Risk assessment tools for osteoporosis and fractures in 2022

Could point-of-care bioimpedance analysis be another tool in the prevention of osteoporotic fractures?

A treatment gap exists in osteoporosis, with people at risk of fracture often not identified. Dual X-Ray Absorptiometry is the gold standard technique for the identification of low bone mass, but it is not always easily accessible. Bioimpedance analysis (BIA) is a non-invasive, safe and portable technology, which can provide a calculated estimate of bone mass. However, the validity of using BIA in the assessment of bone health is largely unknown. The objective of this study was to examine BIA-derived bone mass (BBM) data from a local population, with the aim of exploring its potential for use as a preliminary osteoporosis screening tool. A convenience sample of 124 participants (40 males, 84 females) was recruited from the local population. BIA was performed on participants according to standard procedures. BBM data was analysed in relation to weight, height, sex, age and BMI. Data was analysed using ANOVA, hierarchial regression, and bivariate correlation as appropriate. Weight was strongly associated with BBM (R2 = 0.637, p < 0.001), providing the greatest contribution to variance, of the factors examined. BBM was also positively associated with height, in a model that included weight (ΔR2 = 0.218, p < 0.001). Females had a significantly lower bone mass than males, independent of weight and height (ΔR2 = 0.055, p < 0.001). There was a small negative association of BBM with age, in a model that included weight and sex (ΔR2 = 0.011; p = 0.002). A positive correlation between BMI and BBM was found in both males (r s (38) = 0.482, p = 0.002), and females (r s (82) = 0.565, p < 0.001). The finding that BBM values are associated with factors known to be relevant to fracture risk, provides a rationale to perform further studies to investigate if BBM values could have validity for point-of-care assessment of bone health.

Comparative accuracy of osteoporosis risk assessment tools in postmenopausal women: A systematic review and network meta-analysis

BACKGROUND

The Fracture Risk Assessment Tool (FRAX, threshold ≥9.3 %), Osteoporosis Risk Assessment Instrument (ORAI, ≥9), Osteoporosis Index of Risk (OSIRIS, <1), Osteoporosis Self-Assessment Tool (OST, <2), and Simple Calculated Osteoporosis Risk Estimation (SCORE, ≥6) have been endorsed by the US Preventive Services Task Force for evaluating the need for bone mineral density measurement by dual-energy X-ray absorptiometry in postmenopausal women.

OBJECTIVE

To systematically compare the sensitivity and specificity of the five osteoporosis risk assessment tools for detecting bone mineral density-defined osteoporosis.

METHODS

A systematic search was conducted across the Cochrane Library, Embase, PubMed and Web of Science databases up to January 29, 2024, to identify observational studies that evaluated comparative accuracy of these tools in postmenopausal women. The Quality Assessment of Diagnostic Accuracy Studies-2 and its comparative extension were utilized to evaluate the risk of bias and applicability. Pooled odds ratios (ORs) and 95 % confidence intervals (CIs) for relative sensitivity and specificity were calculated using a multivariate random-effects model, with tool rankings determined by Surface Under the Cumulative Ranking (SUCRA).

RESULTS

17 studies were included, involving 9669 postmenopausal women with bone mineral density-defined osteoporosis and 34,143 without the condition. The SCORE (OR = 12.11, 95 % CI [4.46-32.86]) exhibited significantly higher sensitivity than FRAX, followed by ORAI (OR = 7.01, 95 % CI [2.84-17.31]) and OST (OR = 6.90, 95 % CI [3.07-15.52]). Compared to OSIRIS, higher sensitivity was observed for SCORE (OR = 4.92, 95 % CI [2.41-10.05]), ORAI (OR = 2.85, 95 % CI [1.63-4.99]), and OST (OR = 2.80, 95 % CI [1.58-4.97]). However, specificity was lower for SCORE (OR = 0.16, 95 % CI [0.08-0.33]), ORAI (OR = 0.26, 95 % CI [0.13-0.51]), and OST (OR = 0.28, 95 % CI [0.15-0.53]) compared to FRAX. Similarly, SCORE (OR = 0.25, 95 % CI [0.15-0.41]), ORAI (OR = 0.40, 95 % CI [0.26-0.62]), and OST (OR = 0.44, 95 % CI [0.27-0.69]) showed significantly lower specificity than OSIRIS. Based on SUCRA values, SCORE (98.2 %) ranked as the most sensitive tool, followed by ORAI (64.2 %) and OST (62.6 %), whereas FRAX (96.7 %) was the most specific, followed by OSIRIS (78.3 %).

CONCLUSIONS

The risk assessment tools for identifying postmenopausal women with bone mineral density-defined osteoporosis, endorsed by the US Preventive Services Task Force, can be categorized into two groups. SCORE (≥6), ORAI (≥9), and OST (<2) offer higher sensitivity, identifying more osteoporosis patients, whereas FRAX (≥9.3 %) and OSIRIS (<1) provide higher specificity, identifying those without the condition more accurately.

REGISTRATION

PROSPERO (CRD42024507532).

Evaluation of bone fragility in cognitively or physically impaired elderly care home patients using radiofrequency echographic multi-spectrometry

Dual-energy X-ray absorptiometry (DXA) is the standard for bone mineral density (BMD) assessment but is often inaccessible to cognitively or physically impaired care home patients. Radiofrequency echographic multi-spectrometry (REMS), a portable and radiation-free alternative, enables effective BMD evaluation in this vulnerable and underserved population. This cross-sectional study assessed BMD using REMS in 260 patients aged ≥ 70 years (39 males, 221 females; mean age 82.29 years) between April 2023 and July 2024. Osteoporosis diagnosis was based on T-scores <  - 2.5 SD or history of fragility fractures, with severe osteoporosis defined by WHO criteria and high fracture risk by lumbar T-scores <  - 3.3 SD. Care home patients had significantly lower BMD and T-scores than outpatients, with 56.3% diagnosed with severe osteoporosis and 71.8% exhibiting lumbar T-scores <  - 3.3 SD. Despite high fracture risks, only 12.7% of care home patients received treatment. These trends were consistent across all age groups, revealing a high prevalence and severity of osteoporosis in care home residents. REMS has unveiled a substantial treatment gap in this population, emphasizing the critical need for improved osteoporosis management and proactive interventions to reduce fracture risks among care home patients worldwide.

Is surgeon assessed bone quality during total knee arthroplasty a valid tool to diagnose osteoporosis?

Osteoporosis continues to have a high prevalence amongst people undergoing total knee arthroplasty (TKA). The surgeon assessed intraoperative bone quality using a visual analogue scale has a strong correlation with bone mineral density. Surgeon assessment of bone quality has a high specificity(100%) and positive predictive value(100%) in diagnosing osteoporosis and osteopenia.

BACKGROUND

Patients undergoing TKA have a high prevalence of osteoporosis. Our aim is to study (a) the correlation of intraoperative surgeon assessed bone quality with bone mineral density(BMD) as measured by dual-energy x-ray absorptiometry(DEXA) and (b) the diagnostic strength of intraoperative surgeon assessment of bone quality in diagnosing osteoporosis and osteopenia, in patients undergoing TKA.

METHODS

We prospectively recruited 31 patients undergoing TKA. Patients were classified into normal, osteopenia or osteoporosis based on preoperative DEXA. Intraoperatively, the senior surgeon by visual and tactile assessment, graded the bone quality(BQ) using a visual analogue scale(VAS) from 0 to 10, with 10 being the strongest bone. Using the VAS score, we classified patients as normal(≥ 8), osteopenia(5-7) and osteoporosis(≤ 4).

RESULTS

The Spearman's rho correlation between BMD and VAS was 0.954.(p < 0.001). VAS < 8 to diagnose osteopenia and osteoporosis had a sensitivity of 70.83%, specificity of 100%, positive predictive value of 100% and diagnostic accuracy of 77.42%(p = 0.001). VAS ≤ 4 to diagnose osteoporosis had a sensitivity of 71.43%, specificity of 100%, positive predictive value of 100% and diagnostic accuracy of 93.55%(p < 0.001).

CONCLUSION

The surgeon assessed intraoperative bone quality using a VAS during TKA has a strong correlation with the gold standard BMD as measured by DEXA scan. VAS ≤ 4 can help diagnose osteoporosis, allowing surgeons to augment implant fixation with stem and cement as well as guide osteoporosis treatment postoperatively. VAS < 8 can identify osteopenic or osteoporotic bone, thus allowing the surgeon to better identify weaker bone and help titrate implant choice.

Frequency-Regulated Repeated Micro-Vibration Promotes Osteoblast Differentiation Through BMP Signaling in MC3T3-E1 Cells

Physical stimulation, which is a key factor affecting the metabolism of osteoblasts and their precursor cells, plays an important role in bone remodeling; however, the role of micro-vibrations in osteoblast differentiation is unclear. In the present study, we determined the effects of frequency-regulated repeated micro-vibration (FRMV) on cell proliferation and established a method to induce osteoblast differentiation through FRMV using the mouse pre-osteoblast-like cell line MC3T3-E1, which is widely used in bone metabolism research. The results indicated that FRMV significantly influenced the proliferation of MC3T3-E1 cells in a normal growth medium. FRMV at 42.2 Hz significantly promoted proliferation, whereas FRMV at 92.1 Hz showed no effect on the proliferation rate. Moreover, FRMV at 42.2 Hz significantly increased alkaline phosphatase (ALP) enzyme activity and ALP gene expression in MC3T3-E1 cells. Treatment with LDN193189, a bone morphogenetic protein (BMP) signaling inhibitor, revealed that the FRMV-induced upregulation in ALP enzyme activity and ALP gene expression were significantly suppressed in MC3T3-E1 cells. The results suggest that the FRMV protocol developed in the present study induces osteoblast differentiation through the BMP signaling pathway. Thus, FRMV may contribute to the development of effective bone regeneration technologies.

DXA and cardiovascular disease in rheumatoid arthritis: A scoping review

DXA technology is widely available today in many regions of the world. There is a growing realization of the value of DXA not only for osteoporosis management but also for sports medicine, sarcopenia, and the assessment of cardiovascular disease and mortality. Such features may be of particular interest for populations with a greater risk of these outcomes such as those with diabetes mellitus or rheumatoid arthritis. Recent systematic reviews and meta-analyses show DXA can robustly predict fractures, cardiovascular disease, dementia and mortality. Rheumatoid arthritis (RA) is a chronic inflammatory disease affecting multiple organs including synovial joints, bone and other tissues. People suffering from RA have a greater propensity to osteoporotic fracture, cardiovascular disease, infection and premature death, which is well recognised. RA is the only unique disease included in some fracture risk algorithms such as FRAX, and so RA patients are often referred for a DXA scan to evaluate their risk of osteoporosis. We have previously shown vertebral fractures, aortic calcification and cardiovascular disease are prevalent in our RA population, with strong association. In this paper we performed a scoping review of published literature in Medline and Embase to better understand the current status of DXA and cardiovascular disease in RA populations. 822 papers were identified in an initial search of which 7 papers reflecting 2,038 RA patients from 7 different countries were included. Study design included 4 cross-sectional, 2 longitudinal and 1 case-control. All included associations with various cardiovascular measures, while only 1 included clinical events as an outcome. Our results suggest this is an area which remains relatively unexplored but has substantial important clinical potential.

Shoulder Arthroplasty Patients Are Underscreened for Osteoporosis

INTRODUCTION

Osteoporosis screening and subsequent treatment has been shown to be efficacious in decreasing the rates of fragility fractures and periprosthetic fractures (PPF). However, current screening and treatment rates are low. This study aims to determine (1) the prevalence of total shoulder arthroplasty (TSA) patients who meet criteria for osteoporosis screening, (2) the prevalence of those screened, and (3) the 5-year cumulative incidence of fragility fracture (FF) and periprosthetic fractures (PPF).

METHODS

The PearlDiver database was used to identify all patients older than 50 years who underwent TSA. Guidelines from the American Association of Clinical Endocrinologists were used to stratify patients into "high risk" and "low risk" of osteoporosis cohorts using International Classification of Disease codes for various risk factors. The prevalence of osteoporosis screening using dual-energy x-ray absorptiometry (DXA) scan was analyzed, and the 5-year cumulative incidence of FF and PPF was calculated between the "low-risk" and "high-risk" groups using Kaplan-Meier analysis.

RESULTS

In total, 66,140 (65.5%) who underwent TSA were considered "high risk" for osteoporosis. Of the "high-risk" patients, 11.7% patients received routine osteoporosis screening preoperatively. Within 5 years, "high-risk" TSA patients had markedly higher cumulative incidence for PPF (HR: 1.4; 95% CI: 1.0-1.9; P = 0.037) and FF (HR: 2.42; 95% CI: 2.1-2.8; P < 0.001) when compared with those at "low risk".

DISCUSSION

There is a high prevalence of osteoporosis among patients undergoing TSA but a low rate of routine osteoporosis screening in this cohort. Patients with osteoporosis who are categorized as "high risk" have an increased rate of fragility fractures and PPF. Therefore, there is an opportunity to increase appropriate osteoporosis screening and management in this cohort, which may affect future risk of FF and periprosthetic fracture.

LEVEL OF EVIDENCE

III.

A cross-sectional study comparing machine learning and logistic regression techniques for predicting osteoporosis in a group at high risk of cardiovascular disease among old adults

BACKGROUND

Osteoporosis has become a significant public health concern that necessitates the application of appropriate techniques to calculate disease risk. Traditional methods, such as logistic regression,have been widely used to identify risk factors and predict disease probability. However,with the advent of advanced statistics techniques,machine learning models offer promising alternatives for improving prediction accuracy. What's more, studies that use risk factors and prediction models for osteoporosis in high-risk groups for cardiovascular diseases are scarce. We aimed to explore the risk factors and disease probability of osteoporosis by comparing logistic regression with four machine learning models. By doing so,we seek to provide insights into the most effective methods for osteoporosis risk assessment and contribute to the development of tailored prevention strategies at high risk of cardiovascular disease among old adults.

METHODS

We carried out a cross-sectional investigation of a high-risk group in cardiovascular patients. A logistic regression model and four common machine learning methods,DT,RF,SVM,and XGBoost were implemented to create a prediction model using information from 211 participants who met the inclusion requirements. Metrics for calibration and discrimination were used to compare the models.

RESULTS

In total,211 patients were enrolled. The AUCs were 0.751 for the logistic regression model,0.72 for the SVM model,0.70 for the random forest model,0.697 for the model XGBoost,and 0.69 for the decision tree model. The logistic regression model outperforms other models for machine learning. According to the logistic regression model,there were nine predictors,including age,sex,glucose,TG (triglyceride),fracture history,stroke history,and CNV (copy number variation) nssv659422, and low-sodium salt. A well-calibrated result of 0.199 on the Brier scale. The findings of the internal validation demonstrated the high degree of repeatability of the prediction model employed in this study.

CONCLUSIONS

In this study, we discovered that when predicting osteoporosis,a number of machine learning techniques fell short of logistic regression. In a specific population, we have innovatively developed a risk prediction model for osteoporosis events that integrates genetic and environmental factors, is an effective tool for assessing osteoporosis risk and can serve as the basis for specialized intervention approaches.

A causal association between osteoporosis and postural instability: a Mendelian randomization study

Many observational studies have found an association between osteoporosis and postural instability. However, it is unclear whether there is a genetic causal relationship between osteoporosis and postural instability. In this study, we conducted a two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between osteoporosis and postural instability, with osteoporosis represented by bone mineral density (BMD). We used random effects Inverse Variance Weighted (IVW), weighted median, and MR-Egger methods after Steiger filtering, followed by FDR correction, to assess the causal relationship. We also used the Cochran Q statistic and MR-PRESSO to detect and exclude heterogeneity, the MR-Egger intercept to detect horizontal pleiotropy, and the leave-one-out method for sensitivity analyses. After excluding the heterogeneity in causal estimates across different SNPs and after Steiger filtering, the inverse variance weighted analysis showed a significant negative correlation between femoral neck BMD (FN-BMD) and the occurrence of postural instability, with an OR of 0.9171 (95% CI: 0.8745-0.9617; FDR P.value = 0.0009). Similar results were obtained in the weighted median analysis, with an OR of 0.923 (95% CI: 0.8717-0.9733; FDR P = 0.0180), and in the analysis of lumbar spine BMD (LS-BMD) in IVW, with an OR of 0.9491 (95% CI: 0.9156-0.9838; FDR P.value = 0.0129). However, there was no significant correlation between forearm BMD (FA-BMD) and postural instability. Further analysis showed no horizontal pleiotropy or heterogeneity in FN-BMD and LS-BMD after excluding heterogeneous SNPs. This study demonstrates a causal association between BMD and postural instability, suggesting that individuals with osteoporosis may be at higher risk of experiencing postural instability.

Updated practice guideline for dual-energy X-ray absorptiometry (DXA)

The introduction of dual-energy X-ray absorptiometry (DXA) technology in the 1980s revolutionized the diagnosis, management and monitoring of osteoporosis, providing a clinical tool which is now available worldwide. However, DXA measurements are influenced by many technical factors, including the quality control procedures for the instrument, positioning of the patient, and approach to analysis. Reporting of DXA results may be confounded by factors such as selection of reference ranges for T-scores and Z-scores, as well as inadequate knowledge of current standards for interpretation. These points are addressed at length in many international guidelines but are not always easily assimilated by practising clinicians and technicians. Our aim in this report is to identify key elements pertaining to the use of DXA in clinical practice, considering both technical and clinical aspects. Here, we discuss technical aspects of DXA procedures, approaches to interpretation and integration into clinical practice, and the use of non-bone mineral density measurements, such as a vertebral fracture assessment, in clinical risk assessment.

Distribution and diagnostic modeling of osteoporosis and comorbidities across demographic factors: A cross-sectional study of 2224 female patients

OBJECTIVE

This study investigates the distribution of osteoporosis (OP) and its associated comorbidities across different demographic factors. Furthermore, this study seeks to develop a statistically-based diagnostic model leveraging demographic and health indicators to provide personalized risk assessments for OP.

METHODS

A retrospective analysis was conducted on the demographic data, health profiles, and bone density measurements of 2224 female patients. Key variables associated with OP were identified using chi-square tests. Feature selection was refined through Lasso regression and recursive feature elimination (RFE), which guided the development of a logistic regression-based dynamic nomogram. This model was subsequently implemented on the Shiny platform for personalized online OP risk assessments.

RESULTS

Among 2224 female patients, 801 (36.0 %) were diagnosed with OP. Women aged 70 and older exhibited a significantly higher prevalence of OP compared to younger age groups (OR = 5.83, 95 % CI: 1.74-19.61, P = 0.004), and this remained significant in the multivariable analysis (OR = 5.18, 95 % CI: 1.19-22.52, P = 0.028). Later age at menarche was associated with increased OP risk (OR = 1.31, 95 % CI: 1.09-1.57, P = 0.004), persisting in multivariable analysis (OR = 1.25, 95 % CI: 1.03-1.52, P = 0.023). In rheumatoid arthritis (RA) patients, higher education reduced OP risk, with secondary education (OR = 0.09, P = 0.024) and college education (OR = 0.04, P = 0.009) showing protective effects. Diabetic patients who were unmarried or had non-traditional marital statuses showed increased OP risk (univariate OR = 2.73, P = 0.006; multivariate OR = 2.34, P = 0.029). Among nonalcoholic fatty liver disease (NAFLD) patients, age at menopause was significantly linked to OP risk (univariate OR = 1.04, P = 0.012). The prediction model showed strong performance (AUC = 0.720), and the dynamic nomogram on the Shiny platform provided effective personalized OP risk assessments.

CONCLUSION

Age and age at menarche are significant risk factors for OP, with later menarche increasing the risk. In RA patients, higher education levels were associated with a lower risk of OP. In contrast, unmarried or non-traditional marital statuses increased OP risk among diabetic patients. Additionally, age at menopause was found to be a significant factor for OP risk in NAFLD patients. The prediction model developed in this study, with an AUC of 0.720, provides a reliable method for personalized OP risk assessment through a dynamic nomogram. These findings highlight the crucial role of demographic factors in predicting OP risk and underscore the importance of personalized treatment strategies for effective OP prevention and management.

Levels of parathyroid hormone and IGF binding protein 1 and associations with mortality and hip fractures in older women

In this study we examined the effect of simultaneously elevated levels of parathyroid hormone (PTH) (≥ 65 ng/mL) and high levels of insulin-like growth factor-binding protein 1 (IGFBP-1) on the 10-year risk of all-cause mortality and hip fractures. Blood tests for levels of PTH and IGFBP-1 was collected at baseline in 338 community-dwelling women in Stockholm aged between 69 and 79 years. Data on hip fractures and all-cause mortality over the next 10 years were retrieved from healthcare registers. The participants were divided into four groups depending on their levels of PTH and IGFBP-1: (A) normal PTH and low IGFBP-1; (B) normal PTH and high IGFBP-1; (C) elevated PTH and low IGFBP-1; (D) elevated PTH and high IGFBP-1. Group D was used as reference. Cox proportional hazard regression (HR) model was used to compare age-adjusted association with hip fractures and all-cause mortality of the four groups. The group with elevated levels of PTH and high IGFBP-1 had a two to three times higher risk of all-cause mortality compared to the other groups but we found no association with hip fractures.

The influence of proliferative tissue on Hounsfield unit and its correlation with BMD in middle-aged and elderly patients with lumbar degenerative diseases

PURPOSE

The difference of Hounsfield Unit (HU) value in different regions of L3 vertebra in middle-aged and elderly patients with lumbar degeneration diseases (LDD) was analyzed. To investigate the influence of proliferative tissue on HU value of cancellous bone and its correlation with bone mineral density (BMD).

METHODS

The medical records of middle-aged and elderly patients with LDD in our hospital from December 2020 to December 2023 were retrospectively analyzed. The patients were divided into osteophyte group and no-osteophyte group according to the presence or absence of osteophyte formation on lumbar spine X-ray. In osteophyte group, cancellous bone HU value, containing cortical bone overall HU value and containing osteophyte overall HU value in L3 vertebra were measured on the lumbar CT cross-section. In no-osteophyte group, only the cancellous bone HU value and the containing cortical bone overall HU value were measured. Differences in HU value in different regions of the L3 vertebral body were compared within and between groups of middle-aged and elderly patients with LDD, respectively. To investigate its effect on cancellous bone HU measurements and to do a correlation analysis with patients' BMD.

RESULTS

A total of 115 patients with LDD were included in this study, including 65 males and 50 females, with an average age of 67.83 ± 6.59 years. The results of the study showed no statistical differences in age (P = 0.15), gender (P = 0.57), smoking (P = 0.88), drinking history (P = 0.76), medical history (P > 0.05) and BMI(P = 0.29) between the two groups. In osteophyte group, the mean cancellous bone HU value was 98.00 ± 25.50 HU, the containing cortical bone overall HU value was 189.02 ± 46.18 HU, and the containing osteophyte overall HU value was 232.69 ± 56.01 HU. The overall HU values containing cortical bone and containing osteophyte were significantly higher than cancellous bone HU value (P < 0.001). In no-osteophyte group, the mean cancellous bone HU value was 102.04 ± 19.64 HU, and the containing cortical bone overall HU value was 175.00 ± 28.97 HU, which was statistically significantly different (P < 0.001). There was no significant difference in cancellous bone HU value and the containing cortical bone overall HU value between the two groups (P > 0.05). The results of the Pearson correlation analysis showed a significant correlation between the cancellous bone HU value of the L3 vertebrae and the QCT BMD value of the patients (r = 0.95, P < 0.001). However, there was no significant correlation between containing cortical bone overall HU value and containing osteophyte overall HU value and the patient's QCT BMD value (P > 0.05).

CONCLUSIONS

Vertebral HU value is an alternative measurement that effectively reflects the patient's BMD. In middle-aged and elderly LDD patients, HU values in different areas of L3 vertebra are significantly different, and hyperplastic tissues such as cortical bone and osteophytes may exponentially lead to higher HU value in patients. Compared with other measurement areas, vertebral cancellous bone HU value have the advantage of accurately assessing patients' BMD.

Modelling future bone mineral density: Simplicity or complexity?

BACKGROUND

Osteoporotic fractures are a major global public health issue, leading to patient suffering and death, and considerable healthcare costs. Bone mineral density (BMD) measurement is important to identify those with osteoporosis and assess their risk of fracture. Both the absolute BMD and the change in BMD over time contribute to fracture risk. Predicting future fracture in individual patients is challenging and impacts clinical decisions such as when to intervene or repeat BMD measurement. Although the importance of BMD change is recognised, an effective way to incorporate this marginal effect into clinical algorithms is lacking.

METHODS

We compared two methods using longitudinal DXA data generated from subjects with two or more hip DXA scans on the same machine between 2000 and 2018. A simpler statistical method (ZBM) was used to predict an individual's future BMD based on the mean BMD and the standard deviation of the reference group and their BMD measured in the latest scan. A more complex deep learning (DL)-based method was developed to cope with multidimensional longitudinal data, variables extracted from patients' historical DXA scan(s), as well as features drawn from the ZBM method. Sensitivity analyses of several subgroups was conducted to evaluate the performance of the derived models.

RESULTS

2948 white adults aged 40-90 years met our study inclusion: 2652 (90 %) females and 296 (10 %) males. Our DL-based models performed significantly better than the ZBM models in women, particularly our Hybrid-DL model. In contrast, the ZBM-based models performed as well or better than DL-based models in men.

CONCLUSIONS

Deep learning-based and statistical models have potential to forecast future BMD using longitudinal clinical data. These methods have the potential to augment clinical decisions regarding when to repeat BMD testing in the assessment of osteoporosis.

Analysis of the impact of underlying diseases in the elderly on postoperative re-fractures after osteoporotic compression fractures

BACKGROUND

Postoperative refracture of osteoporotic compression fractures in the elderly due to underlying illnesses is a complicated matter involving several variables. A multidisciplinary approach involving orthopedics, geriatrics, endocrinology, and rehabilitation medicine is necessary for an investigation of these issues. investigating the impact of older patients' underlying medical conditions on the refracture of osteoporotic compression fractures following surgery.

METHODS

A retrospective analysis was conducted on 2383 patients between August 2013 and August 2023. 550 patients with comorbid geriatric underlying diseases were screened, 183 patients underwent refractories, and 367 patients were classified as non-refractories. The patients were then divided into two groups: those undergoing refractories and those not, and the underlying diseases of the patients in both groups were examined using ROC curves and unifactorial and multifactorial logistic regression analyses.

RESULTS

Among the patients gathered, the frequency of re-fracture was 33.3%. A statistically significant difference was observed when re-fracture was linked to patients with long-term alcohol consumption, operated vertebrae ≤ 1, hypertension, COPD, diabetes mellitus, stroke sequelae, conservative treatment of coronary heart disease, trauma, mental abnormality, scoliosis, and chronic renal disease. Having hypertension decreased the risk of re-fracture (P = 0.018, OR = 0.548), while alcohol intake ≥ 10years (P = 0.003, OR = 2.165), mental abnormality (P < 0.001, OR = 4.093), scoliosis (P < 0.001, OR = 6.243), chronic kidney disease (P = 0.002, OR = 2.208), and traumatic injuries (P = 0.029, OR = 3.512) were the risk factors examined in a binary logistic regression analysis. The results of multiple linear stepwise regression analysis indicated that re-fracture was more influenced by scoliosis.

CONCLUSIONS

Hypertensive disorders were protective factors against the formation of re-fracture, while alcohol intake usage for more than ten years, psychological abnormalities, scoliosis, chronic kidney disease, and trauma were risk factors. Scoliosis had the highest influence on re-fracture.

Effect of bisphosphonate on bone microstructure, mechanical strength in osteoporotic rats by ovariectomy

BACKGROUND

Bisphosphonate (BP) can treat osteoporosis and prevent osteoporotic fractures in clinical. However, the effect of BP on microstructure and mechanical properties of cortical and trabecular bone has been taken little attention, separately.

METHODS

In this study, BP was used to intervene in ovariectomized female SD rats. The femoral micro-CT images were used to measure the structural parameters and reconstruct the 3D models in volume of interest. The structural parameters of cortical and trabecular bone were measured, and the mechanical properties were predicted using micro-finite element analysis.

RESULTS

There was almost no significant difference in the morphological structure parameters and mechanical properties of cortical bone between normal, ovariectomized (sham-OVX) and BP intervention groups. However, BP could significantly improve bone volume fraction (BV/TV) and trabecular separation (Tb.SP) in inter-femoral condyles (IT) (sham-OVX vs. BP, p < 0.001), and had no significant effect on BV/TV in medial and lateral femoral condyles (MT, LT). Similarly, BPs could significantly affect the effective modulus in IT (sham-OVX vs. BP, p < 0.001), and had no significant difference in MT and LT. In addition, the structural parameters and effective modulus showed a good linear correlation.

CONCLUSION

In a short time, the effects of BP intervention and osteoporosis on cortical bone were not obvious. The effects of BP on trabecular bone in non-main weight-bearing area (IT) were valuable, while for osteoporosis, the main weight-bearing area (MT, LT) may improve the structural quality and mechanical strength of trabecular bone through exercise compensation.

Uric acid-to-high-density lipoprotein cholesterol ratio and osteoporosis: Evidence from the national health and nutrition examination survey

Background: The uric acid-to-high-density lipoprotein cholesterol ratio (UHR) has emerged as a novel indicator of inflammatory and metabolic status. This study aims to examine the association between UHR and bone mineral density (BMD), as well as the risk of osteoporosis, in individuals aged ≥50 years. Methods: This cross-sectional study used data from the National Health and Nutrition Examination Survey, focusing on participants aged ≥50 years. Femoral neck BMD (FN-BMD) was measured using dual-energy X-ray absorptiometry. Linear regression models were employed to examine the association between UHR and FN-BMD. Additionally, generalised additive models were used to assess the nonlinear relationship between UHR and FN-BMD. Logistic regression models were employed to evaluate the association between UHR and the risk of osteoporosis. Results: Finally, the study included 2963 adults with a mean age of 64.16 ± 8.92 years. Linear regression analyses revealed a positive association between UHR and FN-BMD, regardless of covariate adjustments. Logistic regression analyses indicated that elevated UHR was associated with a reduced risk of osteoporosis with or without covariate adjustments. Subgroup analyses revealed that the positive association between UHR and BMD was significant in individuals aged ≥65 years but not in those aged 50 to 64 years. Interaction analyses by age showed significant differences after adjusting for all covariates. Conclusions: Clinicians should be vigilant regarding the potential risk of osteoporosis in individuals with a low UHR. UHR might serve as a risk indicator for osteoporosis.

Radiofrequency echographic multi-spectrometry-based measurement of bone mineral density in patients with severe motor and intellectual disability: An opportunity for patients with severe scoliosis and hip dislocation

Purpose

Radiofrequency echographic multi-spectrometry (REMS) is an ultrasound technology currently used for the densitometric evaluation of osteoporosis and has been validated against dual-energy X-ray absorptiometry. However, the use of REMS for bone densitometry in patients with severe motor and intellectual disabilities (SMID) remains to be reported. This study aimed to investigate whether REMS technology can be used for densitometric evaluation of osteoporosis in patients with SMID with hip dislocation and severe scoliosis.

Methods

Sixty-five patients with SMID, who resided in a long-term care facility and received comprehensive medical and rehabilitation care, underwent REMS scans of the femoral neck and/or lumbar spine. Data regarding anthropometric parameters (height and weight), bone mineral density (BMD), clinical diagnostic classification, physical ability, presence of scoliosis and hip dislocation, and frontal radiographs of both hip joints were obtained.

Results

We included 29 men and 34 women (mean age: 52.6 years). All patients underwent successful scanning at either the femoral neck (82.5 %) or lumbar spine (95.2 %). BMD measurements obtained using REMS revealed low values, with a mean BMD, T-score, and Z-score of 0.67 g/cm2, -2.39 standard deviation (SD), and - 1.38 SD, respectively, at the femoral neck and 0.66 g/cm2, -2.70 SD, and - 1.87 SD, respectively, at the lumbar spine. The average Cobb angle of the lumbar spine was 34.0°; furthermore, dislocation rates did not significantly differ between those with and without successful BMD measurements (p = 0.073). Lumbar BMD T-scores were significantly correlated with femoral neck BMD T-scores (p < 0.001, r = 0.530).

Conclusion

All patients with SMID were able to undergo measurements of either spinal or femoral neck BMD; furthermore, 77.7 % of the patients underwent measurements at both the lumbar spine and femur. Our data suggest that REMS is useful for measuring BMD in patients with SMID who are residing in institutions.

Characterization of gut microbiota in the Uyghur osteopenia population

The objectives of this study were to investigate the composition of gut microbiota and its relationship with bone loss in the Uyghur osteopenia population, identify potential disease-related taxa and collect information for the prevention and treatment of osteopenia in different people by regulating gut microbiota. We selected Uyghur residents, measured their heel BMD, collected faeces and general information, grouped them by BMD level, obtained faecal 16S rRNA sequences, and compared and analysed the differences between the groups. This study showed that the numbers of OTUs and species in the gut microbiota in the osteopenia group were higher than those in the control. At the phylum level, Erysipelotrichia was more abundant in the osteopenia group. At the genus level, Phascolarctobacterium was less abundant, and Ruminiclostridium_5 was more abundant in the osteopenia group compared to the control. Phascolarctobacterium and Z-score were positively correlated, and Ruminiclostridium_5 was negatively correlated with T and Z score. The different composition of the gut microbiota in Uyghur osteopenia patients and controls found in this study fills a knowledge gap in this ethnic group. The relationship between Uyghur osteopenia and BMD-associated bacterial genera deserves further exploration.

Fully Automatic Deep Learning Model for Spine Refracture in Patients with OVCF: A Multi-Center Study

BACKGROUND

The reaserch of artificial intelligence (AI) model for predicting spinal refracture is limited to bone mineral density, X-ray and some conventional laboratory indicators, which has its own limitations. Besides, it lacks specific indicators related to osteoporosis and imaging factors that can better reflect bone quality, such as computed tomography (CT).

OBJECTIVE

To construct a novel predicting model based on bone turn-over markers and CT to identify patients who were more inclined to suffer spine refracture.

METHODS

CT images and clinical information of 383 patients (training set = 240 cases of osteoporotic vertebral compression fractures (OVCF), validation set = 63, test set = 80) were retrospectively collected from January 2015 to October 2022 at three medical centers. The U-net model was adopted to automatically segment ROI. Three-dimensional (3D) cropping of all spine regions was used to achieve the final ROI regions including 3D_Full and 3D_RoiOnly. We used the Densenet 121-3D model to model the cropped region and simultaneously build a T-NIPT prediction model. Diagnostics of deep learning models were assessed by constructing ROC curves. We generated calibration curves to assess the calibration performance. Additionally, decision curve analysis (DCA) was used to assess the clinical utility of the predictive models.

RESULTS

The performance of the test model is comparable to its performance on the training set (dice coefficients of 0.798, an mIOU of 0.755, an SA of 0.767, and an OS of 0.017). Univariable and multivariable analysis indicate that T_P1NT was an independent risk factor for refracture. The performance of predicting refractures in different ROI regions showed that 3D_Full model exhibits the highest calibration performance, with a Hosmer-Lemeshow goodness-of-fit (HL) test statistic exceeding 0.05. The analysis of the training and test sets showed that the 3D_Full model, which integrates clinical and deep learning results, demonstrated superior performance with significant improvement (p-value < 0.05) compared to using clinical features independently or using only 3D_RoiOnly.

CONCLUSION

T_P1NT was an independent risk factor of refracture. Our 3D-FULL model showed better performance in predicting high-risk population of spine refracture than other models and junior doctors do. This model can be applicable to real-world translation due to its automatic segmentation and detection.

Jaboticaba Peel Extract Attenuates Ovariectomy-Induced Bone Loss by Preserving Osteoblast Activity

Therapies to prevent osteoporosis are relevant since it is one of the most common non-communicable human diseases in the world and the most prevalent bone disorder in adults. Since jaboticaba peel extract (JPE) added to the culture medium enhanced the osteogenic potential of mesenchymal stem cells (MSCs) derived from osteoporotic rats, we hypothesized that JPE prevents the development of ovariectomy-induced osteoporosis. Ovariectomized rats were treated with either JPE (30 mg/kg of body weight) or its vehicle for 90 days, starting 7 days after the ovariectomy. Then, the femurs were subjected to microcomputed tomography and histological analyses, and the osteoblast and adipocyte differentiation of MSCs was evaluated. JPE attenuated ovariectomy-induced bone loss, as evidenced by higher bone volume/total volume and trabecular number, along with lower trabecular separation and bone marrow adiposity. These protective effects of JPE on bone tissue are due to its ability to prevent the imbalance between osteoblast and adipocyte differentiation of MSCs, since, compared with MSCs derived from ovariectomized rats treated with vehicle, MSCs treated with JPE exhibited higher gene and protein expression of osteogenic markers and extracellular matrix mineralization, as well as lower gene expression of adipogenic markers. These data highlight the potential therapeutic use of JPE to prevent osteoporosis.

Effectiveness of bone-filled mesh bag technology and angle vertebroplasty in the treatment of osteoporotic thoracic vertebral compression fractures in the elderly

OBJECTIVE

To evaluate the effectiveness, pain level, and lung function in elderly patients with osteoporotic thoracic vertebral compression fractures using bone filling mesh bag technology compared to curved vertebroplasty.

METHODS

This retrospective analysis reviewed 72 elderly patients with osteoporotic thoracic vertebral compression fractures treated at Xindu District People's Hospital of Chengdu between February 2021 and January 2022. The patients were separated into two groups according to surgery approach: an observation group using bone filling mesh bag technology and a control group using curved vertebroplasty. The overall response rate, pain degree, pulmonary function, life quality grades, surgical indicators, and bone cement leakage rates of the two groups were evaluated.

RESULTS

The variation in overall response rate (P=0.420), pain degree (P=0.270), pulmonary function (peak expiratory flow: P=0.660, forced expiratory volume in the first second: P=0.775, forced vital capacity: 0.062), and life quality grades (physical health: P=0.949, social function: P=0.935, physiological function: P=0.970, vitality: P=0.778) between the observation group and the control group after treatment was not statistically meaningful. The Cobb angle (P<0.001) and vertebral height (P<0.001) of patients in the observation group were significantly higher than those in the control group after therapy. The leakage rates of bone cement (intervertebral disc leakage, paravertebral vein leakage, paravertebral soft tissue leakage) of patients in the observation group were notably lower than those in the control group after therapy (P=0.029).

CONCLUSION

Bone filling mesh bag technology offers significant improvements in Cobb angle and vertebral height for treating elderly patients with osteoporotic thoracic vertebral compression fractures, and reduced the leakage rate of bone cement. This technique achieves comparable therapeutic outcomes to curved vertebroplasty.

Integrated analysis of genes shared between type 2 diabetes mellitus and osteoporosis

Background

The relationship between type 2 diabetes mellitus (T2DM) and osteoporosis (OP) has been widely recognized in recent years, but the mechanism of interaction remains unknown. The aim of this study was to investigate the genetic features and signaling pathways that are shared between T2DM and OP.

Methods

We analyzed the GSE76894 and GSE76895 datasets for T2DM and GSE56815 and GSE7429 for OP from the Gene Expression Omnibus (GEO) database to identify shared genes in T2DM and OP, and we constructed coexpression networks based on weighted gene coexpression network analysis (WGCNA). Shared genes were then further analyzed for functional pathway enrichment. We selected the best common biomarkers using the least absolute shrinkage and selection operator (LASSO) algorithm and validated the common biomarkers, followed by RT-PCR, immunofluorescence, Western blotting, and enzyme-linked immunosorbent assay (ELISA) to validate the expression of these hub genes in T2DM and OP mouse models and patients.

Results

We found 8,506 and 2,030 DEGs in T2DM and OP, respectively. Four modules were identified as significant for T2DM and OP using WGCNA. A total of 19 genes overlapped with the strongest positive and negative modules of T2DM and OP. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed these genes may be involved in pantothenate and CoA biosynthesis and the glycosaminoglycan biosynthesis-chondroitin sulfate/dermatan sulfate and renin-angiotensin system signaling pathway. The LASSO algorithm calculates the six optimal common biomarkers. RT-PCR results show that LTB, TPBG, and VNN1 were upregulated in T2DM and OP. Immunofluorescence and Western blot show that VNN1 is upregulated in the pancreas and bones of T2DM model mice and osteoporosis model mice. Similarly, the level of VNN1 in the sera of patients with T2DM, OP, and T2DM and OP was higher than that in the healthy group.

Conclusion

Based on the WGCNA and LASSO algorithms, we identified genes and pathways that were shared between T2DM and OP. Both pantothenate and CoA biosynthesis and the glycosaminoglycan biosynthesis-chondroitin sulfate/dermatan sulfate and renin-angiotensin systems may be associated with the pathogenesis of T2DM and OP. Moreover, VNN1 may be a potential diagnostic marker for patients with T2DM complicated by OP. This study provides a new perspective for the systematic study of possible mechanisms of combined OP and T2DM.

Osteoporosis, Osteoarthritis, and Subchondral Insufficiency Fracture: Recent Insights

The increased incidence of osteoarthritis (OA), particularly knee and hip OA, and osteoporosis (OP), owing to population aging, have escalated the medical expense burden. Osteoarthritis is more prevalent in older women, and the involvement of subchondral bone fragility spotlights its association with OP. Notably, subchondral insufficiency fracture (SIF) may represent a more pronounced condition of OA pathophysiology. This review summarizes the relationship between OA and OP, incorporating recent insights into SIF. Progressive SIF leads to joint collapse and secondary OA and is associated with OP. Furthermore, the thinning and fragility of subchondral bone in early-stage OA suggest that SIF may be a subtype of OA (osteoporosis-related OA, OPOA) characterized by significant subchondral bone damage. The high bone mineral density observed in OA may be overestimated due to osteophytes and sclerosis and can potentially contribute to OPOA. The incidence of OPOA is expected to increase along with population aging. Therefore, prioritizing OP screening, early interventions for patients with early-stage OA, and fracture prevention measures such as rehabilitation, fracture liaison services, nutritional management, and medication guidance are essential.

Deep learning in the radiologic diagnosis of osteoporosis: a literature review

OBJECTIVE

Osteoporosis is a systemic bone disease characterized by low bone mass, damaged bone microstructure, increased bone fragility, and susceptibility to fractures. With the rapid development of artificial intelligence, a series of studies have reported deep learning applications in the screening and diagnosis of osteoporosis. The aim of this review was to summary the application of deep learning methods in the radiologic diagnosis of osteoporosis.

METHODS

We conducted a two-step literature search using the PubMed and Web of Science databases. In this review, we focused on routine radiologic methods, such as X-ray, computed tomography, and magnetic resonance imaging, used to opportunistically screen for osteoporosis.

RESULTS

A total of 40 studies were included in this review. These studies were divided into three categories: osteoporosis screening (n = 20), bone mineral density prediction (n = 13), and osteoporotic fracture risk prediction and detection (n = 7).

CONCLUSIONS

Deep learning has demonstrated a remarkable capacity for osteoporosis screening. However, clinical commercialization of a diagnostic model for osteoporosis remains a challenge.

Predicting Osteoporotic Fracture in Patients With Early-Stage Diabetic Kidney Disease Using a Radiomic Model: A Longitudinal Cohort Study

OBJECTIVE

There is an urgent need for effective predictive strategies to accurately evaluate the risk of fragility fractures in elderly patients in the early stages of diabetic kidney disease (DKD).

METHODS

This longitudinal cohort study included 715 older patients in the early stages of DKD diagnosed between January 2015 and August 2019. Patients were randomly allocated to a training cohort (n = 499) and a validation cohort (n = 216). The least absolute shrinkage and selection operator method was used to select key features for dual-energy x-ray absorptiometry-based radiomic analysis. A radiomic model was constructed using Cox proportional hazards regression. The performance of the radiomic model was compared with that of traditional fracture assessment tools through a receiver operating characteristic curve, calibration curve, and decision curve analysis.

RESULTS

Over a mean follow-up period of 4.72 ± 1.60 years, 65 participants (9.09%) experienced incident fragility fractures. Seventeen features were ultimately selected to create the radiomic model. The calibration plots of this model demonstrated satisfactory agreement between the observed and predicted outcomes. Moreover, the radiomic model outperformed traditional fracture assessment tools in both the training and validation cohorts according to the area under the receiver operating characteristic curve and decision curve analysis.

CONCLUSIONS

The novel radiomic model has demonstrated a more effective prediction of fragility fracture in elderly patients in the early stages of DKDcompared to traditional fracture assessment tools.

Radiofrequency Echographic Multispectrometry (REMS) can Overcome the Effects of Structural Internal Artifacts and Evaluate Bone Fragility Accurately

PURPOSE

This study measured bone mineral density (BMD) in a Japanese population using the novel non-ionizing system using radiofrequency echographic multispectrometry (REMS) and compared the results with those obtained using traditional dual-energy X-ray absorptiometry (DXA). We aimed to identify any discrepancies between measurements obtained using these instruments and identify the influencing factors.

METHODS

This cross-sectional study examined patients with osteoporosis treated at a single center from April to August 2023. We examined BMD assessment by DXA and REMS in lumbar spine and proximal femur. Patients were categorized into two groups: those with discrepancies between lumbar spine BMD measured by DXA and REMS, and those without. Semiquantitative evaluation of vertebral fractures and abdominal aortic calcification scoring were also performed and compared between the two groups, along with various patient characteristics.

RESULTS

A total of 70 patients (88.6% female; mean age 78.39 ± 9.50 years) undergoing osteoporosis treatment were included in the study. A significant difference was noted between DXA and REMS measurement of BMD and T-scores, with REMS recording consistently lower values. The discrepancy group exhibited a higher incidence of multiple vertebral fractures and increased vascular calcification than the non-discrepancy group. Multivariate analysis indicated that diabetes mellitus, severe vertebral fractures, and increased abdominal aortic calcification scores were significantly associated with discrepancies in lumbar spine T-scores.

CONCLUSION

This study suggests that REMS may offer a more accurate measurement of BMD, overcoming the overestimation of BMD by DXA owing to factors such as vertebral deformities, abdominal aortic calcification, and diabetes mellitus.

The Association Between SHBG and Osteoporosis: A NHANES Cross-Sectional Study and A Bidirectional Mendelian Randomization

This study aimed to examine the association between sex hormone-binding globulin (SHBG) and osteoporosis through a cross-sectional study and a two-sample bidirectional Mendelian randomization (MR). We used the National Health and Nutrition Examination Survey (NHANES) 2013-2014 and 2015-2016 data, with exposure as serum SHBG and outcome as osteoporosis and performed multivariate logistic regression to test the correlation between SHBG and osteoporosis. To determine the causal relationship between SHBG and osteoporosis, a two-sample bidirectional MR was employed. The genome-wide association study (GWAS) dataset for SHBG (n = 189,473) was obtained from the IEU database, and the GWAS dataset for osteoporosis (n = 212,778) was obtained from the FinnGen bioBank. The principal MR technique was inverse-variance weighting (IVW). In MR analyses, the MR-Egger intercept and Cochran Q test were used to detect multiple validity and horizontal heterogeneity. 1249 older adult participants (age ≥ 60) were involved in the cross-sectional study, including 113 osteoporosis cases. We identified a significant relationship between circulating SHBG concentration and osteoporosis risk [OR 3.963, 95% CI (2.095-7.495), P < 0.05]. Subgroup analysis indicated that SHBG was closely linked to the risk of osteoporosis in the female population [OR 1.008, 95% CI (1.002-1.013), P = 0.005] but not in males (P = 0.065). In addition, The IVW approach suggested a causal connection between SHBG and increased osteoporosis risk [OR 1.479, 95% CI (1.144-1.912), P = 0.003], and the MR-Egger intercept and the Cochran Q test validated the consistency of the MR results. Finally, the reverse MR analysis declined to identify a causal relation between SHBG and osteoporosis. Our research demonstrates a significant causal connection between circulating SHBG levels and increased osteoporosis risk. These results indicate that high SHBG may be associated with the risk of osteoporosis in postmenopausal women, but more research is needed.

Insights and implications of sexual dimorphism in osteoporosis

Osteoporosis, a metabolic bone disease characterized by low bone mineral density and deterioration of bone microarchitecture, has led to a high risk of fatal osteoporotic fractures worldwide. Accumulating evidence has revealed that sexual dimorphism is a notable feature of osteoporosis, with sex-specific differences in epidemiology and pathogenesis. Specifically, females are more susceptible than males to osteoporosis, while males are more prone to disability or death from the disease. To date, sex chromosome abnormalities and steroid hormones have been proven to contribute greatly to sexual dimorphism in osteoporosis by regulating the functions of bone cells. Understanding the sex-specific differences in osteoporosis and its related complications is essential for improving treatment strategies tailored to women and men. This literature review focuses on the mechanisms underlying sexual dimorphism in osteoporosis, mainly in a population of aging patients, chronic glucocorticoid administration, and diabetes. Moreover, we highlight the implications of sexual dimorphism for developing therapeutics and preventive strategies and screening approaches tailored to women and men. Additionally, the challenges in translating bench research to bedside treatments and future directions to overcome these obstacles will be discussed.

Bone-Targeted Nanoparticle Drug Delivery System-Mediated Macrophage Modulation for Enhanced Fracture Healing

Despite decades of progress, developing minimally invasive bone-specific drug delivery systems (DDS) to improve fracture healing remains a significant clinical challenge. To address this critical therapeutic need, nanoparticle (NP) DDS comprised of poly(styrene-alt-maleic anhydride)-b-poly(styrene) (PSMA-b-PS) functionalized with a peptide that targets tartrate-resistant acid phosphatase (TRAP) and achieves preferential fracture accumulation has been developed. The delivery of AR28, a glycogen synthase kinase-3 beta (GSK3β) inhibitor, via the TRAP binding peptide-NP (TBP-NP) expedites fracture healing. Interestingly, however, NPs are predominantly taken up by fracture-associated macrophages rather than cells typically associated with fracture healing. Therefore, the underlying mechanism of healing via TBP-NP is comprehensively investigated herein. TBP-NPAR28 promotes M2 macrophage polarization and enhances osteogenesis in preosteoblast-macrophage co-cultures in vitro. Longitudinal analysis of TBP-NPAR28 -mediated fracture healing reveals distinct spatial distributions of M2 macrophages, an increased M2/M1 ratio, and upregulation of anti-inflammatory and downregulated pro-inflammatory genes compared to controls. This work demonstrates the underlying therapeutic mechanism of bone-targeted NP DDS, which leverages macrophages as druggable targets and modulates M2 macrophage polarization to enhance fracture healing, highlighting the therapeutic benefit of this approach for fractures and bone-associated diseases.

Global Publication Trends and Research Hotspots of the Immune System and Osteoporosis: A Bibliometric and Visualization Analysis from 2012 to 2022

BACKGROUND

Osteoporosis (OP) is a systemic bone metabolism disorder in which the immune system and bone metabolism interact.

OBJECTIVE

The purpose of this study was to explore the research status, hot spots and trends regarding the influence of the immune system on OP and to provide a basis for research directions and applications in this field.

METHODS

We searched and collected literature about the immune system and OP published from 2012 to 2022 in the Web of Science Core Collection database. All the included studies were subjected to bibliometrics analysis using Hiplot Pro, VOSviewer and CiteSpace software to produce statistics and visual analyses of the literature output, countries, institutions, authors, keywords and journals.

RESULTS

A total of 1201 papers were included, and the number of citations of these articles reached 31,776. The number of publications and citations on the immune system and OP has increased year by year. The top three countries with the greatest number of papers published were China, the United States of America (USA) and Italy. The two institutions with the largest number of papers published were Sichuan University and Soochow University, both located in China. De Martinis Massimo (Italy) and Ginaldi Lia (Italy) are prolific authors in this field. The representative academic journals are Osteoporosis International, Frontiers in Immunology, Journal of Bone and Mineral Research, PloS One and Bone. The results of the keyword cooccurrence analysis showed that the research topics in this field mainly focused on T cells, cytokines, signaling pathways, vitamin D, postmenopausal OP and immune diseases. The keyword burst results showed that zoledronic acid, chain fatty acids and gut microbiota are the frontiers and trends of future research on this topic.

CONCLUSION

The influence of the immune system on OP has been widely studied, and the current research in this field focuses on the effect or mechanism of immune-related cytokines, signaling pathways and vitamin D on OP. Future research trends in this field should focus on the immune regulation mechanism and clinical transformation of zoledronic acid, chain fatty acids and the gut microbiota in OP.

Plasma serotonin precursors and metabolite are correlated with bone mineral density and bone turnover markers in patients with postmenopausal osteoporosis

BACKGROUND

Serotonin (5-HT) precursors regulate bone remodeling. This study aims to investigate the correlation of plasma 5-HT precursors and metabolite with bone mineral density (BMD) and bone turnover markers in postmenopausal osteoporosis (PMOP) patients.

METHODS

The age, body mass index (BMI), and years since menopause (YSM) were documented for 348 postmenopausal women in normal/osteopenia/osteoporosis (OP) groups, with lumbar spine and femoral neck BMD measured. Serum bone turnover markers (PINP/β-CTX) and plasma 5-HT, 5-HT precursors (Trp/5-HTP) and metabolite (5-HIAA) were measured by ELISA. OP patients were allocated to high/low expression groups following ROC analysis of 5-HT/Trp/5-HTP/5-HIAA. The relationship of plasma 5-HT/Trp/5-HTP/5-HIAA, BMD, and bone turnover markers with PMOP was analyzed using logistic regression analysis. The correlation of plasma 5-HT/Trp/5-HTP/5-HIAA with BMD and bone turnover markers was analyzed using Pearson's correlation analysis, followed by logistic regression analysis of the relationship between plasma 5-HT/Trp/5-HTP/5-HIAA and BMD, bone turnover markers and PMOP.

RESULTS

BMI, YSM, BMD and PINP, and β-CTX levels differed among groups. Levels of plasma 5-HT precursors/metabolite were increased in OP patients. Individuals with high 5-HT precursors/metabolite levels had low BMD and high PINP/β-CTX levels. The 5-HT precursors/metabolite negatively-correlated with BMD and positively-correlated with PINP/β-CTX. BMI, YSM, BMD, and PINP/β-CTX/Trp/5-HTP/5-HT related to PMOP and were independent risk factors for OP.

CONCLUSION

Plasma 5-HT precursors and metabolite negatively-correlate with BMD and positively-correlate with PINP/β-CTX in PMOP patients. Peripheral 5-HT precursors and metabolite level may be a new direction of treatment of PMOP and bone metabolism-related disorders.

Assessment of spatially offset Raman spectroscopy to detect differences in bone matrix quality

Since spatially offset Raman spectroscopy (SORS) can acquire biochemical measurements of tissue quality through light scattering materials, we investigated the feasibility of this technique to acquire Raman bands related to the fracture resistance of bone. Designed to maximize signals at different offsets, a SORS probe was used to acquire spectra from cadaveric bone with and without skin-like tissue phantoms attenuating the light. Autoclaving the lateral side of femur mid-shafts from 5 female and 5 male donors at 100 °C and again at 120 °C reduced the yield stress of cortical beams subjected to three-point bending. It did not affect the volumetric bone mineral density or porosity. Without tissue phantoms, autoclaving affected more Raman characteristics of the organic matrix when determined by peak intensity ratios, but fewer matrix properties depended on the three offsets (5 mm, 6 mm, and 7 mm) when determined by band area ratios. The cut-off in the thickness of the tissue phantom layers was ∼4 mm for most properties, irrespective of offset. Matching trends when spectra were acquired without phantom layers between bone and the probe, ν1PO43-/Amide III and ν1PO43-/(proline + OH-proline) were higher and lower in the non-treated bone than in the autoclaved bone, respectively, when the thickness of tissue phantom layers was 4 mm. The layers, however, caused a loss of sensitivity to autoclaving-related changes in ν3CO3/ν1PO43- and crystallinity. Without advanced post-processing of Raman spectra, SORS acquisition through turbid layers can detect changes in Raman properties of bone that accompany a loss in bone strength.

Introduction to Osteoporosis, Osteomalacia, and Fragility Fractures

Background

Osteoporosis is a disease of the bones leading to decreased bone mineral density, leading to fragility fractures. This article is an overview of osteoporosis, osteomalacia and fragility fractures and serves as an introductory article for this special issue on osteoporosis.

Methods

This is a short, comprehensive account of the given conditions with concepts and a review from the recent literature. The authors provide relevant references from the literature in the bibliography. The sections herein have also been deliberated in the meetings of experts of osteoporosis.

Results

An overview of osteoporosis, osteomalacia and fragility fractures is provided, including definitions and summaries of aetiology, pathophysiology, diagnosis, prevention, and management. A detailed account of some of these topics will be provided in subsequent chapters.

Conclusion

Osteoporosis is a silent disease with the potential to cause significant morbidity and mortality if not detected early. It is important to differentiate from and diagnose associated osteomalacia to provide accurate therapy. It is also important to identify the type of fragility fractures and initiate treatment for bone strengthening to prevent subsequent fractures.

Demystifying the Risk Factors and Preventive Measures for Osteoporosis

Background

Osteoporosis is a major health problem, globally. It is characterized by structural bone weakness leading to an increased risk of fragility fractures. These fractures commonly affect the spine, hip and wrist bones. Consequently, Osteoporosis related proximal femur and vertebral fractures represent a substantial, growing social and economic burden on healthcare systems worldwide. Indentification of the risk factors, clinical risk assessment, utilization of risk assessment tools and appropriate management that play a crucial role in reducing the burden of Osteoporosis by tackling modifiable risk factors.

Methods

This chapter explores various risk factors that are associated with Osteoporosis and provides an overview of various clinical and diagnostic risk assessment tools with a particular emphasis on evidence-based strategies for their prevention.

Conclusion

The role of emerging technologies such as Artificial Intelligence (AI) and perspectives such as newer diagnostic modalities, monitoring and surveillance approaches in prevention of risk factors in the pathogenesis of Osteoporosis is highlighted.

E, Wang T, Carey JJ, Whelan B, Silke C, O’Sullivan M, Gsel A, Brennan A, Dempsey M, Yu M. Bone mineral density and fractures in patients with rheumatoid arthritis: the DXA-HIP project

Objectives

RA is a chronic disabling disease affecting 0.5-1% of adults worldwide. People with RA have a greater prevalence of multimorbidity, particularly osteoporosis and associated fractures. Recent studies suggest that fracture risk is related to both non-RA and RA factors, whose importance is heterogeneous across studies. This study seeks to compare baseline demographic and DXA data across three cohorts: healthy controls, RA patients and a non-RA cohort with major risk factors and/or prior major osteoporotic fracture (MOF).

Methods

This is a cross-sectional study using data collected from three DXA centres in the west of Ireland from January 2000 to November 2018.

Results

Data were available for 30 503 subjects who met our inclusion criteria: 9539 (31.3%) healthy controls, 1797 (5.9%) with RA and 19 167 (62.8%) others. Although age, BMI and BMD were similar between healthy controls, the RA cohort and the other cohort, 289 (16.1%) RA patients and 5419 (28.3%) of the non-RA cohort had prior MOF. In the RA and non-RA cohorts, patients with previous MOF were significantly older and had significantly lower BMD at the femoral neck, total hip and spine.

Conclusion

Although age, BMI and BMD were similar between a healthy control cohort and RA patients and others with major fracture risk factors, those with a previous MOF were older and had significantly lower BMD at all three measured skeletal sites. Further studies are needed to address the importance of these and other factors for identifying those RA patients most likely to experience fractures.

Long-term and sequential treatment for osteoporosis

Osteoporosis is a skeletal disorder that causes impairment of bone structure and strength, leading to a progressively increased risk of fragility fractures. The global prevalence of osteoporosis is increasing in the ageing population. Owing to the chronic character of osteoporosis, years or even decades of preventive measures or therapy are required. The long-term use of bone-specific pharmacological treatment options, including antiresorptive and/or osteoanabolic approaches, has raised concerns around adverse effects or potential rebound phenomena after treatment discontinuation. Imaging options, risk scores and the assessment of bone turnover during initiation and monitoring of such therapies could help to inform individualized treatment strategies. Combination therapies are currently used less often than 'sequential' treatments. However, all patients with osteoporosis, including those with secondary and rare causes of osteoporosis, as well as specific patient populations (for example, young adults, men and pregnant women) require new approaches for long-term therapy and disease monitoring. New pathophysiological aspects of bone metabolism might therefore help to inform and revolutionize the diagnosis and treatment of osteoporosis.

Immune-related gene IL17RA as a diagnostic marker in osteoporosis

Objectives: Bone immune disorders are major contributors to osteoporosis development. This study aims to identify potential diagnostic markers and molecular targets for osteoporosis treatment from an immunological perspective. Method: We downloaded dataset GSE56116 from the Gene Expression Omnibus database, and identified differentially expressed genes (DEGs) between normal and osteoporosis groups. Subsequently, differentially expressed immune-related genes (DEIRGs) were identified, and a functional enrichment analysis was performed. A protein-protein interaction network was also constructed based on data from STRING database to identify hub genes. Following external validation using an additional dataset (GSE35959), effective biomarkers were confirmed using RT-qPCR and immunohistochemical (IHC) staining. ROC curves were constructed to validate the diagnostic values of the identified biomarkers. Finally, a ceRNA and a transcription factor network was constructed, and a Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis was performed to explore the biological functions of these diagnostic markers. Results: In total, 307 and 31 DEGs and DEIRGs were identified, respectively. The enrichment analysis revealed that the DEIRGs are mainly associated with Gene Ontology terms of positive regulation of MAPK cascade, granulocyte chemotaxis, and cytokine receptor. protein-protein interaction network analysis revealed 10 hub genes: FGF8, KL, CCL3, FGF4, IL9, FGF9, BMP7, IL17RA, IL12RB2, CD40LG. The expression level of IL17RA was also found to be significantly high. RT-qPCR and immunohistochemical results showed that the expression of IL17RA was significantly higher in osteoporosis patients compared to the normal group, as evidenced by the area under the curve Area Under Curve of 0.802. Then, we constructed NEAT1-hsa-miR-128-3p-IL17RA, and SNHG1-hsa-miR-128-3p-IL17RA ceRNA networks in addition to ERF-IL17RA, IRF8-IL17RA, POLR2A-IL17RA and ERG-IL17RA transcriptional networks. Finally, functional enrichment analysis revealed that IL17RA was involved in the development and progression of osteoporosis by regulating local immune and inflammatory processes in bone tissue. Conclusion: This study identifies the immune-related gene IL17RA as a diagnostic marker of osteoporosis from an immunological perspective, and provides insight into its biological function.

In Vitro Evaluation of Ag- and Sr-Doped Hydroxyapatite Coatings for Medical Applications

Osseointegration plays the most important role in the success of an implant. One of the applications of hydroxyapatite (HAp) is as a coating for metallic implants due to its bioactive nature, which improves osteoconduction. The purpose of this research was to assess the in vitro behavior of HAp undoped and doped with Ag and/or Sr obtained by galvanostatic pulsed electrochemical deposition. The coatings were investigated in terms of chemical bonds, contact angle and surface free energy, electrochemical behavior, in vitro biomineralization in acellular media (SBF and PBS), and biocompatibility with preosteoblasts cells (MC3T3-E1 cell line). The obtained results highlighted the beneficial impact of Ag and/or Sr on the HAp. The FTIR spectra confirmed the presence of hydroxyapatite within all coatings, while in terms of wettability, the contact angle and surface free energy investigations showed that all surfaces were hydrophilic. The in vitro behavior of MC3T3-E1 indicated that the presence of Sr in the HAp coatings as a unique doping agent or in combination with Ag elicited improved cytocompatibility in terms of cell proliferation and osteogenic differentiation. Therefore, the composite HAp-based coatings showed promising potential for bone regeneration applications.

End to End Multitask Joint Learning Model for Osteoporosis Classification in CT Images

Osteoporosis is a significant global health concern that can be difficult to detect early due to a lack of symptoms. At present, the examination of osteoporosis depends mainly on methods containing dual-energyX-ray, quantitative CT, etc., which are high costs in terms of equipment and human time. Therefore, a more efficient and economical method is urgently needed for diagnosing osteoporosis. With the development of deep learning, automatic diagnosis models for various diseases have been proposed. However, the establishment of these models generally requires images with only lesion areas, and annotating the lesion areas is time-consuming. To address this challenge, we propose a joint learning framework for osteoporosis diagnosis that combines localization, segmentation, and classification to enhance diagnostic accuracy. Our method includes a boundary heat map regression branch for thinning segmentation and a gated convolution module for adjusting context features in the classification module. We also integrate segmentation and classification features and propose a feature fusion module to adjust the weight of different levels of vertebrae. We trained our model on a self-built dataset and achieved an overall accuracy rate of 93.3% for the three label categories (normal, osteopenia, and osteoporosis) in the testing datasets. The area under the curve for the normal category is 0.973; for the osteopenia category, it is 0.965; and for the osteoporosis category, it is 0.985. Our method provides a promising alternative for the diagnosis of osteoporosis at present.

Lactobacillus acidophilus (LA) Fermenting Astragalus Polysaccharides (APS) Improves Calcium Absorption and Osteoporosis by Altering Gut Microbiota

Lactobacillus acidophilus (LA) and Astragalus polysaccharides (APS) have each been shown to have anti-osteoporotic activity, and the aim of this study was to further investigate whether the LA fermenting APS was more effective in improving calcium absorption and osteoporosis than the unfermented mixed solution (MS). We found that the fermentation solution (FS) intervention improved the calcium absorption, BMD, and bone microarchitecture in osteoporotic rats and resulted in better inhibition of osteoclast differentiation markers ACP-5 and pro-inflammatory cytokines TNF-α and IL-6 and promotion of osteoblast differentiation marker OCN. This better performance may be due to the improved restoration of the relative abundance of specific bacteria associated with improved calcium absorption and osteoporosis such as Lactobacillus, Allobaculum, and UCG-005. Several key metabolites, including indicaxanthin, chlorogenic acid, and 3-hydroxymelatonin, may also be the key to the better improvement. In conclusion, the LA fermenting APS can better improve calcium absorption and osteoporosis by increasing active metabolites and altering gut microbiota. This finding should become a solid foundation for the development of LA fermenting APS in functional foods.

The Dietary and Non-Dietary Management of Osteoporosis in Adult-Onset Celiac Disease: Current Status and Practical Guidance

Impaired bone mineral density (BMD) is a frequent complication of adult-onset celiac disease (CeD). This is usually due to malabsorption of nutrients, changes in bone metabolism in association with inflammation, and to a lesser extent, decreased overall physical health and mobility. This review aims to highlight the current status concerning surveillance, prevention, and treatment strategies for bone disease in CeD. A practical guidance on these matters is suggested. The available published research on the prevention and treatment of decreased BMD in relation to CeD is scarce. In general, publications were based on expert opinions or extrapolation from studies on postmenopausal women or inflammatory bowel disease. Optimal dietary treatment and an adequate supply of calcium and vitamin D are the cornerstones for the reduction in fracture risk in patients with CeD. In adults with low BMD or fragility fractures, CeD needs to be considered and specifically approached. When osteoporosis is documented, start treatment with an antiresorptive agent; these agents are proven to result in a long-term reduction in fracture risk in high-risk individuals. However, there are some important differences between the management of male and female patients, particularly premenopausal women, that need to be addressed. In patients with persisting diarrhea and malabsorption, parenteral medications may be preferable. Future research specifically focusing on celiac disease and the associated disorders in bone mineralization is mandatory to provide evidence-based recommendations in this field.