Journal of Bone and Mineral Research最新文献

Osteoporosis is common, affecting more than 20% of women and 6% of men globally over the age of 50. Anti-resorptive drugs, bisphosphonates and denosumab, have been effective treatments for osteoporosis for more than 30 years. Rare complications of anti-resorptive therapy include medication-related osteonecrosis of the jaw and atypical femur fractures (AFF). The American Society for Bone and Mineral Research (ASBMR) proposed a case definition for these atypical femoral fractures in 2010, which was updated in 2013. However, atypical fractures at non-classical sites have been increasingly described. We aimed to systematically identify atypical fracture cases excluded from the ASBMR AFF case definition in patients receiving anti-resorptive medication for longer than 3 yr. A structured search of electronic databases, including PubMed, Medline (Ovid), Embase (Ovid), Cochrane, and Web of Sciences, and hand-searching of conference abstracts were undertaken. All full-text articles written in English describing an atypical fracture in patients (aged >18 yr) and receiving anti-resorptive medication for >3 yr were included, with data extracted and analyzed by two independent reviewers. Sixty-six articles were identified, describing 151 cases of atypical fractures in 114 individuals. The most frequent fracture site was the ulna, followed by the tibia. All patients were taking anti-resorptive treatment prior to or at the time of fracture, most frequently alendronate monotherapy (44%). Most commonly, fractures were transverse in nature (95%), following minimal or no trauma (96%), and non-comminuted (98%) with cortical thickening of the surrounding bone (69%). Anti-resorptive treatment was ceased following an atypical fracture in the majority (89%). Atypical fractures are rare and should not deter physicians from appropriate anti-resorptive therapy for osteoporosis. However, clinicians should be alert to their presence at additional sites to the femur. An update of the current ASBMR AFF case definition to include other skeletal sites could be timely.

HR-pQCT has become standard practice when quantifying volumetric BMD (vBMD) in vivo. Yet, it is only accessible to peripheral sites, with small fields of view and lengthy scanning times. This limits general applicability in clinical workflows. The goal of this study was to assess the potential of photon counting CT (PCCT) in quantitative bone imaging. Using the European Forearm Phantom, PCCT was calibrated to hydroxyapatite (HA) density. Eight cadaveric forearms were scanned twice with PCCT and once with HR-pQCT. The dominant forearm of two volunteers was scanned twice with PCCT. In each scan, the carpals were delineated. At bone level, accuracy was assessed with a paired measurement of total vBMD (Tt.vBMD) calculated with PCCT and HR-pQCT. At voxel-level, repeatability was assessed by image registration and voxel-wise subtraction of the ex vivo PCCT scans. In an ideal scenario, this difference would be zero; any deviation was interpreted as falsely detected remodeling. For clinical usage, the least detectable remodeling was determined by finding a threshold in the PCCT difference image that resulted in a classification of bone formation and resorption below acceptable noise levels (<0.5%). The paired measurement of Tt.vBMD had a Pearson correlation of 0.986. Compared to HR-pQCT, PCCT showed a bias of 7.46 mgHA/cm3. At voxel-level, the repeated PCCT scans showed a bias of 17.66 mgHA/cm3 and a standard error of 96.23 mgHA/cm3. Least detectable remodeling was found to be 250 mgHA/cm3, for which 0.37% of the voxels was incorrectly classified as newly added or resorbed bone. In vivo, this volume increased to 0.97%. Based on the cadaver data, we conclude that PCCT can be used to quantify vBMD and bone turnover. We provided proof of principle that this technique is also accurate in vivo, hence, that it has high potential for clinical applications.

Chronic nonbacterial osteomyelitis (CNO) is an autoinflammatory bone disease that primarily affects children and young people. It can cause significant pain, reduced function, bone swelling, and even (vertebral body) fractures. Because of a limited understanding of its pathophysiology, the treatment of CNO remains empiric and is based on relatively small case series, expert opinion, and personal experience. Several studies have linked pathological NOD-kike receptor (NLR) family pyrin domain containing 3 (NLRP3) inflammasome activation and the resulting imbalance between pro- and anti-inflammatory cytokine expression with CNO. This agrees with elevated pro-inflammatory (mostly) monocyte-derived protein signatures in the blood of CNO patients that may be used as future diagnostic and/or prognostic biomarkers. Recently, rare variants in the P2RX7 gene, encoding for an ATP-dependent transmembrane channel, were linked with increased NLRP3 inflammasome assembly and prolonged monocyte/macrophage survival in CNO. Although the exact molecular mechanisms remain unclear, this will inform future target-directed and individualized treatment. This manuscript reviews most recent developments and their impact on diagnostic and therapeutic strategies in CNO.

Extracellular vesicles (EVs) are key mediators of cell-cell communication and are involved in transferring specific biomolecular cargo to recipient cells to regulate their physiological functions. A major challenge in the understanding of EV function in vivo is the difficulty ascertaining the origin of the EV particles. The recent development of the "Snorkel-tag," which includes EV-membrane-targeted CD81 fused to a series of extra-vesicular protein tags, can be used to mark EVs originating from a specific source for subsequent isolation and characterization. We developed an in vivo mouse model, termed "CAGS-Snorkel," which expresses the Snorkel-tag under the control of the Cre-lox system, and crossed this mouse with either Prx1-Cre (mesenchymal progenitors) or Ocn-Cre (osteoblasts/osteocytes) and isolated Snorkel-tagged EVs from the mouse bone marrow plasma using a magnetic bead affinity column. miRNA-sequencing was performed on the isolated EVs, and although similar profiles were observed, a few key miRNAs involved in bone metabolism (miR-106b-5p, miRs-19b-3p, and miRs-219a-5p) were enriched in the Ocn-derived relative to the Prx1-derived EV subpopulations. To characterize the effects of these small EVs on a bone cell target, cultured mouse bone marrow stromal cells were treated with Prx1 or Ocn EVs, and mRNA-sequencing was performed. Pathways involved in ossification, bone development, and extracellular matrix interactions were regulated by both EV subpopulations, whereas a few pathways including advanced glycation end-products signaling were uniquely regulated in the Ocn EV subpopulation, underlying important biological effects of specific EV subpopulations within the bone marrow microenvironment. These data demonstrate that EV isolation in vivo using the CAGS-Snorkel mouse model is a useful tool in characterizing the cargo and understanding the biology of tissue-specific EVs. Moreover, while bone mesenchymal cell populations share a common EV secretory profile, we uncover key differences based on the stage of osteoblastic differentiation that may have important biological consequences.

The cartilage growth plate is essential for maintaining skeletal growth; however, the mechanisms governing postnatal growth plate homeostasis are still poorly understood. Using approaches of molecular mouse genetics and spatial transcriptomics applied to formalin-fixed, paraffin-embedded tissues, we show that ADGRG6/GPR126, a cartilage-enriched adhesion G protein-coupled receptor (GPCR), is essential for maintaining slow-cycling resting zone cells, appropriate chondrocyte proliferation and differentiation, and growth plate homeostasis in mice. Constitutive ablation of Adgrg6 in osteochondral progenitor cells with Col2a1Cre leads to a shortened resting zone, formation of cell clusters within the proliferative zone, and an elongated hypertrophic growth plate, marked by limited expression of parathyroid hormone-related protein (PTHrP) but increased Indian Hedgehog (IHH) signaling throughout the growth plate. Attenuation of smoothened-dependent hedgehog signaling restored the Adgrg6 deficiency-induced expansion of hypertrophic chondrocytes, confirming that IHH signaling can promote chondrocyte hypertrophy in a PTHrP-independent manner. In contrast, postnatal ablation of Adgrg6 in mature chondrocytes with AcanCreERT2, induced after the formation of the resting zone, does not affect PTHrP expression but causes an overall reduction of growth plate thickness marked by increased cell death specifically in the resting zone cells and a general reduction of chondrocyte proliferation and differentiation. Spatial transcriptomics reveals that ADGRG6 is essential for maintaining chondrocyte homeostasis by regulating osteogenic and catabolic genes in all the zones of the postnatal growth plates, potentially through positive regulation of SOX9 expression. Our findings elucidate the essential role of a cartilage-enriched adhesion GPCR in regulating cell proliferation and hypertrophic differentiation by regulation of PTHrP/IHH signaling, maintenance of slow-cycle resting zone chondrocytes, and safeguarding chondrocyte homeostasis in postnatal mouse growth plates.

Shared decision-making (SDM) aims to improve patients' experiences with care, treatment adherence, and health outcomes. However, the effectiveness of SDM in patients with a recent fracture who require anti-osteoporosis medication (AOM) is unclear. The objective of this study was to assess the effectiveness of a multicomponent adherence intervention (MCAI) including a patient decision aid (PDA) and motivational interviewing at Fracture Liaison Services (FLS) on multiple outcomes compared with usual care (UC). This pre-post superiority study included patients with a recent fracture attending FLS and with AOM treatment indication. The primary outcome was 1-year AOM persistence measured by pharmacy records. Secondary outcomes included treatment initiation, AOM adherence (measured by medication possession ratio [MPR]), decision quality (SDM process; 0-100, best), and decisional conflict (0-100, highest conflict), subsequent fractures, and mortality. Outcomes were tested in MCAI and UC groups at the first FLS visit and 4 and 12 months afterwards. Multiple imputation and uni- and multivariable analyses were performed. Post hoc analyses assessed the role of health literacy level. In total, 245 patients (MCAI: n = 136, UC: n = 109) were included. AOM persistence was 80.4% in the MCAI and 76.7% in the UC group (p=.626). SDM process scores were significantly better in MCAI (60.4 vs 55.1; p = .003). AOM initiation (97.8% vs 97.5%), MPR (90.9% vs 88.3%, p=.582), and decisional conflict (21.7 vs 23.0; p = .314) did not differ between groups. Results did not change importantly after adjustment. Stratified analyses by health literacy showed a better effect on MPR and SDM in those with adequate health literacy. This study showed no significant effect on AOM persistence; however, it demonstrated a significant positive effect of MCAI on SDM process in FLS attendees. (Netherlands Trial Registry, Trial NL7236 [NTR7435]; version 1.0; 26-11-2020 https://onderzoekmetmensen.nl/nl/trial/22858).

An abundance of medical data and enhanced computational power have led to a surge in artificial intelligence (AI) applications. Published studies involving AI in bone and osteoporosis research have increased exponentially, raising the need for transparent model development and reporting strategies. This review offers a comprehensive overview and systematic quality assessment of AI articles in osteoporosis while highlighting recent advancements. A systematic search in the PubMed database, from December 17, 2020 to February 1, 2023 was conducted to identify AI articles that relate to osteoporosis. The quality assessment of the studies relied on the systematic evaluation of 12 quality items derived from the minimum information about clinical artificial intelligence modeling checklist. The systematic search yielded 97 articles that fell into 5 areas; bone properties assessment (11 articles), osteoporosis classification (26 articles), fracture detection/classification (25 articles), risk prediction (24 articles), and bone segmentation (11 articles). The average quality score for each study area was 8.9 (range: 7-11) for bone properties assessment, 7.8 (range: 5-11) for osteoporosis classification, 8.4 (range: 7-11) for fracture detection, 7.6 (range: 4-11) for risk prediction, and 9.0 (range: 6-11) for bone segmentation. A sixth area, AI-driven clinical decision support, identified the studies from the 5 preceding areas that aimed to improve clinician efficiency, diagnostic accuracy, and patient outcomes through AI-driven models and opportunistic screening by automating or assisting with specific clinical tasks in complex scenarios. The current work highlights disparities in study quality and a lack of standardized reporting practices. Despite these limitations, a wide range of models and examination strategies have shown promising outcomes to aid in the earlier diagnosis and improve clinical decision-making. Through careful consideration of sources of bias in model performance assessment, the field can build confidence in AI-based approaches, ultimately leading to improved clinical workflows and patient outcomes.