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Observational Study
. 2024 Aug 12;14(1):18705.
doi: 10.1038/s41598-024-69820-7.

Distinctive duodenal microbiomes and bile acid profiles in duodenal tumor patients revealed by prospective observational study

Yoko Kubosawa  1   2 , Tomohisa Sujino  3   4   5 , Kentaro Miyamoto  1   6 , Atsuto Kayashima  1 , Daisuke Minezaki  2 , Kohei Morioka  1   2 , Kentaro Iwata  1   2 , Kurato Miyazaki  1   2 , Teppei Masunaga  2 , Mari Mizutani  1   2 , Teppei Akimoto  2 , Yusaku Takatori  2 , Noriko Matsuura  2 , Atsushi Nakayama  2 , Kaoru Takabayashi  7 , Nobuhiro Nakamoto  1 , Akira Honda  8 , Motohiko Kato  7 , Naohisa Yahagi  2 , Takanori Kanai  9   10
Affiliations
Observational Study

Distinctive duodenal microbiomes and bile acid profiles in duodenal tumor patients revealed by prospective observational study

Yoko Kubosawa et al. Sci Rep. .

Abstract

The incidence of duodenal tumors (DTs) is increasing. However, the mechanisms underlying its development remain unclear. Environmental factors, including the microbiome and bile acids (BAs), are believed to influence tumor development. Therefore, we conducted a single-center, prospective, observational study to investigate the potential differences between patients with DTs and healthy controls (HCs) based on these factors. In addition, the BAs in the duodenal fluid were measured using liquid chromatography-tandem mass spectrometry. We recruited 41 patients and performed 16S rRNA-seq. There was no difference in the observed ASVs or PCoA plot of Bray-Curtis dissimilarity between the DTs and HCs. The lithocholic acid concentration was significantly lower in the DT group than in the control group. The ratio of CDCA to LCA was significantly higher in patients with DTs. No significant differences in microbiota were observed between DTs and HCs. In patients with DTs, the lithocholic acid concentration in duodenal was significantly lower than in HCs.

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Conflict of interest statement

Kentaro Miyamoto is an employee of Miyarisan Pharm. Yoko Kubosawa, Tomohisa Sujino, Atsuto Kayashima, Daisuke Minezaki, Kohei Morioka, Kentaro Iwata, Kurato Miyazaki, Teppei Masunaga, Mari Mizutani, Teppei Akimoto, Yusaku Takatori, Noriko Matsuura, Atsushi Nakayama, Kaoru Takabayashi, Nobuhiro Nakamoto, Akira Honda, Motohiko Kato, Naohisa Yahagi, Takanori Kanai have no competing interests.

Figures

Figure 1
Figure 1
Schema of this study.
Figure 2
Figure 2
(a). The workflow for microbiome analysis between study samples and negative control using QIIME2 and the Venn diagram of observed ASVs in samples and negative control. (b). The workflow for microbiome analysis using QIIME2. (c). The observed ASVs alpha rarefaction curve.
Figure 3
Figure 3
(a). The observed ASVs of DT groups and HC groups. (b). PCoA plot of Bray–Curtis dissimilarity between DT groups and HC groups microbiome. (c). The profiles of duodenal microbiome at the genus level. (d). The PCoA plot of Bray–Curtis dissimilarity between DT group and HC group in 44–66 s. (e). The PCoA plot of Bray–Curtis dissimilarity between Young and Old people microbiome.
Figure 4
Figure 4
The result of ANCOM analysis. (a). Comparison at species level between DT and HC groups. For ANCOM analysis, the clr represents centered log ratio, and the W value represents the number of times of the null-hypothesis (the average abundance of a given species in a group is equal to that in the other group) was rejected for a given species. (b). Comparison at genus level between DT and HC groups.
Figure 5
Figure 5
(a). The log scale of concentration of total bile acids and each bile acid in duodenal fluid. (*P < 0.05) (b). Proportion of each bile acid in total bile acid. (c). Ratio of unconjugated BAs: conjugated BAs, CD: DCA, CDCA: LCA, and CA + CDCA: DCA + LCA + UDCA.
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