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

The association of lipids and novel non-statin lipid-lowering drug target with osteoporosis: evidence from genetic correlations and Mendelian randomization

BACKGROUND

It remains controversial whether lipids affect osteoporosis (OP) or bone mineral density (BMD), and causality has not been established. This study aimed to investigate the genetic associations between lipids, novel non-statin lipid-lowering drug target genes, and OP and BMD.

METHODS

Mendelian randomization (MR) method was used to explore the genetic associations between 179 lipid species and OP, BMD. Drug-target MR analysis was used to explore the causal associations between angiopoietin-like protein 3 (ANGPTL3) and apolipoprotein C3 (APOC3) inhibitors on BMD.

RESULTS

The IVW results with Bonferroni correction indicated that triglyceride (TG) (51:3) (OR = 1.0029; 95% CI: 1.0014-1.0045; P = 0.0002) and TG (56:6) (OR = 1.0021; 95% CI: 1.0008-1.0033; P = 0.0011) were associated with an increased risk of OP; TG (51:2) (OR = 0.9543; 95% CI: 0.9148-0.9954; P = 0.0298) was associated with decreased BMD; and ANGPTL3 inhibitor (OR = 1.1342; 95% CI: 1.0393-1.2290; P = 0.0093) and APOC3 inhibitor (OR = 1.0506; 95% CI: 1.0155-1.0857; P = 0.0058) was associated with increased BMD.

CONCLUSIONS

MR analysis indicated causal associations between genetically predicted TGs and OP and BMD. Drug-target MR analysis showed that ANGPTL3 and APOC3 have the potential to serve as novel non-statin lipid-lowering drug targets to treat or prevent OP.

Serum metabolomics and 16S rRNA amplicon sequencing reveal the role of puerarin in alleviating bone loss aggravated by antidiabetic agent pioglitazone in type 2 diabetic mice

ETHNOPHARMACOLOGICAL RELEVANCE

Pioglitazone (PIO) was an anti type 2 diabetes (T2D) agent but caused bone loss and bone marrow fat accumulation. Puerarin (PUE) was a natural component of herbal medicine extracted from Pueraria lobata (Willd.) Ohwi and reduced glycemia and improved bone mass as a supplementary drug. A combination of PIO and PUE might be good for maintaining bone mass and blood glucose.

AIM OF THE STUDY

We aimed to elucidate the potential correlation and underlying mechanisms of dietary supplement PUE in reducing side effects caused by PIO.

MATERIALS AND METHODS

In vitro, alkaline phosphatase (ALP) staining, alizarin S (ARS) staining and qRT-PCR were performed to detect the osteogenesis activity in MC3T3-E1 cells. In vivo, we established the T2D model by treating C57BL6/J mice with high-fat diets and streptozotocin (STZ). Micro-CT, hematoxylin and eosin (H&E) staining and tartrate-resistant acid phosphatase (TRAcP) staining were performed to observe the difference in skeletal phenotype. Serum metabolomics and 16S rRNA amplicon sequencing were applied to analyze the potential effect of the combination of PIO and PUE.

RESULTS

We showed that the PUE could increase ALP activity and mineralization nodes of MC3T3-E1 with PIO. PIO could aggravate bone loss but PUE alleviated the effect caused by PIO in T2D mice. PUE promoted alpha-linolenic acid metabolism and glycerophospholipid metabolism, and affected the alpha diversity of the gut microbiome by regulating the genera of Alloprevotella, Fusobacterium, Rodentibacter, etc. Correlation analysis indicated that sphingosine-1-phosphate, nonadecylic acid, and margaric acid were associated with the effect of PUE.

CONCLUSIONS

Taken together, we demonstrated that PIO combined with PUE was able to lower blood sugar levels without causing bone loss. The effect of PUE mainly correlated with the genua of Alloprevotella, Fusobacterium, Rodentibacter, and Alistipes. Also, alpha-linolenic acid metabolism and glycerophospholipid metabolism were major targets of PUE.

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.

Comprehensive Metabolomic Profiling in Adults with X-Linked Hypophosphatemia: A Case-Control Study

BACKGROUND

X-linked hypophosphatemia (XLH) is a rare disorder characterized by elevated levels of fibroblast growth factor 23 (FGF-23), leading to hypophosphatemia and complications in diagnosis due to its clinical heterogeneity. Metabolomic analysis, which examines metabolites as the final products of cellular processes, is a powerful tool for identifying in vivo biochemical changes, serving as biomarkers of pathological abnormalities, and revealing previously uncharted metabolic pathways.

METHODS

A multicenter cross-sectional case-control study of adult patients diagnosed with XLH was conducted. Serum metabolomic analysis was performed with an Ultra-Performance Liquid Chromatography equipment (UPLC) coupled to a high-resolution mass spectrometer (MS). An analysis of metabolic pathways using MetaboAnalyst version 5.0 and a quantitative enrichment analysis (QEA) was performed. We employed multivariate statistical models, including a principal component analysis (PCA) and an orthogonal partial least squares discriminant analysis (OPLS-DA) regression model.

RESULTS

A cohort of 20 XLH patients and 19 control subjects were recruited. A total of 104 metabolites were identified. The differential metabolites identified included glycine, taurine, hypotaurine, phosphoethanolamine, pyruvate, guanidoacetic acid, serine, succinate, 2-aminobutyric acid, glutamine, 2-hydroxyvaleric acid, methionine, ornithine, phosphorylcholine, hypoxanthine, lysine, and N-methylnicotinamide. Enrichment analysis identified disturbances in key metabolic pathways, including phosphatidylethanolamine biosynthesis, sphingolipid metabolism, and phosphatidylcholine biosynthesis. Additionally, pathways related to cysteine metabolism, glycolysis, and pyruvate metabolism.

CONCLUSIONS

This study identified significant differences in the metabolic profiles of individuals with XLH compared to healthy controls. These findings enhance understanding of potential pathogenic mechanisms and offer a metabolic basis for further in-depth investigations into XLH.

Integrated metabolomics and microbiome analysis reveal blended oil diet improves meat quality of broiler chickens by modulating flavor and gut microbiota

This study was to evaluate the effects of different dietary oils in chicken diets on meat quality, lipid metabolites, the composition of volatile compounds, and gut microbiota. Nine hundred female 817 crossbred broilers at one day old with an average body weight of 43.56 ± 0.03 g were randomly divided into five treatments, each consisting of 6 replicates of 30 birds. The control group received soybean oil (SO); other groups received diets supplemented with rice bran oil (RO), lard (LO), poultry fat (PO), and blended oil (BO), respectively. All diets were formulated as isoenergic and isonitrogenous. Compared with SO, RO decreased ADG and 42 d BW (P < 0.05). Compared with the RO, BO increased ADG and 42 d BW and decreased FCR (P < 0.05). Compared with SO, BO increased 24 h redness (a∗) value and reduced the malondialdehyde concentration (P < 0.05), and further improved drip loss of breast muscle (P > 0.05). The proportions of C18:0 and saturated fatty acid were the highest in LO, and the proportions of C16:1, C18:1, and monounsaturated fatty acids were the highest in BO. The content of C18:2, C18:3, and polyunsaturated fatty acids were the highest in SO. The contents of glyceryl triglycerides and total esters in BO were significantly higher than those in the SO and LO group (P < 0.05). There was a substantial increment in the relative abundance of peroxisome proliferator activated receptor alpha (PPARα), acyl-CoA oxidase 1 (ACOX1), and carnitine palmitoyl-transferase 1 (CPT1A) transcripts in breast of chickens fed BO (P < 0.05). Further, dietary BO increased the relative cecal abundance of Firmicutes phylum, Ruminococcus_torques and Christensenellaceae _R-7 genera, and decreased that of Campylobacterota, Proteobacteria, and Phascolarctobacterium (P < 0.05). Genera g_Lactobacillus and Christensenellaceae _R-7 may mainly be involved in the formation of volatile flavor compounds in breast muscle. In conclusion, dietary BO improved the flavor of chickens by increasing the concentration of triglycerides and volatile flavor compounds, improving gut microbiota structure, and suppressing lipid oxidation. The potential positive effects of BO may be associated with the regulation of lipid metabolism.

The association between metabolite profiles and impaired bone microstructure in adult growth hormone deficient rats

BACKGROUND

Adult growth hormone deficiency (AGHD) is associated with an increased risk of fractures and impaired bone microstructure. Understanding the metabolic changes accompanying bone deterioration in AGHD might provide insights into mechanisms behind molecular changes and develop new biomarkers or nutritional strategies for bone destruction. Our study aimed to investigate the association between altered metabolite patterns and impaired bone microstructure in adult rats with growth hormone deficiency.

METHODS

Thirty seven-week-aged adult Lewis dwarf homozygous (dw/dw) rats (five females and five males), and adult Lewis dwarf heterozygous (dw/ +) rats (five females and five males) rats were compared. Micro-computed tomography (Micro-CT) was used to examine the bone's microstructure. Hematoxylin and eosin (H&E) staining were used to quantify the histological characteristics. Liquid chromatography-mass spectrometry untargeted serum metabolomic analysis was applied in the study. ELISA was used to measure serum bone turnover markers and IGF-1 levels.

RESULTS

Adult dw/dw rats exhibited great reductions in trabecular volume bone density (Tb.vBMD), bone volume/total volume (BV/TV), and cortical thickness (Ct. Th) compared with adult dw/ + rats (all p values < 0.05), indicating significant impairment in bone microstructure. The serum metabolite profiles revealed substantial differences between the dw/dw rats and dw/ + rats. A total of 134 differential metabolites in positive ion mode and 49 differential metabolites in negative mode were identified. Five metabolites, including Lysophosphatidylcholine(LPC) 20:3, LPC22:6, LPC22:4, cortisol and histamine levels were upregulated in dw/dw rats. The steroid hormone biosynthesis and bile secretion pathways were the main perturbed metabolic pathways. There were significant associations between differential metabolites and the impaired bone microstructure parameters, indicating that the selected metabolites might serve as potential biomarkers for deteriorated bone microstructure in AGHD.

CONCLUSION

Adult dw/dw rats exhibit impaired bone microstructure and distinct serum metabolic profiles, and the altered metabolites were significantly associated with bone microstructure destruction. This provides a new insight into understanding the mechanism of bone deterioration in AGHD patients from a metabolic perspective.

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.

New insight into primary hyperparathyroidism using untargeted metabolomics

Primary Hyperparathyroidism (PHPT) is characterized by excessive parathormone (PTH) secretion and disrupted calcium homeostasis. Untargeted metabolomics offers a valuable approach to understanding the complex metabolic alterations associated with different diseases, including PHPT. Plasma untargeted metabolomics was applied to investigate the metabolic profiles of PHPT patients compared to a control group. Two complementary liquid-phase separation techniques were employed to comprehensively explore the metabolic landscape in this retrospective, single-center study. The study comprised 28 female patients diagnosed following the current guidelines of PHPT diagnosis and a group of 30 healthy females as a control group. To evaluate their association with PHPT, we identified changes in plasma metabolic profiles in patients with PHPT compared to the control group. The primary outcome measure included detecting plasma metabolites and discriminating PHPT patients from controls. The study unveiled specific metabolic imbalances that may link L-amino acids with peptic ulcer disease, gamma-glutamyls with oxidative stress, and asymmetric dimethylarginine (ADMA) with cardiovascular complications. Several metabolites, such as gamma-glutamyls, caffeine, sex hormones, carnitine, sphingosine-1-phosphate (S-1-P), and steroids, were connected with reduced bone mineral density (BMD). Metabolic profiling identified distinct metabolic patterns between patients with PHPT and healthy controls. These findings provided valuable insights into the pathophysiology of PHPT.

Lipidomics analysis of bone marrow in a mouse model of postmenopausal osteoporosis

Postmenopausal osteoporosis (PMOP) is a major public health problem worldwide, afflicting many postmenopausal women. Although many studies have focused on the biological role of individual lipids in osteoporosis, no studies have systematically elucidated the lipid profile of osteoporosis. In this study, liquid chromatography-tandem mass spectrometry (LC-MS/MS) technology based on multiple reaction monitoring (MRM) method was used to compare the levels of lipid molecules in bone marrow cells of osteoporotic mice (OVX) group and sham-operation (Sham) group. Principal component analysis (PCA) was used for multivariate statistics. Differential lipids were obtained by bar graph, heatmap and volcano map. A total of 400 lipid molecules were identified. A total of 199 lipid molecules were identified to be associated with PMOP, including 6 phospholipids and 3 sphingolipids. These differential lipid molecules provide a systematic lipid profile for osteoporosis, which helps to discover new candidate osteoporosis biomarkers, and their changes at the molecular level can be used as new targets for diagnosis or prevention.

MRI-based vertebral bone quality score in cervical ossification of the posterior longitudinal ligament: a comparison with cervical spondylotic myelopathy using propensity score matching

BACKGROUND

Bone mineral density plays a key role in the assessment of operative instrumentation complications and clinical outcomes. The MRI-based vertebral bone quality (VBQ) score has been introduced as a novel marker of bone quality. However, few studies have investigated the relationship between VBQ score and patients associated with cervical ossification of the posterior longitudinal ligament (OPLL).

PURPOSE

The aims of the study were (1) to reveal bone mineral density between cervical OPLL and cervical spondylotic myelopathy (CSM) group by VBQ score, (2) to compare the VBQ score of cervical OPLL between male and female group, (3) to explore the relationship between segmental VBQ scores associated with OPLL.

STUDY DESIGN

Retrospective cohort study.

PATIENT SAMPLE

Consecutive series of 425 patients at a single academic institution.

OUTCOME MEASURES

MRI based measurements of C2-C7 VBQ scores.

METHODS

Preoperative noncontrast T1-weighted MRIs of the cervical spine was used to measure the VBQ score. The VBQ score was defined as the mean value of the signal intensity of the vertebrae divided by that of the cerebrospinal fluid (CSF) space at the cisterna magna. Patients with cervical OPLL and CSM were matched based on age, sex, body mass index (BMI), comorbidity, medication history, diet habit, smoking, alcohol consumption via propensity score matching (PSM). Normality of each VBQ score was tested by the Shapiro-Wilk test. Wilcoxon's rank-sum test was used to compare matched cohorts. Kruskal-Wallis test was performed to compare the VBQ scores between segments. Multivariate logistic regression analysis was used to evaluate factors associated with the development of cervical OPLL.

RESULTS

A total of 425 patients were assessed. For final analysis, 135 paired patients were compared between the cervical OPLL and CSM groups, and 22 paired patients were compared between male and female group associated with cervical OPLL. There were no statistically significant differences in age, sex, BMI, comorbidity, medication history, diet habit, smoking, alcohol between the matched cohorts. OPLL group was associated with lower VBQ score compared with CSM group at C3, while there were no differences in VBQ score for the other levels between the two groups. There were no differences between male and female group associated with OPLL in C2-C7 VBQ scores. VBQ scores of cervical OPLL are variable between segments, with significantly lower scores at C6, C7 compared with C1-C5. Multivariate logistic regression analysis showed that BMI was correlated with the development of OPLL (regression coefficient, 0.162; 95% confidence interval, 0.010-0.037). Additional risk factors included hypertension, calcium supple history and smoking.

CONCLUSIONS

This study demonstrates that cervical OPLL is associated with lower VBQ score at C3, with no differences for the other levels when compared with CSM derived from measurements on MRI. No differences were found between male and female group associated with OPLL in C2-C7 VBQ scores. Cervical OPLL were found to have smaller VBQ score at C6, C7 compared with C1-C5. Our findings provide new insight for bone density assessment in cervical OPLL patient.

Obesity and lipid metabolism in the development of osteoporosis (Review)

Osteoporosis is a common bone metabolic disease that causes a heavy social burden and seriously threatens life. Improving osteogenic capacity is necessary to correct bone mass loss in the treatment of osteoporosis. Osteoblasts are derived from the differentiation of bone marrow mesenchymal stem cells, a process that opposes adipogenic differentiation. The peroxisome proliferator‑activated receptor γ and Wnt/β‑catenin signaling pathways mediate the mutual regulation of osteogenesis and adipogenesis. Lipid substances play an important role in the occurrence and development of osteoporosis. The content and proportion of lipids modulate the activity of immunocytes, mainly macrophages, and the secretion of inflammatory factors, such as IL‑1, IL‑6 and TNF‑α. These inflammatory effectors increase the activity and promote the differentiation of osteoclasts, which leads to bone imbalance and stronger bone resorption. Obesity also decreases the activity of antioxidases and leads to oxidative stress, thereby inhibiting osteogenesis. The present review starts by examining the bidirectional differentiation of BM‑MSCs, describes in detail the mechanism by which lipids affect bone metabolism, and discusses the regulatory role of inflammation and oxidative stress in this process. The review concludes that a reasonable adjustment of the content and proportion of lipids, and the alleviation of inflammatory storms and oxidative damage induced by lipid imbalances, will improve bone mass and treat osteoporosis.

The bone marrow lipidomics of mice reveal sex-related differences

Osteoporosis is a common skeletal disorder characterized by an imbalance between bone resorption and formation, exhibiting a higher prevalence in women compared with men. While previous studies have primarily focused on genomics and genetics in osteoporosis susceptibility, there is a lack of systematic exploration of sex-specific differences in lipid levels in mouse bone marrow. Multiple reaction monitoring-based liquid chromatography-trandem mass spectrometry (LC-MS/MS) was used to quantify lipidomic profiles in bone marrow samples from three female mice and three male mice. The LC-MS/MS technique based on the multiple reaction monitoring method identified and quantified 184 lipids from 15 lipid classes. The contents of most lipids in the bone marrow cells of female mice were higher than those in male mice, including four polyunsaturated fatty acids, three phospholipids and four sphingolipids. Among all the lipid molecules, lactosylceramide (d18:0/16:0) showed the highest fold change in female mice, while its precursor lipid, glucosylceramide, was the most up-regulated in male mice. This study, focusing on bone marrow lipidomics, elucidates significant sexual dimorphism in lipid levels within bone marrow cells. It provides novel evidence supporting the higher prevalence of osteoporosis in women and enhances our understanding of the connection between sex-specific lipid levels and the risk of osteoporosis.

Relationship between polymorphisms and mutations at rs7125942 and rs3736228 of LRP5 gene and bone metabolism in postmenopausal women

OBJECTIVE

To analyze the relationship between the polymorphism and mutation of rs7125942 and rs3736228 locus in the low-density lipoprotein receptor-related protein 5 (LRP5) genotype and bone mineral density (BMD) in postmenopausal women in Xinjiang, China, to provide a basis for prevention and treatment of the disease.

METHODS

According to the results of dual-energy X-ray (DEXA) determination of BMD, the 136 subjects were divided into three groups: Group A: normal bone mass, Group B: osteopenia, Group C: osteoporosis. 1. Age, body, mass index (BMI), and menopause of all subjects were recorded. 2. Fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), calcium (Ca), phosphorus (P), alkaline phosphatase (ALP), and clinical biochemical data were determined. 3. LRP5 locus polymorphisms were determined by time-of-flight mass spectrometry.

RESULTS

1. Compared with group A, the age, ALP, Cr, and BUN levels in group B and group C were increased, but UA levels were lower (P < 0.05), and Serum P was higher in the group C (P < 0.05). 2. There was no statistically significant difference in the prevalence of diabetes between the three groups (P > 0.05). 3. The ROC curves for different BMD sites such as L1, L2, L3, L4, L total, and femoral neck were 0.929, 0.955, 0.901, 0.914, 0.885, and 0.873 (P < 0.01). 4. At rs7125942 locus, there was statistically significant difference in the distribution of wild-type (CC) and mutant (CG) with the normal bone mass (NBM) group and the abnormal bone mass (ABM) group (P < 0.05). 5. At rs7125942 locus, compared with wild-type (CC), mutant (CG) had lower LDL and FPG in NBM group (P < 0.05), and lower serum ALP in the ABM group (P < 0.05). At rs3736228 locus, the BMD (Femoral neck) of mutant (CT/TT) was lower than that of wild-type (CC) in the NBM group (P < 0.05). 6. Age and menopausal years were negatively correlated with BMD of the femoral neck and L1-4 (P < 0.05), and BMI and TG were positively (P < 0.05), and the results of multiple linear regression analysis showed that age, BMI, and TG were both independent factors affecting BMD (P < 0.05).

TC and LDL-C are negatively correlated with bone mineral density in patients with osteoporosis

OBJECTIVE

To investigate the relationships of multiple lipid metabolism indicators and bone turnover markers (BTMs) with bone mineral density (BMD) and osteoporosis, in order to identify high-risk populations.

METHODS

A total of 380 patients were recruited and their general information was collected. Linear and logistic regression models were used to analyze the correlation of these indicators with BMD and osteoporosis.

RESULTS

Lipid metabolism indices and BTMs exhibited varying degrees of positive or negative correlation with BMD. Elevated levels of triglycerides (r = -0.204, P = 0.004), total cholesterol (TC) (r = -0.244, P < 0.001), low-density lipoprotein cholesterol (LDL-C) (r = -0.256, P < 0.001), apoprotein B (r = -0.292, P < 0.001) and lipoprotein-associated phospholipase A2 (Lp-PLA2) (r = -0.221, P = 0.002) in women were associated with a reduction in BMD. This relationship persisted even after adjusting for confounding factors and in the subgroup analysis of elderly women. In males, TC (r = 0.159, P = 0.033), LDL-C (r = 0.187, P = 0.012), apoprotein B (r = 0.157, P = 0.035), and Lp-PLA2 (r = 0.168, P = 0.024) exhibited a positive correlation with BMD, while free fatty acid (FFA) (r = -0.153, P = 0.041) was negatively correlated with BMD. However, after adjusting for confounding factors, only FFA remained negatively correlated with BMD, which was not observed in the age subgroup analysis. Furthermore, elevated levels of TC and LDL-C in elderly women were positively associated with the risk of osteoporosis or low bone mass.

CONCLUSION

Elevated levels of TC and LDL-C not only indicate a decrease in BMD in females but also positively correlate with the occurrence of osteoporosis and low bone mass in elderly females.

Consequences of Aging on Bone

With the aging of the global population, the incidence of musculoskeletal diseases has been increasing, seriously affecting people's health. As people age, the microenvironment within skeleton favors bone resorption and inhibits bone formation, accompanied by bone marrow fat accumulation and multiple cellular senescence. Specifically, skeletal stem/stromal cells (SSCs) during aging tend to undergo adipogenesis rather than osteogenesis. Meanwhile, osteoblasts, as well as osteocytes, showed increased apoptosis, decreased quantity, and multiple functional limitations including impaired mechanical sensing, intercellular modulation, and exosome secretion. Also, the bone resorption function of macrophage-lineage cells (including osteoclasts and preosteoclasts) was significantly enhanced, as well as impaired vascularization and innervation. In this study, we systematically reviewed the effect of aging on bone and the within microenvironment (including skeletal cells as well as their intracellular structure variations, vascular structures, innervation, marrow fat distribution, and lymphatic system) caused by aging, and mechanisms of osteoimmune regulation of the bone environment in the aging state, and the causal relationship with multiple musculoskeletal diseases in addition with their potential therapeutic strategy.

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.

Mediating role of host metabolites in strontium's effect on osteoporosis among older individuals: Findings from Wuhan, China

Strontium is receiving widespread attention due to its remarkable biological qualities in preventing bone resorption and fostering osteogenesis. However, the chemical processes behind strontium's dual activities on bone cells are not yet fully understood. This study used the metabolomic technique to identify and examine potential biomarkers between strontium exposure and osteoporosis (OP) risk. A total of 806 participants were recruited for the detection of plasma strontium content via inductively coupled plasma-mass spectrometry. Plasma metabolites were profiled in 254 participants through an untargeted metabolomics technique. Generalized linear models were primarily used to analyze associations among plasma strontium, metabolites, and OP. The mediating effects of metabolites on the strontium-OP association were further investigated. A total of 31 differential metabolites were observed, 10 of which were upregulated and 21 were downregulated in the OP group compared with the non-OP group. Five metabolites (3-phenoxybenzoic acid, Cer (t18:0/16:1), HexCer(t16:1/12:1(2OH)), HexCer(t14:2/18:1(2OH)), and TG(16:0-18:1-24:4)) were selected as potential mediators based on their significant association with OP risk and with femoral neck and lumbar spine bone mineral density (BMD). Moreover, all except TG(16:0-18:1-24:4) were involved in the OP discrimination model with excellent power combined with several traditional variables. 3-Phenoxybenzoic acid and Cer(t18:0/16:1) had significant indirect effects on the strontium-OP association. The five candidate metabolites mediated 83.79 % of the strontium-OP association. Plasma strontium level was associated with reduced OP risk in the Han population in Wuhan. Thus, plasma metabolite profiling revealed five BMD/OP-associated metabolites that acted as mediators in the strontium-OP association. Our findings provided evidence of the mediating role of host plasma metabolites in strontium's effect on OP pathology.

Mendelian Randomization Study of Lipid Metabolites Reveals Causal Associations with Heel Bone Mineral Density

BACKGROUND

Osteoporosis, which is a bone disease, is characterized by low bone mineral density and an increased risk of fractures. The heel bone mineral density is often used as a representative measure of overall bone mineral density. Lipid metabolism, which includes processes such as fatty acid metabolism, glycerol metabolism, inositol metabolism, bile acid metabolism, carnitine metabolism, ketone body metabolism, sterol and steroid metabolism, etc., may have an impact on changes in bone mineral density. While some studies have reported correlations between lipid metabolism and heel bone mineral density, the overall causal relationship between metabolites and heel bone mineral density remains unclear.

OBJECTIVE

to investigate the causal relationship between lipid metabolites and heel bone mineral density using two-sample Mendelian randomization analysis.

METHODS

Summary-level data from large-scale genome-wide association studies were extracted to identify genetic variants linked to lipid metabolite levels. These genetic variants were subsequently employed as instrumental variables in Mendelian randomization analysis to estimate the causal effects of each lipid metabolite on heel bone mineral density. Furthermore, metabolites that could potentially be influenced by causal relationships with bone mineral density were extracted from the KEGG and WikiPathways databases. The causal associations between these downstream metabolites and heel bone mineral density were then examined. Lastly, a sensitivity analysis was conducted to evaluate the robustness of the results and address potential sources of bias.

RESULTS

A total of 130 lipid metabolites were analyzed, and it was found that acetylcarnitine, propionylcarnitine, hexadecanedioate, tetradecanedioate, myo-inositol, 1-arachidonoylglycerophosphorine, 1-linoleoylglycerophoethanolamine, and epiandrosterone sulfate had a causal relationship with heel bone mineral density (p < 0.05). Furthermore, our findings also indicate an absence of causal association between the downstream metabolites associated with the aforementioned metabolites identified in the KEGG and WikiPathways databases and heel bone mineral density.

CONCLUSION

This work supports the hypothesis that lipid metabolites have an impact on bone health through demonstrating a causal relationship between specific lipid metabolites and heel bone mineral density. This study has significant implications for the development of new strategies to osteoporosis prevention and treatment.

Metabolomic profile of patients on levothyroxine treatment for hypothyroidism

Background

Hypothyroidism is clinically characterized by a decrease in levels of the circulating thyroid hormones namely thyroxine and triiodothyronine. The main treatment for hypothyroidism is thyroid hormone replacement using levothyroxine to normalize serum thyroid hormone levels.

Objectives

In this study, we explored the metabolic changes in the plasma of patients with hypothyroidism after reaching a euthyroid state with levothyroxine treatment.

Methods

Plasma samples from 18 patients diagnosed as overt hypothyroidism were collected before and after levothyroxine treatment upon reaching a euthyroid state and were analyzed by high-resolution mass spectrometry-based metabolomics. Multivariate and univariate analyses evaluated data to highlight potential metabolic biomarkers.

Results

Liquid chromatography-mass spectrometry-based metabolomics revealed a significant decrease in the levels of ceramide, phosphatidylcholine, triglycerides, acylcarnitine, and peptides after levothyroxine treatment; this could indicate a change in the fatty acid transportation system and an enhanced β-oxidation, compared with a hypothyroid state. At the same time, the decrease in the peptides suggested a shift in protein synthesis. In addition, there was a considerable rise in glycocholic acid following therapy, suggesting the involvement of thyroid hormones in stimulating bile acid production and secretion.

Conclusions

A metabolomic analysis of patients with hypothyroidism revealed significant changes in several metabolites and lipids after treatment. This study showed the value of the metabolomics technique in providing a complementary understanding of the pathophysiology of hypothyroidism and as a crucial tool for examining the molecular impact of levothyroxine treatment on hypothyroidism. It was an important tool for investigating the therapeutic effects of levothyroxine on hypothyroidism at the molecular level.

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.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

Lipids are biological molecules that play vital roles in all living organisms. They perform many cellular functions, such as 1) forming cellular and subcellular membranes, 2) storing and using energy, and 3) serving as chemical messengers during intra- and inter-cellular signal transduction. The large-scale study of the pathways and networks of cellular lipids in biological systems is called "lipidomics" and is one of the fastest-growing omics technologies of the last two decades. With state-of-the-art mass spectrometry instrumentation and sophisticated data handling, clinical studies show how human lipid composition changes in health and disease, thereby making it a valuable medium to collect for clinical applications, such as disease diagnostics, therapeutic decision-making, and drug development. This review gives a comprehensive overview of current workflows used in clinical research, from sample collection and preparation to data and clinical interpretations. This is followed by an appraisal of applications in 2022 and a perspective on the exciting future of clinical lipidomics.