Interactions between genetic and epidemiological factors influencing mammographic density.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАПоддержка правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Suger Austin Hammermeister, Chen Hongjie, Haas Cameron B, Fan Shaoqi, Scott Christopher G, Bolla Manjeet K, Dennis Joe, Dunning Alison M, Michailidou Kyriaki, Wang Qin, Fasching Peter A, Haeberle Lothar, Stone Jennifer, Gago-Dominguez Manuela, Castelao Jose E, Murphy Rachel A, Aronson Kristan, Couch Fergus J, Yadav Siddhartha, Milne Roger L, Hopper John L, Norman Aaron, Eliassen A Heather, Tapper William J, Eccles Diana M, Evans D Gareth, Astley Susan, Hall Per, Czene Kamila, Pharoah Paul D P, Antoniou Antonis C, García-Closas Montserrat, Berrington Amy, Easton Douglas F, Gierach Gretchen L, Tamimi Rulla M, Vachon Celine M, Lindström Sara, Harrison Tabitha A
Аннотация
Studies have identified genetic and epidemiologic factors associated with mammographic density (MD) phenotypes. However, MD-associated genetic variants only account for a small proportion of the total estimated heritability. Interrogating interactions between genetic and epidemiologic factors could potentially identify additional MD-associated loci, expand our understanding of the genetic basis of MD phenotypes, and clarify how epidemiologic factors modulate relationships between genetic variants and MD. We conducted six separate genome-wide, gene-environment (GxE) interaction analyses, applying 2 degrees of freedom (df) and 1df interaction tests, for each of three MD phenotypes (percent density, dense area (DA), and nondense area (NDA)). The six epidemiologic factors considered were height, ever parous, parity, ever menopausal hormone therapy, ever breastfeeding, and months of breastfeeding. We included European ancestry participants from multiple studies within the Markers of Density consortium and the Breast Cancer Association Consortium (n = 4895-16 218 depending on specific analyses). We identified 11 loci with genome-wide significant (P < 5 × 10-8) interaction tests including two novel common genetic signals interacting with parity (8p21.2) and ever breastfeeding (19p13.2) for NDA. Our results suggest that epidemiologic risk factors might influence relationships between common genetic variants and MD phenotypes at particular genomic loci.