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Fecal Akkermansia Muciniphila Is Associated with Body Composition and Microbiota Diversity in Overweight and Obese Women with Breast Cancer Participating in a Presurgical Weight Loss Trial

Overview
Publisher Elsevier
Date 2018 Nov 14
PMID 30420171
Citations 50
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Abstract

Background: Akkermansia muciniphila (AM) is a gram-negative, mucin-degrading bacteria inhabiting the gastrointestinal tract associated with host phenotypes and disease states.

Objective: Explore characteristics of overweight and obese female early-stage (0 to II) breast cancer patients with low AM relative abundance (LAM) vs high (HAM) enrolled in a presurgical weight-loss trial.

Design: Secondary analysis of pooled participants in a randomized controlled trial (NCT02224807).

Participants/setting: During the period from 2014 to 2017, 32 female patients with breast cancer were randomized to weight-loss or attention-control arms from time of diagnosis-to-lumpectomy (mean=30±9 days).

Intervention: All were instructed to correct nutrient deficiencies via food sources and on upper-body exercises. The weight-loss group received additional guidance to promote 0.5 to 1 kg/wk weight-loss via energy restriction and aerobic exercise.

Main Outcome Measures: At baseline and follow-up, sera, fecal samples, two-24 hour dietary recalls and dual x-ray absorptiometry were obtained. Bacterial DNA was isolated from feces and polymerase chain reaction (16S) amplified. Inflammatory cytokines were measured in sera.

Statistical Analyses Performed: Differences between LAM and HAM participants were analyzed using t tests and nonparametric tests. Spearman correlations explored relationships between continuous variables.

Results: Participants were aged 61±9 years with body mass index 34.8±6. Mean AM relative abundance was 0.02% (0.007% to 0.06%) and 1.59% (0.59% to 13.57%) for LAM and HAM participants, respectively. At baseline, women with HAM vs LAM had lower fat mass (38.9±11.2 kg vs 46.4±9.0 kg; P=0.044). Alpha diversity (ie, species richness) was higher in women with HAM (360.8±84.8 vs 282.4±69.6; P=0.008) at baseline, but attenuated after weight-loss (P=0.058). At baseline, interleukin-6 level was associated with species richness (ρ=-0.471, P=0.008) and fat mass (ρ=0.529, P=0.002), but not AM. Change in total dietary fiber was positively associated with AM in LAM (ρ=0.626, P=0.002), but not HAM (ρ=0.436, P=0.180) participants.

Conclusions: Among women with early-stage breast cancer, body composition is associated with AM, microbiota diversity, and interleukin-6 level. AM may mediate the effects of dietary fiber in improving microbiota composition.

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References
1.
Faith D, Baker A . Phylogenetic diversity (PD) and biodiversity conservation: some bioinformatics challenges. Evol Bioinform Online. 2009; 2:121-8. PMC: 2674678. View

2.
Agnoli C, Grioni S, Pala V, Allione A, Matullo G, Di Gaetano C . Biomarkers of inflammation and breast cancer risk: a case-control study nested in the EPIC-Varese cohort. Sci Rep. 2017; 7(1):12708. PMC: 5629213. DOI: 10.1038/s41598-017-12703-x. View

3.
DeSantis T, Hugenholtz P, Larsen N, Rojas M, Brodie E, Keller K . Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006; 72(7):5069-72. PMC: 1489311. DOI: 10.1128/AEM.03006-05. View

4.
Caporaso J, Lauber C, Walters W, Berg-Lyons D, Lozupone C, Turnbaugh P . Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci U S A. 2010; 108 Suppl 1:4516-22. PMC: 3063599. DOI: 10.1073/pnas.1000080107. View

5.
Bultman S . Emerging roles of the microbiome in cancer. Carcinogenesis. 2013; 35(2):249-55. PMC: 3908754. DOI: 10.1093/carcin/bgt392. View