Journal of Bone and Mineral Research最新文献

Patients who have suffered an atypical femoral fracture while on bisphosphonates or denosumab may continue to be at risk for typical osteoporotic fractures. There are no studies to provide guidance on safe treatment for such patients. Instead, using an illustrative case, 5 principles of management are provided that may lead to decreased osteoporotic fracture risk. The first principle is to discontinue the anti-resorptive medications, which may be challenging in the patient on denosumab because of rebound vertebral fractures reported in patients stopping denosumab. The second principle is to maximize non-pharmacologic management to reduce falls and fractures. Home safety, other methods of fall risk reduction, adequate nutrition, and an exercise prescription should help reduce fracture risk. Investigating potential secondary causes of osteoporosis, particularly if the original workup was not comprehensive, is the third principle because treatment of some specific causes may lower fracture risk. Reviewing the medication list is the fourth principle, with the goal of eliminating drugs that may increase fracture risk; and considering thiazides for some patients, which may lower fracture risk. Finally, some patients may benefit from anabolic therapy. One potential (but not FDA-approved) method is to use long-term cyclic teriparatide or abaloparatide on a three-months on, three-months off schedule. Tailoring the approach to each patient is important, based on the five clinical principles, in the absence of evidence-based management recommendations.

The craniofacial bone, crucial for protecting brain tissue and supporting facial structure, undergoes continuous remodeling through mesenchymal (MSCs) or skeletal stem cells (SSCs) in their niches. Gli1 is an ideal marker for labeling MSCs and osteoprogenitors in this region, and Gli1-lineage cells are identified as pivotal for bone growth, development, repair, and regeneration. Despite its significance, the distribution of Gli1-lineage cells across the dental, oral, and craniofacial (DOC) regions remains to be systematically explored. Utilizing tissue-clearing and light sheet fluorescence microscopy (LSFM) with a Gli1CreER; tdTomatoAi14 mouse model, we mapped the spatial distribution of Gli1-lineage cells throughout the skull, focusing on calvarial bones, sutures, bone marrow, teeth, periodontium, jaw bones, and the temporomandibular joint (TMJ). We found Gli1-lineage cells widespread in these areas, underscoring their significance in DOC regions. Additionally, we observed their role in repairing calvarial bone defects, providing novel insights into craniofacial biology and stem cell niches and enhancing our understanding of stem cells and their progeny's behavior in vivo.

Recent advancements in deep learning (DL) have revolutionized the capability of artificial intelligence (AI) by enabling the analysis of large-scale, complex datasets that are difficult for humans to interpret. However, large amounts of high-quality data are required to train such generative AI models successfully. With the rapid commercialization of single-cell sequencing and spatial transcriptomics platforms, the field is increasingly producing large-scale datasets such as histological images, single-cell molecular data, and spatial transcriptomic data. These molecular and morphological datasets parallel the multimodal text and image data used to train highly successful generative AI models for natural language processing and computer vision. Thus, these emerging data types offer great potential to train generative AI models that uncover intricate biological processes of bone cells at a cellular level. In this Perspective, we summarize the progress and prospects of generative AI applied to these datasets and their potential applications to bone research. In particular, we highlight three AI applications: predicting cell differentiation dynamics, linking molecular and morphological features, and predicting cellular responses to perturbations. To make generative AI models beneficial for bone research, important issues, such as technical biases in bone single-cell datasets, lack of profiling of important bone cell types, and lack of spatial information, need to be addressed. Realizing the potential of generative AI for bone biology will also likely require generating large-scale, high-quality cellular-resolution spatial transcriptomics datasets, improving the sensitivity of current spatial transcriptomics datasets, and thorough experimental validation of model predictions.

Background: Type 2 diabetes mellitus and lower weight are both associated with osteoporotic fractures, but the roles of variability and trajectory are less clear.1 The associations of these factors among older adults with dysglycemia, who are at highest risk of fracture, with fracture risk and bone mineral density (BMD) remains uncertain.

Methods: We followed 775 men and 1080 women from the Cardiovascular Health Study (mean age 77.4 years) with abnormal oral glucose tolerance testing in 1989-1990. We measured their weights yearly through 1994-1995 and derived intra-individual mean weight, weight slope, and weight variability. We also used growth mixture modelling to derive four latent body-mass index trajectories over time. We used Cox proportional hazards models to calculate hazard ratios (HR) and 95% confidence intervals (CI) for subsequent hip fracture through 2015 and linear regression models to estimate cross-sectional associations with bone mineral density (BMD) of the hip.

Results: Each 10 kg higher mean weight was associated with a lower risk of subsequent hip fracture overall (HR 0.81; CI 0.70-0.94) and among women (HR 0.76; CI 0.64-0.91) and with higher BMD (P-value <0.001). Higher weight variability was directly associated with incident hip fracture among women (HR 1.18; CI: 1.03-1.35). Compared with a stable trajectory, a "progressive overweight" trajectory was associated with lower risk of hip fracture (HR 0.66; CI: 0.44-0.99). An uncommon trajectory of "accelerating obesity" was associated with higher BMD.

Conclusions: Among older adults with dysglycemia at high risk for fracture, lower mean weight is associated with higher fracture risk, but variability and trajectory may also contribute. These results highlight the complex effects of weight in older age.

Mitochondria in osteoblasts have been demonstrated to play multiple crucial functions in bone formation from intracellular adenosine triphosphate production to extracellular secretion of mitochondrial components. The present review explores the current knowledge about mitochondrial biology in osteoblasts, including mitochondrial biogenesis, bioenergetics, oxidative stress generation, and dynamic changes in morphology. Special attention is given to recent findings, including mitochondrial donut formation in osteoblasts, which actively generates mitochondrial-derived vesicles (MDVs), followed by extracellular secretion of small mitochondria and MDVs. We also discuss the therapeutic effects of targeting osteoblast mitochondria, highlighting their potential applications in improving bone health.

The Physical Activity Scale for the Elderly (PASE) is a validated test to assess physical activity in older people. It has not been investigated if physical activity, according to PASE, is associated with fracture risk independently from the clinical risk factors (CRFs) in FRAX, bone mineral density (BMD), comorbidity, and if such an association is due to differences in physical performance or bone parameters. The purpose of this study was to evaluate if PASE score is associated with bone characteristics, physical function, and independently predicts incident fracture in 3014 75-80-yr-old women from the population-based cross-sectional SUPERB study. At baseline, participants answered questionnaires and underwent physical function tests, detailed bone phenotyping with DXA, and high-resolution peripheral quantitative CT. Incident fractures were X-ray verified. Cox regression models were used to assess the association between PASE score and incident fractures, with adjustments for CRFs, femoral neck (FN) BMD, and Charlson comorbidity index. Women were divided into quartiles according to PASE score. Quartile differences in bone parameters (1.56% for cortical volumetric BMD and 4.08% for cortical area, Q4 vs Q1, p = .007 and p = .022, respectively) were smaller than quartile differences in physical performance (27% shorter timed up and go test, 52% longer one leg standing time, Q4 vs Q1). During 8 yr (median, range 0.20-9.9) of follow-up, 1077 women had any fracture, 806 a major osteoporotic fracture (MOF; spine, hip, forearm, humerus), and 236 a hip fracture. Women in Q4 vs. Q1 had 30% lower risk of any fracture, 32% lower risk of MOF, and 54% lower risk of hip fracture. These associations remained in fully adjusted models. In conclusion, high physical activity was associated with substantially better physical function and a lower risk of any fracture, MOF and hip fracture, independently of risk factors used in FRAX, FN BMD, and comorbidity.