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A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study
Previous studies suggest associations of metabolic syndromes with breast cancer prognosis, yet the evidence is mixed. In recent years, the maturation of genome-wide association study findings has led to the development of polygenic scores (PGS) for many common traits, making it feasible to use Mende...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for Cancer Research
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10286812/ https://www.ncbi.nlm.nih.gov/pubmed/37377609 http://dx.doi.org/10.1158/2767-9764.CRC-23-0047 |
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author | Fiorica, Peter N. Sheng, Haiyang Zhu, Qianqian Roh, Janise M. Laurent, Cecile A. Ergas, Isaac J. Delmerico, Jennifer Kwan, Marilyn L. Kushi, Lawrence H. Ambrosone, Christine B. Yao, Song |
author_facet | Fiorica, Peter N. Sheng, Haiyang Zhu, Qianqian Roh, Janise M. Laurent, Cecile A. Ergas, Isaac J. Delmerico, Jennifer Kwan, Marilyn L. Kushi, Lawrence H. Ambrosone, Christine B. Yao, Song |
author_sort | Fiorica, Peter N. |
collection | PubMed |
description | Previous studies suggest associations of metabolic syndromes with breast cancer prognosis, yet the evidence is mixed. In recent years, the maturation of genome-wide association study findings has led to the development of polygenic scores (PGS) for many common traits, making it feasible to use Mendelian randomization to examine associations between metabolic traits and breast cancer outcomes. In the Pathways Study of 3,902 patients and a median follow-up time of 10.5 years, we adapted a Mendelian randomization approach to calculate PGS for 55 metabolic traits and tested their associations with seven survival outcomes. Multivariable Cox proportional hazards models were used to derive HRs and 95% confidence intervals (CI) with adjustment for covariates. The highest tertile (T3) of PGS for cardiovascular disease was associated with shorter overall survival (HR = 1.34, 95% CI = 1.11–1.61) and second primary cancer–free survival (HR = 1.31, 95% CI = 1.12–1.53). PGS for hypertension (T3) was associated with shorter overall survival (HR = 1.20, 95% CI = 1.00–1.43), second primary cancer–free survival (HR = 1.24, 95% CI = 1.06–1.45), invasive disease-free survival (HR = 1.18, 95% CI = 1.01–1.38), and disease-free survival (HR = 1.21, 95% CI = 1.04–1.39). PGS for serum cystatin C levels (T3) was associated with longer disease-free survival (HR = 0.82, 95% CI = 0.71–0.95), breast event-free survival (HR = 0.74, 95% CI = 0.61–0.91), and breast cancer–specific survival (HR = 0.72, 95% CI = 0.54–0.95). The above associations were significant at a nominal P < 0.05 level but not after correcting for multiple testing (Bonferroni P < 0.0009). Our analyses revealed notable associations of PGS for cardiovascular disease, hypertension, and cystatin C levels with breast cancer survival outcomes. These findings implicate metabolic traits in breast cancer prognosis. SIGNIFICANCE: To our knowledge, this is the largest study of PGS for metabolic traits with breast cancer prognosis. The findings revealed significant associations of PGS for cardiovascular disease, hypertension, and cystatin C levels with several breast cancer survival outcomes. These findings implicate an underappreciated role of metabolic traits in breast cancer prognosis that would warrant further exploration. |
format | Online Article Text |
id | pubmed-10286812 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Association for Cancer Research |
record_format | MEDLINE/PubMed |
spelling | pubmed-102868122023-06-23 A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study Fiorica, Peter N. Sheng, Haiyang Zhu, Qianqian Roh, Janise M. Laurent, Cecile A. Ergas, Isaac J. Delmerico, Jennifer Kwan, Marilyn L. Kushi, Lawrence H. Ambrosone, Christine B. Yao, Song Cancer Res Commun Research Article Previous studies suggest associations of metabolic syndromes with breast cancer prognosis, yet the evidence is mixed. In recent years, the maturation of genome-wide association study findings has led to the development of polygenic scores (PGS) for many common traits, making it feasible to use Mendelian randomization to examine associations between metabolic traits and breast cancer outcomes. In the Pathways Study of 3,902 patients and a median follow-up time of 10.5 years, we adapted a Mendelian randomization approach to calculate PGS for 55 metabolic traits and tested their associations with seven survival outcomes. Multivariable Cox proportional hazards models were used to derive HRs and 95% confidence intervals (CI) with adjustment for covariates. The highest tertile (T3) of PGS for cardiovascular disease was associated with shorter overall survival (HR = 1.34, 95% CI = 1.11–1.61) and second primary cancer–free survival (HR = 1.31, 95% CI = 1.12–1.53). PGS for hypertension (T3) was associated with shorter overall survival (HR = 1.20, 95% CI = 1.00–1.43), second primary cancer–free survival (HR = 1.24, 95% CI = 1.06–1.45), invasive disease-free survival (HR = 1.18, 95% CI = 1.01–1.38), and disease-free survival (HR = 1.21, 95% CI = 1.04–1.39). PGS for serum cystatin C levels (T3) was associated with longer disease-free survival (HR = 0.82, 95% CI = 0.71–0.95), breast event-free survival (HR = 0.74, 95% CI = 0.61–0.91), and breast cancer–specific survival (HR = 0.72, 95% CI = 0.54–0.95). The above associations were significant at a nominal P < 0.05 level but not after correcting for multiple testing (Bonferroni P < 0.0009). Our analyses revealed notable associations of PGS for cardiovascular disease, hypertension, and cystatin C levels with breast cancer survival outcomes. These findings implicate metabolic traits in breast cancer prognosis. SIGNIFICANCE: To our knowledge, this is the largest study of PGS for metabolic traits with breast cancer prognosis. The findings revealed significant associations of PGS for cardiovascular disease, hypertension, and cystatin C levels with several breast cancer survival outcomes. These findings implicate an underappreciated role of metabolic traits in breast cancer prognosis that would warrant further exploration. American Association for Cancer Research 2023-06-22 /pmc/articles/PMC10286812/ /pubmed/37377609 http://dx.doi.org/10.1158/2767-9764.CRC-23-0047 Text en © 2023 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by/4.0/This open access article is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. |
spellingShingle | Research Article Fiorica, Peter N. Sheng, Haiyang Zhu, Qianqian Roh, Janise M. Laurent, Cecile A. Ergas, Isaac J. Delmerico, Jennifer Kwan, Marilyn L. Kushi, Lawrence H. Ambrosone, Christine B. Yao, Song A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study |
title | A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study |
title_full | A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study |
title_fullStr | A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study |
title_full_unstemmed | A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study |
title_short | A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study |
title_sort | mendelian randomization analysis of 55 genetically predicted metabolic traits with breast cancer survival outcomes in the pathways study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10286812/ https://www.ncbi.nlm.nih.gov/pubmed/37377609 http://dx.doi.org/10.1158/2767-9764.CRC-23-0047 |
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