  
Light At Night ◽  
Related Factors ◽  
Dense Area

BackgroundIncreased mammographic density is one of the strongest risk factors for breast cancer. Night shiftwork and its related factors, which include light at night, phase shift and sleep disruption, are believed to increase breast cancer risk however, their effects on mammographic density have barely been studied.MethodsThis study included 1821 women enrolled in the Breast Cancer Environment and Employment Study between 2009 and 2011. Mammographic density was measured using the Cumulus software program. The association of night shiftwork factors with square root transformed absolute dense area (DA) and percentage dense area (PDA) were modelled using linear regression adjusted for confounders.ResultsEver doing graveyard shiftwork (between 24:00 and 05:00 hours) was not associated with PDA (β=−0.10; 95% CI −0.27 to 0.08)) and DA (β=−0.12; 95% CI −0.33 to 0.09)). No association was found between night shiftwork related factors (light at night, phase shift and sleep disturbance) with PDA or DA.ConclusionsShiftwork and its related factors are not associated with mammographic density. Using high-quality, comprehensive shiftwork data from a large population-based breast cancer case–control study, this study suggests that mammographic density does not play a role in the relationship between shiftwork and breast cancer risk.

scholarly journals DNA methylation-based biological age, genome-wide average DNA methylation, and conventional breast cancer risk factors

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Minyuan Chen ◽  
Ee Ming Wong ◽  
Tuong L. Nguyen ◽  
Gillian S. Dite ◽  
Jennifer Stone ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Dna Methylation ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Biological Age ◽  
Age At Menarche ◽  
Cancer Risk Factors ◽  
Genome Wide ◽  
Breast Cancer Risk Factors

Abstract DNA methylation-based biological age (DNAm age), as well as genome-wide average DNA methylation, have been reported to predict breast cancer risk. We aimed to investigate the associations between these DNA methylation-based risk factors and 18 conventional breast cancer risk factors for disease-free women. A sample of 479 individuals from the Australian Mammographic Density Twins and Sisters was used for discovery, a sample of 3354 individuals from the Melbourne Collaborative Cohort Study was used for replication, and meta-analyses pooling results from the two studies were conducted. DNAm age based on three epigenetic clocks (Hannum, Horvath and Levine) and genome-wide average DNA methylation were calculated using the HumanMethylation 450 K BeadChip assay data. The DNAm age measures were positively associated with body mass index (BMI), smoking, alcohol drinking and age at menarche (all nominal P < 0.05). Genome-wide average DNA methylation was negatively associated with smoking and number of live births, and positively associated with age at first live birth (all nominal P < 0.05). The association of DNAm age with BMI was also evident in within-twin-pair analyses that control for familial factors. This study suggests that some lifestyle and hormonal risk factors are associated with these DNA methylation-based breast cancer risk factors, and the observed associations are unlikely to be due to familial confounding but are likely causal. DNA methylation-based risk factors could interplay with conventional risk factors in modifying breast cancer risk.

scholarly journals Novel mammogram‐based measures improve breast cancer risk prediction beyond an established mammographic density measure

2020 ◽  
Author(s):  
Tuong L. Nguyen ◽  
Daniel F. Schmidt ◽  
Enes Makalic ◽  
Gertraud Maskarinec ◽  
Shuai Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Prediction ◽  
Mammographic Density ◽  
Density Measure

scholarly journals Blood DNA methylation and breast cancer risk: a meta-analysis of four prospective cohort studies

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Clara Bodelon ◽  
Srikant Ambatipudi ◽  
Pierre-Antoine Dugué ◽  
Annelie Johansson ◽  
Joshua N. Sampson ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Cohort Studies ◽  
Prospective Cohort ◽  
Meta Analysis ◽  
Blood Collection ◽  
Prospective Cohort Studies ◽  
Average Methylation

Abstract Background Environmental and genetic factors play an important role in the etiology of breast cancer. Several small blood-based DNA methylation studies have reported risk associations with methylation at individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1663 incident cases and 1885 controls, the largest study of blood DNA methylation and breast cancer risk to date. Methods We assessed associations with methylation at 365,145 CpGs present in the HumanMethylation450 (HM450K) Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. Stratified analyses were conducted by age at diagnosis (< 50, ≥ 50), estrogen receptor (ER) status (+/−), and time since blood collection (< 5, 5–10, > 10 years). The false discovery rate (q value) was used to account for multiple testing. Results The average age at blood draw ranged from 52.2 to 62.2 years across the four cohorts. Median follow-up time ranged from 6.6 to 8.4 years. The methylation measured at individual CpGs was not associated with breast cancer risk (q value > 0.59). In addition, higher average methylation level was not associated with risk of breast cancer (OR = 0.94, 95% CI = 0.85, 1.05; P = 0.26; P for study heterogeneity = 0.86). We found no evidence of modification of this association by age at diagnosis (P = 0.17), ER status (P = 0.88), time since blood collection (P = 0.98), or CpG location (P = 0.98). Conclusions Our data indicate that DNA methylation measured in the blood prior to breast cancer diagnosis in predominantly postmenopausal women is unlikely to be associated with substantial breast cancer risk on the HM450K array. Larger studies or with greater methylation coverage are needed to determine if associations exist between blood DNA methylation and breast cancer risk.

scholarly journals A Novel Automated Mammographic Density Measure and Breast 
Cancer Risk

2012 ◽  
Vol 104 (13) ◽  
pp. 1028-1037 ◽  
Author(s):  
John J. Heine ◽  
Christopher G. Scott ◽  
Thomas A. Sellers ◽  
Kathleen R. Brandt ◽  
Daniel J. Serie ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density ◽  
Density Measure

scholarly journals Using mammographic density to predict breast cancer risk: dense area or percentage dense area

2010 ◽  
Vol 12 (6) ◽  
Author(s):  
Jennifer Stone ◽  
Jane Ding ◽  
Ruth ML Warren ◽  
Stephen W Duffy ◽  
John L Hopper
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density ◽  
Dense Area
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