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Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk
DNA methylation patterns in the blood, genetic risk scores (GRSs), and environmental risk factors can potentially improve breast cancer (BC) risk prediction. We assessed the individual and joint predictive performance of methylation, GRS, and environmental risk factors for BC incidence in a prospect...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6944111/ https://www.ncbi.nlm.nih.gov/pubmed/31677238 http://dx.doi.org/10.1002/1878-0261.12594 |
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author | Guan, Zhong Raut, Janhavi R. Weigl, Korbinian Schöttker, Ben Holleczek, Bernd Zhang, Yan Brenner, Hermann |
author_facet | Guan, Zhong Raut, Janhavi R. Weigl, Korbinian Schöttker, Ben Holleczek, Bernd Zhang, Yan Brenner, Hermann |
author_sort | Guan, Zhong |
collection | PubMed |
description | DNA methylation patterns in the blood, genetic risk scores (GRSs), and environmental risk factors can potentially improve breast cancer (BC) risk prediction. We assessed the individual and joint predictive performance of methylation, GRS, and environmental risk factors for BC incidence in a prospective cohort study. In a cohort of 5462 women aged 50–75 from Germany, 101 BC cases were identified during 14 years of follow‐up and were compared to 263 BC‐free controls in a nested case–control design. Three previously suggested methylation risk scores (MRSs) based on methylation of 423, 248, and 131 cytosine‐phosphate‐guanine (CpG) loci, and a GRS based on the risk alleles from 269 recently identified single nucleotide polymorphisms were constructed. Additionally, multiple previously proposed environmental risk scores (ERSs) were built based on environmental variables. Areas under the receiver operating characteristic curves (AUCs) were estimated for evaluating BC risk prediction performance. MRS and ERS showed limited accuracy in predicting BC incidence, with AUCs ranging from 0.52 to 0.56 and from 0.52 to 0.59, respectively. The GRS predicted BC incidence with a higher accuracy (AUC = 0.61). Adjusted odds ratios per standard deviation increase (95% confidence interval) were 1.07 (0.84–1.36) and 1.40 (1.09–1.80) for the best performing MRS and ERS, respectively, and 1.48 (1.16–1.90) for the GRS. A full risk model combining the MRS, GRS, and ERS predicted BC incidence with the highest accuracy (AUC = 0.64) and might be useful for identifying high‐risk populations for BC screening. |
format | Online Article Text |
id | pubmed-6944111 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-69441112020-01-07 Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk Guan, Zhong Raut, Janhavi R. Weigl, Korbinian Schöttker, Ben Holleczek, Bernd Zhang, Yan Brenner, Hermann Mol Oncol Research Articles DNA methylation patterns in the blood, genetic risk scores (GRSs), and environmental risk factors can potentially improve breast cancer (BC) risk prediction. We assessed the individual and joint predictive performance of methylation, GRS, and environmental risk factors for BC incidence in a prospective cohort study. In a cohort of 5462 women aged 50–75 from Germany, 101 BC cases were identified during 14 years of follow‐up and were compared to 263 BC‐free controls in a nested case–control design. Three previously suggested methylation risk scores (MRSs) based on methylation of 423, 248, and 131 cytosine‐phosphate‐guanine (CpG) loci, and a GRS based on the risk alleles from 269 recently identified single nucleotide polymorphisms were constructed. Additionally, multiple previously proposed environmental risk scores (ERSs) were built based on environmental variables. Areas under the receiver operating characteristic curves (AUCs) were estimated for evaluating BC risk prediction performance. MRS and ERS showed limited accuracy in predicting BC incidence, with AUCs ranging from 0.52 to 0.56 and from 0.52 to 0.59, respectively. The GRS predicted BC incidence with a higher accuracy (AUC = 0.61). Adjusted odds ratios per standard deviation increase (95% confidence interval) were 1.07 (0.84–1.36) and 1.40 (1.09–1.80) for the best performing MRS and ERS, respectively, and 1.48 (1.16–1.90) for the GRS. A full risk model combining the MRS, GRS, and ERS predicted BC incidence with the highest accuracy (AUC = 0.64) and might be useful for identifying high‐risk populations for BC screening. John Wiley and Sons Inc. 2019-11-19 2020-01 /pmc/articles/PMC6944111/ /pubmed/31677238 http://dx.doi.org/10.1002/1878-0261.12594 Text en © 2019 The Authors. Published by FEBS Press and John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Guan, Zhong Raut, Janhavi R. Weigl, Korbinian Schöttker, Ben Holleczek, Bernd Zhang, Yan Brenner, Hermann Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk |
title | Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk |
title_full | Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk |
title_fullStr | Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk |
title_full_unstemmed | Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk |
title_short | Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk |
title_sort | individual and joint performance of dna methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6944111/ https://www.ncbi.nlm.nih.gov/pubmed/31677238 http://dx.doi.org/10.1002/1878-0261.12594 |
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