Background: Percent mammographic density (PMD) is a risk factor for breast cancer. Our previous twin study showed that the heritability of PMD was 63%. This study determined the heritabilities of the components of PMD, the areas of dense and nondense tissue in the mammogram.
Methods: We combined two twin studies comprising 571 monozygous and 380 dizygous twin pairs recruited from Australia and North America. Dense and nondense areas were measured using a computer-assisted method, and information about potential determinants was obtained by questionnaire. Under the assumptions of the classic twin model, we estimated the heritability of the log dense area and log nondense area and the genetic and environmental contributions to the covariance between the two traits, using maximum likelihood theory and the statistical package FISHER.
Results: After adjusting for measured determinants, for each of the log dense area and the log nondense area, the monozygous correlations were greater than the dizygous correlations. Heritability was estimated to be 65% (95% confidence interval, 60-70%) for dense area and 66% (95% confidence interval, 61-71%) for nondense area. The correlations (SE) between the two adjusted traits were -0.35 (0.023) in the same individual, -0.26 (0.026) across monozygous pairs, and -0.14 (0.034) across dizygous pairs.
Conclusion: Genetic factors may play a large role in explaining variation in the mammographic areas of both dense and nondense tissue. About two thirds of the negative correlation between dense and nondense area is explained by the same genetic factors influencing both traits, but in opposite directions.
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http://dx.doi.org/10.1158/1055-9965.EPI-05-0127 | DOI Listing |
Sci Rep
January 2025
Exploration and Development Research Institute, PetroChina Tarim Oilfield Company, Korla, 841000, China.
The target reservoir is a typical blocky bottom water reservoir. There are several interlayers of varying scales inside it, which impact the characteristics of the oil production and water breakthrough curves of the wells in the water flooding development oilfield, resulting in strong heterogeneity within the reservoir. The Sangtamu Oilfield has an average well spacing of approximately 600 m, causing a challenge in accurately identifying the range of small-scale interlayer spreading.
View Article and Find Full Text PDFClin Breast Cancer
February 2025
Department of Breast Oncology and Surgery, Tokyo Medical University, Shinjuku-ku, Tokyo, Japan. Electronic address:
Asian Pac J Cancer Prev
November 2024
Clinical Research Center, Shizuoka Cancer Center Hospital, Shizuoka, Japan.
Purpose: Breast density assessment is an essential component of risk-stratified and supplemental breast cancer screenings for the future generation. International collaborative research and cooperation are required to determine global trends and differences in mammographic breast density. Due to the cost and energy associated with the use of film or digital mammograms, international breast density assessment studies tend to be challenging.
View Article and Find Full Text PDFCancer Epidemiol Biomarkers Prev
November 2024
National Cancer Institute, Bethesda, MD, United States.
Background Increased mammographic density (MD) is a known breast cancer (BC) risk factor, but its influencing factors are unclear in Asian populations. This study examined the links between known BC risk factors and quantitatively measured MD in 7,351 Chinese women with non-malignant mammographic findings. Methods VolparaDensity software quantified volumetric MD measures: total breast (TBV), absolute dense (ADV), percent dense (PDV= ADV/TBV), and non-dense volumes (NDV= TBV-ADV).
View Article and Find Full Text PDFBreast Cancer Res Treat
November 2024
Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Purpose: To examine the discrepancy in breast density assessments by radiologists, LIBRA software, and AI algorithm and their association with breast cancer risk.
Methods: Among 74,610 Korean women aged ≥ 34 years, who underwent screening mammography, density estimates obtained from both LIBRA and the AI algorithm were compared to radiologists using BI-RADS density categories (A-D, designating C and D as dense breasts). The breast cancer risks were compared according to concordant or discordant dense breasts identified by radiologists, LIBRA, and AI.
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