Association of a poly-metabolite score for ultra-processed food intake and breast cancer risk
Principal Investigator
Name
Leila Abar
Degrees
PhD
Institution
National Cancer Institute
Position Title
Postdoc fellow
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-1596
Initial CDAS Request Approval
Jun 17, 2024
Title
Association of a poly-metabolite score for ultra-processed food intake and breast cancer risk
Summary
Summary
Epidemiological studies indicate that high ultra-processed food (UPF) intake may increase the risk of breast cancer. A recent systematic review and meta-analysis, which includes 6 observational studies, showed a 5% increased risk per 10% increment of UPF intake (RR = 1.05; 95% CI: 1.00–1.10, p = 0.05)1. Another study among women in Latin America demonstrated that diets high in UPFs, which are typically energy-dense and low in essential nutrients, are associated with a higher risk of breast cancer2. Metabolomics offers novel insight into the mechanisms underlying diet-health associations. A metabolomics analysis3 in the French NutriNet-Santé cohort study reported that certain emulsifiers used in UPFs, such as mono- and diglycerides of fatty acids and carrageenan, were linked higher risk of breast cancer. However, studies of UPF-related metabolites and breast cancer risk are limited, and no studies have explored poly-metabolite scores predictive of UPF intake. The IDATA Study assessed diet with ≤6 24-hour dietary recalls (ASA-24) and serial blood and urine, collected over 12-months, were used for generating metabolomics data. In PLCO, metabolomics data was generated in a nested case-control study of breast cancer. This presents a unique opportunity to explore the connections between a ploy-metabolite score of UPF, developed in IDATA, with breast cancer in PLCO. We expect that the proposed analysis will enhance our understanding of the association between UPF intake and breast cancer.
Methods
We have developed a poly-metabolite score using data from the IDATA Study. In PLCO, we will calculate this score in the existing nested breast cancer case-control set (N postmenopausal breast cancer cases=621, N controls=621) and estimate the associations with risk of breast cancer using conditional logistic regression, conditioned on the matching factors. All models will be adjusted for age, sex, racial/ethnic group, body mass index and detailed smoking history.
References
1. Shu L, Zhang X, Zhu Q et al., Association between ultra-processed food consumption and risk of breast cancer: a systematic review and dose-response meta-analysis of observational studies. Front Nutr. 2023 Sep 4; 10:1250361. doi: 10.3389/fnut.2023.1250361.
2. Romieu I, Khandpur N, Katsikari A, et al., Consumption of industrial processed foods and risk of premenopausal breast cancer among Latin American women: the PRECAMA study. BMJ Nutr Prev Health. 2022 Jan 4;5(1):1-9. doi: 10.1136/bmjnph-2021-000335.
3. Sellem L, Srour B, Javaux G, et al., Food additive emulsifiers and cancer risk: Results from the French perspective NutriNet-Santé cohort. PLoS Med. 2024 Feb 13;21(2):e1004338. doi: 10.1371/journal.pmed.1004338.
Epidemiological studies indicate that high ultra-processed food (UPF) intake may increase the risk of breast cancer. A recent systematic review and meta-analysis, which includes 6 observational studies, showed a 5% increased risk per 10% increment of UPF intake (RR = 1.05; 95% CI: 1.00–1.10, p = 0.05)1. Another study among women in Latin America demonstrated that diets high in UPFs, which are typically energy-dense and low in essential nutrients, are associated with a higher risk of breast cancer2. Metabolomics offers novel insight into the mechanisms underlying diet-health associations. A metabolomics analysis3 in the French NutriNet-Santé cohort study reported that certain emulsifiers used in UPFs, such as mono- and diglycerides of fatty acids and carrageenan, were linked higher risk of breast cancer. However, studies of UPF-related metabolites and breast cancer risk are limited, and no studies have explored poly-metabolite scores predictive of UPF intake. The IDATA Study assessed diet with ≤6 24-hour dietary recalls (ASA-24) and serial blood and urine, collected over 12-months, were used for generating metabolomics data. In PLCO, metabolomics data was generated in a nested case-control study of breast cancer. This presents a unique opportunity to explore the connections between a ploy-metabolite score of UPF, developed in IDATA, with breast cancer in PLCO. We expect that the proposed analysis will enhance our understanding of the association between UPF intake and breast cancer.
Methods
We have developed a poly-metabolite score using data from the IDATA Study. In PLCO, we will calculate this score in the existing nested breast cancer case-control set (N postmenopausal breast cancer cases=621, N controls=621) and estimate the associations with risk of breast cancer using conditional logistic regression, conditioned on the matching factors. All models will be adjusted for age, sex, racial/ethnic group, body mass index and detailed smoking history.
References
1. Shu L, Zhang X, Zhu Q et al., Association between ultra-processed food consumption and risk of breast cancer: a systematic review and dose-response meta-analysis of observational studies. Front Nutr. 2023 Sep 4; 10:1250361. doi: 10.3389/fnut.2023.1250361.
2. Romieu I, Khandpur N, Katsikari A, et al., Consumption of industrial processed foods and risk of premenopausal breast cancer among Latin American women: the PRECAMA study. BMJ Nutr Prev Health. 2022 Jan 4;5(1):1-9. doi: 10.1136/bmjnph-2021-000335.
3. Sellem L, Srour B, Javaux G, et al., Food additive emulsifiers and cancer risk: Results from the French perspective NutriNet-Santé cohort. PLoS Med. 2024 Feb 13;21(2):e1004338. doi: 10.1371/journal.pmed.1004338.
Aims
Aims
• Investigate associations of poly-metabolite score for UPF with breast cancer risk in PLCO.
Collaborators
Collaborators
Erikka Loftfield: Division of Cancer Epidemiology and Genetics, NCI, MD, USA
Steven Moore: Division of Cancer Epidemiology and Genetics, NCI, MD, USA
Elleanor Watt: Division of Cancer Epidemiology and Genetics, NCI, MD, USA