Bone

PurposeOsteoporosis and associated hip fractures are a major public health concern. Dualenergy X-ray Absorptiometry (DXA) remains the diagnostic gold standard, but its areal (a) bone mineral density (BMD) measurements have limited sensitivity, as many fractures occur at T-scores above -2.5. Three-dimensional (3D) DXA provides compartment-specific volumetric parameters of the hip, potentially improving osteoporosis management. This study aimed to establish reference data for 3D-DXA parameters to improve osteoporosis management and investigate potential compartmental imbalances at the hip. MethodThis multicenter, cross-sectional, population-based observational study (SEIOMM-3D-DXA project), supported by the Spanish Society for Bone and Mineral Metabolism (SEIOMM), analyzed hip DXA scans from 1366 Spanish men and women across six centers. 3D-DXA analyses were conducted using the 3D-Shaper software (3D-Shaper Medical, Barcelona, Spain), producing estimates of trabecular volumetric (v) BMD and cortical surface (s) BMD. Age- and sex-specific reference curves were generated using the LMS method, and thresholds were established based on regression with T-score values. Moreover, trabecular vBMD and cortical sBMD Z-scores were calculated to evaluate potential compartmental imbalances. ResultsThe derived aBMD curves closely aligned with the NHANES III Caucasian reference. Sex-specific thresholds for trabecular vBMD and cortical sBMD were established for patient stratification. Z-score comparisons revealed significant discrepancies between trabecular and cortical compartments in 52.0% of females and 48.7% of males, underlining the importance of compartment-specific bone assessment. ConclusionsThis study establishes reference curves for clinical interpretation of 3D-DXA parameters and demonstrates the potential of 3D-DXA to capture compartmental imbalances at the hip. Mini AbstractIn this study, hip scans from over a thousand men and women in Spain were analyzed to create normative reference values for 3D-DXA parameters. These results can help doctors better stratify people based on the status of each part of the bone and improve the management of osteoporosis.

To evaluate how recent advances in deep learning can improve the construction of quantitative phenotypes for genome-wide association studies (GWAS), we focused on the context of osteoporosis and bone mineral density (BMD) measurements. We applied image classifiers and transformer models to three distinct tasks. First, we developed quantitative estimates of osteoporosis severity using bone X-ray images. Second, we compared standard approaches for handling confounding variables with a multi-factor strategy based on transformer models trained on UK Biobank data. Third, we investigated whether image-based models could predict how single nucleotide polymorphisms (SNPs) associated with BMD influence bone structure. While our results were promising, application of deep learning methods did not yield substantial improvements over established approaches. Nonetheless, our findings highlight the potential of integrating imaging and machine learning techniques to refine phenotype definitions in genetic studies.

BACKGROUNDSOsteopetrosis, a rare skeletal disease, is characterized by an increased bone mass resulting from impaired bone remodeling process. Platelet is the major bone-healing blood component involved in the regulation of bone resorption, particularly in the removal of compromised bones. Several actin-associated proteins contribute to the orchestration of actin ring formation in osteoclasts closely related to bone resorption. However, the role of coactosin-like F-actin binding protein 1 (Cotl1) in actin ring formation and platelet-mediated bone resorption mechanisms remains unclear. METHODSWhole-mount in situ RNA hybridization was performed to detect cotl1 expression pattern in zebrafish. cotl1 gene knockdown zebrafish using morpholino oligonucleotides and platelet marker-expressing transgenic zebrafish were investigated for finding the phenotypic clues. Cotl1 knockout (Cotl1-/-) mice were generated using Cre/loxP recombination systems. In silico network analysis of the differentially expressed genes between bone marrow samples of wild type and Cotl1-/- mice was conducted. Primary-cultured monocytes from Cotl1-/- mice were examined for osteoclast differentiation and mRNA and protein expression patterns. Cotl1-/- mice underwent hematological examination and bone phenotype assessments including micro-CT, bone density, histology, immunohistochemistry, electron microscopy, and mechanical testing. Genetic association of SNPs in human COTL1 gene with estimated bone mineral density was analyzed. RESULTSZebrafish cotl1 mRNA was highly expressed in the caudal hematopoietic tissue region. Knockdown of cotl1 in zebrafish embryos decreased the expression of c-myb, a marker of hematopoietic stem cells (HSCs). Notably, the platelet receptor CD41 was reduced in the HSCs of cotl1-depleted zebrafish and Cotl1-/- mice showed reduced platelet production with platelet surface markers of CD41 and CD61. Significantly reduced osteoclast differentiation and bone resorption pit, and impaired actin ring formation were observed in the primary myocytes from Cotl1-/- mice. Structural and histological analyses of the femur revealed sclerotic bone phenotypes in Cotl1-/- mice. Mechanical assessment of Cotl1-/- mouse femoral bones revealed osteopetrotic phenotypes. Association analysis of genetic variants in COTL1 gene in subjects from the UK Biobank suggested that COTL1 is susceptible to bone density in humans. CONCLUSIONSOur results provide insights into the role of Cotl1 in platelet-mediated osteoclastogenesis and the novel finding that the loss of Cotl1-/- mice causes osteopetrosis phenotypes. Clinical PerspectiveWhat Is New? O_LIDeficiency of Cotl1 decreased platelet production in zebrafish and mice. C_LIO_LIAbsence of Cotl1 disrupted the actin ring formation which is crucial for osteoclast differentiation in bone remodeling process. C_LIO_LICotl1 knockout mice displayed sclerotic bone phenotypes and increased bone density that are representative characteristics of osteopetrosis. C_LIO_LIGenetic variants in COTL1 gene in subjects from the UK Biobank are significantly associated with bone density. C_LI What Are the Clinical Implications? O_LIThe current findings suggest that Cotl1 plays a fundamental role in platelet production-mediated osteoclastogenesis during bone remodeling, providing valuable insights into novel strategies for bone health maintenance. C_LIO_LICotl1 may be a promising target for novel therapeutic strategies for the treatment and/or prevention of impaired osteoclastogenesis-mediated bone diseases such as osteopetrosis and osteoporosis. C_LI

AbstractA reliable, widely available method to detect osteoporosis prior to fracture is needed. Serum levels of C-reactive protein may independently predict low bone mineral density (BMD) and high fracture risk. Existing empirical data focus on sexually and/or racially homogenous populations. This study tests the hypotheses that: C-reactive protein (1) negatively correlates with BMD and (2) fracture history, and (3) independently predicts BMD and fracture history in a diverse population. NHANES 2017-2020 pre-pandemic cycle data were analyzed in R studio. Strength and direction of relationships (-1 to +1) between variables were determined using Kendalls rank correlation coefficient ({tau}). Linear models were optimized to predict femoral neck or lumbar spine BMD. C-reactive protein positively correlated with femoral ({tau}=0.09, p<0.0001) and spine BMD ({tau}=0.10, p<0.0001). Individuals identifying as female demonstrated more robust, but still weak, correlations between C-reactive protein and femoral neck ({tau}=0.15, p<0.0001; male, {tau}=0.06, p=0.051) and spine BMD ({tau}=0.16, p<0.0001; male, {tau}=0.06, p=0.04). C-reactive protein positively correlated with fracture history ({tau}=0.083, p=0.0009). C-reactive protein significantly predicted femoral neck (R2=0.022, p=0.0001) and spine BMD (R2=0.028, p<0.0001) and fracture history (R2=0.015, p<0.0001). Exploratory analyses identified weight was the single best predictor for femoral neck (R2=0.24, p<0.0001) and spine BMD (R2=0.21, p<0.0001). In sum, C-reactive protein statistically correlates with and predicts femoral neck and spine BMD, but the magnitude is too low to be biologically meaningful. While weight is a more robust predictor, individuals who are overweight or obese account for nearly half of all osteoporotic fractures, limiting the predictive power of this variable at identifying individuals at risk for osteoporosis. Identification of a robust predictor of fracture risk in a diverse population and across of range of body weights and compositions is needed.

BackgroundBone microarchitecture is a critical determinant of bone strength and fracture risk, yet its genetic basis and relationship to systemic health remain largely unexplored. This study aimed to identify genetic determinants of bone microarchitecture using trabecular bone score (TBS) and investigate the causal relationships between bone microarchitecture and various health outcomes. MethodsWe conducted a genome-wide association study (GWAS) of TBS in 25,268 UK Biobank participants to identify genetic loci associated with bone microarchitecture. Two-sample Mendelian randomization (MR) was employed to assess the causal relationships between systemic health risk factors and bone microarchitecture, as well as the impact of bone microarchitecture on musculoskeletal disorders. FindingsThe GWAS identified 75 significant single nucleotide polymorphisms (SNPs) across 19 genomic loci, with an estimated heritability of TBS at 24.5%. Many of these loci (18/19) were also associated with bone mineral density (BMD) and fractures, indicating a shared genetic basis for bone microarchitecture and bone mass. MR analysis revealed that rheumatoid arthritis has a significant causal effect on the deterioration of bone microarchitecture ({beta} = -0.003, P = 1.14x10-4). Suggestive associations were found between bone microarchitecture deterioration and inflammatory bowel disease, cardiovascular disease, and depression (P < 0.05). Moreover, genetically predicted TBS was significantly associated with fracture risk (OR = 0.003, P = 1.89x10-8) and suggestively associated with osteonecrosis (OR = 0.002, P = 0.040). InterpretationThis study identified novel genetic determinants of bone microarchitecture and demonstrated its association with various systemic diseases, highlighting the critical role of bone microarchitecture in skeletal health. The results advocate for the clinical use of TBS to better assess the risk of osteoporosis and fractures and to improve bone and overall health assessments. The causal effect of rheumatoid arthritis on microarchitectural deterioration underscores the need for increased monitoring of bone health in this population. FundingThis work supported by Shanghai "Rising Stars of Medical Talent" Youth Development Program, Youth Medical Talents-Specialist Program (grant number SHHWRS 2023-62), the Fundamental Research Funds for the Central Universities (grant number AF0820060), Outstanding Research-oriented Doctor Cultivation Program at the Ninth Peoples Hospital affiliated with the School of Medicine, Shanghai Jiao Tong University, National Natural Science Foundation of China (grant number 31900941).

IntroductionTrabecular bone exhibits brittle behaviour governed by microscale deformation and damage processes, yet quantitative characterisation of crack progression remains challenging because classical fracture mechanics approaches do not apply to architecturally discontinuous porous tissues. This study evaluates whether synchrotron X-ray computed tomography (XCT) combined with digital volume correlation (DVC) can provide a practical experimental approach for quantifying crack opening behaviour in human trabecular bone. MethodSemicylindrical specimens harvested from femoral heads of hip-fracture donors (n = 5) and non-fracture controls (n = 5) underwent stepwise three-point-bending during XCT imaging. Full-field displacement maps enabled direct measurement of crack mouth opening displacement (CMOD), crack length (a), and their ratio, CMOD/a, used here as a geometry-normalised comparative descriptor of brittle response. Automated crack segmentation using phase-congruency crack detection (PCCD) was compared against manual measurements. ResultsXCT-DVC successfully resolved three-dimensional displacement discontinuities during crack initiation and propagation in all specimens. Hip-fracture donors exhibited significantly lower critical crack-opening ratios (CMOD/a)* than Controls (0.31 vs 0.47; p = 0.008) and reached mechanical instability at lower applied loads, consistent with a more brittle structural response under this test configuration. Despite these differences, total crack extension ({Delta}a*) was similar between groups. Automated crack tracking using phase-congruency-based segmentation showed excellent agreement with manual measurements (r{superscript 2} = 0.98), confirming reliable extraction of crack geometry from DVC displacement fields. DiscussionThese results indicate that XCT-DVC can provide a practical approach for quantifying crack-opening behaviour in trabecular bone when classical fracture-mechanics parameters are not applicable in anatomically constrained specimens. The reduced critical crack-opening ratios and earlier instability observed in Hip-fracture donors are consistent with a more brittle comparative mechanical response that is not captured by crack extension alone. The strong agreement between automated and manual crack measurements further supports displacement-based descriptors as reliable comparative indicators of brittle behaviour in porous, architecturally discontinuous tissues. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/714043v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@31c5d7org.highwire.dtl.DTLVardef@1b3d9a4org.highwire.dtl.DTLVardef@95df7borg.highwire.dtl.DTLVardef@1834216_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

3D-DXA reconstructs DXA hip scans to 3-dimensional images allowing measurement of trabecular and cortical bone parameters. Given the higher image quality of GE Healthcare iDXA than GE Healthcare Prodigy, it could be hypothesized that the reconstruction might differ, thereby affecting 3D-DXA results. The aim of the study was to assess agreement and precision of 3D-DXA cortical and trabecular femur parameters between Prodigy and iDXA densitometers in adult subjects. The study cohort was composed of 391 men and women recruited from 3 clinical centers (USA and Brazil). All subjects were scanned on either Prodigy or iDXA scanners. Short-term precision was assessed on two Prodigy and two iDXA densitometers. 3D-DXA analyses were performed using 3D-Shaper software version 2.14. Agreement between densitometers was assessed by regression and Bland-Altman analyses. Short-term precision was determined following International Society for Clinical Densitometry recommendations. Strong agreements for 3D-DXA parameters were obtained between devices regardless of the center or the DXA device model (all R2 > 0.96). Bland-Altman analyses demonstrated statistically (p < 0.05), but not clinically, significant difference between both aBMD and 3D-DXA measurements obtained using Prodigy and iDXA scanners. Short-term precision of areal BMD and 3D-DXA parameters was similar between densitometers. This study demonstrated excellent 3D-DXA measurement agreement and similar precision between iDXA and Prodigy densitometers. These data provide evidence that no adjustments are required when using 3D-Shaper software on iDXA or Prodigy instruments. Mini AbstractWe assessed agreement and precision of 3D-DXA parameters between GE Healthcare Prodigy and iDXA densitometers in adults. Strong agreement was observed between devices, and short-term precision was comparable. Findings indicate that no adjustment is needed when using 3D-DXA with GE Healthcare densitometers.

BackgroundOsteoporosis is prevalent in elderly women, which causes fragility fracture and hence increased mortality and morbidity. Predicting osteoporotic fracture risk is both clinically-beneficial and cost-effective. However, traditional tools using clinical factors and bone mineral density (BMD) fail to reflect bone microstructure. Here we aim to use high-resolution peripheral quantitative CT (HR-pQCT) images to construct deep-learning models which predict fragility fracture history in elderly Chinese women. MethodsWe used ChiVOS, a community-based national cohort of 2,664 Chinese elderly women. Demographic data, BMD, and HR-pQCT from 216 patients were used to construct three groups of models: BMD, pQCT-index, and DeepQCT. For DeepQCT, we used ResNet34 as classifier, and logistic regression for late fusion. Models were developed using 6-fold cross-validation in development set (90%, N=195), and tested in internal test set (10%, N=21). We applied unsupervised clustering on HR-pQCT indices to derive patient subgroups. FindingsDeepQCT (best model AUC 0.86-0.94) was superior or similar to pQCT-index (best model AUC 0.8-0.93), which both outperformed BMD (best model AUC 0.54-0.78). Surprisingly, DeepQCT built from non-weight-bearing bones performed similarly to weight-bearing bones. Furthermore, two distinct patient groups were classified using HR-pQCT indices. The one with higher DeepQCT risk score showed lower volumetric BMD, bone more microarchitectural abnormalities, and had higher probability of osteoporosis and fragility fracture history. InterpretationDeepQCT scores and HR-pQCT-index permit early recognition of patients with high risk of fragility fracture. This established framework can be easily adapted for other diagnostic tasks using HR-pQCT scans, which promotes bone health management via digital medicine. FundingThis research was supported by the National Natural Science Foundation of China (LC, 82100946; WX, 82270938), CAMS Innovation Fund for Medical Sciences (WX, 2021-I2M-1-002), National Key R&D Program of China (WX, 2021YFC2501700), National High Level Hospital Clinical Research Funding (WX, 2022-PUMCH-D-006), the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (LC, 2023-PT320-10), and Young Elite Scientists Sponsorship Program by BAST (LC, No.BYESS2023171). Part of the study was supported by Merck Sharp & Dohme China, Hangzhou, China. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSBone mineral density (BMD) from dual X-ray absorptiometry was firstly used to predict fragility fracture, but had low sensitivity. Tools like FRAX, QFracture, and Garvan, which also incorporated clinical factors into prediction models, showed improved performance. Models containing standard HR-pQCT indices (FRAC) further surpassed most clinical tools. Nevertheless, direct learning from original HR-pQCT images is always desired to reduce labor and bias. Deep learning being the most common method for image-based learning, we searched PubMed for articles published up to Mar 25, 2024, using keywords "( fragility fracture OR osteoporotic fracture) and ( prediction model) and ( HR-pQCT or High-resolution peripheral quantitative CT) and ( deep-learning OR deep learning)". Results showed that no study has built deep learning models from HR-pQCT for fragility fracture prediction. Added value of this studyWe developed DeepQCT from HR-pQCT of 216 elderly Chinese women from a national cohort (ChiVOS), which calculated risk scores using individual bone images and clinical features. BMD and pQCT-index models were compared to DeepQCT. We found both DeepQCT (best model AUC 0.86-0.94) and pQCT-index (best model AUC 0.8-0.93) outperformed BMD (best model AUC 0.54-0.78). DeepQCT using non-weight-bearing bones (ulna, fibula) performed similarly to weight-bearing bones (tibia, radius). Specifically, HR-pQCT revealed one patient subgroup with higher DeepQCT risk scores, which showed lower BMD and multiple bone microarchitectural abnormalities, associated with osteoporosis and fragility fracture history. Implications of all the available evidenceDeepQCT is the first method which uses deep-learning to predict fragility fracture directly from HR-pQCT images. It is also the first to use single bones individually in prediction models, including non-weight-bearing bones, which are excluded in HR-pQCT-index computation. Of note, DeepQCT risk score is highly clinically relevant, as showed in bone density or microarchitectural features differences between patient subgroups. The non-inferior performance of DeepQCT compared to the manual annotation-dependent pQCT-index, supported its application to reduce labor and enhance efficiency. Performance of non-weight-bearing bones also challenges traditional perception of using load-bearing bones only in predicting osteoporotic conditions. Most importantly, the DeepQCT framework can be easily adapted for other tasks using HR-pQCT scans, which greatly expands application of digital medicine in bone mineral disease diagnosis or management.

The Linker of Nucleoskeleton and Cytoskeleton (LINC) complex is a crucial connective component between the nuclear envelope and the cytoskeleton involving various cellular processes including nuclear positioning, nuclear architecture, and mechanotransduction. How LINC complexes regulate bone formation in vivo, however, is not well understood. To start bridging this gap, here we created a LINC disruption murine model using transgenic mice expressing Cre recombinase enzyme under the control of the Osterix (Osx-Cre) which is primarily active in pre-osteoblasts and floxed Tg(CAG-LacZ/EGFP-KASH2) mice. Tg(CAG-LacZ/EGFP-KASH2) mice contain a lox-STOP-lox flanked LacZ gene which is deleted upon cre recombination allowing for the overexpression of an EGFP-KASH2 fusion protein. This overexpressed protein disrupts endogenous Nesprin-Sun binding leading to disruption of LINC complexes. Thus, crossing these two lines results in a Osx-driven LINC disruption (ODLD) specific to pre-osteoblasts. In this study, we investigated how this LINC disruption affects exercise induced bone accrual. ODLD cells had decreased osteogenic and adipogenic potential in vitro compared to non-disrupted controls and sedentary ODLD mice showed decreased bone quality at 8-weeks. Upon access to a voluntary running wheel ODLD animals showed increased running time and distance; however, our 6-week exercise intervention did not significantly affect bone microarchitecture and bone mechanical properties.

Although body mass index is positively associated with bone mineral density, suggesting obesity is protective against fracture, elderly obese individuals experience greater fracture risk at certain sites than non-obese peers, suggesting bone structural or material changes contribute to fragility. Diet-induced obesity rodent studies have reported detrimental changes to bone microstructure and some apparent-level material properties, but tissue-level material changes are not well understood. Because adipose tissue is highly vascularized, and bone remodeling depends critically on functional vascular supply, concurrent effects on osteovascular perfusion and structure may provide insight about obesity-related bone fragility. This study aimed to determine the effects of obesity on both tissue-level bone properties and osteovascular properties that could negatively impact bone strength. Five-week-old male C57Bl/6J mice were fed either high fat diet (HFD) or control fat diet (CFD) for 17 weeks and received daily treadmill exercise or remained sedentary for eight weeks at ages 14-22 weeks. HFD negatively affected femur bending strength, with 18% lower yield load than CFD. Although HFD negatively altered cancellous microstructure in the distal femur, with 32% lower bone volume fraction than CFD, it did not affect cortical bone geometry in the femoral metaphysis or diaphysis. HFD caused increased carbonate substitution but had no effect on other composition metrics or apparent- or tissue-level material properties in the femoral diaphysis. Exercise did not affect bone strength or microstructure but increased endosteal mineralizing surface in the tibial diaphysis, mineral crystallinity and mineral-to-matrix ratio in the femur, and blood supply to the proximal tibial metaphysis. HFD did not affect blood supply in the tibia or 2D osteovascular structure in the distal femoral metaphysis, indicating that HFD negatively affects cancellous bone without affecting osteovasculature. This study reveals that HFD negatively affected cancellous microstructure without affecting osteovascular structure, and whole-bone strength without altering cortical geometry or material properties.

BackgroundOsteoporosis is a prevalent bone metabolic disorder characterized by reduced bone mass, disruption of bone microarchitecture, and increased bone fragility, leading to a heightened risk of fracture. This condition significantly impairs patients quality of life and increases mortality risk. Emerging evidence suggests that DNA methylation may play a crucial role in regulating the expression of genes related to bone metabolism, thereby influencing the development of osteoporosis. However, the precise relationship between DNA methylation and osteoporosis remains unclear and warrants further investigation. ResultsOur study revealed significant differences in both the quantity and ratio of DNA methylation between individuals with osteoporosis and non-osteoporosis controls, with differences predominantly occurring in CpG islands. GO/KEGG enrichment analyses highlighted distinct osteoporosis-related gene pathways. Notably, we identified six genes, MSX1, HOXD4, AXIN2, WNT5A, TGFB1, and STAT3, respectively, that are potentially involved in the pathogenesis of osteoporosis and are broadly involved in various diseases and biological processes. ConclusionsThese findings indicate distinct methylation patterns between osteoporosis patients and healthy individuals, with differential methylation levels in genes associated with osteoporosis. This research offers new insights into the epigenetic mechanisms underlying osteoporosis.

Type 2 diabetes mellitus (T2DM) is associated with an increased fracture risk independent of bone mass. The exact origin of this increased fracture risk is still not well understood. Using a polygenic diabetic rat model, synchrotron radiation micro-computed tomography (SRCT), and in situ scanning electron microscope (SEM) fracture toughness, we related the changes at the microscale to toughness and material properties of diabetic rat femurs. The diabetic rat model (ZDSD) displayed overnight fasting hyperglycemia and an increased AGEs content. Additionally, we measured the impairment of post-yield properties and toughness in diabetic rats. The cortical geometry and porosity were also affected in this ZDSD model. We measured a decrease in osteocyte lacunar density associated with a decreased lacunar volume. Moreover, we found decreased canal density while maintaining a similar canal diameter. These results indicate that diabetes impairs bone remodeling, affecting bone microstructure. Because canals and lacunae are also linked with extrinsic toughening mechanisms, we attribute the decreased toughness largely to these microstructural changes. In conclusion, we showed that changes in lacunae and canal density, combined with AGEs accumulation, decreased toughness in T2DM rat bone.

Recently, automatic disease diagnosis based on medical images has become an integral part of digital pathology packages. To create, develop, evaluate, and compare these systems, we need diverse data sets. One of the key features in the diagnosis of bone diseases is measuring bone mineral density (BMD). Most research in this field uses manual methods to directly extract bone image features despite the underlying correlation between diseased and healthy bones, which explains the limited results. Detection of significant changes in bone mineral density (BMD) relies on minimally invasive dual energy x-ray absorptiometry (DXA) scanners. This article presents a collection of bone density test results along with a patient profile called Arak Bone Densitometry Center data. The patient profile includes height and weight and information about the patient, along with photos of the imaging areas. The number of these patients is 3,643, with about 4,020 photos stored next to them. Which can be used to develop automatic disease diagnosis methods and software. Datasethttps://drive.google.com/drive/folders/1HmLTG4GFgB2s4D0x7TTRx8vV_VWY3sW3?usp=sharing

PurposeLamellar bone that forms in moderate and severe osteogenesis imperfecta (OI) is often composed of structurally irregular lamellae compared to those in normal bone. Polarization light microscopy (PLM) demonstrates lamellar bone well but has rarely been used for quantitative studies; information available on normal bone lamellae tends to be variable and studies specifically assessing OI bone lamellae have not been done. We report on PLM histomorphometry quantifying bright and dark lamellar thicknesses in normal and OI bone. Manual measurements of individual lamellar thicknesses have been made on histologic sections using the cellSens image analysis system; in an effort to augment the number of measurements we also developed a method of automated thickness averaging in quantifying regions of lamellae. MethodsFemoral and tibial cortical bone fragments from 5 individuals 5 - 26 years old (without molecular bone disorders) and 8 individuals 5 - 16 years old with progressively deforming (Sillence III) OI were obtained. The fragments were decalcified, infiltrated in JB4 solution, embedded in JB4 plastic, sectioned at 5 thickness and stained with 1% toluidine blue for light and polarizing microscopy. Manual measurements: Strict criteria for measurement, primarily to eliminate oblique lamellae, included accumulations of 16-20 bright and dark lamellae under PLM with a relatively narrow range of thicknesses, flattened elliptical osteocytes along the longitudinal axis of the lamellae and canaliculi passing from the walls of the osteocyte lacunae at right angles to the lamellae. Histomorphometric measurements of bright and dark lamellae by PLM were made at 20X magnification. Automated measurements: A script for automated measurement of average lamellar thicknesses from PLM images was developed in MATLAB (Mathworks, Natick, MA) to make measurement faster and less subjective. The script isolates a region from an image for measurement and marks each pixel as either bright or dark based on a local average intensity threshold. It then takes multiple pixel measurements along the length of the lamellae in the image and returns the average thickness of each in m. Results1. OI bone mean lamellar thickness values are always less than those in normal bone. The mean value for all OI bright and dark lamellae combined is 1.80 {+/-} 0.72 m and the value in normal bone is 2.54 {+/-} 0.92 m. 2. Mean value for the bright lamellae is less than that for the dark lamellae in both normal and OI bone. The mean value for bright lamellae in OI is 1.47 {+/-} 0.53 m and for dark lamellae 2.18 {+/-} 0.72 m; in normal bone the mean value for bright lamellae is 2.06 {+/-} 0.54 m and for dark lamellae 3.07 {+/-} 0.96 m. The differences are statistically significant: between groups of normal and OI lamellae (p<0.001), normal and OI light bands (p<0.001), and normal and OI dark bands (p<0.001). 3. Ratio of mean values for bright/dark lamellar thicknesses is the same in OI and normal bone. The ratio in OI bone is 0.67 (range: 0.54 - 0.83) and in normal bone 0.67 (range: 0.60 - 0.88). 4. Validation of automated vs. manual datasets: For each lamella in the validation dataset, the percent difference between the automated and manual measurements was calculated. The mean of the absolute values of these percent differences was 18.9%, a statistically non-significant difference (p = 0.0518). Discussion and conclusionsLamellar bone that forms in moderate and severe OI is composed of thinner and less regular lamellae than those in normal bone. i) PLM histomorphometry shows mean lamellar thicknesses (bright and dark merged) are statistically significantly decreased in OI compared to normal bone as are bright and dark lamellar thicknesses measured independently. ii) The automated method can be adapted readily to the assessment process for lamellar thicknesses and is, most likely, more accurate since it averages a greatly increased number of measurements per individual lamella. iii) Lamellar thickness measurements can be helpful in assessing the effect of specific collagen mutations on OI bone synthesis and warrant inclusion in both research and clinical histomorphometric assessments.

Exercise has long-lasting benefits to bone health. Bone mass and the ability to exercise both decline with age, making it ideal to exercise earlier in life and to maximize gains in bone mass. Increasing strain on bone and frequency of loading during exercise can increase bone formation rate and cross-sectional area. Combining a short-term exercise program with a calcium- and phosphorus-supplemented diet increases cortical bone tissue mineral content (TMC) and area more than exercise alone in adult mice. It was hypothesized that combining high-speed running with a mineral-supplemented diet would lead to greater cortical TMC and area than high-speed running on a standard diet and low-speed running on a supplemented diet after 4 weeks. Male, 15-week old mice were assigned to 7 groups - a baseline group, non-exercised groups fed a control or supplemented diet, low-speed exercised groups fed a control or supplemented diet, and high-speed exercised groups fed a control or supplemented diet. Exercise consisted of 4 weeks of daily treadmill running for 20 min/day at 12 m/min or 20 m/min for low- and high-speed exercise, respectively. High-speed exercised mice had significantly lower body weight and lower tibial length after 4 weeks. Cortical TMC and area were significantly higher in high-speed exercised mice on the supplemented diet than high-speed exercised mice on the control diet. Trabecular bone volume (BV) and bone density were significantly higher in all groups on the supplemented diet than groups on the control diet, regardless of exercise. For mice on the control diet, non-exercised mice had significantly lower trabecular BV than baseline, while both speeds of exercise prevented this decline. There were few effects of exercise or diet on mechanical properties. For mice on the control diet, exercise significantly decreased serum PINP/CTX ratio on day 9 which may be preventing exercise from increasing bone mass or strength after only 4 weeks. For non-exercised mice on the supplemented diet, the serum PINP/CTX ratio on day 30 was significantly greater than for exercised mice, suggesting the supplemented diet may also lead to significantly greater bone mass in non-exercised mice if these interventions were extended beyond 4 weeks. Increasing treadmill speed can lower body weight while maintaining cortical and trabecular bone mass. A mineral-supplemented diet increases cortical and trabecular bone mass with high-speed exercise.

ImportanceCurrent fracture risk prediction tools, including the Fracture Risk Assessment Tool (FRAX), do not incorporate genetic risk factors limiting accuracy and contributing to misclassification and suboptimal care. ObjectiveTo develop and validate a novel genome-informed fracture risk assessment tool (Bayes-FRAX) integrating Bayesian genome-wide polygenic scores (GPS) into the established FRAX to enhance major osteoporotic fracture (MOF) prediction. Design, Setting, and ParticipantsThis retrospective cohort study analyzed clinical and genetic data from 6,932 postmenopausal women enrolled in the Womens Health Initiative (1993-1998). ExposuresIntegration of GPS derived using Polygenic Risk Score Continuous Shrinkage (PRS-CS) and Summary data-based Bayesian regression (SBayesR) into FRAX. Main Outcomes and MeasuresPrimary outcomes included the incidence of MOF. Predictive performance metrics assessed were area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), calibration slopes, Hosmer-Lemeshow goodness-of-fit tests, net reclassification improvement (NRI), diagnostic sensitivity, decision curve analysis (DCA), and external validation metrics. ResultsOf 6,932 women, 513 (7.4%) experienced MOF. Bayes-FRAX significantly improved prediction over standard FRAX based solely on clinical risk factors, increasing AUROC from 0.662 to 0.680 for both PRS-CS and SBayesR. AUPRC improved from 0.120 (FRAX) to 0.140 (PRS-CS) and 0.138 (SBayesR). Calibration slopes were ideal (GPS-PRS-CS: 1.00 [95% CI: 0.8569-1.1431]; GPS-SBayesR: 1.00 [95% CI: 0.8560-1.1437]). Bayes-FRAX reclassified 3.5% of women, 34% near the intervention threshold. NRI improved by 4.59% (SBayesR) and 4.34% (PRS-CS), largely from better classification of women who fractured (5.85% and 5.65%). Decision curve analyses demonstrated greater net clinical benefit at clinically relevant thresholds, notably at the 20% threshold. External validation in 852 independent White postmenopausal women confirmed robust generalizability, with GPS significantly associated with fracture risk (PRS-CS OR = 0.148, 95% CI: 0.052-0.411; SBayesR OR = 0.116, 95% CI: 0.040-0.324). Likelihood ratio tests also supported improved model fit after GPS inclusion (PRS-CS: P < 0.001; SBayesR: P <0.001). Sensitivity analysis without BMD demonstrated stable AUROC (0.74). Conclusions and RelevanceIntegrating GPS into FRAX using Bayesian methods improved fracture risk prediction, reclassification, and decision-making. Bayes-FRAX provides a generalizable tool for personalized osteoporosis care, especially for women near treatment thresholds. Key PointsO_ST_ABSQuestionC_ST_ABSDoes incorporating genome-wide polygenic scores using Bayesian methods improve fracture risk prediction beyond the traditional FRAX? FindingsIn this cohort study of 6,932 postmenopausal women, adding Bayesian polygenic scores significantly improved prediction accuracy, calibration, and clinical reclassification, particularly among women older than 65 years, with robust external validation. MeaningBayes-FRAX provides a personalized, more accurate fracture risk assessment, potentially improving clinical decision-making for postmenopausal women near treatment thresholds.

Osteoporosis and fractures are major health concerns. We developed and validated a polygenic score (PGS) for osteoporosis in a Japanese population using heel quantitative ultrasound-derived T-scores. Genome-wide association study data from 12,371 participants in the Tohoku Medical Megabank Community-Based Cohort identified genome-wide significant loci, including MBL2, TMEM135, and WNT16. PGS models were constructed and evaluated using independent datasets for model selection (n = 1,419) and validation (n = 8,711). Adding the PGS to age and sex yielded modest improvements in discrimination but supported genetic risk stratification. Compared with the intermediate group, the lowest PGS quintile (bottom 20%, genetically high-risk) had higher odds of osteoporosis (OR = 1.22, 95% confidence interval (CI): 1.07-1.40), whereas the highest PGS quintile (top 20%, genetically low-risk) had lower odds of osteoporosis (OR = 0.85, 95% CI: 0.71-0.98). Prospective follow-up (mean 3.4 years) showed a similar gradient for incident osteoporosis, with higher incidence rate ratios in the high-risk group (1.42, 95% CI: 1.17-1.73) and lower incidence rate ratios in the low-risk group (0.70, 95% CI: 0.54-0.89). Age-stratified analyses revealed no significant age-PGS interaction and no differences in the slope of age-related T-score declines across genetic risk groups. Observed T-scores in young adults (20-44 years) and extrapolation to age 20 suggested lower bone status around peak bone mass among genetically high-risk individuals. These findings indicate that a Japanese-specific PGS can stratify osteoporosis risk and may help identify individuals at elevated genetic risk earlier in adulthood.

BackgroundFZD8 could be a promising therapeutic target in osteoporosis (OP), although the signal transduction mechanism in OP regarding FZD8 has not been completely elucidated. AimsWe used the CRISPR/Cas9 technique to develop an Fzd8-knockout mouse model to study whether Fzd8 inactivation results in genetic changes with potential correlations to OP. Materials and MethodsGenotypes of distinguished classified knockout mice, i.e., heterozygous, homozygous, and wild-type were identified through PCR. Applying the murine model, third generation mice were used for the downstream experiments. We investigated the potential relevance of differentially expressed genes (DEGs) in OP. ResultsWe found that osteoclasts significantly increased in Fzd8-knockout homozygous mice, compared to wild-type mice, while osteoblasts reduced significantly. Before transcription, heterozygous and homozygous mice possessed DEGs related to exons SNP, which are associated with exons CNV. After transcription, DEGs related to exons SNP in heterozygous and homozygous mice were observed, some of which are potentially associated with OP based on pathway and gene set enrichment analyses. ConclusionsOur Fzd8-knockout murine model showed that there were significant alternations in Fzd10 and Lta gene expressions and Itgb3 and RANK protein expressions among the wild-type and homozygous mice, which are significantly associated with bone remodeling. Our results revealed that FZD8 could be a therapeutic target in OP. This study elucidates the molecular mechanisms in OP, providing evidence-based data for OP drug development and treatment.

Bones adapt to external mechanical loads through a process known as mechanoadaptation. Osteocytes are the bone cells that sense the mechanical environment and initiate a biological response. Investigating the changes in osteocyte molecular expression following mechanical loading has been instrumental in characterizing the regulatory pathways involved in bone adaptation. However, current methods for examining osteocyte molecular expression do not preserve the three-dimensional structure of the bone, which plays a critical role in the mechanical stimuli sensed by the osteocytes and their spatially controlled biological responses. In this study, we used WISH-BONE to investigate the spatial distribution of Sost-mRNA transcripts and its encoded protein, sclerostin, in 3D mouse tibia midshaft following in vivo tibia loading. Our findings showed a decrease in the percentage of Sost-positive osteocytes predominantly at 25% and 37% of the bone length, and in the posterior-lateral side of the tibia after loading. Sclerostin-positive osteocytes in the loaded legs were found to be similar to the contralateral legs after 2 weeks of loading. This work is the first to provide a 3D analysis of Sost and sclerostin distribution in loaded versus contralateral mouse tibia midshafts. It also highlights the importance of the bone region analyzed and the method utilized when interpreting mechanoadaptation results. WISH-BONE represents a powerful tool for further characterization of mechanosensitive genes regulation in bone and holds potential for advancing the development of new treatments targeting mechanosensitivity-related bone disorders.

Recent studies in mice have indicated that the gut microbiome can regulate bone tissue strength. However, prior work involved modifications to the gut microbiome in growing animals and it is unclear if the same changes in the microbiome, applied later in life, would change matrix strength. Here we changed the composition of the gut microbiome before and/or after skeletal maturity (16 weeks of age) using oral antibiotics (ampicillin + neomycin). Male and female mice (n=143 total, n=12-17/group/sex) were allocated into five study groups:1) Unaltered, 2) Continuous (dosing 4-24 weeks of age), 3) Delayed (dosing only 16-24 weeks of age), 4) Initial (dosing 4-16 weeks of age, suspended at 16 weeks), and 5) Reconstituted (dosing from 4-16 weeks following by fecal microbiota transplant from Unaltered donors). Animals were euthanized at 24 weeks of age. In males, bone matrix strength in the femur was 25-35% less than expected from geometry in mice from the Continuous (p= 0.001), Delayed (p= 0.005), and Initial (p=0.040) groups as compared to Unaltered. Reconstitution of the gut microbiota, however, led to a bone matrix strength similar to Unaltered animals (p=0.929). In females, microbiome-induced changes in bone matrix strength followed the same trend as males but were not significantly different, demonstrating sex-related differences in the response of bone matrix to the gut microbiota. Minor differences in chemical composition of bone matrix were observed (Raman spectroscopy). Our findings indicate that microbiome-induced impairment of bone matrix in males can be initiated and/or reversed after skeletal maturity. The portion of the femoral cortical bone formed after skeletal maturity (16 weeks) is small; however, this suggests that microbiome-induced changes in bone matrix occur without osteoblast/osteoclast turnover using an, as of yet unidentified mechanism. These findings add to evidence that the mechanical properties of bone matrix can be altered in the adult skeleton.