Identification of Osteoporosis-Associated Protein Biomarkers from Ovariectomized Rat Urine

Proteomic Biomarkers Associated with Low Bone Mineral Density: A Systematic Review

Osteoporosis is a globally relevant public health issue. Our study aimed to summarize the knowledge on the proteomic biomarkers for low bone mineral density over the last years. We conducted a systematic review following the PRISMA guidelines; the scoured databases were PubMed, Web of Sciences, Scopus, and EBSCO, from inception to 2 June 2023. A total of 610 relevant studies were identified and 33 were assessed for eligibility. Finally, 29 studies met the criteria for this systematic review. The risk of bias was evaluated using the Joanna Briggs Institute Critical Appraisal Checklist tool. From the studies selected, 154 proteins were associated with changes of bone mineral density, from which only 10 were reported in at least two articles. The protein-protein network analysis indicated potential biomarkers involved in the skeletal system, immune system process, regulation of protein metabolic process, regulation of signaling, transport, cellular component assembly, cell differentiation, hemostasis, and extracellular matrix organization. Mass spectrometry-based proteomic profiling has allowed the discovery of new biomarkers with diagnostic potential. However, it is necessary to compare and validate the potential biomarkers in different populations to determine their association with bone metabolism and evaluate their translation to the clinical management of osteoporosis.

Proteomic Insights into Osteoporosis: Unraveling Diagnostic Markers of and Therapeutic Targets for the Metabolic Bone Disease

Osteoporosis (OP), a prevalent skeletal disorder characterized by compromised bone strength and increased susceptibility to fractures, poses a significant public health concern. This review aims to provide a comprehensive analysis of the current state of research in the field, focusing on the application of proteomic techniques to elucidate diagnostic markers and therapeutic targets for OP. The integration of cutting-edge proteomic technologies has enabled the identification and quantification of proteins associated with bone metabolism, leading to a deeper understanding of the molecular mechanisms underlying OP. In this review, we systematically examine recent advancements in proteomic studies related to OP, emphasizing the identification of potential biomarkers for OP diagnosis and the discovery of novel therapeutic targets. Additionally, we discuss the challenges and future directions in the field, highlighting the potential impact of proteomic research in transforming the landscape of OP diagnosis and treatment.

Alterations in DNA methylation profiles in cancellous bone of postmenopausal women with osteoporosis

Osteoporosis is characterized by systemic microarchitecture impairment and bone loss, which ultimately lead to fragility fractures. This disease is most common in older people, especially in postmenopausal women. Cancellous bone is affected by osteoporosis earlier than cortical bone, and DNA methylation microarray analysis of the hip cancellous bone of patients with osteoarthritis revealed differential methylation. In view of the important role of cancellous bone in bone development, we examined genome‐wide DNA methylation profiles in the cancellous bone from patients with postmenopausal osteoporosis versus healthy postmenopausal women using Illumina 850K methylation microarray analysis. Under a threshold of P < 0.05, we obtained a total of 8973 differentially methylated genes, such as SOX6, ACE, SYK and TGFB3. Under a threshold of P < 0.05 and |△β| > 0.2, a total of 17 and 34 key differentially methylated genes were further identified at the promoter region and cytosine‐ phosphate‐ guanine (CpG) islands (such as PRKCZ, GNA11 and COL4A1), respectively. PLEKHA2, PLEKHB1, PNPLA7, SCD, MGST3 and TSNAX were the most common differentially methylated genes at both the promoter region and CpG islands. Five important signaling pathways, including the calcium signaling pathway, the cyclic guanosine phospho‐protein kinase G (cGMP‐PKG) signaling pathway, endocytosis, the Rap1 signaling pathway and the AMPK signaling pathway were identified. Our study may be suitable as a basis for exploring the mechanisms underlying osteoporosis in postmenopausal women.

Evaluation of the structure of the otoconial layer using micro-computed tomography

OBJECTIVE

Estrogen deficiency caused by bilateral ovariectomy (OVX) has been reported to lead to morphological changes in otoconia. Thus, we examined the morphological changes in the otoconial layer after OVX. We also investigated whether micro-computed tomography (µCT) is useful for the detection of morphological changes in the otoconial layer.

METHODS

The otic capsules of C57BL/6 J mice were removed and evaluated using histological techniques and µCT at 2, 4, and 8 weeks after OVX or sham surgery. The volume of the utricle otoconial layer was measured and compared between the OVX and sham groups. The µCT scan and histological study results were also compared.

RESULTS

The volume of the utricle otoconial layer was significantly increased 4 weeks after OVX compared to the sham group in both histological and µCT studies (p < 0.05). The volume of the otoconial layer measured using µCT was significantly correlated with the histological study results (p < 0.05).

CONCLUSION

The volume of the utricle otoconial layer increased after OVX. These morphological changes could be detected by µCT.

Identification of hub genes associated with postmenopausal osteoporosis by Gibbs sampling method

Underlying pivotal pathways were identified to reveal potential key genes correlated with postmenopausal osteoporosis (PMOP). The pathways were enriched by Kyoto Encyclopedia of Genes and Genomes (KEGG) with genes intersection greater than 5 based on gene expression profile data, and the acquired pathways were then transformed to Markov chain (MC). Gibbs sampling was conducted to obtain a new MC. Moreover, the average probabilities of each pathway in normal and PMOP were computed via an MC Monte Carlo (MCMC) algorithm, and differential pathways were identified based on probabilities more than 0.7. In addition, frequencies of appearance of pathway genes were counted via MCMC and the hub genes were achieved with the probabilities of gene expression efficiencies in two states. Judging by the gene intersection more than 5, overall 280 pathways were determined. After Gibbs sampling, 2 differential pathways were obtained on the basis of probabilities more than 0.7. Moreover, the hub genes comprising TNNC1, MYL2, and TTN were achieved according to probabilities more than 0.7. The identified pathways and the three hub genes probably are useful for developing approaches for the diagnosis and treatment of PMOP in future preclinical and clinical applications.

Utility of the Serum Cystatin C Level for Diagnosis of Osteoporosis among Middle-Aged and Elderly People

Purpose

Osteoporosis is a common age-related disorder leading to increased bone fragility and risk of fracture. Early diagnosis of osteoporosis is a vital step in providing early therapeutic intervention. Serum cystatin C is a marker of early renal dysfunction, a predictor of cardiovascular and inflammatory diseases, and an inhibitor of the differentiation of osteoclast precursor cells. The purpose of this study was to evaluate the relationship between serum cystatin C and osteoporosis.

Methods

We enrolled 46 subjects who attended a health checkup and underwent measurement of bone status by quantitative ultrasound and determination of the level of serum cystatin C. A comparative study was conducted between those with and without osteoporosis for all subjects collectively and in two subgroups aged <65 and ≥65 years.

Results

Serum cystatin C levels were strongly correlated with age, creatinine, and bone status data, with significant negative correlations with stiffness, T-score, and percentage of young adult mean. Among patients with osteoporosis, serum cystatin C was significantly higher even after adjustment for age and sex, whereas no significant difference was noted in creatinine. For patients aged ≥ 65 years, serum cystatin C was significantly higher in subjects with osteoporosis, although there was no significant difference in age between normal subjects and those with osteoporosis.

Conclusions

To the best of our knowledge, this is the first study to demonstrate an association between serum cystatin C and osteoporosis. Serum cystatin C is significantly higher in osteoporosis and in particular may be a useful marker for osteoporosis among middle and elderly people aged ≥ 65 years. Measurement of serum cystatin C can be carried out easily and may contribute to early diagnosis and treatment of osteoporosis.

A low phase angle measured with bioelectrical impedance analysis is associated with osteoporosis and is a risk factor for osteoporosis in community-dwelling people: the Yakumo study

Although the phase angle has been reported to be related to predictive factors and therapeutic effects in various diseases, its relation with osteoporosis is unclear. In our large prospective survey of community-dwelling people, a low phase angle was related with osteoporosis, and it could be a predictor of osteoporosis.

PURPOSE

The phase angle measured with bioelectrical impedance analysis (BIA) is one of the clinically important impedance parameters, and it is a predictor of prognosis and mortality for several diseases. The present cross-sectional study aimed to elucidate the association between osteoporosis and variables measured with BIA, including the phase angle.

METHODS

The study included 307 participants from an annual health checkup. All participants underwent measurement of bone status by quantitative ultrasound and body composition by BIA. Osteoporosis was diagnosed according to the WHO classification, and statistical comparisons were conducted between normal individuals and osteoporosis patients.

RESULTS

Age, proteins, minerals, and the phase angle were significantly different between normal individuals and osteoporosis patients (p < 0.001). Furthermore, after controlling for age and sex, proteins, minerals, and the phase angle were significantly lower in osteoporosis patients than those in normal individuals (p < 0.001). In multivariate logistic regression analysis, older age and a low phase angle were risk factors for osteoporosis. Additionally, multiple regression analysis showed that age, sex, proteins, minerals, and the appendicular skeletal muscle index were significantly related to the phase angle.

CONCLUSIONS

The phase angle is a predictor of osteoporosis, which is unaffected by age and sex, and a lower phase angle is associated with greater probability of osteoporosis. The phase angle can be easily measured, and osteoporosis can be confirmed even at home. This may facilitate early diagnosis and treatment, which may be useful for preventing diseases related to osteoporosis.