Gut microbiota signatures and fecal metabolites in postmenopausal women with osteoporosis

Abstract

Background Women suffer from various distress and disturbances after menopause, including osteoporosis, a risk factor associated with multiple diseases. Altered gut microbiota has been implicated in postmenopausal osteoporosis. In this study, to understand gut microbiota signatures and fecal metabolite changes in postmenopausal women with osteoporosis, 108 postmenopausal women were recruited for intestinal microbiota and fecal metabolite detection. Among these participants, 98 patients, who met the inclusion criteria, were divided into postmenopausal osteoporosis (PMO) and non-postmenopausal osteoporosis (non-PMO) groups based on bone mineral density (BMD). The compositions of gut bacteria and fungi were examined by 16 S rRNA gene sequencing and ITS sequencing, respectively. Meanwhile, fecal metabolites were analyzed using liquid chromatography coupled with mass spectrometry (LC-MS). Results We found that bacterial α-diversity and β-diversity were significantly altered in PMO compared to non-PMO patients. Interestingly, fungi composition showed larger changes, and the differences in β-diversity were more significant between PMO and non-PMO patients. Metabolomics analysis revealed that fecal metabolites, such as levulinic acid, N-Acetylneuraminic acid, and the corresponding signaling pathways were also changed significantly, especially in the alpha-Linolenic acid metabolism and selenocompound metabolism. The screened differential bacteria, fungi, and metabolites closely correlated with clinical findings between these two groups, for example, the bacterial genus, Fusobacterium, the fungal genus, Devriesia, and the metabolite, L-pipecolic acid, were significantly associated with BMD. Conclusions Our findings indicated that there were remarkable changes in gut bacteria, fungi, and fecal metabolites in postmenopausal women, and such changes were notably correlated with patients’ BMD ​​and clinical findings. These correlations provide novel insights into the mechanism of PMO development, potential early diagnostic indicators, and new therapeutic approaches to improve bone health in postmenopausal women.

Characteristics of the gut microbiota and serum metabolites in postmenopausal women with reduced bone mineral density

“…In this study, T-PINP, β-CTX and N-MID were increased in the OS group compared with the normal group, consistent with the findings of previous studies ( He et al., 2020 ; Wang et al., 2023 ). In addition, our data demonstrated a positive association between the Bacteroides / CAG-352 / [Eubacterium]_siraeum_group and BMD and a negative association between the Agathobacter / Lactobacillus ratio and BMD.…”

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“…In this study, T-PINP, b-CTX and N-MID were increased in the OS group compared with the normal group, consistent with the findings of previous studies (He et al, 2020;Wang et al, 2023). In addition, our data demonstrated a positive association between the Bacteroides/CAG-352/[Eubacterium]_siraeum_group and BMD and a negative association between the Agathobacter/Lactobacillus ratio and BMD.…”

Mapping knowledge landscapes and research frontiers of gastrointestinal microbiota and bone metabolism: a text-mining study

“…To further quantify the frequency distribution of these keywords, the study summarized the top 20 high-frequency keywords in Table 2 . Apart from the search term gut microbiota, other popular keywords in this research field include osteoporosis ( Biver et al., 2019 ; Xu et al., 2022 ; Lyu et al., 2023 ), bone density ( Wang et al., 2023 ; Zhang et al., 2023b ), probiotics ( Jia et al., 2021 ), inflammation ( Ding et al., 2022 ; Zhu et al., 2022 ), SCFAs ( Derrien et al., 2004 ; Psichas et al., 2015 ; Whisner et al., 2016 ; Larraufie et al., 2018 ; Nath et al., 2018 ; Shetty et al., 2018 ; Keirns et al., 2020 ; Massy and Drueke, 2020 ; Mohamed et al., 2024 ; Verstraeten et al., 2024 ), metabolism ( Zhang et al., 2023a ), osteoarthritis ( Liu et al., 2022 ; Guan et al., 2023 ), calcium absorption ( Zhou et al., 2023 ), obesity ( Sato et al., 2021 ), double-blind ( Nilsson et al., 2018 ; Jansson et al., 2019 ), prebiotics ( Mohamed et al., 2024 ), mechanisms ( Zhou et al., 2023 ), postmenopausal women ( Wang et al., 2023 ), supplements ( Li et al., 2023 ), risk factors ( Chen et al., 2021 ), oxidative stress ( Li et al., 2019 ), and immune system ( Kim et al., 2017 ; Dar et al., 2018b ; Dar et al., 2018a ). Similarly to citation burst analysis, this study also conducted a burst analysis on keywords that garnered significant attention during a certain period from 2000 to 2023.…”