A Distinctive Human Metabolomics Alteration Associated with Osteopenic and Osteoporotic Patients

Combining untargeted and targeted metabolomic profiling reveals principal differences between osteopenia, Osteoporosis and healthy controls

BACKGROUND

Osteopenia (ON) and osteoporosis (OP) are highly prevalent among postmenopausal women and poses a challenge for early diagnosis. Therefore, identifying reliable biomarkers for early prediction using metabolomics is critically important.

METHODS

Initially, non-targeted metabolomics was employed to identify differential metabolites in plasma samples from cohort 1, which included healthy controls (HC, n = 23), osteonecrosis (ON, n = 36), and osteoporosis (OP, n = 37). Subsequently, we performed targeted metabolomic validation of 37 amino acids and their derivatives in plasma samples from cohort 2, consisting of healthy controls (HC, n = 10), osteonecrosis (ON, n = 10), and osteoporosis (OP, n = 10).

RESULTS

The non-targeted metabolomic analysis revealed an increase in differential metabolites with the progression of the disease, showing abnormalities in lipid and organic acid metabolism in ON and OP patients. Several substances were found to correlate positively or negatively with bone mineral density (BMD), for example, N-undecanoylglycine, sphingomyelins, and phosphatidylinositols exhibited positive correlations with BMD, while acetic acid, phenylalanine, taurine, inosine, and pyruvic acid showed negative correlations with BMD. Subsequently, targeted validation of 37 amino acids and their metabolites revealed six amino acids related to ON and OP.

CONCLUSION

Significant metabolomic features were identified between HC and patients with ON/OP, with multiple metabolites correlating positively or negatively with BMD. Integrating both targeted and non-targeted metabolomic results suggests that lipid, organic acid, and amino acid metabolism may represent important metabolomic characteristics of patients with OP, offering new insights into the development of metabolomic applications in OP.

Osteopenia Metabolomic Biomarkers for Early Warning of Osteoporosis

Introduction: This study aimed to capture the early metabolic changes before osteoporosis occurs and identify metabolomic biomarkers at the osteopenia stage for the early prevention of osteoporosis. Materials and Methods: Metabolomic data were generated from normal, osteopenia, and osteoporosis groups with 320 participants recruited from the Nicheng community in Shanghai. We conducted individual edge network analysis (iENA) combined with a random forest to detect metabolomic biomarkers for the early warning of osteoporosis. Weighted Gene Co-Expression Network Analysis (WGCNA) and mediation analysis were used to explore the clinical impacts of metabolomic biomarkers. Results: Visual separations of the metabolic profiles were observed between three bone mineral density (BMD) groups in both genders. According to the iENA approach, several metabolites had significant abundance and association changes in osteopenia participants, confirming that osteopenia is a critical stage in the development of osteoporosis. Metabolites were further selected to identify osteopenia (nine metabolites in females; eight metabolites in males), and their ability to discriminate osteopenia was improved significantly compared to traditional bone turnover markers (BTMs) (female AUC = 0.717, 95% CI 0.547-0.882, versus BTMs: p = 0.036; male AUC = 0.801, 95% CI 0.636-0.966, versus BTMs: p = 0.007). The roles of the identified key metabolites were involved in the association between total fat-free mass (TFFM) and osteopenia in females. Conclusion: Osteopenia was identified as a tipping point during the development of osteoporosis with metabolomic characteristics. A few metabolites were identified as candidate early-warning biomarkers by machine learning analysis, which could indicate bone loss and provide new prevention guidance for osteoporosis.

Postprandial Metabolomic Profiling: Insights into Macronutrient-Specific Metabolic Responses in Healthy Individuals

BACKGROUND/OBJECTIVES

Understanding the metabolic responses to different macronutrients is crucial for assessing their impacts on health. This study aims to investigate the postprandial metabolomic profiles of healthy individuals following the consumption of glucose, protein, and lipids.

METHODS

Twenty-three healthy, normal-weight adults participated in the study, randomly assigned to consume 300 kcal from glucose, protein, or lipids after an overnight fast. Blood samples were collected at baseline and at 1, 2, and 3 h post-ingestion. An untargeted metabolomic approach using mass spectrometry was employed to analyze plasma metabolites.

RESULTS

In total, 21, 59, and 156 dysregulated metabolites were identified after glucose, protein, and lipid intake, respectively. Notably, 3'-O-methylguanosine levels decreased significantly after glucose consumption while remaining stable during lipid intake before increasing at 2 h. Common metabolites shared between glucose and lipid groups included 3'-O-methylguanosine, 3-oxotetradecanoic acid, poly-g-D-glutamate, and triglyceride (TG) (15:0/18:4/18:1).

CONCLUSIONS

The findings highlight distinct metabolic responses to macronutrient intake, emphasizing the role of specific metabolites in regulating postprandial metabolism. These insights contribute to understanding how dietary components influence metabolic health and insulin sensitivity.

From Genomics to Metabolomics: Molecular Insights into Osteoporosis for Enhanced Diagnostic and Therapeutic Approaches

Osteoporosis (OP) is a prevalent skeletal disorder characterized by decreased bone mineral density (BMD) and increased fracture risk. The advancements in omics technologies-genomics, transcriptomics, proteomics, and metabolomics-have provided significant insights into the molecular mechanisms driving OP. These technologies offer critical perspectives on genetic predispositions, gene expression regulation, protein signatures, and metabolic alterations, enabling the identification of novel biomarkers for diagnosis and therapeutic targets. This review underscores the potential of these multi-omics approaches to bridge the gap between basic research and clinical applications, paving the way for precision medicine in OP management. By integrating these technologies, researchers can contribute to improved diagnostics, preventative strategies, and treatments for patients suffering from OP and related conditions.

Lipid metabolites are associated with the risk of osteoporotic fractures

We conducted this cross-sectional study to investigate the independent associations between lipid metabolites and osteoporotic fractures among participants aged 40-69 years from the UK Biobank. Serum lipid, lipoprotein levels and nuclear magnetic resonance (NMR) based metabolic biomarkers were measured at the baseline. We conducted multivariable logistic analyses to investigate potential independent associations between concentrations of lipid metabolites and osteoporotic fractures in both men and women. The odds ratios (ORs) for lipid metabolites were calculated based on their lowest tertile. Over a median follow-up period of 15 years, a total of 978 men and 4515 women were diagnosed with osteoporosis, whereas 138 men and 327 women encountered incident fractures. Statistically significant disparities were identified in NMR-based metabolic biomarkers among men and women with incident fractures compared to those without. Out of the 144 distinct lipid metabolites known, 35 exhibited significant associations with incident fractures in patients diagnosed with osteoporosis. Following the adjustment for confounding factors, degree of unsaturation (p = 0.0066) and docosahexaenoic acids (p = 0.0011) in male patients increased the risk of incident fractures. And high level of different metabolites of HDL (p = 0.0153), 3-Hydroxybutyrate (p = 0.0012) and Sphingomyelins (p = 0.0036) decreased the risk of incident fractures in female patients. This outcome indicates that these identified lipid metabolites may potentially have unique roles in independently contributing to the occurrence of osteoporotic fractures.

Comparative Analysis of Breast Cancer Metabolomes Highlights Fascin's Central Role in Regulating Key Pathways Related to Disease Progression

Omics technologies provide useful tools for the identification of novel biomarkers in many diseases, including breast cancer, which is the most diagnosed cancer in women worldwide. We and others have reported a central role for the actin-bundling protein (fascin) in regulating breast cancer disease progression at different levels. However, whether fascin expression promotes metabolic molecules that could predict disease progression has not been fully elucidated. Here, fascin expression was manipulated via knockdown (fascinKD+NORF) and rescue (fascinKD+FORF) in the naturally fascin-positive (fascinpos+NORF) MDA-MB-231 breast cancer cells. Whether fascin dysregulates metabolic profiles that are associated with disease progression was assessed using untargeted metabolomics analyses via liquid chromatography-mass spectrometry. Overall, 12,226 metabolic features were detected in the tested cell pellets. Fascinpos+NORF cell pellets showed 2510 and 3804 significantly dysregulated metabolites compared to their fascinKD+NORF counterparts. Fascin rescue (fascinKD+FORF) revealed 2710 significantly dysregulated cellular metabolites compared to fascinKD+NORF counterparts. A total of 101 overlapped cellular metabolites between fascinKD+FORF and fascinpos+NORF were significantly dysregulated in the fascinKD+NORF cells. Analysis of the significantly dysregulated metabolites by fascin expression revealed their involvement in the metabolism of sphingolipid, phenylalanine, tyrosine, and tryptophan biosynthesis, and pantothenate and CoA biosynthesis, which are critical pathways for breast cancer progression. Our findings of fascin-mediated alteration of metabolic pathways could be used as putative poor prognostic biomarkers and highlight other underlying mechanisms of fascin contribution to breast cancer progression.

Gut microbiota, plasma metabolites, and osteoporosis: unraveling links via Mendelian randomization

Objective

Osteoporosis, characterized by reduced bone density and heightened fracture risk, is influenced by genetic and environmental factors. This study investigates the interplay between gut microbiota, plasma metabolomics, and osteoporosis, identifying potential causal relationships mediated by plasma metabolites.

Methods

Utilizing aggregated genome-wide association studies (GWAS) data, a comprehensive two-sample Mendelian Randomization (MR) analysis was performed involving 196 gut microbiota taxa, 1,400 plasma metabolites, and osteoporosis indicators. Causal relationships between gut microbiota, plasma metabolites, and osteoporosis were explored.

Results

The MR analyses revealed ten gut microbiota taxa associated with osteoporosis, with five taxa positively linked to increased risk and five negatively associated. Additionally, 96 plasma metabolites exhibited potential causal relationships with osteoporosis, with 49 showing positive associations and 47 displaying negative associations. Mediation analyses identified six causal pathways connecting gut microbiota to osteoporosis through ten mediating relationships involving seven distinct plasma metabolites, two of which demonstrated suppression effects.

Conclusion

This study provides suggestive evidence of genetic correlations and causal links between gut microbiota, plasma metabolites, and osteoporosis. The findings underscore the complex, multifactorial nature of osteoporosis and suggest the potential of gut microbiota and plasma metabolite profiles as biomarkers or therapeutic targets in the management of osteoporosis.

Energy homeostasis in the bone

The bone serves as an energy reservoir and actively engages in whole-body energy metabolism. Numerous studies have determined fuel requirements and bioenergetic properties of bone under physiological conditions as well as the dysregulation of energy metabolism associated with bone metabolic diseases. Here, we review the main sources of energy in bone cells and their regulation, as well as the endocrine role of the bone in systemic energy homeostasis. Moreover, we discuss metabolic changes that occur as a result of osteoporosis. Exploration in this area will contribute to an enhanced comprehension of bone energy metabolism, presenting novel possibilities to address metabolic diseases.

Distinct Metabolites in Osteopenia and Osteoporosis: A Systematic Review and Meta-Analysis

Multiple studies have indicated that distinct metabolites are involved in the occurrence and development of osteopenia (ON) and osteoporosis (OP); however, these metabolites in OP and ON have not yet been classified and standardized. This systematic review and meta-analysis included 21 articles aiming to investigate the distinct metabolites in patients with ON and OP. The quality of the included articles was generally high; seventeen studies had >7 stars, and the remaining four received 6 stars. This systematic review showed that three metabolites (phosphatidylcholine (PC) (lipid metabolites), galactose (carbohydrate metabolites), and succinic acid (other metabolites)) increased, four (glycylglycine (gly-gly), cystine (amino acids), sphingomyelin (SM) (lipid metabolites) and glucose (carbohydrate metabolites)) decreased, and five (glutamine, hydroxyproline, taurine (amino acids), lysophosphatidylcholine (LPC) (lipid metabolites), and lactate (other metabolites)) had conflicting directions in OP/ON. The results of the meta-analysis show that gly-gly (MD = -0.77, 95%CI -1.43 to -0.11, p = 0.02) and cystine (MD = -5.52, 95%CI -7.35 to -3.68, p < 0.00001) decreased in the OP group compared with the healthy control group. Moreover, LPC (MD = 1.48, 95%CI 0.11 to 2.86, p = 0.03) increased in the OP group compared with the healthy control group. These results indicate that distinct metabolites were associated with ON and OP, which could be considered a predictor for OP.

Application and prospect of metabolomics in the early diagnosis of osteoporosis: a narrative review

This paper reviews the application of metabolomics in the early diagnosis of osteoporosis in recent years. The authors searched electronic databases for the keywords "metabolomics", "osteoporosis" and "biomarkers", then analyzed the relationship between functional markers and osteoporosis using categorical summarization. Lipid metabolism, amino acid metabolism and energy metabolism are closely related to osteoporosis development and can become early diagnostic markers of the condition. However, the existing studies in metabolomics suffer from varying application methods, difficulty in identifying isomers, small study cohorts and insufficient research on metabolic mechanisms. Consequently, it is important for future research to focus on broadening and standardizing the scope of the application of metabolomics. High-quality studies on a large scale should also be conducted while promoting the early diagnosis of osteoporosis in a more precise, comprehensive and sensitive manner.

Metabolomics provides insights into acceleration of bone healing in fractured patients with traumatic brain injuries

While clinical surveys have frequently reported that patients with traumatic brain injuries (TBIs) and comorbidities experience faster healing, the underlying mechanisms have been investigated but remain unclear. As a comprehensive comparison and analysis of the metabolic characteristics of these two pathologies have not been undertaken, we developed a rat model of fracture and TBI and collected serum samples for metabolomic analysis using ultra-high performance liquid chromatography-quadrupole time-of-flight MS (UHPLC-Q-TOF/MS). In total, we identified 40 differential metabolites and uncovered related pathways and potential mechanisms, including aminoacyl-transfer RNA biosynthesis; differential amino acids such as leucine, cholylhistidine, aspartyl-lysine; and related lipid metabolism, and discussed their impacts on bone formation in detail. This study highlights that the UHPLC-Q-TOF/MS-based metabolomics approach offers a better understanding of the metabolic links between TBI and accelerated bone recovery.

Longbie capsules reduce bone loss in the subchondral bone of rats with comorbid osteoporosis and osteoarthritis by regulating metabolite alterations

Background and objective

With the development of global population aging, comorbidity (≥2 diseases) is a common health problem among elderly people. Osteoarthritis (OA) and osteoporosis (OP) are common in elderly individuals. There is a lack of drug therapy for OA and OP comorbidities. The purpose of this study was to explore the efficacy and mechanism of Longbie capsule (LBJN), which contains various plant herbs, in treating OA and OP comorbidities (OA + OP) in rats using metabolomics techniques.

Methods

We created an OA + OP rat model through bilateral oophorectomy combined with meniscus instability surgery. Thirty SD rats were randomly divided into five groups (six in each group), namely, the sham group, OA group, OA + OP group, LBJN low-dose group (0.625 g/kg, OA + OP+LB-L group) and LBJN high-dose group (1.25 g/kg, OA + OP+LB-H group). After 8 weeks of intervention, we used micro-CT to detect bone microstructure status, ELISA to measure bone metabolism indicators, and UPLC-MS technology for metabolomics analysis. Finally, the screened differentially expressed metabolites were subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and functional enrichment analysis.

Results

The micro-CT results showed that LBJN significantly improved the bone mineral density (BMD) and bone quality of subchondral bone in OA + OP rats, and LBJN regulated the expression of bone alkaline phosphatase (BALP), osteoprotegerin (OPG), and tartrate-resistant acid phosphatase (TRACP) in serum to maintain bone metabolism balance. Metabolomics analysis showed that the metabolic trajectory of OA + OP rats after intervention in the OA + OP+LB-H group showed significant changes, and 107 potential biomarkers could be identified. Among them, 50 metabolites were upregulated (such as zeranol) and 57 were downregulated (such as vanillactic acid). The KEGG functional enrichment results indicated that the differentially expressed metabolites are mainly involved in amino acid metabolism, lipid metabolism, and carbohydrate metabolism. The KEGG pathway enrichment results indicated that LBJN may exert therapeutic effects on OA + OP rats by regulating the cAMP signaling pathway, and the FoxO signaling pathway.

Conclusion

LBJN can maintain bone metabolism balance by regulating serum lipid metabolism, amino acid metabolism, carbohydrate metabolism, and estrogen, thereby reducing bone loss in subchondral bone, which may be a potential mechanism through which LBJN treats OA + OP.

Bone Trans-omics: Integrating Omics to Unveil Mechanistic Molecular Networks Regulating Bone Biology and Disease

PURPOSE OF REVIEW

Recent advancements in "omics" technologies and bioinformatics have afforded researchers new tools to study bone biology in an unbiased and holistic way. The purpose of this review is to highlight recent studies integrating multi-omics data gathered from multiple molecular layers (i.e.; trans-omics) to reveal new molecular mechanisms that regulate bone biology and underpin skeletal diseases.

RECENT FINDINGS

Bone biologists have traditionally relied on single-omics technologies (genomics, transcriptomics, proteomics, and metabolomics) to profile measureable differences (both qualitative and quantitative) of individual molecular layers for biological discovery and to investigate mechanisms of disease. Recently, literature has grown on the implementation of integrative multi-omics to study bone biology, which combines computational and informatics support to connect multiple layers of data derived from individual "omic" platforms. This emerging discipline termed "trans-omics" has enabled bone biologists to identify and construct detailed molecular networks, unveiling new pathways and unexpected interactions that have advanced our mechanistic understanding of bone biology and disease. While the era of trans-omics is poised to revolutionize our capacity to answer more complex and diverse questions pertinent to bone pathobiology, it also brings new challenges that are inherent when trying to connect "Big Data" sets. A concerted effort between bone biologists and interdisciplinary scientists will undoubtedly be needed to extract physiologically and clinically meaningful data from bone trans-omics in order to advance its implementation in the field.

Metabolic characteristics and pathogenesis of precocious puberty in girls: the role of perfluorinated compounds

BACKGROUND

Precocious puberty (PP) in girls is traditionally defined as the onset of breast development before the age of 8 years. The specific biomarkers of premature thelarche (PT) and central precocious puberty (CPP) girls are uncertain, and little is known about their metabolic characteristics driven by perfluorinated compounds (PFCs) and clinical phenotype. This study aimed to screen specific biomarkers of PT and CPP and elucidate their underlying pathogenesis. The relationships of clinical phenotype-serum PFCs-metabolic characteristics were also explored to reveal the relationship between PFCs and the occurrence and development of PT and CPP.

METHODS

Nuclear magnetic resonance (NMR)-based cross-metabolomics strategy was performed on serum from 146 PP (including 30 CPP, 40 PT, and 76 unspecified PP) girls and 64 healthy girls (including 36 prepubertal and 28 adolescent). Specific biomarkers were screened by the uni- and multivariate statistical analyses. The relationships between serum PFCs and clinical phenotype were performed by correlation analysis and weighted gene co-expression network analysis to explore the link of clinical phenotype-PFCs-metabolic characteristics in PT and CPP.

RESULTS

The disordered trend of pyruvate and butyrate metabolisms (metabolites mapped as formate, ethanol, and 3-hydroxybutyrate) were shared and kept almost consistent in PT and CPP. Eight and eleven specific biomarkers were screened for PT and CPP, respectively. The area under curve of specific biomarker combination was 0.721 in CPP vs. prepubertal, 0.972 in PT vs. prepubertal, 0.646 in CPP vs. prepubertal integrated adolescent, and 0.822 in PT vs. prepubertal integrated adolescent, respectively. Perfluoro-n-heptanoic acid and perfluoro-n-hexanoic acid were statistically different between PT and CPP. Estradiol and prolactin were significantly correlated with PFCs in CPP and PT. Clinical phenotypes and PFCs drive the metabolic characteristics and cause metabolic disturbances in CPP and PT.

CONCLUSIONS

The elevation of formate, ethanol, and 3-hydroxybutyrate may serve as the early diagnostic indicator for PP in girls. But the stratification of PP still needs to be further determined based on the specific biomarkers. Specific biomarkers of CPP and PT exhibited good sensitivity and can facilitate the classification diagnosis of CPP and PT. PFC exposure is associated with endocrine homeostasis imbalance. PFC exposure and/or endocrine disturbance directly or indirectly drive metabolic changes and form overall metabolic network perturbations in CPP and PT.

Effects of Menaquinone-7 on the Bone Health of Growing Rats under Calcium Restriction: New Insights from Microbiome-Metabolomics

Insufficient calcium intake during growth is a global public health concern. The aim of this study was to investigate the effects of dietary menaquinone-7 (MK-7) on bone accrual in growing Sprague-Dawley rats under calcium restriction. Following 13 weeks of treatment, various bone quality parameters, including microarchitecture, were measured. Fecal and cecal samples were subjected to microbiome (16S rRNA gene sequencing) analyses, while metabolomics analysis of the cecum and humerus samples was analyzed based on UHPLC-Q/TOF-MS. We found that calcium deficiency diminished the richness of the microbiome and disrupted microbiome composition, accompanied by an elevation in the relative abundance of Parasutterella. Furthermore, calcium insufficiency escalated the level of isovaleric acid and modified the metabolic profiles. MK-7 supplementation significantly increased the cortical thickness, cortical bone area, and the calcium content of the femur. Apart from improving bone calcium deposition and diminishing bone resorption, the mechanisms underlying the beneficial effects of MK on bone quality also involve the modulation of the host's metabolic pathways and the composition of gut microbiota. The gut-bone axis holds promise as an efficacious target for ameliorating calcium deficiency in children's bone quality, and MK-7 is a promising dietary supplement from this perspective.

Discovery of potential biomarkers for osteoporosis diagnosis by individual omics and multi-omics technologies

INTRODUCTION

Global aging has made osteoporosis an increasingly serious public health problem. Osteoporotic fractures seriously affect the quality of life of patients and increase disability and mortality rates. Early diagnosis is important for timely intervention. The continuous development of individual- and multi-omics methods is helpful for the exploration and discovery of biomarkers for the diagnosis of osteoporosis.

AREAS COVERED

In this review, we first introduce the epidemiological status of osteoporosis and then describe the pathogenesis of osteoporosis. Furthermore, the latest progress in individual- and multi-omics technologies for exploring biomarkers for osteoporosis diagnosis is summarized. Moreover, we clarify the advantages and disadvantages of the application of osteoporosis biomarkers obtained using the omics method. Finally, we put forward valuable views on the future research direction of diagnostic biomarkers of osteoporosis.

EXPERT OPINION

Omics methods undoubtedly provide greatly contribute to the exploration of diagnostic biomarkers of osteoporosis; however, in the future, the clinical validity and clinical utility of the obtained potential biomarkers should be thoroughly examined. In addition, the improvement and optimization of the detection methods for different types of biomarkers and standardization of the detection process guarantee the reliability and accuracy of the detection results.

Metabolomics of Osteoporosis in Humans: A Systematic Review

PURPOSE OF REVIEW

To systematically review recent studies investigating the association between metabolites and bone mineral density (BMD) in humans.

METHODS

Using predefined keywords, we searched literature published from Jan 1, 2019 to Feb 20, 2022 in PubMed, Web of Science, Embase, and Scopus. Studies that met the predefined exclusion criteria were excluded. Among the included studies, we identified metabolites that were reported to be associated with BMD by at least three independent studies.

RECENT FINDINGS

A total of 170 studies were retrieved from the databases. After excluding studies that did not meet our predefined inclusion criteria, 16 articles were used in this review. More than 400 unique metabolites in blood were shown to be significantly associated with BMD. Of these, three metabolites were reported by ≥ 3 studies, namely valine, leucine and glycine. Glycine was consistently shown to be inversely associated with BMD, while valine was consistently observed to be positively associated with BMD. Inconsistent associations with BMD was observed for leucine. With advances in metabolomics technology, an increasing number of metabolites associated with BMD have been identified. Two of these metabolites, namely valine and glycine, were consistently associated with BMD, highlighting their potential for clinical application in osteoporosis. International collaboration with a larger population to conduct clinical studies on these metabolites is warranted. On the other hand, given that metabolomics could be affected by genetics and environmental factors, whether the inconsistent association of the metabolites with BMD is due to the interaction between metabolites and genes and/or lifestyle warrants further study.

Integrating Untargeted and Targeted Metabolomics Coupled with Pathway Analysis Reveals Muscle Disorder in Osteoporosis on Orchiectomized Mice

Most osteoporosis (OP) fracture accidents in men are due not only to a low BMD but also because of unhealthy muscle support. However, there has been a limited number of reports about how muscle metabolism is disturbed by OP in males. In this work, a pathway analysis based on metabolomic research was carried out to fill this gap. A classical orchiectomy procedure was adapted to create an OP animal model. A micro-CT and pathological section were applied for a bone and muscle phenotype assessment and a pathology analysis. UPLC-Q-TOF/MS and UPLC-QQQ-MS/MS were applied to measure metabolites in skeletal muscle samples among groups. In total, 31 significantly differential metabolites were detected by comparing healthy models and OP animals, and 7 representative metabolites among the 31 significantly differential metabolites were identified and validated experimentally by UPLC-QQQ-MS/MS (xanthine, L-phenylalanine, choline, hypoxanthine, L-tryptophan, succinic acid, and L-tyrosine). An ingenuity pathway analysis (IPA) analysis revealed significantly enriched pathways involved in inflammation, oxidative stress, and necrosis. To our best knowledge, this is the first study to investigate early muscle disorder processes in Cases of OP at a metabolic level, facilitating early intervention and protection from OP fractures for aged men.

Bifidobacterium lactis Probio-M8 improves bone metabolism in patients with postmenopausal osteoporosis, possibly by modulating the gut microbiota

PURPOSE

Postmenopausal osteoporosis (PMO) is usually managed by conventional drug treatment. However, prolonged use of these drugs cause side effects. Gut microbiota may be a potential target for treatment of PMO. This work was a three-month intervention trial aiming to evaluate the added effect of probiotics as adjunctive treatment for PMO.

METHODS

Forty patients with PMO were randomized into probiotic (n = 20; received Bifidobacterium animalis subsp. lactis Probio-M8 [Probio-M8], calcium, calcitriol) and placebo (n = 20; received placebo material, calcium, calcitriol) groups. The bone mineral density of patients was measured at month 0 (0 M; baseline) and month 3 (3 M; after three-month intervention). Blood and fecal samples were collected 0 M and 3 M. Only 15 and 12 patients from Probio-M8 and placebo groups, respectively, provided complete fecal samples for gut microbiota analysis.

RESULTS

No significant change was observed in the bone mineral density of patients at 3 M. Co-administering Probio-M8 improved the bone metabolism, reflected by an increased vitamin D3 level and decreased PTH and procalcitonin levels in serum at 3 M. Fecal metagenomic analysis revealed modest changes in the gut microbiome in both groups at 3 M. Interestingly, Probio-M8 co-administration affected the gut microbial interactive correlation network, particularly the short-chain fatty acid-producing bacteria. Probio-M8 co-administration significantly increased genes encoding some carbohydrate metabolism pathways (including ABC transporters, the phosphotransferase system, and fructose and mannose metabolism) and a choline-phosphate cytidylyltransferase.

CONCLUSIONS

Co-administering Probio-M8 with conventional drugs/supplements was more efficacious than conventional drugs/supplements alone in managing PMO. Our study shed insights into the beneficial mechanism of probiotic adjunctive treatment.

REGISTRATION NUMBER OF CLINICAL TRIAL

Chinese Clinical Trial Registry (identifier number: ChiCTR1800019268).

Facile synthesis of curcumin-containing poly(amidoamine) dendrimers as pH-responsive delivery system for osteoporosis treatment

Osteoporosis is an age-related metabolic disease of bone, resulting in bone pain and even bone fragility and brittle fracture. Inhibiting overactive osteoclasts while promoting osteoblast activity is an ideal way to treat osteoporosis. Previous studies have demonstrated that natural compounds, such as curcumin (Cur) have dual roles both in promoting bone formation and inhibiting bone resorption, making them promising candidates for osteoporosis treatment. However, their poor water solubility, high dosage of curative effect and significant toxicity to other organs have largely limited their clinical translations. In this study, a novel method was reported to conjugate Cur and poly(amidoamine) dendrimers (PAD) using hexachlorocyclotriphosphazene (HCCP) as the linkage through a one-pot reaction, forming stable and uniform Cur loaded nanospheres (HCCP-Cur-PAD, HCP NPs). Owing to the hydrophilicity of PAD and hydrophobicity of Cur, HCP NPs can self-assemble into nanoparticles with particle size of 138.8 ± 78.7 nm and display excellent water dispersity. The loading capacity of Cur can reach 27.2% and it can be released from HCP NPs with pH-responsiveness. In vitro experimental results demonstrated that the HCP NPs entered lysosomes by endocytosis and proved dual anti-osteoporosis effects of inhibiting osteoclasts and promoting osteoblasts.

PPI-Induced Changes in Plasma Metabolite Levels Influence Total Hip Bone Mineral Density in a UK Cohort

Proton pump inhibitors (PPIs) are among the most used drugs in the UK. PPI use has been associated with decreased bone mineral density (BMD) and increased fracture risk, although these results have been inconsistent. We hypothesized that PPI could modulate BMD by altering gut and/or host systemic metabolic environments. Using data from more than 5000 British male and female individuals, we confirmed that PPI use is associated with decreased lumbar spine and total hip BMD. This effect was not mediated through the gut microbiome. We suggest here that PPI use may influence total hip BMD, both directly and indirectly, via plasma metabolites involved in the sex hormone pathway. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Untargeted metabolomics reveals the effect of rearing systems on bone quality parameters in chickens

The objective of this study was to investigate the effects of rearing systems on the bone quality parameters in chickens using a metabolomics strategy. A total of 419 male one-day-old chicks were randomly allocated to two groups, a floor rearing group (FRG, n = 173) and a cage rearing group (CRG, n = 246). At 6, 8, 10, and 12 weeks of age, all chickens were radiographed by a digital X-ray machine, and body weight was recorded. At 12 weeks of age, 12 birds were selected from each group to obtain tibia and femur, and bone quality parameters of bone mineral density (BMD), mineral content (BMC), breaking strength (BBS), stiffness, Young's modulus (YM), ash content, calcium content, and phosphorus content were determined. An untargeted metabolomics assay was performed to identify changes in the serum metabolic profile (n = 8 birds/group). The results showed that cage-reared chickens had wider tibiae and greater body weight compared with floor-reared chickens. There were no significant differences in BMC or BBS between the two groups (p > 0.05), but BMD, ash content, calcium content, and phosphorus content of the tibia and femur of FRG were significantly higher than those of CRG (p < 0.05). Greater stiffness and YM of the femur were also observed in birds raised in the FRG compared with those raised in the CRG (p < 0.05). Taken together, the results suggest that rearing systems affected bone quality parameters. Furthermore, 148 and 149 differential metabolites were identified in positive and negative ion modes by LC-MS/MS analysis, among which 257 metabolites were significantly correlated with 16 bone quality parameters, including leucine, myristoleic acid, glycocholic acid, and N-phenylacetamide. KEGG analysis indicated that 15 metabolic pathways, including six pathways of amino acid metabolism, two pathways of lipid metabolism, and two pathways of carbohydrate metabolism, were responsible for bone quality. Overall, the present study demonstrated the effect of rearing systems on bone quality parameters, and identified several metabolites and metabolic pathways associated with bone quality parameters.

Lipidomics Profiling of Patients with Low Bone Mineral Density (LBMD)

The relationship between lipid metabolism and bone mineral density (BMD) is still not fully elucidated. Despite the presence of investigations using osteoporotic animal models, clinical studies in humans are limited. In this work, untargeted lipidomics profiling using liquid chromatography-mass spectrometry (LC-MS) analysis of human serum samples was performed to identify the lipidomics profile associated with low bone mineral density (LBMD), with a subsequent examination of potential biomarkers related to OP risk prediction or progression. A total of 69 participants were recruited for this cohort study, including the osteoporotic group (OP, n = 25), osteopenia group (ON, n = 22), and control (Ctrl, n = 22). The LBMD group included OP and ON patients. The lipidomics effect of confounding factors such as age, gender, lipid profile, body mass index (BMD), chronic diseases, and medications was excluded from the dataset. The results showed a clear group separation and clustering between LBMD and Ctrl (Q² = 0.944, R² = 0.991), indicating a significant difference in the lipids profile. In addition, 322 putatively identified lipid molecules were dysregulated, with 163 up- and 159 down-regulated in LBMD, compared with the Ctrl. The most significantly dysregulated subclasses were phosphatidylcholines (PC) (n = 81, 25.16% of all dysregulated lipids 322), followed by triacylglycerol (TG) (n = 65, 20.19%), and then phosphatidylethanolamine (PE) (n = 40, 12.42%). In addition, groups of glycerophospholipids, including LPC (7.45%), LPE (5.59%), and PI (2.48%) were also dysregulated as of LBMD. These findings provide insights into the lipidomics alteration involved in bone remodeling and LBMD. and may drive the development of therapeutic targets and nutritional strategies for OP management.

Applications of Metabolomics in Calcium Metabolism Disorders in Humans

The pathogenesis of the disorders of calcium metabolism is not fully understood. This review discusses the studies in which metabolomics was applied in this area. Indeed, metabolomics could play an essential role in discovering biomarkers and elucidating pathological mechanisms. Despite the limited bibliography, the present review highlights the potential of metabolomics in identifying the biomarkers of some of the most common endocrine disorders, such as primary hyperparathyroidism (PHPT), secondary hyperparathyroidism (SHPT), calcium deficiency, osteoporosis and vitamin D supplementation. Metabolites related to above-mentioned diseorders were grouped into specific classes and mapped into metabolic pathways. Furthermore, disturbed metabolic pathways can open up new directions for the in-depth exploration of the basic mechanisms of these diseases at the molecular level.

Proteomics Profiling of Osteoporosis and Osteopenia Patients and Associated Network Analysis

Bone mass reduction due to an imbalance in osteogenesis and osteolysis is characterized by low bone mineral density (LBMD) and is clinically classified as osteopenia (ON) or osteoporosis (OP), which is more severe. Multiple biomarkers for diagnosing OP and its progression have been reported; however, most of these lack specificity. This cohort study aimed to investigate sensitive and specific LBMD-associated protein biomarkers in patients diagnosed with ON and OP. A label-free liquid chromatography-mass spectrometry (LC-MS) proteomics approach was used to analyze serum samples. Patients’ proteomics profiles were filtered for potential confounding effects, such as age, sex, chronic diseases, and medication. A distinctive proteomics profile between the control, ON, and OP groups (Q² = 0.7295, R² = 0.9180) was identified, and significant dysregulation in a panel of proteins (n = 20) was common among the three groups. A comparison of these proteins showed that the levels of eight proteins were upregulated in ON, compared to those in the control and the OP groups, while the levels of eleven proteins were downregulated in the ON group compared to those in the control group. Interestingly, only one protein, myosin heavy chain 14 (MYH14), showed a linear increase from the control to the ON group, with the highest abundance in the OP group. A significant separation in the proteomics profile between the ON and OP groups (Q² = 0.8760, R² = 0.991) was also noted. Furthermore, a total of twenty-six proteins were found to be dysregulated between the ON and the OP groups, with fourteen upregulated and twelve downregulated proteins in the OP, compared to that in the ON group. Most of the identified dysregulated proteins were immunoglobulins, complement proteins, cytoskeletal proteins, coagulation factors, and various enzymes. Of these identified proteins, the highest area under the curve (AUC) in the receiver operating characteristic (ROC) analysis was related to three proteins (immunoglobulin Lambda constant 1 (IGLC1), RNA binding protein (MEX3B), and fibulin 1 (FBLN1)). Multiple reaction monitoring (MRM), LC-MS, was used to validate some of the identified proteins. A network pathway analysis of the differentially abundant proteins demonstrated dysregulation of inflammatory signaling pathways in the LBMD patients, including the tumor necrosis factor (TNF), toll-like receptor (TL4), and interferon-γ (IFNG) signaling pathways. These results reveal the existence of potentially sensitive protein biomarkers that could be used in further investigations of bone health and OP progression.

GCTOF-MS Combined LC-QTRAP-MS/MS Reveals Metabolic Difference Between Osteoarthritis and Osteoporotic Osteoarthritis and the Intervention Effect of Erxian Decoction

PURPOSE

OP and OA are chronic bone diseases with high incidence in the middle-aged and elderly populations. The latest research shows that the pathological environment of OP may be involved in the aggravation of the pathological process of OA, and the pathological state of OP plays an important role in the aggravation of OA pathology. EXD is a traditional Chinese medicine decoction that has been used to treat osteoporosis. Therefore, we further study whether OA will be aggravated in the OP environment and whether EXD can alleviate OA by intervening in the OP environment. The purpose of this study was to analyze the effect of OP on OA metabolites by using metabolomic methods and to explore the intervention mechanism of EXD on osteoporotic OA.

METHOD

Thirty-two SD rats were randomly divided into normal group, OA group, OP-OA group, and EXD group. EXD was administered by gavage. Histopathological evaluation of cartilage tissue was performed using Saffron fast green and HE staining. Western blot and qRT-PCR were used to detect the expression levels of chondrogenesis genes SOX9, COL2A1, and COMP in cartilage tissue. GC-TOFMS and LC-QTRAP-MS/MS metabolomics methods were used to analyze the changes of metabolites in serum samples of rats in each group.

RESULT

The slice results showed that the cartilage damage in the OP-OA group was more serious than that in the OA group, which was significantly relieved after EXD intervention, indicating that the cartilage damage in the OP-OA group was more severe than that in the OA group and further reduced the protein and gene expressions of cartilage markers SOX9, COL2A1, and COMP. Thirty-seven substances were identified, and gentiopicroside, emodin, quercetin, and diosmetin were analyzed as possible active components of EXD. EXD treatment significantly reduced cartilage damage and reversed the expression of these markers. Metabolomics showed that EXD attenuated cartilage destruction by modulating the expression of cystine, chenodeoxycholate, and D-Turanose, involving glycolysis/gluconeogenesis, pantothenate, and CoA biosynthesis metabolic pathways.

CONCLUSION

The OP environment may promote the progression of OA through metabolic factors. The benign intervention of EXD in osteoporotic OA involves cystine, chenodeoxycholate, and D-Turanose, and their associated glycolysis/gluconeogenesis, pantothenate, and CoA biosynthesis metabolic pathways. Therefore, we have a deep understanding of the metabolic-related intervention of EXD in osteoporotic OA and are eager to better understand the mechanism of multi-targeted intervention of EXD in bone metabolic lesions.

Application of metabolomics in osteoporosis research

Osteoporosis (OP) is a systemic disease characterized by bone metabolism imbalance and bone microstructure destruction, which causes serious social and economic burden. At present, the diagnosis and treatment of OP mainly rely on imaging combined with drugs. However, the existing pathogenic mechanisms, diagnosis and treatment strategies for OP are not clear and effective enough, and the disease progression that cannot reflect OP further restricts its effective treatment. The application of metabolomics has facilitated the study of OP, further exploring the mechanism and behavior of bone cells, prevention, and treatment of the disease from various metabolic perspectives, finally realizing the possibility of a holistic approach. In this review, we focus on the application of metabolomics in OP research, especially the newer systematic application of metabolomics and treatment with herbal medicine and their extracts. In addition, the prospects of clinical transformation in related fields are also discussed. The aim of this study is to highlight the use of metabolomics in OP research, especially in exploring the pathogenesis of OP and the therapeutic mechanisms of natural herbal medicine, for the benefit of interdisciplinary researchers including clinicians, biologists, and materials engineers.