Uncovering the shared lipidomic markers of subclinical osteoporosis-atherosclerosis comorbidity: The Young Finns Study

Uptake of ox-LDL by binding to LRP6 mediates oxidative stress-induced BMSCs senescence promoting obesity-related bone loss

Obesity has long been thought to be a main cause of hyperlipidemia. As a systemic disease, the impact of obesity on organs, tissues and cells is almost entirely negative. However, the relationship between obesity and bone loss is highly controversial. On the one hand, obesity has long been thought to have a positive effect on bone due to increased mechanical loading on the skeleton, conducive to increasing bone mass to accommodate the extra weight. On the other hand, obesity-related metabolic oxidative modification of low-density lipoprotein (LDL) in vivo causes a gradual increase of oxidized LDL (ox-LDL) in the bone marrow microenvironment. We have reported that low-density lipoprotein receptor-related protein 6 (LRP6) acts as a receptor of ox-LDL and mediates the bone marrow stromal cells (BMSCs) uptake of ox-LDL. We detected elevated serum ox-LDL in obese mice. We found that ox-LDL uptake by LRP6 led to an increase of intracellular reactive oxygen species (ROS) in BMSCs, and N-acetyl-L-cysteine (NAC) alleviated the cellular senescence and impairment of osteogenesis induced by ox-LDL. Moreover, LRP6 is a co-receptor of Wnt signaling. We found that LRP6 preferentially binds to ox-LDL rather than dickkopf-related protein 1 (DKK1), both inhibiting Wnt signaling and promoting BMSCs senescence. Mesoderm development LRP chaperone (MESD) overexpression inhibits ox-LDL binding to LRP6, attenuating oxidative stress and BMSCs senescence, eventually rescuing bone phenotype.

Association of Decreased Bone Density and Hyperlipidemia in a Taiwanese Older Adult Population

Objective

This study aimed to determine if a combination of 2 abnormal lipid profiles revealed a stronger association with low bone mass than a single blood lipid abnormality alone.

Methods

This study enrolled 1373 participants who had received a dual-energy x-ray absorptiometry scan from January 2016 to December 2016 in a medical center in southern Taiwan. Logistic regression was used to examine association between lipid profiles and osteopenia or osteoporosis after adjusting for covariates.

Results

Compared to people with total cholesterol (TC) < 200 mg/dL, those with TC ≥ 240 mg/dL tended to have osteopenia or osteoporosis (OR 2.61; 95% CI, 1.44-4.71). Compared to people with low-density lipoprotein cholesterol (LDL-C) < 130 mg/dL, those with LDL-C ≥ 160 mg/dL tended to develop osteopenia or osteoporosis (OR 2.13; 95% CI, 1.21-3.74). The association of increased triglyceride and decreased bone mass was similar, although not statistically significant. Those with the combination of TG ≥ 200 mg/dL and TC ≥ 240 mg/dL had a stronger tendency to have osteopenia or osteoporosis (OR 3.51; 95% CI, 1.11-11.13) than people with only one blood lipid abnormality. Similarly, people with TG ≥ 200 mg/dL and LDL-C ≥ 160 mg/dL had a stronger tendency to have osteopenia or osteoporosis (OR 9.31; 95% CI, 1.15-75.42) than people with only one blood lipid abnormality, after adjustment for the same covariates.

Conclusion

Blood levels of TC, LDL-C, and TG were associated with osteopenia or osteoporosis. Results indicate that individuals aged older than 50 years with abnormal lipid profiles should be urged to participate in a bone density survey to exclude osteopenia or osteoporosis.

Association between monocyte to high-density lipoprotein-cholesterol ratio and osteoporosis: An analysis of the National Health and Nutrition Examination Survey 2013-2014

The monocyte to high-density lipoprotein-cholesterol (HDL-C) ratio (monocyte-to-HDL-C ratio) was proposed as a marker of atherosclerosis. Osteoporosis and atherosclerosis share common risk factors and pathophysiological mechanisms. This study aimed to assess the relationship between monocyte-to-HDL-C ratio and osteoporosis. Participants aged ≥50 years with complete bone mineral density (BMD), monocyte, and HDL-C examination data from the National Health and Nutrition Examination Survey (NHANES) 2013-2014 were included. Descriptive analysis was performed separately according to males and females. Weight linear regression and weight logistic regression analyses were used to analyze the association between the monocyte-to-HDL-C ratio and BMD and osteopenia and osteoporosis and vertebral fracture. A total of 1804 participants were included. Among the participants with osteopenia, 398 (48.31%) were males and 466 (51.91%) were females. Among those with osteoporosis, 38 (2.77%) were males and 95 (9.50%) were females. In females, monocyte-to-HDL-C ratio was negatively associated with femoral neck BMD (regression coefficient (β) = -0.18; 95% confidence interval (CI): (-0.29, -0.07)) and high monocyte-to-HDL-C ratio was associated with higher odds of osteopenia (odds ratio (OR) = 1.22; 95% CI: (1.01, 1.47)) and osteoporosis (OR = 1.68; 95% CI: (1.13, 2.49)) after adjusting for confounders. In males, only monocyte-to-HDL-C ratio >0.35 was observed to be associated with higher odds of osteoporosis (OR = 1.96; 95% CI: (1.02, 3.79)). Stratified analyses showed that similar results were also found in different populations. This study showed that the monocyte-to-HDL-C ratio was negatively associated with BMD and the risk of osteopenia and osteoporosis in females. The monocyte-to-HDL-C ratio may be a new marker of osteoporosis or osteopenia.

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.

Rapid trabecular bone growth in puberty associated with stiffer arteries in adulthood - longitudinal study on healthy young males

Longitudinal bone content data from puberty to adulthood was assessed in 102 healthy males and associations with arterial health in adulthood was analysed. Bone growth in puberty was related to arterial stiffening and final bone mineral content to decreased arterial stiffness. Relationships with arterial stiffness were dependent on the studied bone regions.

INTRODUCTION

Our aim was to assess the relationships between arterial parameters in adulthood and bone parameters in several locations longitudinally from puberty to 18-years and cross-sectionally at 18-years.

METHODS

102 healthy male data from a 7-year follow-up study was used to analyse total body (TB), femoral neck (FN) and lumbar spine (LS) mineral content and density by DXA, carotid intima-media thickness (cIMT) by ultrasound, carotid-femoral pulse wave velocity (cfPWV) and heart rate adjusted augmentation index (AIxHR75) by applanation tonometry.

RESULTS

Linear regression analysis revealed negative associations between LS bone mineral density (BMD) and cfPWV [ß=-1.861, CI -3.589, -0.132, p=0.035] which remained significant [ß=-2.679, CI -4.837, -0.522, p=0.016] after adjustment to smoking, lean mass, weight category, pubertal stage, physical fitness, and activity. For AIxHR75 similar results were present [ß=-0.286, CI -0.553, -0.020, p=0.035], but were dependent on confounders. Analysis on pubertal bone growth speed showed independent positive associations to AIxHR75 between Δ FN bone mineral apparent density (BMAD) [ß=672.50, CI 348.07, 996.93, p<0.001] and Δ LS BMAD [ß=700.40, CI 57.384, 1343.423, p=0.033]. Further analysis combining pubertal bone growth and adulthood BMC revealed that the relationships of AIxHR75 with LS BMC and ΔFN BMAD were independent of each other.

CONCLUSION

Trabecular bone regions like lumbar spine and femoral neck, showed stronger relationships with arterial stiffness. Rapid bone growth in puberty is related to arterial stiffening, while final bone mineral content relates to decreased arterial stiffness. These results could indicate that bone metabolism is independently associated with arterial stiffness rather than bone and arteries just having common traits of growth and maturation.

Uncovering the complex genetic architecture of human plasma lipidome using machine learning methods

Genetic architecture of plasma lipidome provides insights into regulation of lipid metabolism and related diseases. We applied an unsupervised machine learning method, PGMRA, to discover phenotype-genotype many-to-many relations between genotype and plasma lipidome (phenotype) in order to identify the genetic architecture of plasma lipidome profiled from 1,426 Finnish individuals aged 30-45 years. PGMRA involves biclustering genotype and lipidome data independently followed by their inter-domain integration based on hypergeometric tests of the number of shared individuals. Pathway enrichment analysis was performed on the SNP sets to identify their associated biological processes. We identified 93 statistically significant (hypergeometric p-value < 0.01) lipidome-genotype relations. Genotype biclusters in these 93 relations contained 5977 SNPs across 3164 genes. Twenty nine of the 93 relations contained genotype biclusters with more than 50% unique SNPs and participants, thus representing most distinct subgroups. We identified 30 significantly enriched biological processes among the SNPs involved in 21 of these 29 most distinct genotype-lipidome subgroups through which the identified genetic variants can influence and regulate plasma lipid related metabolism and profiles. This study identified 29 distinct genotype-lipidome subgroups in the studied Finnish population that may have distinct disease trajectories and therefore could be useful in precision medicine research.

Gene set analysis of transcriptomics data identifies new biological processes associated with early markers of atherosclerosis but not with those of osteoporosis: Atherosclerosis-osteoporosis co/multimorbidity study in the Young Finns Study

AIM

We aimed at identifying the shared biological processes underlying atherosclerosis-osteoporosis co/multimorbidity.

METHODS

We performed gene set analysis (GSA) of whole-blood transcriptomic data to identify biological processes shared by the early markers of these two diseases. Early markers of diseases, carotid intima-media thickness (CIMT) for atherosclerosis and trabecular bone mineral density (BMD) from distal radius and tibia for osteoporosis, were used to categorize the study participants into cases and controls. Participants with high CIMT (>90th percentile) were defined as cases for subclinical atherosclerosis. Study population-based T-scores for BMD were calculated and T-score ≤ -1 was used for the definition of low BMD cases i.e., early indicator of osteoporosis.

RESULTS

We did not identify any gene sets jointly associated with early markers of atherosclerosis and osteoporosis. We identified three novel and replicated 234 gene sets significantly associated with high CIMT with false discovery rate (FDR) ≤ 0.01. Only two genes, both related to the immune system, were identified to be associated with high CIMT by traditional differential gene expression analysis. However, none of the studied gene sets or individual genes were significantly associated with tibial or radial BMD. The three novel CIMT associated gene sets contained genes involved in copper homeostasis, neural crest cell migration and nicotinate and nicotinamide metabolism. The 234 replicated gene sets in this study are related to the immune system, hypoxia and apoptosis, consistent with the existing literature on atherosclerosis.

CONCLUSIONS

This study identified novel biological processes associated with high CIMT but not with reduced BMD.

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.

High cholesterol and low triglycerides are associated with total lumbar bone mineral density among adults aged 50 years and over: The NHANES 2017–2020

Background

The association between cholesterol and triglycerides with the lumbar bone mineral density (BMD) was widely investigated, but the results remained conflicting. This study aimed to investigate the relationship between total cholesterol, triglycerides, and total lumbar BMD in adults.

Materials and methods

This cross-sectional study included 1,985 individuals aged 50 years and over. The data on total cholesterol, triglycerides, total lumbar BMD, and other covariates were obtained from the National Health and Nutritional (NHANES) between 2017 and March 2020 pre-pandemic. Multivariate logistic regression models were utilized to investigate the association between cholesterol, triglycerides, and total lumbar BMD. Smooth curve fittings and generalized additive models were also used to analyze the potential non-linearity.

Results

A total of 901 men and 1,084 women with a mean age of 63.02 ± 8.72 years (age 50–80 years) were included in this study. In multivariate regression analysis, the association between cholesterol and total lumbar BMD was negative (β = −0.026, 95% CI: −0.033, −0.020). This relationship still existed after adjusted for gender and race (β = −0.018, 95% CI: −0.025, −0.012) and fully adjusted for all covariates (β = −0.022, 95% CI: −0.029, −0.015). The association between triglycerides and total lumbar BMD was positive (β = 0.024, 95% CI: 0.017, 0.031). This relationship still existed after adjusted for gender and race (β = 0.021, 95% CI: 0.015, 0.028) and fully adjusted for all covariates (β = 0.021, 95% CI: 0.014, 0.028). In threshold effect analysis, the relationship between triglycerides and total lumbar BMD was an inverted U-shaped curve with the inflection point at 2.597 mmol/L.

Conclusion

High levels of total cholesterol and relatively low levels of triglycerides are significantly associated with the total lumbar BMD in adults aged 50 years and over.

STAT3-mediated osteogenesis and osteoclastogenesis in osteoporosis

Osteoporosis is a common skeletal disease with marked bone loss, deterioration of the bone microstructure and bone fragility. An abnormal bone remodelling cycle with relatively increased bone resorption is the crucial pathophysiological mechanism. Bone remodelling is predominantly controlled by osteoblasts and osteoclasts, which are specialized cell types that are regulated by a variety of osteogenic and osteoclastic factors, including cytokines expressed within the bone microenvironment under local or systemic inflammatory conditions. Signal transducer and activator of transcription 3 (STAT3) plays a prominent role in the communication between cytokines and kinases by binding downstream gene promotors and is involved in a wide range of biological or pathological processes. Emerging evidence suggests that STAT3 and its network participate in bone remodelling and the development of osteoporosis, and this factor may be a potent target for osteoporosis treatment. This review focuses on the role and molecular mechanism of the STAT3 signalling pathway in osteogenesis, osteoclastogenesis and osteoporosis, particularly the bone-related cytokines that regulate the osteoblastic differentiation of bone marrow stromal cells and the osteoclastic differentiation of bone marrow macrophages by initiating STAT3 signalling. This review also examines the cellular interactions among immune cells, haematopoietic cells and osteoblastic/osteoclastic cells.

Integrated Bioinformatic Analysis of the Shared Molecular Mechanisms Between Osteoporosis and Atherosclerosis

Background

Osteoporosis and atherosclerosis are common in the elderly population, conferring a heavy worldwide burden. Evidence links osteoporosis and atherosclerosis but the exact underlying common mechanism of its occurrence is unclear. The purpose of this study is to further explore the molecular mechanism between osteoporosis and atherosclerosis through integrated bioinformatic analysis.

Methods

The microarray data of osteoporosis and atherosclerosis in the Gene Expression Omnibus (GEO) database were downloaded. The Weighted Gene Co-Expression Network Analysis (WGCNA) and differentially expressed genes (DEGs) analysis were used to identify the co-expression genes related to osteoporosis and atherosclerosis. In addition, the common gene targets of osteoporosis and atherosclerosis were analyzed and screened through three public databases (CTD, DISEASES, and GeneCards). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Metascape. Then, the common microRNAs (miRNAs) in osteoporosis and atherosclerosis were screened out from the Human microRNA Disease Database (HMDD) and the target genes of whom were predicted through the miRTarbase. Finally, the common miRNAs-genes network was constructed by Cytoscape software.

Results

The results of common genes analysis showed that immune and inflammatory response may be a common feature in the pathophysiology of osteoporosis and atherosclerosis. Six hub genes (namely, COL1A1, IBSP, CTSD, RAC2, MAF, and THBS1) were obtained via taking interaction of different analysis results. The miRNAs-genes network showed that has-let-7g might play an important role in the common mechanisms between osteoporosis and atherosclerosis.

Conclusion

This study provides new sights into shared molecular mechanisms between osteoporosis and atherosclerosis. These common pathways and hub genes may offer promising clues for further experimental studies.

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.

Identifying a possible new target for diagnosis and treatment of postmenopausal osteoporosis through bioinformatics and clinical sample analysis

Background

Postmenopausal osteoporosis, a common yet chronic systemic metabolic disease, has become a major public health problem due to life expectancy increasing around the world. The differentiation of mesenchymal stem cells (MSCs) into osteoblasts, and the differentiation of circulating monocyte cells into osteoclasts, play an important role in the balance of bone metabolism. However, when both undergo pathological changes, it can lead to abnormalities, resulting in osteoporosis. This study aims to explore a new biomarker for postmenopausal osteoporosis, thereby providing a new entry point for bioinformatic research into the clinical diagnosis and treatment of the disease.

Methods

Using the Gene Expression Omnibus (GEO) database, microarray analysis was conducted to identify differentially expressed genes in MSCs and monocytes in both postmenopausal osteoporosis patients and a healthy control group. The Database for Annotation, Visualization and Integrated Discovery (DAVID) database was used to analyze the function and enrichment of the selected genes, and a protein-protein interaction (PPI) network was constructed from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website and displayed in Cytoscape. To achieve the final results, module analysis of the PPI network was performed by using Molecular Complex Detection (MCODE).

Results

We identified 45 high-expression and 26 low-expression genes through the study, all of which underwent pathway enrichment analysis. This enrichment was observed in the cell cycle regulation, osteoclast differentiation, tumor necrosis factor (TNF) signaling pathway, and RNA transport. The top 10 hub genes of the PPI network were SF3B1, SRSF5, FUBP1, SRSF3, TIA1, KHSRP, LUC7L3, PNN, SRC, and ATRX. Comparing the MSCs and monocytes between the postmenopausal osteoporosis patients and the healthy control group, we noted that the expression of the above genes differed greatly.

Conclusions

Through bioinformatic analysis and clinical specimen validation, our study provides a new way for exploring the pathogenesis of postmenopausal osteoporosis. Most importantly, it suggests that the hub genes, SF3B1, SRSF5, FUBP1, KHSRP, and SRC, may become new diagnostic markers and therapeutic targets for diagnosing and treating postmenopausal osteoporosis in the future.