The potential of Klebsiella and Escherichia-Shigella and amino acids metabolism to monitor patients with postmenopausal osteoporosis in northwest China

克雷伯氏菌、大肠杆菌-志贺氏菌及氨基酸代谢对中国西北地区绝经后骨质疏松症患者的监测潜力

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作者:Zhuang Liang #, Yuqi Hao #, Lei Yang #, Puwei Yuan, Wulin Kang, Tingting Liang, Bing Gu, Bo Dong

Background

Intestinal flora has been proposed to mediate the occurrence of postmenopausal osteoporosis (PMO). However, the mechanism by which microbes and their metabolites interactively promote PMO remains unknown.

Conclusions

This study provides robust evidence connecting the intestinal flora and fecal metabolomics with PMO. Integrated metabolite and microbiota analyses demonstrated that in addition to dysregulated bacteria, indole-3-acetic acid, 7-ketodeoxycholic acid, and other metabolites can be used for the distinguish of LBM and PMO.

Methods

This study aimed to investigate changes in the intestinal flora and associated metabolites, and their role in PMO. 16S rRNA gene sequencing and metabolomics were performed to obtain postmenopausal women with osteopenia (lower bone mass, LBM), postmenopausal women with osteoporosis (OST), and healthy women as the control group.

Results

We identified taxa-specific and metabolite differences in the intestinal flora of the participants of this study. The pathogenic bacteria Klebsiella (0.59% and 0.71%, respectively) and Escherichia-Shigella (2.72% and 4.30%, respectively) were enriched in the LBM and OST groups (p < 0.05). Some short-chain fatty acid (SCFAs) producing bacteria, Lactobacillus, Akkermansia, Prevotella, Alistipes, and Butyricicoccus, were reduced in patients with LBM and OST compared to the control. Moreover, fecal metabolomic analyses suggested that the metabolites of indole-3-acetic acid and 7-ketodeoxycholic acid were altered in the LBM and OST groups compared to the control (p < 0.05). Enrichment analysis suggested that valine, leucine, and isoleucine biosynthesis; aromatic amino acid biosynthesis; and phenylalanine metabolism were significantly associated with the identified microbiota biomarkers and OST. Moreover, metabolite marker signatures distinguished patients in the OST from those in the control group with an area under the curve (AUC) of 0.978 and 1.00 in the negative and positive ion modes, respectively. Finally, we also found that the fecal level of interleukin-10 (IL-10) in the OST group was significantly lower than that in the control group and LBM group (p < 0.05), while tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) were significantly higher in the OST group than that in the control group (p < 0.05). Conclusions: This study provides robust evidence connecting the intestinal flora and fecal metabolomics with PMO. Integrated metabolite and microbiota analyses demonstrated that in addition to dysregulated bacteria, indole-3-acetic acid, 7-ketodeoxycholic acid, and other metabolites can be used for the distinguish of LBM and PMO.

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