高级检索
当前位置: 首页 > 详情页

A genome-wide association study of mammographic texture variation

文献详情

资源类型:
Pubmed体系:
机构: [1]Department of Epidemiology, Harvard T.H. Chan School of Public Health, . Boston, MA, USA. [2]Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Building 2-249A, Boston, MA 02115, USA. [3]Department of Epidemiology, University of Washington, Seattle, WA, USA. [4]Division of Population Sciences, H. Lee Mof- ftt Cancer Center & Research Institute, Tampa, FL, USA. [5]Public Health Sciences Division, Fred Hutchinson Cancer Research ( enter, Seattle, WA, USA. [6]Clinical and Translational Epidemiology Unit, Department of Medicine, Mongan Institute, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. [7]Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA. [8]Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA. [9]Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. [10]Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA. [11]Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. [12]Department of Clinical Neuroscience, ( enter for Molecular Medicine, Karolinska Institutet, Visions- gatan 18, 171 77 Solna, Stockholm, Sweden. [13]West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
出处:
ISSN:

摘要:
Breast parenchymal texture features, including grayscale variation (V), capture the patterns of texture variation on a mammogram and are associated with breast cancer risk, independent of mammographic density (MD). However, our knowledge on the genetic basis of these texture features is limited.We conducted a genome-wide association study of V in 7040 European-ancestry women. V assessments were generated from digitized film mammograms. We used linear regression to test the single-nucleotide polymorphism (SNP)-phenotype associations adjusting for age, body mass index (BMI), MD phenotypes, and the top four genetic principal components. We further calculated genetic correlations and performed SNP-set tests of V with MD, breast cancer risk, and other breast cancer risk factors.We identified three genome-wide significant loci associated with V: rs138141444 (6q24.1) in ECT2L, rs79670367 (8q24.22) in LINC01591, and rs113174754 (12q22) near PGAM1P5. 6q24.1 and 8q24.22 have not previously been associated with MD phenotypes or breast cancer risk, while 12q22 is a known locus for both MD and breast cancer risk. Among known MD and breast cancer risk SNPs, we identified four variants that were associated with V at the Bonferroni-corrected thresholds accounting for the number of SNPs tested: rs335189 (5q23.2) in PRDM6, rs13256025 (8p21.2) in EBF2, rs11836164 (12p12.1) near SSPN, and rs17817449 (16q12.2) in FTO. We observed significant genetic correlations between V and mammographic dense area (r<sub>g</sub> = 0.79, P = 5.91 × 10<sup>-5</sup>), percent density (r<sub>g</sub> = 0.73, P = 1.00 × 10<sup>-4</sup>), and adult BMI (r<sub>g</sub> =  - 0.36, P = 3.88 × 10<sup>-7</sup>). Additional significant relationships were observed for non-dense area (z =  - 4.14, P = 3.42 × 10<sup>-5</sup>), estrogen receptor-positive breast cancer (z = 3.41, P = 6.41 × 10<sup>-4</sup>), and childhood body fatness (z =  - 4.91, P = 9.05 × 10<sup>-7</sup>) from the SNP-set tests.These findings provide new insights into the genetic basis of mammographic texture variation and their associations with MD, breast cancer risk, and other breast cancer risk factors.© 2022. The Author(s).

基金:
语种:
PubmedID:
中科院(CAS)分区:
出版当年[2022]版:
大类 | 1 区 医学
小类 | 2 区 肿瘤学
最新[2023]版:
大类 | 1 区 医学
小类 | 2 区 肿瘤学
第一作者:
第一作者机构: [1]Department of Epidemiology, Harvard T.H. Chan School of Public Health, . Boston, MA, USA. [2]Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Building 2-249A, Boston, MA 02115, USA.
通讯作者:
通讯机构: [1]Department of Epidemiology, Harvard T.H. Chan School of Public Health, . Boston, MA, USA. [2]Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Building 2-249A, Boston, MA 02115, USA. [11]Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. [12]Department of Clinical Neuroscience, ( enter for Molecular Medicine, Karolinska Institutet, Visions- gatan 18, 171 77 Solna, Stockholm, Sweden. [13]West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:43377 今日访问量:0 总访问量:3120 更新日期:2024-09-01 建议使用谷歌、火狐浏览器 常见问题

版权所有©2020 四川省肿瘤医院 技术支持:重庆聚合科技有限公司 地址:成都市人民南路四段55号