Kim Young Kwan, Kameo Yoshitaka, Tanaka Sakae, Adachi Taiji
Laboratory of Biomechanics, Department of Biosystems Science, Institute for Life and Medical Sciences, Kyoto University, Kyoto 606-8507, Japan.
Department of Orthopaedic Surgery, Faculty of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.
JBMR Plus. 2024 Jan 4;8(1):ziad003. doi: 10.1093/jbmrpl/ziad003. eCollection 2024 Jan.
Bone turnover markers (BTMs) are commonly used in osteoporosis treatment as indicators of cell activities of bone-resorbing osteoclasts and bone-forming osteoblasts. The wide variability in their values due to multiple factors, such as aging and diseases, makes it difficult for physicians to utilize them for clinical decision-making. The progenitors of osteoclasts and osteoblasts are indispensable for a comprehensive interpretation of the variability in BTM values because these upstream progenitors strongly regulate the downstream cell activities of bone turnover. However, understanding the complex interactions among the multiple populations of bone cells is challenging. In this study, we aimed to gain a fundamental understanding of the mechanism by which the progenitor dynamics affect the variability in bone turnover through in silico experiments by exploring the cell dynamics with aging effects on osteoporosis. Negative feedback control driven by the consumptive loss of progenitors prevents rapid bone loss due to excessive bone turnover, and through feedback regulation, aging effects on osteoclast differentiation and osteoclast progenitor proliferation cause variability in the osteoclast and osteoblast activity balance and its temporal transition. By expressing the variability in the bone turnover status, our model describes the individualities of patients based on their clinical backgrounds. Therefore, our model could play a powerful role in assisting tailored treatment and has the potential to resolve the various health problems associated with osteoporosis worldwide.
骨转换标志物（BTMs）在骨质疏松症治疗中常用作破骨细胞骨吸收和成骨细胞骨形成细胞活动的指标。由于衰老和疾病等多种因素，其值存在很大差异，这使得医生难以将其用于临床决策。破骨细胞和成骨细胞的祖细胞对于全面解释BTM值的变异性不可或缺，因为这些上游祖细胞强烈调节骨转换的下游细胞活动。然而，了解多种骨细胞群体之间的复杂相互作用具有挑战性。在本研究中，我们旨在通过探索衰老对骨质疏松症影响的细胞动力学，通过计算机模拟实验，对祖细胞动力学影响骨转换变异性的机制有一个基本的了解。祖细胞消耗性损失驱动的负反馈控制可防止由于过度骨转换导致的快速骨质流失，并且通过反馈调节，衰老对破骨细胞分化和破骨细胞祖细胞增殖的影响会导致破骨细胞和成骨细胞活性平衡及其时间转换的变异性。通过表达骨转换状态的变异性，我们的模型根据患者的临床背景描述了患者的个体特征。因此，我们的模型可以在协助定制治疗方面发挥强大作用，并有可能解决全球范围内与骨质疏松症相关的各种健康问题。
