Gut microbiota signatures and fecal metabolites in postmenopausal women with osteoporosis Original paper

What was studied?

This original research investigated the gut microbiota signatures and fecal metabolite profiles in postmenopausal women with and without osteoporosis (PMO and non-PMO, respectively). The study aimed to elucidate the specific changes in both bacterial and fungal components of the intestinal microbiota, as well as associated fecal metabolites, that correlate with bone mineral density (BMD) in this population. Using 16S rRNA gene sequencing for bacteria, ITS sequencing for fungi, and LC-MS for metabolomics, the study comprehensively evaluated the compositional and functional alterations in the gut ecosystem of postmenopausal women stratified by osteoporosis status. The researchers also applied machine learning models to assess whether these microbial and metabolic signatures could serve as early diagnostic indicators for PMO.

Who was studied?

A total of 98 postmenopausal women aged 50–70 years were enrolled, divided into two groups based on BMD: 40 women with postmenopausal osteoporosis (PMO) and 58 women without osteoporosis (non-PMO). All participants were recruited from Zhongshan Hospital of Xiamen University, with strict inclusion and exclusion criteria to eliminate confounding factors such as organ dysfunction, recent antibiotic use, gastrointestinal diseases, and secondary causes of osteoporosis. For model validation, an independent cohort of 23 women (10 non-PMO, 13 PMO) from Xinyu People’s Hospital was included. Clinical data, serological markers, and BMD measurements were obtained alongside fecal samples for multi-omics analysis.

Most important findings

The study revealed marked differences in both bacterial and fungal gut communities between PMO and non-PMO women. Bacterial α-diversity (measured by Chao1, ACE, and Shannon indices) was significantly reduced in the PMO group, while fungal diversity changes were even more pronounced at the β-diversity level, indicating a distinct fungal signature in osteoporosis. Key bacterial genera enriched in PMO included Veillonella, Parabacteroides, and Harryflintia, while Prevotella and Enterobacterium were more abundant in non-PMO. Fungal genera such as Eurotium and Penicillium were elevated in PMO, whereas Pichia and Auricularia were enriched in non-PMO. Metabolomics identified higher levels of metabolites like levulinic acid and N-acetylneuraminic acid in PMO, with significant pathway alterations including alpha-linolenic acid and selenocompound metabolism. Correlation analysis showed that specific bacteria (e.g., Fusobacterium), fungi (e.g., Devriesia), and metabolites (e.g., L-pipecolic acid) were significantly associated with BMD. Machine learning models based on these microbial signatures distinguished PMO from non-PMO with high accuracy, underscoring their diagnostic potential.

Key implications

This study provides compelling evidence that gut microbial and metabolic profiles are closely tied to bone health in postmenopausal women. The identification of distinct bacterial, fungal, and metabolite signatures associated with osteoporosis advances our understanding of the gut-bone axis, suggesting potential mechanisms involving immune modulation and metabolic pathways. The robust diagnostic models highlight the clinical utility of gut microbiota analysis as a non-invasive tool for early PMO detection. The findings suggest that microbiome-targeted interventions, such as probiotics or dietary modifications, could be developed to prevent or mitigate osteoporosis in at-risk women, paving the way for personalized therapeutic strategies.