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. 2021 Dec 17:11:794610.
doi: 10.3389/fcimb.2021.794610. eCollection 2021.

The Association Between Breast Density and Gut Microbiota Composition at 2 Years Post-Menarche: A Cross-Sectional Study of Adolescents in Santiago, Chile

Lara S Yoon  1 , Jonathan P Jacobs  1   2   3 , Jessica Hoehner  4 , Ana Pereira  5 , Juan Cristóbal Gana  6 , Camila Corvalán  5 , Karin B Michels  1   7
Affiliations

The Association Between Breast Density and Gut Microbiota Composition at 2 Years Post-Menarche: A Cross-Sectional Study of Adolescents in Santiago, Chile

Lara S Yoon et al. Front Cell Infect Microbiol. .

Abstract

The gut microbiome has been linked to breast cancer via immune, inflammatory, and hormonal mechanisms. We examined the relation between adolescent breast density and gut microbial composition and function in a cohort of Chilean girls. This cross-sectional study included 218 female participants in the Growth and Obesity Cohort Study who were 2 years post-menarche. We measured absolute breast fibroglandular volume (aFGV) and derived percent FGV (%FGV) using dual energy X-ray absorptiometry. All participants provided a fecal sample. The gut microbiome was characterized using 16S ribosomal RNA sequencing of the V3-V4 hypervariable region. We examined alpha diversity and beta diversity across terciles of %FGV and aFGV. We used MaAsLin2 for multivariable general linear modeling to assess differential taxa and predicted metabolic pathway abundance (MetaCyc) between %FGV and aFGV terciles. All models were adjusted for potential confounding variables and corrected for multiple comparisons. The mean %FGV and aFGV was 49.5% and 217.0 cm3, respectively, among study participants. Similar median alpha diversity levels were found across %FGV and aFGV terciles when measured by the Shannon diversity index (%FGV T1: 4.0, T2: 3.9, T3: 4.1; aFGV T1: 4.0, T2: 4.0, T3: 4.1). %FGV was associated with differences in beta diversity (R2 = 0.012, p=0.02). No genera were differentially abundant when comparing %FGV nor aFGV terciles after adjusting for potential confounders (q > 0.56 for all genera). We found no associations between predicted MetaCyc pathway abundance and %FGV and aFGV. Overall, breast density measured at 2 years post-menarche was not associated with composition and predicted function of the gut microbiome among adolescent Chilean girls.

Keywords: 16s rRNA; adolescence; breast cancer; breast density; epidemiology; gut microbiota; human.

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Conflict of interest statement

Author JH is employed by Leidos, Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Microbial mean relative abundance at the phylum level stratified by (A) %FGV tercile and (B) aFGV tercile in fecal microbiota samples from 218 GOCS participants.
Figure 2
Figure 2
Box plots of alpha diversity metrics for observed richness and Shannon index across terciles of %FGV (A, B) and aFGV (C, D). P-values are presented for overall differences in alpha diversity metrics (Kruskal-Wallis) and post-hoc pairwise differences. Boxes represent the lower, median, and upper quartile of the data and whiskers are 1.5*interquartile range.
Figure 3
Figure 3
Principal coordinate analysis (PCoA) plot of microbial composition derived from Bray-Curtis dissimilarity among fecal samples provided by 218 girls in GOCS colored by %FGV (A) and aFGV (B) terciles. Ellipses are 95% confidence regions for each tercile.
Figure 4
Figure 4
Principal coordinate analysis (PCoA) plot of predicted MetaCyc pathway abundance derived from Bray-Curtis dissimilarity among fecal samples provided by 218 girls in GOCS colored by %FGV (A) and aFGV (B) terciles. Ellipses are 95% confidence regions for each tercile.
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References

    1. Baker J. M., Al-Nakkash L., Herbst-Kralovetz M. M. (2017). Estrogen–gut Microbiome Axis: Physiological and Clinical Implications. Maturitas 103, 45–53. doi: 10.1016/j.maturitas.2017.06.025 - DOI - PubMed
    1. Bard J.-M., Luu H. T., Dravet F., Michel C., Moyon T., Pagniez A., et al. . (2015). Relationship Between Intestinal Microbiota and Clinical Characteristics of Patients With Early Stage Breast Cancer. FASEB J. 29, 914.2. doi: 10.1096/fasebj.29.1_supplement.914.2 - DOI
    1. Belkaid Y., Hand T. W. (2014). Role of the Microbiota in Immunity and Inflammation. Cell 157, 121–141. doi: 10.1016/j.cell.2014.03.011 - DOI - PMC - PubMed
    1. Benjamini Y., Hochberg Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J. R. Stat. Society Ser. B (Methodol) 57, 289–300. doi: 10.1111/j.2517-6161.1995.tb02031.x - DOI
    1. Bolyen E., Rideout J. R., Dillon M. R., Bokulich N. A., Abnet C. C., Al-Ghalith G. A., et al. . (2019). Reproducible, Interactive, Scalable and Extensible Microbiome Data Science Using QIIME 2. Nat. Biotechnol. 37, 852–857. doi: 10.1038/s41587-019-0209-9 - DOI - PMC - PubMed

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