OBJECTIVE: Hounsfield unit (HU) values measured using CT have been increasingly recognized to stand as a reliable corollary to dual-energy x-ray absorptiometry (DEXA) scores in evaluating bone mineral density. The authors examined the correlation between cervical HU values and DEXA T- and Z-scores and determined novel cervical HU thresholds for determining bone quality classification.
METHODS: One hundred patients who underwent both cervical spine CT and DEXA, 85 patients who underwent both lumbar CT and DEXA, and 128 patients who underwent cervical and lumbar CT within 24 months at a single institution were included in this retrospective review. Two independent reviewers collected HU values from 3 cervical vertebral levels (C4-6) and 4 lumbar vertebral levels (L1-4), and the averaged values were used. Pearson\'s correlation coefficient analysis was performed to compare the association of cervical HU values with lumbar HU values and T- and Z-scores. The mean cervical HU values for each DEXA classification were calculated and compared. Receiver operating characteristic (ROC) curves were created to determine the threshold and its sensitivity and specificity for diagnosis.
RESULTS: Cervical (C4-6) HU values and average, lumbar, and femoral T- and Z-scores had significant correlations (0.436 > r > 0.274, all p < 0.01). A strong positive correlation between cervical and lumbar HU values was found (r = 0.79, p < 0.01). The average cervical HU value of healthy patients was 361.2 (95% CI 337.1-385.3); of osteopenic patients, 312.1 (95% CI 290.3-333.8); and of osteoporotic patients, 288.4 (95% CI 262.6-314.3). There was a significant difference between the cervical HU values of healthy and osteopenic patients (p = 0.0134) and between those of healthy and osteoporotic patients (p = 0.0304). The cervical HU value of 340.98 was 73.5% specific and 57.9% sensitive for diagnosing osteopenia with an area under the ROC (AUROC) curve of 0.655. The cervical HU value of 326.5 was 88.9% specific and 63.2% sensitive for diagnosing osteoporosis with an AUROC curve of 0.749.
CONCLUSIONS: This is the second large-scale study and first with a patient population from the United States to show that HU values obtained using cervical CT were significantly correlated with bone quality based on DEXA T- and Z-scores and to establish a cervical HU threshold for determining bone quality classification. These results show that cervical HU values can and should be used to predict poor bone quality in surgical cervical spine patients.

UNASSIGNED: The arteriosclerosis index, defined as the ratio of non-high density lipoprotein cholesterol to high density lipoprotein cholesterol (NHHR), has emerged as a novel biomarker for various diseases. The relationship between NHHR and lumbar bone mineral density (BMD) has not been previously examined.
UNASSIGNED: This cross-sectional study analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018. NHHR was calculated as (total cholesterol-high-density lipoprotein cholesterol)/high-density lipoprotein cholesterol. Lumbar BMD was calculated to Z scores. Weighted multivariate linear regression, subgroup analysis, interaction analysis, generalized additive model, and two-piecewise linear regression were used.
UNASSIGNED: A total of 8,602 participants were included. The negative association between NHHR and lumbar BMD was consistent and significant (Model 1: β = -0.039, 95% CI: -0.055, -0.023, p < 0.001; Model 2: β = -0.045, 95% CI: -0.062, -0.027, p < 0.001; Model 3: β = -0.042, 95% CI: -0.061, -0.023, p < 0.001). The linear relationship between NHHR and lumbar BMD was significantly influenced by body mass index (p for interaction = 0.012) and hypertension (p for interaction = 0.047). Non-linear associations between NHHR and lumbar BMD Z scores were observed in specific populations, including U-shaped, reverse U-shaped, L-shaped, reverse L-shaped, and U-shaped relationships among menopausal females, underweight participants, those with impaired glucose tolerance, those with diabetes mellitus and those taking anti-hyperlipidemic drugs, respectively.
UNASSIGNED: NHHR exhibited a negative association with lumbar BMD, but varying across specific populations. These findings suggest that NHHR should be tailored to individual levels to mitigate bone loss through a personalized approach. Individuals at heightened risk of cardiovascular disease should focus on their bone health.

Machine learning (ML) models have been increasingly employed to predict osteoporosis. However, the incorporation of hair minerals into ML models remains unexplored. This study aimed to develop ML models for predicting low bone mass (LBM) using health checkup data and hair mineral analysis. A total of 1206 postmenopausal women and 820 men aged 50 years or older at a health promotion center were included in this study. LBM was defined as a T-score below - 1 at the lumbar, femur neck, or total hip area. The proportion of individuals with LBM was 59.4% (n = 1205). The features used in the models comprised 50 health checkup items and 22 hair minerals. The ML algorithms employed were Extreme Gradient Boosting (XGB), Random Forest (RF), Gradient Boosting (GB), and Adaptive Boosting (AdaBoost). The subjects were divided into training and test datasets with an 80:20 ratio. The area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and an F1 score were evaluated to measure the performances of the models. Through 50 repetitions, the mean (standard deviation) AUROC for LBM was 0.744 (± 0.021) for XGB, the highest among the models, followed by 0.737 (± 0.023) for AdaBoost, and 0.733 (± 0.023) for GB, and 0.732 (± 0.021) for RF. The XGB model had an accuracy of 68.7%, sensitivity of 80.7%, specificity of 51.1%, PPV of 70.9%, NPV of 64.3%, and an F1 score of 0.754. However, these performance metrics did not demonstrate notable differences among the models. The XGB model identified sulfur, sodium, mercury, copper, magnesium, arsenic, and phosphate as crucial hair mineral features. The study findings emphasize the significance of employing ML algorithms for predicting LBM. Integrating health checkup data and hair mineral analysis into these models may provide valuable insights into identifying individuals at risk of LBM.

UNASSIGNED: To investigate the association of the midnight cortisol level with bone mineral density (BMD) in patients with type 2 diabetes mellitus (T2DM).
UNASSIGNED: This study included 249 T2DM patients (148 males with an average age of 53.8 years and 101 postmenopausal females with an average age of 63.6 years) admitted to Xiamen Hospital of Zhongshan Hospital Affiliated to Fudan University from January 2018 to April 2020. Baseline data were compared between patients with normal BMD and those with osteoporosis/osteopenia. The patients also were divided into groups according to the tertiles of midnight cortisol levels.
UNASSIGNED: Among all T2DM, 178 had osteoporosis/osteopenia, including 98 men and 80 women. The baseline data analysis showed that patients with osteoporosis/osteopenia were more likely to be older, female, and thin, and to have high cortisol. Additionally, elevated estradiol levels had a protective effect on bone; once osteoporosis/osteopenia occurred, the probability of severe osteoporotic fracture was significantly increased. The BMD of the femoral neck, hip joint and lumbar spine decreased with increasing midnight cortisol level in men, postmenopausal women, and all T2DM patients (P<0.05). Multivariate logistic regression analysis identified body mass index, estradiol level, and midnight cortisol level as independent risk factors for osteoporosis/osteopenia in T2DM patients.
UNASSIGNED: Higher midnight cortisol levels are significantly associated with increased risk of osteoporosis/osteopenia in T2DM patients. Thus, the midnight cortisol level represents a valuable marker for assessing osteoporosis/osteopenia risk in these patients.

UNASSIGNED: Despite the increasing availability of therapeutic drugs for autoimmune diseases, many patients still struggle to achieve their treatment goals. Our aim was to identify whether drugs originally used to treat bone density could be applied to the treatment of autoimmune diseases through Mendelian randomization (MR).
UNASSIGNED: Using summary statistics from genome-wide association studies, we used a two-sample MR design to estimate the correlation between autoimmune diseases and BMD-related drug targets. Data from the DrugBank and ChEMBL databases were used to identify the drug targets of anti-osteoporosis medications. The Wald ratio test or inverse-variance weighting method was used to assess the impact of genetic variation in drug target(s) on autoimmune disease therapy.
UNASSIGNED: Through our analysis, we discovered a negative correlation between genetic variability in a specific gene (ESR1) in raloxifene/colecalciferol and various autoimmune disorders such as ankylosing spondylitis, endometriosis, IgA nephropathy, rheumatoid arthritis, sarcoidosis, systemic lupus erythematosus, and type 1 diabetes.
UNASSIGNED: These results indicate a possible link between genetic differences in the drug targeting ESR1 and susceptibility to autoimmune disorders. Hence, our study offers significant support for the possible use of drugs targeting ESR1 for the management of autoimmune disorders. MR and drug repurposing are utilized to investigate the relationship between autoimmune diseases and bone mineral density, with a focus on ESR1.

BACKGROUND: Our primary goal was to investigate the independent and combined associations of physical activity (PA) and sitting time (ST) with femoral bone health among cancer survivors aged 60 or older.
METHODS: This cross-sectional study included 1159 cancer survivors aged 60 years or older who underwent femur dual-energy X-ray absorptiometry (DXA) examination from continuous National Health and Nutrition Examination Survey data sets. PA and ST were assessed by self-report, and bone health included bone mineral density (BMD) at all femoral sub-regions, osteopenia/osteoporosis of femoral neck, and total fracture. The independent and combined associations of PA and ST with femoral bone health were determined using multivariable linear or logistic regression analyses.
RESULTS: More than 40% cancer survivors reported engaging in PA < 150 min/week with ST ≥ 6 h/d. PA solely showed no association with bone health at femur sites. Prolonged ST was associated with lower femur\'s BMD, higher prevalence of osteopenia/osteoporosis, and total fracture. Specifically, the negative association of prolonged ST and femur\'s BMD was shown in PA ≥ 150 min/week group, but not in PA < 150 min/week group. In combined analysis, prolonged ST with PA ≥ 150 min/week showed the strongest negative associations with femur\'s BMD.
CONCLUSIONS: PA appears not to be directly associated with femoral bone health. Higher ST is associated with lower BMD and a higher incidence of total fractures, regardless of PA level, among cancer survivors aged 60 or older.

BACKGROUND: Numerous studies have shown that various cytokines are important factors affecting bone mineral density (BMD), but the causality between the two remains uncertain.
METHODS: Genetic variants associated with 41 circulating cytokines from a genome-wide association study (GWAS) in 8,293 Finns were used as instrumental variables (IVs) for a two-sample Mendelian randomization (MR) analysis. Inverse variance weighting (IVW) was employed as the primary method to investigate whether the 41 cytokines were causally associated with BMD at five different sites [total body bone mineral density (TB-BMD), heel bone mineral density (HE-BMD), forearm bone mineral density (FA-BMD), femoral neck bone mineral density (FN-BMD), and lumbar spine bone mineral density (LS-BMD)]. Weighted median and MR-Egger were chosen to further confirm the robustness of the results. We performed MR pleiotropy residual sum and outlier test (MR-PRESSO), MR-Egger regression, and Cochran\'s Q test to detect pleiotropy and sensitivity testing.
RESULTS: After Bonferroni correction, two circulating cytokines had a strong causality with BMD at corresponding sites. Genetically predicted circulating hepatocyte growth factor (HGF) levels and HE-BMD were negatively correlated [β (95 % CI) -0.035(-0.055, -0.016), P=0.00038]. Circulating macrophage inflammatory protein-1α (MIP-1α) levels and TB-BMD were negatively correlated [β(95 %CI): -0.058(-0.092, -0.024), P=0.00074]. Weighted median and MR-Egger results were in line with the IVW results. We also found suggestive causal relationship (IVW P<0.05) between seven circulating cytokines and BMD at corresponding sites. No significant pleiotropy or heterogeneity was observed in our study.
CONCLUSIONS: Our MR analyses indicated a causal effect between two circulating cytokines and BMD at corresponding sites (HGF and HE-BMD, MIP-1α and TB-BMD), along with suggestive evidence of a potential causality between seven cytokines and BMD at the corresponding sites. These findings would provide insights into the prevention and treatment of osteoporosis, especially immunoporosis.

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Glucocorticoid (GC) therapy remains the cornerstone of treatment for many conditions of childhood and an important cause of skeletal and endocrine morbidity. Here, we discuss cases that bring to life the most important concepts in the management of pediatric GC-induced osteoporosis (pGIO). Given the wide variety of underlying conditions linked to pGIO, we focus on the fundamental clinical-biological principles that provide a blueprint for management in any clinical context. In so doing, we underscore the importance of longitudinal vertebral fracture phenotyping, how knowledge about the timing and risk of fractures influences monitoring, the role of bone mineral density in pGIO assessments, and the impact of growth-mediated \"vertebral body reshaping\" after spine fractures on the therapeutic approach. Overall, pGIO management is predicated upon early identification of fractures (including vertebral) in those at risk, and timely intervention when there is limited potential for spontaneous recovery. Even a single, low-trauma long bone or vertebral fracture can signal an osteoporotic event in an at-risk child. The most widely used treatments for pediatric osteoporosis, intravenous bisphosphonates, are currently recommended first-line for the treatment of pGIO. It is recognized, however, that even early identification of bone fragility, combined with timely introduction of the most potent bisphosphonate therapies, may not completely prevent osteoporosis progression in all contexts. Therefore, prevention of first-ever fractures in the highest-risk settings is on the horizon, where there is also a need to move beyond anti-resorptives to the study of anabolic agents.

Background: For years, bone mineral density (BMD) has played a key role in assessing bone health, but the trabecular bone score (TBS) is emerging as an equivalent measure. However, BMD alone may not fully measure bone quality or predict osteoporosis risk. To evaluate the usefulness of TBS and BMD in estimating the risk of bone fracture in young women with FHA, this study examined the association between metabolic parameters and bone quality, which was measured using TBS and BMD. Methods: We analyzed the association of metabolic factors with tests assessing bone quality-TBS and BMD. Patients were checked for BMI, measured body fat, and determined serum glucose levels and insulin levels in a 75g glucose load test. Spearman correlation analysis was used. Results: Significant positive correlations were found between BMD and age (p < 0.001) and body fat (p < 0.001), as well as between TBS values and BMI (p < 0.001) and TBS and percent body fat (p < 0.001). Of the variables analyzed in the multivariate analysis, the only independent predictor of higher bone mineral density in the lumbar spine was found to be higher values of the trabecular bone index in the same segment (p < 0.001). Conclusions: The use of TBS provides a simple tool for estimating the risk of bone damage. Ultimately, early screening, diagnosis and treatment of patients with FHA may help prevent osteoporosis and fragility fractures in the long term.