scholarly journals Gene-environment interactions and predictors of breast cancer in family-based multi-ethnic groups

Oncotarget ◽  
2018 ◽  
Vol 9 (49) ◽  
pp. 29019-29035 ◽  
Author(s):  
Mildred C. Gonzales ◽  
James Grayson ◽  
Amanda Lie ◽  
Chong Ho Yu ◽  
Shyang-Yun Pamela K. Shiao
Keyword(s):  
Breast Cancer ◽  
Ethnic Groups ◽  
Gene Environment ◽  
Family Based

scholarly journals Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups

2018 ◽  
Vol 8 (1) ◽  
pp. 10 ◽  
Author(s):  
S. Shiao ◽  
James Grayson ◽  
Chong Yu ◽  
Brandi Wasek ◽  
Teodoro Bottiglieri
Keyword(s):  
Colorectal Cancer ◽  
Ethnic Groups ◽  
Gene Environment ◽  
Family Based

Gene Environment Interactions in Women with Breast Cancer and Secondary Lung Cancer

2004 ◽  
Author(s):  
Meredith A. Tennis ◽  
Peter G. Shields
Keyword(s):  
Breast Cancer ◽  
Lung Cancer ◽  
Gene Environment

Gene-Gene and Gene-Environment Interactions in the Etiology of Breast Cancer

2007 ◽  
Author(s):  
Dana R. Marshall ◽  
Olufemi J. Adegoke ◽  
Wei Zheng
Keyword(s):  
Breast Cancer ◽  
Gene Environment

scholarly journals Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chao-Yu Guo ◽  
Reng-Hong Wang ◽  
Hsin-Chou Yang
Keyword(s):  
Complex Traits ◽  
Association Studies ◽  
Association Test ◽  
Whole Genome Sequence ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Sequence Kernel Association Test ◽  
Gene Environment ◽  
Family Based

AbstractAfter the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex traits while quickly adjusting for covariates. Such kernel score statistic allows for familial dependencies and adjusts for random confounding effects. However, the etiology of complex traits may involve the effects of genetic and environmental factors and the complex interactions between genes and the environment. Therefore, in this research, a novel method is proposed to detect gene and gene-environment interactions in a complex family-based association study with various correlated structures. We also developed an R function for the Fast Gene-Environment Sequence Kernel Association Test (FGE-SKAT), which is freely available as supplementary material for easy GWAS implementation to unveil such family-based joint effects. Simulation studies confirmed the validity of the new strategy and the superior statistical power. The FGE-SKAT was applied to the whole genome sequence data provided by Genetic Analysis Workshop 18 (GAW18) and discovered concordant and discordant regions compared to the methods without considering gene by environment interactions.

scholarly journals Gene-Environment Interactions Relevant to Estrogen and Risk of Breast Cancer: Can Gene-Environment Interactions Be Detected Only among Candidate SNPs from Genome-Wide Association Studies?

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2370
Author(s):  
JooYong Park ◽  
Ji-Yeob Choi ◽  
Jaesung Choi ◽  
Seokang Chung ◽  
Nan Song ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Environmental Factors ◽  
Minor Allele ◽  
Estrogen Metabolism ◽  
Age At Menarche ◽  
Genome Wide Association Studies ◽  
Estrogen Exposure ◽  
Gene Environment ◽  
Independent Population

In this study we aim to examine gene–environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2 × 10−3). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (p-2df = 1.1 × 10−4). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.

scholarly journals Haplotype analysis on correlation between transcription factor 7-like 2 gene polymorphism and breast cancer risk

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yang Wang ◽  
Xiaojuan Men ◽  
Yongxue Gu ◽  
Huidong Wang ◽  
Zhicai Xu
Keyword(s):  
Breast Cancer ◽  
Transcription Factor ◽  
Logistic Regression ◽  
Abdominal Obesity ◽  
Haplotype Analysis ◽  
Environment Interaction ◽  
Nucleotide Polymorphisms ◽  
Chinese Han ◽  
Locus Model ◽  
Gene Environment

Abstract Background Up to now, limited researches focused on the association between transcription factor 7-like 2 gene (TF7L2) gene single nucleotide polymorphisms (SNPs) and breast cancer (BC) risk. The aim of this study was to evaluate the associations between TF7L2 and BC risk in Chinese Han population. Methods Logistic regression model was used to test the correlation between polymorphisms and BC risk. Strength of association was evaluated by odds ratio (OR) and 95% confidence interval (CI). Generalized multifactor dimensionality reduction (GMDR) was applied to analyze the SNP-SNP and gene-environment interaction. Results Logistic regression analysis indicated that the BC risk was obviously higher in carriers of rs1225404 polymorphism C allele than that in TT genotype carriers (TC or CC versus TT), adjusted OR (95%CI) =1.40 (1.09–1.72). Additionally, we also discovered that people with rs7903146- T allele had an obviously higher risk of BC than people with CC allele (CT or TT versus CC), adjusted OR (95%CI) =1.44 (1.09–1.82). GMDR model was used to research the effect of interaction among 4 SNPs and environmental factors on BC risk. We discovered an important two-locus model (p = 0.0100) including rs1225404 and abdominal obesity, suggesting a potential gene–environment correlation between rs1225404 and abdominal obesity. In general, the cross-validation consistency of two-locus model was 10 of 10, and the testing accuracy was 0.632. Compared with subjects with normal waist circumference (WC) value and rs1225404 TT genotype, abdominal obese subjects with rs1225404 TC or CC genotype had the highest BC risk. After covariate adjustment, OR (95%CI) was 2.23 (1.62–2.89). Haplotype analysis indicated that haplotype containing rs1225404-T and rs7903146-C alleles were associated with higher BC risk. Conclusions C allele of rs1225404 and T allele of rs7903146, interaction between rs1225404 and abdominal obesity, rs1225404-T and rs7903146-C haplotype were all related to increased BC risk.

Family-based genetic association study of insulin-like growth factor I microsatellite markers and premenopausal breast cancer risk

2009 ◽  
Vol 118 (2) ◽  
pp. 415-424 ◽  
Author(s):  
Gordon Fehringer ◽  
Norman F. Boyd ◽  
Julia A. Knight ◽  
Andrew D. Paterson ◽  
Gillian S. Dite ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Growth Factor ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Microsatellite Markers ◽  
Association Study ◽  
Genetic Association Study ◽  
Premenopausal Breast Cancer ◽  
Factor I ◽  
Family Based

scholarly journals Breast cancer screening behaviors and attitudes in three racial/ethnic groups

Cancer ◽  
1992 ◽  
Vol 69 (1) ◽  
pp. 165-174 ◽  
Author(s):  
Sally W. Vernon ◽  
Victor G. Vogel ◽  
Susan Halabi ◽  
Gilchrist L. Jackson ◽  
Ray O. Lundy ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Screening ◽  
Ethnic Groups ◽  
Breast Cancer Screening ◽  
Screening Behaviors ◽  
Racial Ethnic
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