| Autor: |
Sara Lindström, Jenny Chang-Claude, Peter Kraft, Li Hsu, Roger L. Milne, Douglas F. Easton, Håkan Olsson, Sophia Wang, James V. Lacey, Nick Orr, Anthony J. Swerdlow, Jack A. Taylor, Dale P. Sandler, Alicja Wolk, Kamila Czene, Per Hall, Anthony Howell, D. Gareth Evans, Rose Yang, Thomas Ahearn, Jonine Figueroa, Montserrat García-Closas, Heather Eliassen, Rulla Tamimi, Cheng Peng, Michael I. Love, Melissa A. Troester, Jirong Long, Wei Zheng, Mark S. Goldberg, Jacques Simard, Stacey Winham, Christopher Scott, Gertraud Maskarinec, Christopher A. Haiman, Graham G. Giles, Heiko Becher, Audrey Jung, Veli-Matti Kosma, Arto Mannermaa, Sabine Behrens, Wing-Yee Lo, Reiner Hoppe, Volker Arndt, Hermann Brenner, Rudolf Kaaks, Federico Canzian, James M. Hodge, Lauren R. Teras, Thérèse Truong, Pascal Guénel, Kristan Aronson, Rachel A. Murphy, Rana Shibli, Gad Rennert, Jennifer Stone, Laura E. Beane Freeman, Stella Koutros, Melissa C. Southey, John L. Hopper, Paul D.P. Pharoah, Kyriaki Michailidou, Qin Wang, Michael Lush, Alison M. Dunning, Joe Dennis, Manjeet K. Bolla, Yu-Ru Su, Pooja Middha Kapoor, Hongjie Chen, Xiaoliang Wang |
| Rok vydání: |
2023 |
| DOI: |
10.1158/2767-9764.c.6550751.v1 |
| Popis: |
Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this.We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P < 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test.After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE = 4.44 × 10−6).In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk.Our study suggests a limited role of gene–environment interactions in breast cancer risk. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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