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Gene-environment interactions and predictors of breast cancer in family-based multi-ethnic groups
Breast cancer (BC) is the most common cancer in women worldwide and second leading cause of cancer-related death. Understanding gene-environment interactions could play a critical role for next stage of BC prevention efforts. Hence, the purpose of this study was to examine the key gene-environmental...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6044380/ https://www.ncbi.nlm.nih.gov/pubmed/30018733 http://dx.doi.org/10.18632/oncotarget.25520 |
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author | Gonzales, Mildred C. Grayson, James Lie, Amanda Yu, Chong Ho Shiao, Shyang-Yun Pamela K. |
author_facet | Gonzales, Mildred C. Grayson, James Lie, Amanda Yu, Chong Ho Shiao, Shyang-Yun Pamela K. |
author_sort | Gonzales, Mildred C. |
collection | PubMed |
description | Breast cancer (BC) is the most common cancer in women worldwide and second leading cause of cancer-related death. Understanding gene-environment interactions could play a critical role for next stage of BC prevention efforts. Hence, the purpose of this study was to examine the key gene-environmental factors affecting the risks of BC in a diverse sample. Five genes in one-carbon metabolism pathway including MTHFR 677, MTHFR 1298, MTR 2756, MTRR 66, and DHFR 19bp together with demographics, lifestyle, and dietary intake factors were examined in association with BC risks. A total of 80 participants (40 BC cases and 40 family/friend controls) in southern California were interviewed and provided salivary samples for genotyping. We presented the first study utilizing both conventional and new analytics including ensemble method and predictive modeling based on smallest errors to predict BC risks. Predictive modeling of Generalized Regression Elastic Net Leave-One-Out demonstrated alcohol use (p = 0.0126) and age (p < 0.0001) as significant predictors; and significant interactions were noted between body mass index (BMI) and alcohol use (p = 0.0027), and between BMI and MTR 2756 polymorphisms (p = 0.0090). Our findings identified the modifiable lifestyle factors in gene-environment interactions that are valuable for BC prevention. |
format | Online Article Text |
id | pubmed-6044380 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-60443802018-07-17 Gene-environment interactions and predictors of breast cancer in family-based multi-ethnic groups Gonzales, Mildred C. Grayson, James Lie, Amanda Yu, Chong Ho Shiao, Shyang-Yun Pamela K. Oncotarget Research Paper Breast cancer (BC) is the most common cancer in women worldwide and second leading cause of cancer-related death. Understanding gene-environment interactions could play a critical role for next stage of BC prevention efforts. Hence, the purpose of this study was to examine the key gene-environmental factors affecting the risks of BC in a diverse sample. Five genes in one-carbon metabolism pathway including MTHFR 677, MTHFR 1298, MTR 2756, MTRR 66, and DHFR 19bp together with demographics, lifestyle, and dietary intake factors were examined in association with BC risks. A total of 80 participants (40 BC cases and 40 family/friend controls) in southern California were interviewed and provided salivary samples for genotyping. We presented the first study utilizing both conventional and new analytics including ensemble method and predictive modeling based on smallest errors to predict BC risks. Predictive modeling of Generalized Regression Elastic Net Leave-One-Out demonstrated alcohol use (p = 0.0126) and age (p < 0.0001) as significant predictors; and significant interactions were noted between body mass index (BMI) and alcohol use (p = 0.0027), and between BMI and MTR 2756 polymorphisms (p = 0.0090). Our findings identified the modifiable lifestyle factors in gene-environment interactions that are valuable for BC prevention. Impact Journals LLC 2018-06-26 /pmc/articles/PMC6044380/ /pubmed/30018733 http://dx.doi.org/10.18632/oncotarget.25520 Text en Copyright: © 2018 Gonzales et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Gonzales, Mildred C. Grayson, James Lie, Amanda Yu, Chong Ho Shiao, Shyang-Yun Pamela K. Gene-environment interactions and predictors of breast cancer in family-based multi-ethnic groups |
title | Gene-environment interactions and predictors of breast cancer in family-based multi-ethnic groups |
title_full | Gene-environment interactions and predictors of breast cancer in family-based multi-ethnic groups |
title_fullStr | Gene-environment interactions and predictors of breast cancer in family-based multi-ethnic groups |
title_full_unstemmed | Gene-environment interactions and predictors of breast cancer in family-based multi-ethnic groups |
title_short | Gene-environment interactions and predictors of breast cancer in family-based multi-ethnic groups |
title_sort | gene-environment interactions and predictors of breast cancer in family-based multi-ethnic groups |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6044380/ https://www.ncbi.nlm.nih.gov/pubmed/30018733 http://dx.doi.org/10.18632/oncotarget.25520 |
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