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A prospective case–cohort analysis of plasma metabolites and breast cancer risk
BACKGROUND: Breast cancer incidence rates have not declined despite an improvement in risk prediction and the identification of modifiable risk factors, suggesting the need to identify novel risk factors and etiological pathways involved in this cancer. Metabolomics has emerged as a promising tool t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9847033/ https://www.ncbi.nlm.nih.gov/pubmed/36650550 http://dx.doi.org/10.1186/s13058-023-01602-x |
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author | Stevens, Victoria L. Carter, Brian D. Jacobs, Eric J. McCullough, Marjorie L. Teras, Lauren R. Wang, Ying |
author_facet | Stevens, Victoria L. Carter, Brian D. Jacobs, Eric J. McCullough, Marjorie L. Teras, Lauren R. Wang, Ying |
author_sort | Stevens, Victoria L. |
collection | PubMed |
description | BACKGROUND: Breast cancer incidence rates have not declined despite an improvement in risk prediction and the identification of modifiable risk factors, suggesting the need to identify novel risk factors and etiological pathways involved in this cancer. Metabolomics has emerged as a promising tool to find circulating metabolites associated with breast cancer risk. METHODS: Untargeted metabolomic analysis was done on prediagnostic plasma samples from a case–cohort study of 1695 incident breast cancer cases and a 1983 women subcohort drawn from Cancer Prevention Study 3. The associations of 868 named metabolites (per one standard deviation increase) with breast cancer were determined using Prentice-weighted Cox proportional hazards regression modeling. RESULTS: A total of 11 metabolites were associated with breast cancer at false discovery rate (FDR) < 0.05 with the majority having inverse association [ranging from RR = 0.85 (95% CI 0.80–0.92) to RR = 0.88 (95% CI 0.82–0.94)] and one having a positive association [RR = 1.14 (95% CI 1.06–1.23)]. An additional 50 metabolites were associated at FDR < 0.20 with inverse associations ranging from RR = 0.88 (95% CI 0.81–0.94) to RR = 0.91 (95% CI 0.85–0.98) and positive associations ranging from RR = 1.13 (95% CI 1.05–1.22) to RR = 1.11 (95% CI 1.02–1.20). Several of these associations validated the findings of previous metabolomic studies. These included findings that several progestogen and androgen steroids were associated with increased risk of breast cancer in postmenopausal women and four phospholipids, and the amino acids glutamine and asparagine were associated with decreased risk of this cancer in pre- and postmenopausal women. Several novel associations were also identified, including a positive association for syringol sulfate, a biomarker for smoked meat, and 3-methylcatechol sulfate and 3-hydroxypyridine glucuronide, which are metabolites of xenobiotics used for the production of pesticides and other products. CONCLUSIONS: Our study validated previous metabolite findings and identified novel metabolites associated with breast cancer risk, demonstrating the utility of large metabolomic studies to provide new leads for understanding breast cancer etiology. Our novel findings suggest that consumption of smoked meats and exposure to catechol and pyridine should be investigated as potential risk factors for breast cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13058-023-01602-x. |
format | Online Article Text |
id | pubmed-9847033 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98470332023-01-19 A prospective case–cohort analysis of plasma metabolites and breast cancer risk Stevens, Victoria L. Carter, Brian D. Jacobs, Eric J. McCullough, Marjorie L. Teras, Lauren R. Wang, Ying Breast Cancer Res Research BACKGROUND: Breast cancer incidence rates have not declined despite an improvement in risk prediction and the identification of modifiable risk factors, suggesting the need to identify novel risk factors and etiological pathways involved in this cancer. Metabolomics has emerged as a promising tool to find circulating metabolites associated with breast cancer risk. METHODS: Untargeted metabolomic analysis was done on prediagnostic plasma samples from a case–cohort study of 1695 incident breast cancer cases and a 1983 women subcohort drawn from Cancer Prevention Study 3. The associations of 868 named metabolites (per one standard deviation increase) with breast cancer were determined using Prentice-weighted Cox proportional hazards regression modeling. RESULTS: A total of 11 metabolites were associated with breast cancer at false discovery rate (FDR) < 0.05 with the majority having inverse association [ranging from RR = 0.85 (95% CI 0.80–0.92) to RR = 0.88 (95% CI 0.82–0.94)] and one having a positive association [RR = 1.14 (95% CI 1.06–1.23)]. An additional 50 metabolites were associated at FDR < 0.20 with inverse associations ranging from RR = 0.88 (95% CI 0.81–0.94) to RR = 0.91 (95% CI 0.85–0.98) and positive associations ranging from RR = 1.13 (95% CI 1.05–1.22) to RR = 1.11 (95% CI 1.02–1.20). Several of these associations validated the findings of previous metabolomic studies. These included findings that several progestogen and androgen steroids were associated with increased risk of breast cancer in postmenopausal women and four phospholipids, and the amino acids glutamine and asparagine were associated with decreased risk of this cancer in pre- and postmenopausal women. Several novel associations were also identified, including a positive association for syringol sulfate, a biomarker for smoked meat, and 3-methylcatechol sulfate and 3-hydroxypyridine glucuronide, which are metabolites of xenobiotics used for the production of pesticides and other products. CONCLUSIONS: Our study validated previous metabolite findings and identified novel metabolites associated with breast cancer risk, demonstrating the utility of large metabolomic studies to provide new leads for understanding breast cancer etiology. Our novel findings suggest that consumption of smoked meats and exposure to catechol and pyridine should be investigated as potential risk factors for breast cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13058-023-01602-x. BioMed Central 2023-01-17 2023 /pmc/articles/PMC9847033/ /pubmed/36650550 http://dx.doi.org/10.1186/s13058-023-01602-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Stevens, Victoria L. Carter, Brian D. Jacobs, Eric J. McCullough, Marjorie L. Teras, Lauren R. Wang, Ying A prospective case–cohort analysis of plasma metabolites and breast cancer risk |
title | A prospective case–cohort analysis of plasma metabolites and breast cancer risk |
title_full | A prospective case–cohort analysis of plasma metabolites and breast cancer risk |
title_fullStr | A prospective case–cohort analysis of plasma metabolites and breast cancer risk |
title_full_unstemmed | A prospective case–cohort analysis of plasma metabolites and breast cancer risk |
title_short | A prospective case–cohort analysis of plasma metabolites and breast cancer risk |
title_sort | prospective case–cohort analysis of plasma metabolites and breast cancer risk |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9847033/ https://www.ncbi.nlm.nih.gov/pubmed/36650550 http://dx.doi.org/10.1186/s13058-023-01602-x |
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