ORCID Profile
0000-0001-9506-6624
Current Organisation
University of North Carolina at Chapel Hill
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Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.C.6550751.V1
Abstract: 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 ( i P /i 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 i C13orf45 /i gene and age at first full-term pregnancy (P sub GXE /sub = 4.44 × 10 sup −6 /sup ). 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. /
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544795
Abstract: Supplementary Table 1. S le Size of each participated study, by case-control status and genotype platform. Supplementary Table 2. Association between fourteen environmental factors and the risk of breast cancer. Supplementary Table 3. Interactions between genes and fourteen environmental factors.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544801
Abstract: Quantile-Quantile plot (Q-Q plot) of the aMiSTi p-values for each set of the GxE interactions.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.C.6550751
Abstract: 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 ( i P /i 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 i C13orf45 /i gene and age at first full-term pregnancy (P sub GXE /sub = 4.44 × 10 sup −6 /sup ). 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. /
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544801.V1
Abstract: Quantile-Quantile plot (Q-Q plot) of the aMiSTi p-values for each set of the GxE interactions.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544798
Abstract: Funding and acknowledgements.
Publisher: American Association for Cancer Research (AACR)
Date: 08-04-2022
DOI: 10.1158/2767-9764.CRC-21-0119
Abstract: 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.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544798.V1
Abstract: Funding and acknowledgements.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2767-9764.22544795.V1
Abstract: Supplementary Table 1. S le Size of each participated study, by case-control status and genotype platform. Supplementary Table 2. Association between fourteen environmental factors and the risk of breast cancer. Supplementary Table 3. Interactions between genes and fourteen environmental factors.
Location: United States of America
No related grants have been discovered for Melissa Troester.