Although the gut microbiota has been reported to influence osteoporosis risk, the individual species involved, and underlying mechanisms, remain largely unknown. We performed integrative analyses in a Chinese cohort of peri-/post-menopausal women with metagenomics/targeted metabolomics/whole-genome sequencing to identify novel microbiome-related biomarkers for bone health. Bacteroides vulgatus was found to be negatively associated with bone mineral density (BMD), which was validated in US white people. Serum valeric acid (VA), a microbiota derived metabolite, was positively associated with BMD and causally downregulated by B. vulgatus. Ovariectomized mice fed B. vulgatus demonstrated increased bone resorption and poorer bone micro-structure, while those fed VA demonstrated reduced bone resorption and better bone micro-structure. VA suppressed RELA protein production (pro-inflammatory), and enhanced IL10 mRNA expression (anti-inflammatory), leading to suppressed maturation of osteoclast-like cells and enhanced maturation of osteoblasts in vitro. The findings suggest that B. vulgatus and VA may represent promising targets for osteoporosis prevention/treatment.

Individuals’ peak bone mineral density (BMD) achieved and maintained at ages 20–40 years is the most powerful predictor of low bone mass and osteoporotic fractures later in life. The aim of this study was to identify metabolomic factors associated with peak BMD variation in US Caucasian women. A total of 136 women aged 20–40 years, including 65 subjects with low and 71 with high hip BMD, were enrolled. The serum metabolites were assessed using a liquid chromatography-mass spectrometry (LC-MS) method. The partial least-squares discriminant analysis (PLS-DA) method and logistic regression models were used, respectively, to examine the associations of metabolomic profiles and individual metabolites with BMD. The low and high BMD groups could be differentiated by the detected serum metabolites using PLS-DA (P permutation = 0.008). A total of 14 metabolites, including seven amino acids and amino acid derivatives, five lipids (including three bile acids), and two organic acids, were significantly associated with the risk for low BMD. Most of these metabolites are novel in that they have never been linked with BMD in humans earlier. The prediction model including the newly identified metabolites significantly improved the classification of the groups with low and high BMD. The area under the receiver operating characteristic curve without and with metabolites were 0.88 (95% CI: 0.83–0.94) and 0.97 (95% CI: 0.94–0.99), respectively (P for the difference = 0.0004). Metabolomic profiling may improve the risk prediction of osteoporosis among Caucasian women. Our findings also suggest the potential importance of the metabolism of amino acids and bile acids in bone health.

We investigated the associations between maternal dietary patterns during pregnancy and early childhood growth trajectories and overweight/obesity risk in offspring. Maternal diet was assessed using a food frequency questionnaire during the second trimester, and dietary patterns were derived by reduced rank regression. The associations between maternal dietary pattern scores and body mass index (BMI) trajectories from birth to age four (rising-high, moderate, and low BMI trajectories) as well as overweight/obesity risk at age four were analyzed (n = 1257). Two maternal dietary patterns were identified. The fast food pattern included a higher intake of fried chicken and fish, fruit juices, mayonnaise, and sugar-sweetened beverages, while the processed food pattern included a higher intake of dairy, salad dressing, processed meat, and cold breakfast cereal. Women with greater adherence to the fast food pattern were more likely to have children in the rising-high BMI trajectory group [OR (95% CI) = 1.32 (1.07–1.62); p = 0.008] or having overweight/obesity at age four [OR (95% CI) = 1.31 (1.11–1.54); p = 0.001]. The processed food pattern was not associated with these outcomes. The maternal dietary pattern during pregnancy represented by fried foods and sugar-sweetened beverages may contribute to rapid early childhood growth and increased risk for obesity in offspring.

Purpose: To compare the endocrine and metabolic indexes of obese and normal body mass index (BMI) polycystic ovary syndrome (PCOS) patients, and explore factors affecting the pathogenesis and progression of PCOS. Methods: This study included obese (n=79) and normal BMI (n=40) PCOS patients, and obese (n=30) and normal BMI (n=30) non-PCOS controls. Blood glucose, insulin (INS), blood lipids, sex hormones, and other metabolic and endocrine indicators were measured, and the correlations between the indicators were analyzed. Results: HOMA-IR, 0min INS, 60min INS, 120min INS, 180min INS, FAI, TG, TC, LDL-C and sd-LDL in obese PCOS group were higher, while SHBG, LH, LH/FSH and HDL-C were lower than those in normal weight PCOS group (P < 0.05). 120min PBG, HOMA-IR, FAI, T, LH, LH/FSH, AMH, TC and LDL-C in obese PCOS group were higher than those in obese control group (P < 0.05). 0min PBG, 60min PBG, 120min PBG, 180min PBG, 0min INS, 60min INS, 120min INS, 180min INS, HOMA-IR, LH, LH/FSH and T in normal weight PCOS group were higher than those in normal weight control group (P < 0.05). In both normal weight group and obesity group, HOMA-IR entered the regression equation with FAI as dependent variable, and the absolute value of HOMA-IR standardized partial regression coefficient was higher than that of hs-CRP and AMH. In PCOS patients, FAI in the obese and non-obese PCOS groups was positively correlated with HOMA-IR. Conclusion: Endocrine metabolic disorders in women with PCOS were more obvious than that in women with non-PCOS with matched BMI. The abnormality of glucose and lipid metabolism in obese PCOS patients is more serious than that in PCOS patients with normal BMI. Both obese and normal BMI PCOS patients were affected by hyperinsulinemia, and IR may play a key role in the pathogenesis and development of PCOS.