Literature DB >> 29902077

Biomarker of long-chain n-3 fatty acid intake and breast cancer: Accumulative evidence from an updated meta-analysis of epidemiological studies.

Bo Yang1, Xiao L Ren1, Zhi Y Wang2, Liang Wang3, Feng Zhao4, Xiao J Guo1, Duo Li4.   

Abstract

Objective: We aimed to summarize the up-to-date epidemiology evidence on biomarkers of long-chain (LC) n-3 fatty acid (FA) intake in relation to breast cancer (BC).
Methods: Epidemiology studies determining FA levels in biospecimen (circulating blood or adipose tissue (AT)) were identified from PubMed, EMBASE, and Cochrane Library databases until March 2018. Multivariate-adjusted risk ratios (RRs) with 95% confidence intervals (CIs) were pooled using a random-effect model. Difference in biospecimen proportions of LC n-3 FA between BC cases and non-cases were analyzed as a standardized mean difference (SMD).
Results: Thirteen cohort and eleven case-control studies were eligible for the present meta-analysis. The estimated SMD was -0.14 (95% CI: -0.27, -0.11) for LC n-3 FA and -0.27 (95% CI: -0.42, -0.11) for LC n-3/n-6 FA ratio. When comparing the top tertiles with the bottom baseline levels, circulating LC n-3 FA was significantly associated with a lower risk of BC (RR: 0.84, 95% CI: 0.74, 0.96), but not AT (RR: 1.02, 95% CI: 0.70, 1.48). Significant inverse dose-response associations were observed for each 1% increment of circulating 20:5n-3 and 22:6n-3.
Conclusion: This meta-analysis highlights that circulating LC n-3 FA as a biomarker of intake may be an independent predictive factor for BC, especially 20:5n-3 and 22:6n-3.

Entities:  

Keywords:  Diet; biomarker; breast cancer; fatty acid; meta-analysis

Mesh:

Substances:

Year:  2018        PMID: 29902077     DOI: 10.1080/10408398.2018.1485133

Source DB:  PubMed          Journal:  Crit Rev Food Sci Nutr        ISSN: 1040-8398            Impact factor:   11.176


  3 in total

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Authors:  Mostefa Fodil; Vincent Blanckaert; Lionel Ulmann; Virginie Mimouni; Benoît Chénais
Journal:  Int J Environ Res Public Health       Date:  2022-06-28       Impact factor: 4.614

2.  Identification of potential immunotherapy biomarkers for breast cancer by bioinformatics analysis.

Authors:  Yao Song; Meiling Lu; Lijin Feng; Qian Chen; Hua Huang; Qing Lin
Journal:  Biosci Rep       Date:  2022-02-25       Impact factor: 3.840

3.  Using Genetic Variants to Evaluate the Causal Effect of Plasma Phospholipid Fatty Acids on Breast Cancer and Prostate Cancer: A Mendelian Randomization Study.

Authors:  Ze Yang; Jingjia Li; Yandi Sun; Zihao Qu; Yindan Lin; Lihong Zhang; Qian He; Xueyao Jia; Mashaal Ahmad; Xueyun Zhang; Yan Luo
Journal:  Front Genet       Date:  2021-06-30       Impact factor: 4.599

  3 in total

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