Open AccessReview Modeling the Clockwork of Bone: A Narrative Review of Experimental Approaches to Circadian Rhythm in Bone Metabolism Xiang Gao Xiang Gao , Xinyuan Cai Xinyuan Cai Andreas K. Nussler Andreas K. Nussler * Siegfried Weller Research Institute, BG Unfallklinik Tuebingen, Department of Trauma and Reconstructive Surgery, University of Tuebingen, Schnarrenbergstr. 95, D-72076 Tuebingen, Germany * Author to whom correspondence should be addressed. Int. J. Mol. Sci. 2026, 27(12), 5167; https://doi.org/10.3390/ijms27125167 (registering DOI) Submission received: 21 April 2026 / Revised: 29 May 2026 / Accepted: 4 June 2026 / Published: 7 June 2026 Circadian rhythms are fundamental regulators of skeletal homeostasis, coordinating osteoblast and osteoclast activity through tightly controlled temporal programs. Disruption of these rhythms, whether through environmental misalignment or genetic perturbation of core clock components, alters bone formation, enhances resorption, and contributes to skeletal fragility. This review synthesizes current knowledge on circadian regulation of bone biology across in vivo, ex vivo, and in vitro model systems, highlighting how each platform reveals distinct aspects of rhythmic gene expression, cellular function, and tissue-level remodeling. We critically evaluate the strengths and limitations of these models, outline key controversies such as the interpretation of global clock-gene knockouts, and discuss the emerging relevance of human-derived systems including iPSC-based models, organoids, and microphysiological “bone-on-chip” platforms. Integrative approaches that combine multiple model systems provide the most reliable framework for understanding circadian control of bone and for identifying targets for chronotherapeutic intervention. Advancing human-relevant models and refining temporal experimental design will be essential for translating circadian biology into clinical strategies for metabolic bone diseases. Keywords: circadian rhythm; bone remodeling; in vivo model; ex vivo model; in vitro model; osteoblasts; osteoclasts 1. Introduction Circadian rhythms are fundamental regulators of physiological homeostasis, coordinating metabolic, endocrine, immune, and behavioral processes across multiple organ systems [ 1, 2, 3, 4, 5, 6, 7]. Recent evidence has demonstrated that these rhythms also play a direct and mechanistically relevant role in skeletal biology, influencing the temporal coordination of osteoblast, osteoclast, and osteocyte activity [ 8, 9, 10, 11, 12]. Despite growing interest in this field, the mechanistic pathways linking circadian oscillations to bone remodeling remain only partially defined, and existing studies often differ in experimental design, model selection, and temporal resolution. Disruptions of circadian homeostasis arising from shift work, jet lag, aging, or genetic alterations have been associated with impaired bone mineral density, delayed fracture healing, and increased skeletal fragility [ 10, 11, 12, 13, 14]. At the molecular level, core clock genes such as Bmal1, Clock, Per1/2, and Cry1/2 exhibit rhythmic expression in bone tissue and regulate key markers of bone formation and resorption, including RANKL, OPG, CTX, PINP, ALP, and TRAP [ 15, 16]. Misalignment of these pathways may alter the temporal coupling of bone formation and resorption, thereby contributing to metabolic bone disorders. To provide a more integrated and mechanistically informative perspective, this review critically evaluates the experimental approaches used to investigate circadian regulation in bone metabolism, including in vivo, ex vivo, and in vitro systems. We highlight their respective strengths, limitations, and translational relevance, and we synthesize key findings that illuminate how circadian rhythms shape skeletal homeostasis. In response to recent advances in the field, we further incorporate emerging human-relevant platforms, 3D co-culture systems, and microphysiological models, and we discuss unresolved controversies, methodological challenges, and opportunities for chronotherapeutic applications. 2. Search Strategy A comprehensive literature search was conducted using the PubMed database to identify studies investigating the interplay between circadian rhythms and bone biology. To enhance methodological transparency and reproducibility, we refined the search workflow and explicitly defined the review as a narrative review with systematic elements. The search covered the period from July 2005 to July 2025 and used the keywords “circadian rhythm”, “bone”, and “model”. All article types, including original research and reviews, were considered. The initial search yielded 165 records. The search covered the period from July 2005 to July 2025 and used the keywords “circadian rhythm”, “bone”, and “model”. All article types, including original research and reviews, were considered. The initial search yielded 165 records. Inclusion criteria were: (1) explicit investigation of circadian regulation in bone or bone-related cells; (2) use of an identifiable experimental model (in vivo, ex vivo, or in vitro); and (3) availability of full text in English. Exclusion criteria included (1) studies addressing only circadian biology without skeletal relevance; (2) studies on bone biology without circadian endpoints; and (3) non-English publications. After screening, 60 articles met the criteria, comprising 48 original research papers and 12 reviews. Duplicate entries were removed. A PRISMA-style flow diagram has been added to illustrate the search workflow and study selection process ( Figure 1). 3. Model Systems 3.1. In Vivo Model Systems In vivo models are indispensable for exploring the interplay between circadian rhythms and bone metabolism. By preserving the physiological context of a living organism, these models enable the study of bone remodeling processes under the influence of systemic factors such as hormonal signaling, immune responses, neural regulation, and mechanical loading. Rodents, particularly mice, are commonly employed in this field due to their genetic tractability and physiological similarities to the human circadian system. Murine in vivo systems can be broadly categorized into (1) environmental disruption models and (2) genetic manipulation models, each providing distinct insights into circadian regulation of skeletal physiology. Environmental disruption models frequently employ jet-lag–like protocols, such as shifting the light–dark cycle by eight hours every three days [ 17] or exposing animals to weekly alternating bright/dim cycles [ 18, 19]. While continuous inversion of the bright–dim cycle primarily exacerbates inflammation-associated bone degradation [ 19], repeated weekly shifts induce pronounced trabecular and cortical bone loss, highlighting the sensitivity of skeletal tissue to chronic circadian misalignment [ 18, 19]. Importantly, gestational exposure to circadian disruption has been shown to impair bone development in offspring, suggesting transgenerational effects of rhythm perturbation [ 17]. Similar findings have been reported in periodontal disease models, where circadian disruption exacerbates alveolar bone loss and alters macrophage-mediated inflammatory responses [ 20, 21, 22, 23]. To counter these effects, therapeutic interventions have been explored, notably melatonin, a hormone closely linked to circadian regulation. In experimental models, melatonin has been reported to restore rhythmic stability and attenuate bone degeneration, suggesting potential utility as an adjunctive strategy for conditions such as osteoporosis—for review see [ 24, 25]. However, the magnitude and timing of melatonin’s skeletal effects remain variable across studies, underscoring the need for standardized temporal dosing paradigms. Genetic knockout models provide deeper insight into the molecular basis of skeletal health. For example, removal of BMAL1, a core clock gene, has been shown to interfere with osteoblast maturation [ 26], resulting in reduced bone formation and an osteoporosis-like phenotype—for review see [ 27]. However, global Bmal1 knockouts also exhibit premature aging, sarcopenia, altered feeding behavior, and hormonal dysregulation, complicating the interpretation of bone-specific phenotypes. To address this, conditional knockouts (e.g., Bmal1fl/fl; Ocn-Cre or Bmal1fl/fl; LysM-Cre) have been developed to isolate cell-type-specific circadian effects on osteoblasts and osteoclasts. In addition to mouse models, researchers have employed other species to investigate circadian effects on bone metabolism, including laying hens. Dietary phosphate feeding regimens showed circadian effects on eggshell deposition and thus eggshell quality [ 28]. Simultaneously, medullary bone samples collected showed inverse regulation of bone metabolism (eggshell strengthening led to bone weakening), as detected by osteoblast and osteoclast function [ 28]. These findings illustrate how circadian-driven mineral mobilization can differentially affect skeletal compartments. Despite their advantages, in vivo models face several challenges. Their systemic complexity introduces confounding factors (e.g., altered locomotor activity, feeding behavior, hormonal rhythms), making it difficult to attribute skeletal changes solely to circadian mechanisms. Moreover, these studies are resource-intensive and must comply with rigorous ethical standards. Collecting samples at multiple time-points, which is essential for circadian analysis, is technically demanding and may itself disrupt physiological rhythms. Furthermore, anesthesia, euthanasia timing (ZT vs. CT), and stress responses can significantly bias gene expression and biomarker measurements, a methodological issue often underreported in the literature. In summary, in vivo models remain the cornerstone of circadian bone research due to their physiological relevance, but careful experimental design and temporal control are essential to avoid misinterpretation of systemic versus bone-intrinsic circadian effects ( Figure 4). 3.2. Ex Vivo Model Systems Ex vivo models represent an intermediate platform between in vivo and in vitro systems for investigating circadian regulation in bone biology. These models typically involve the extraction of intact tissues such as bone slices, periodontal segments, or intervertebral discs from animal or human sources at defined circadian time points, followed by short-term culture under controlled environmental conditions [ 37]. This strategy allows the investigation of intrinsic rhythmic activity in bone cells outside the organism, while maintaining native tissue architecture and intercellular interactions. Although recent literature reports on circadian studies using transgenic Per1: Luc mice are limited, this model remains one of the most widely adopted ex vivo systems for circadian research. In Per1: LucPer2: Luc mice, the real-time expression of the core clock genes Per1Per2 can be visualized through bioluminescence imaging in bone explants [ 31, 38, 39]. These studies have demonstrated that peripheral tissues, including bone, retain autonomous circadian oscillations ex vivo for several days, allowing time-resolved analysis of clock gene expression and bone cell function. However, oscillatory amplitude typically dampens after 48–72 h, reflecting the absence of systemic synchronizing cues. In addition to classical ex vivo methodologies, ex vivo models frequently incorporate transgenic mice or rats as cell or tissue sources, offering valuable translational insights into the potential clinical consequences of circadian misalignment on bone physiology. One study showed that surgical procedures were performed on the hind limbs of transgenic mice to induce femoral fractures, followed by external fixation of the fracture site. After a defined period of stabilization, the fractured femoral tissue was excised and subsequently cultured in vitro. The expression of circadian rhythm-related genes in the bone tissue was first assessed under baseline culture conditions. Thereafter, stimulating factors such as parathyroid hormone (PTH) were introduced, and gene expression was reevaluated to determine the regulatory effects of these stimuli on circadian gene expression in bone. The results showed that PTH may have a potential role in promoting fracture healing [ 38]. This approach illustrates how ex vivo systems can be used to dissect time-dependent responses to therapeutic interventions. In another ex vivo experiment, the role of Rev-erbα in growth plate cartilage was investigated. Metatarsal tissue was isolated from mice and cultured under controlled conditions, after which a Rev-erbα antagonist was introduced into the culture medium. Subsequent analyses assessed bone tissue proliferation, differentiation, and mineralization. The findings demonstrated that inhibition of Rev-erbα suppressed growth plate development and longitudinal elongation of metatarsals, primarily through upregulation of the MAPK–ERK1/2 signaling pathway [ 40]. These results highlight the potential of ex vivo systems to evaluate pharmacological modulation of circadian regulators in bone. Ex vivo systems offer distinct advantages for circadian research in bone: they reduce the systemic variability inherent in whole-animal models, permit high-resolution temporal sampling, and preserve native tissue architecture and cell–cell interactions that are absent in traditional monolayer cultures. Nonetheless, these models are constrained by the lack of systemic regulatory inputs, such as hormonal and neural signals, and by the limited viability of tissue outside the organism, which restricts long-term rhythmic analysis [ 44]. Moreover, circadian oscillations in ex vivo bone tissue typically dampen rapidly, and synchronization protocols (e.g., serum shock, temperature cycles, or pharmacological cues) may be required to maintain rhythmicity. These methodological limitations must be carefully considered when interpreting ex vivo circadian data. Taken together, ex vivo models provide a powerful yet temporally constrained platform for studying intrinsic circadian properties of bone tissue. When combined with genetic manipulation, pharmacological perturbation, and advanced imaging techniques, they offer valuable mechanistic insights that complement both in vivo and in vitro approaches ( Figure 5). 3.3. In Vitro Model Systems In vitro systems provide a flexible and controlled framework for exploring the molecular and cellular dynamics of circadian rhythms in bone biology. These models typically involve culturing isolated bone cell types such as osteoblasts, osteoclasts, or mesenchymal stromal cells (MSCs) under well-defined laboratory conditions. This setup enables researchers to examine intrinsic circadian oscillations and functional responses without interference from systemic physiological factors. In vitro approaches can be broadly divided into mono-culture, co-culture, and advanced 3D or microphysiological systems, each offering distinct advantages for dissecting cell-intrinsic circadian mechanisms. 3.3.1. Simulating Circadian Rhythms In Vitro To mimic circadian fluctuations in vitro, cells must be synchronized using external cues known as zeitgebers. Commonly employed zeitgebers include serum starvation followed by serum shock (e.g., 50% fetal bovine serum for 2 h) [ 45] or PTH stimulation [ 38]. Once synchronized, the oscillatory expression of core clock genes such as Bmal1, Clock, Per1/2, and Cry1/2 can be tracked over 24 to 72 h using qRT-PCR, ELISA, Western blot, dot blotting, or bioluminescence-based real-time reporting in luciferase-tagged cell lines or primary cultures [ 46]. However, circadian oscillations in vitro typically dampen rapidly, often within 2–3 cycles, due to the absence of systemic entrainment cues. This limitation necessitates repeated synchronization or the use of perfusion-based culture systems to maintain rhythmicity. 3.3.2. Functional Insights into Circadian Gene Regulation In vitro platforms are instrumental in uncovering how circadian genes influence bone cell behavior. For example, knockdown or gene editing of Bmal1 or Clock in osteoblasts has been shown to influence apoptosis, proliferation, differentiation, and matrix mineralization. These effects are often mediated through pathways such as Wnt, Sirt1, MAPK, and ERK1/2 [ 47, 48, 49, 50]. In osteoclast precursors derived from Bmal1-deficient mice, studies have reported an increase in bone-loss phenotype [ 51], partly due to altered expression of key osteoclast markers such as TRAP and carbonic anhydrase II (CAII) [ 31]. Recent CRISPR-based screens have further identified additional circadian regulators in osteoblasts and osteoclasts, highlighting the complexity of clock-controlled transcriptional networks in bone. One noteworthy investigation employed human periodontal ligament fibroblast (PDLF)-like cells cultured under mechanical stress, supplemented with 10% fetal calf serum and varying concentrations of melatonin, a hormone known to modulate circadian rhythms. The study revealed that PDLFs differentiated into osteoclast-like cells, which was suggested to be mediated by melatonin-induced activation of the core clock gene Bmal1 [ 52]. Such findings underscore the potential of in vitro systems to model both mechanotransduction and hormonal entrainment of circadian pathways in bone cells. 3.3.3. Advanced Co-Culture and 3D Systems Advanced co-culture systems, including osteoblast–osteoclast co-cultures, MSC-derived 3D constructs, and microphysiological “bone-on-chip” platforms, provide more physiologically relevant environments for studying circadian regulation. These systems allow researchers to observe temporal gene expression and dynamic interactions under controlled conditions, providing a more integrated perspective on circadian regulation in bone. 3D scaffolds and perfused microfluidic systems can sustain circadian oscillations longer than traditional monolayers, reduce damping, and enable high-resolution temporal sampling of both gene expression and functional remodeling markers ( Figure 6). 3.3.4. Limitations of In Vitro Systems Despite their advantages, in vitro models face several limitations. Traditional 2D cultures lack the mechanical, biochemical, and spatial cues required for physiological circadian entrainment. Moreover, immortalized cell lines often exhibit weaker or unstable circadian rhythms compared to primary human cells, raising concerns about model validity. Additionally, the absence of systemic hormonal rhythms (e.g., melatonin, cortisol) limits the translational relevance of in vitro findings unless supplemented experimentally. Nevertheless, when combined with genetic manipulation, pharmacological perturbation, and advanced culture technologies, in vitro systems remain indispensable for mechanistic circadian research in bone biology. A comparative summary of the strengths, limitations, and typical readouts of each model system is provided in Table 2. 4. Discussion The present review provides a comprehensive synthesis of experimental approaches used to investigate circadian regulation in bone biology. By evaluating in vivo, ex vivo, and in vitro systems, we highlight how each model contributes unique but complementary perspectives on the temporal regulation of skeletal homeostasis. A key insight from this review is that no single model can fully capture the complexity of circadian regulation in bone. In vivo models provide physiological relevance but are confounded by systemic factors such as hormonal rhythms, feeding behavior, and locomotor activity [ 6, 21, 23, 25, 29, 30]. Ex vivo models preserve tissue architecture but lack endocrine and neural inputs [ 37, 40, 41, 42, 43]. In vitro models offer mechanistic precision but oversimplify the biological environment [ 45, 46]. Integrative approaches that combine these systems are therefore essential for generating reliable and translationally meaningful conclusions. 5. Limitation Finally, the field lacks consensus on appropriate statistical methods for analyzing circadian data. While tools such as cosinor analysis, JTK_CYCLE, and CircaCompare are increasingly used, differences in analytical pipelines can yield divergent interpretations of rhythmicity [ 57]. 6. Controversies, Human-Relevant Models, and Integrative Approaches 6.1. Controversies and Unresolved Questions Despite substantial progress, several controversies remain unresolved. In reality, skeletal circadian phenotypes vary widely depending on species, genetic background, environmental conditions, and methodological choices. Another unresolved issue is the stability of circadian rhythms in primary human bone cells. Emerging evidence suggests that human osteoblasts and osteoclasts may exhibit weaker or more variable oscillations than immortalized cell lines [ 16, 58]. Donor-specific factors such as age, sex, metabolic status, and medication history may further influence rhythmicity. 6.2. Human-Relevant Models Emerging platforms such as bone organoids and microphysiological ‘bone-on-chip’ systems enable multi-cellular interactions, mechanical stimulation, and controlled entrainment. These systems hold promise for modeling human-specific circadian dynamics but remain technically demanding and not yet widely adopted. 6.3. Integrative Approaches Across Model Systems Circadian regulation of bone is a multi-scale process involving molecular, cellular, tissue-level, and systemic interactions. Integrative workflows that combine in vivo, ex vivo, and in vitro models can overcome the limitations of individual systems. For example: Such multi-tiered strategies reduce model-specific bias, enhance reproducibility, and support the development of translationally relevant chronotherapeutic interventions. 7. Conclusions Circadian rhythms play a fundamental role in coordinating bone remodeling, influencing osteoblast and osteoclast activity, and shaping skeletal homeostasis across molecular, cellular, and systemic levels. Evidence from in vivo, ex vivo, and in vitro studies demonstrates that both environmental circadian disruption and genetic perturbation of core clock components can impair bone formation, enhance resorption, and alter tissue-level remodeling dynamics. Although each model system provides unique insights, their inherent limitations underscore the need for integrative, multi-scale approaches to fully understand circadian control of bone biology. Advancing human-relevant platforms and refining temporal experimental design will be essential for translating these findings into clinical strategies, including the development of chronotherapeutic interventions for metabolic bone diseases. Author Contributions Conceptualization, X.G. and A.K.N.; literature research and analysis, X.G. and X.C.; validation, A.K.N.; writing—original draft preparation, X.G.; writing—review and editing, all authors; visualization, X.C.; supervision, A.K.N.; project administration, A.K.N. All authors have read and agreed to the published version of the manuscript. Funding X.G. and X.C. are supported by the China Scholarship Council (grant numbers: 202208410090 (X.G) and 202306380049 (X.C.)). Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement No new data were created or analyzed in this study. Data sharing is not applicable to this article. Acknowledgments English language editing was supported by AI-based tools, including Microsoft Copilot (1.25103.107.0) and ChatGPT (5.0), which were used to refine grammar and phrasing. We acknowledge support from the Open Access Publishing Fund of the University of Tübingen. We would also like to thank Sabrina Ehnert (University of Tübingen) for her critical review of the manuscript. Conflicts of Interest The authors declare no conflicts of interest. Abbreviations ALP alkaline phosphatase CAII carbonic anhydrase II CTX collagen type I C-telopeptide ERK extracellular signal-regulated protein kinases MSC mesenchymal stromal cells NTX n-terminal cross-linked telopeptide of type I collagen MAPK mitogen-activated protein kinase OPG osteoprotegerin OCN osteocalcin PICP carboxy-terminal propeptide of type I procollagen PINP procollagen type I N-terminal propeptide PTH parathyroid hormone PDLF periodontal ligament fibroblast qRT-PCR quantitative reverse-transcription polymerase-chain reaction RANKL receptor activator of nuclear factor kappa-Β ligand TRAP tartrate-resistant acidic phosphatase ZT zeitgeber time References Gentry, N.W.; Ashbrook, L.H.; Fu, Y.H.; Ptacek, L.J. Human circadian variations. J. Clin. Investig. 2021, 131, e148282. [] [ CrossRef] Rijo-Ferreira, F.; Takahashi, J.S. Genomics of circadian rhythms in health and disease. Genome Med. 2019, 11, 82. [] [ CrossRef] Vitaterna, M.H.; Takahashi, J.S.; Turek, F.W. Overview of circadian rhythms. Alcohol Res. Health 2001, 25, 85–93. [] [ PubMed] Rudic, R.D.; McNamara, P.; Curtis, A.M.; Boston, R.C.; Panda, S.; Hogenesch, J.B.; Fitzgerald, G.A. BMAL1 and CLOCK, two essential components of the circadian clock, are involved in glucose homeostasis. PLoS Biol. 2004, 2, e377. [] [ CrossRef] Shimba, S.; Ishii, N.; Ohta, Y.; Ohno, T.; Watabe, Y.; Hayashi, M.; Wada, T.; Aoyagi, T.; Tezuka, M. Brain and muscle Arnt-like protein-1 (BMAL1), a component of the molecular clock, regulates adipogenesis. Proc. Natl. Acad. Sci. USA 2005, 102, 12071–12076. [] [ CrossRef] Marcheva, B.; Ramsey, K.M.; Buhr, E.D.; Kobayashi, Y.; Su, H.; Ko, C.H.; Ivanova, G.; Omura, C.; Mo, S.; Vitaterna, M.H.; et al. Disruption of the clock components CLOCK and BMAL1 leads to hypoinsulinaemia and diabetes. Nature 2010, 466, 627–631. [] [ CrossRef] Curtis, A.M.; Bellet, M.M.; Sassone-Corsi, P.; O’Neill, L.A. Circadian clock proteins and immunity. Immunity 2014, 40, 178–186. [] [ CrossRef] Yu, S.; Tang, Q.; Chen, G.; Lu, X.; Yin, Y.; Xie, M.; Long, Y.; Zheng, W.; Guo, F.; Shao, L.; et al. Circadian rhythm modulates endochondral bone formation via MTR1/AMPKbeta1/BMAL1 signaling axis. Cell Death Differ. 2022, 29, 874–887. [] [ CrossRef] [ PubMed] Chen, G.; Tang, Q.; Yu, S.; Xie, Y.; Sun, J.; Li, S.; Chen, L. The biological function of BMAL1 in skeleton development and disorders. Life Sci. 2020, 253, 117636. [] [ CrossRef] [ PubMed] Tian, Y.; Ming, J. The role of circadian rhythm in osteoporosis; a review. Front. Cell Dev. Biol. 2022, 10, 960456. [] [ CrossRef] Qin, Y.; Chen, Z.H.; Wu, J.J.; Zhang, Z.Y.; Yuan, Z.D.; Guo, D.Y.; Chen, M.N.; Li, X.; Yuan, F.L. Circadian clock genes as promising therapeutic targets for bone loss. Biomed. Pharmacother. 2023, 157, 114019. [] [ CrossRef] Luo, B.; Zhou, X.; Tang, Q.; Yin, Y.; Feng, G.; Li, S.; Chen, L. Circadian rhythms affect bone reconstruction by regulating bone energy metabolism. J. Transl. Med. 2021, 19, 410. [] [ CrossRef] [ PubMed] Bukowska-Damska, A.; Skowronska-Jozwiak, E.; Kaluzny, P.; Lewinski, A. Night shift work and osteoporosis—Bone turnover markers among female blue-collar workers in Poland. Chronobiol. Int. 2022, 39, 818–825. [] [ CrossRef] Bukowska-Damska, A.; Skowronska-Jozwiak, E.; Peplonska, B. Night shift work and osteoporosis: Evidence and hypothesis. Chronobiol. Int. 2019, 36, 171–180. [] [ CrossRef] Zvonic, S.; Ptitsyn, A.A.; Kilroy, G.; Wu, X.; Conrad, S.A.; Scott, L.K.; Guilak, F.; Pelled, G.; Gazit, D.; Gimble, J.M. Circadian oscillation of gene expression in murine calvarial bone. J. Bone Miner. Res. 2007, 22, 357–365. [] [ CrossRef] Diemar, S.S.; Dahl, S.S.; West, A.S.; Simonsen, S.A.; Iversen, H.K.; Jorgensen, N.R. A Systematic Review of the Circadian Rhythm of Bone Markers in Blood. Calcif. Tissue Int. 2023, 112, 126–147. [] [ CrossRef] [ PubMed] Chaves, I.; van der Eerden, B.; Boers, R.; Boers, J.; Streng, A.A.; Ridwan, Y.; Schreuders-Koedam, M.; Vermeulen, M.; van der Pluijm, I.; Essers, J.; et al. Gestational jet lag predisposes to later-life skeletal and cardiac disease. Chronobiol. Int. 2019, 36, 657–671. [] [ CrossRef] Schilperoort, M.; Bravenboer, N.; Lim, J.; Mletzko, K.; Busse, B.; van Ruijven, L.; Kroon, J.; Rensen, P.C.N.; Kooijman, S.; Winter, E.M. Circadian disruption by shifting the light-dark cycle negatively affects bone health in mice. FASEB J. 2020, 34, 1052–1064. [] [ CrossRef] Song, X.; Zhao, M.; Tang, J.; Ma, T.; Bai, H.; Wang, X.; Liu, L.; Li, T.; Xu, X.; Sheng, X.; et al. Dark-light cycle disrupts bone metabolism and suppresses joint deterioration in osteoarthritic rats. Arthritis Res. Ther. 2022, 24, 158. [] [ CrossRef] Zhang, C.; Tan, L.; Li, J.; Shen, Z.; Yao, J.; Huang, Y.; Wu, L.; Yu, C.; Gao, L.; Zhao, C. REV-ERBα Inhibits Osteoclastogenesis and Protects against Alveolar Bone Loss. J. Dent. Res. 2025, 104, 193–203. [] [ CrossRef] [ PubMed] Ye, L.; Mei, G.; Liu, H.; Zhong, R.; Tang, Q.; Yuan, Z. Circadian rhythm disruption aggravates alveolar bone loss in rat apical periodontitis. Int. Endod. J. 2025, 58, 744–756. [] [ CrossRef] [ PubMed] Ma, X.; Chen, X.; Duan, Z.; Wu, Y.; Shu, J.; Wu, P.; Zhao, Y.; Wang, X.; Wang, Y. Circadian rhythm disruption exacerbates the progression of macrophage dysfunction and alveolar bone loss in periodontitis. Int. Immunopharmacol. 2023, 116, 109796. [] [ CrossRef] Liu, X.; Cao, N.; Liu, X.; Deng, Y.; Xin, Y.; Fu, R.; Xin, X.; Hou, Y.; Yu, W. Circadian Rhythm Disorders Aggravate Periodontitis by Modulating BMAL1. Int. J. Mol. Sci. 2022, 24, 374. [] [ CrossRef] Lu, K.H.; Hsieh, Y.H.; Lin, R.C.; Tsai, M.Y.; Yang, S.F. Melatonin: A Potential Therapy for Osteoporosis with Insights into Molecular Mechanisms. J. Pineal Res. 2025, 77, e70062. [] [ CrossRef] Lu, X.; Yu, S.; Chen, G.; Zheng, W.; Peng, J.; Huang, X.; Chen, L. Insight into the roles of melatonin in bone tissue and bone-related diseases (Review). Int. J. Mol. Med. 2021, 47, 82. [] [ CrossRef] Tsang, K.; Liu, H.; Yang, Y.; Charles, J.F.; Ermann, J. Defective circadian control in mesenchymal cells reduces adult bone mass in mice by promoting osteoclast function. Bone 2019, 121, 172–180. [] [ CrossRef] [ PubMed] Ze, Y.; Wu, Y.; Tan, Z.; Li, R.; Li, R.; Gao, W.; Zhao, Q. Signaling pathway mechanisms of circadian clock gene Bmal1 regulating bone and cartilage metabolism: A review. Bone Res. 2025, 13, 19. [] [ CrossRef] Yan, J.; Wang, J.; Chen, J.; Shi, H.; Liao, X.; Pan, C.; Liu, Y.; Yang, X.; Ren, Z.; Yang, X. Adjusting phosphate feeding regimen according to daily rhythm increases eggshell quality via enhancing medullary bone remodeling in laying hens. J. Anim. Sci. Biotechnol. 2023, 14, 17. [] [ CrossRef] Winter, E.M.; Kooijman, S.; Appelman-Dijkstra, N.M.; Meijer, O.C.; Rensen, P.C.; Schilperoort, M. Chronobiology and Chronotherapy of Osteoporosis. JBMR Plus 2021, 5, e10504. [] [ CrossRef] [ PubMed] Swanson, C.M.; Kohrt, W.M.; Buxton, O.M.; Everson, C.A.; Wright, K.P., Jr.; Orwoll, E.S.; Shea, S.A. The importance of the circadian system & sleep for bone health. Metabolism 2018, 84, 28–43. [] [ CrossRef] Takarada, T.; Xu, C.; Ochi, H.; Nakazato, R.; Yamada, D.; Nakamura, S.; Kodama, A.; Shimba, S.; Mieda, M.; Fukasawa, K.; et al. Bone Resorption Is Regulated by Circadian Clock in Osteoblasts. J. Bone Miner. Res. 2017, 32, 872–881. [] [ CrossRef] Wilsbacher, L.D.; Yamazaki, S.; Herzog, E.D.; Song, E.J.; Radcliffe, L.A.; Abe, M.; Block, G.; Spitznagel, E.; Menaker, M.; Takahashi, J.S. Photic and circadian expression of luciferase in mPeriod1-luc transgenic mice invivo. Proc. Natl. Acad. Sci. USA 2002, 99, 489–494. [] [ CrossRef] van der Spoel, E.; Oei, N.; Cachucho, R.; Roelfsema, F.; Berbee, J.F.P.; Blauw, G.J.; Pijl, H.; Appelman-Dijkstra, N.M.; van Heemst, D. The 24-hour serum profiles of bone markers in healthy older men and women. Bone 2019, 120, 61–69. [] [ CrossRef] Fu, L.; Patel, M.S.; Bradley, A.; Wagner, E.F.; Karsenty, G. The molecular clock mediates leptin-regulated bone formation. Cell 2005, 122, 803–815. [] [ CrossRef] Dovio, A.; Generali, D.; Tampellini, M.; Berruti, A.; Tedoldi, S.; Torta, M.; Bonardi, S.; Tucci, M.; Allevi, G.; Aguggini, S.; et al. Variations along the 24-hour cycle of circulating osteoprotegerin and soluble RANKL: A rhythmometric analysis. Osteoporos. Int. 2008, 19, 113–117. [] [ CrossRef] Zhang, J.; Wu, S.; Xing, F.; Kong, N.; Zhao, Y.; Duan, X.; Li, Y.; Wang, K.; Tian, R.; Yang, P. Unveiling the role of melatonin-related gene CSNK1D in osteoclastogenesis and its implications for osteoporosis treatment. Exp. Physiol. 2025, 110, 261–276. [] [ CrossRef] [ PubMed] Szczesny, S.E. Ex vivo models of musculoskeletal tissues. Connect. Tissue Res. 2020, 61, 245–247. [] [ CrossRef] Kunimoto, T.; Okubo, N.; Minami, Y.; Fujiwara, H.; Hosokawa, T.; Asada, M.; Oda, R.; Kubo, T.; Yagita, K. A PTH-responsive circadian clock operates in ex vivo mouse femur fracture healing site. Sci. Rep. 2016, 6, 22409. [] [ CrossRef] [ PubMed] Okubo, N.; Minami, Y.; Fujiwara, H.; Umemura, Y.; Tsuchiya, Y.; Shirai, T.; Oda, R.; Inokawa, H.; Kubo, T.; Yagita, K. Prolonged bioluminescence monitoring in mouse ex vivo bone culture revealed persistent circadian rhythms in articular cartilages and growth plates. PLoS ONE 2013, 8, e78306. [] [ CrossRef] Qian, Z.; Liu, Z.; Feng, Z.; Cai, Z.; Qiu, Y.; Zhu, Z. Blocking circadian clock factor Rev-erbα inhibits growth plate chondrogenesis via up-regulating MAPK-ERK1/2 pathway. Cell Cycle 2023, 22, 73–84. [] [ CrossRef] [ PubMed] Tian, Y.; Liu, X.; Lu, Q.; Li, J.; Wang, T.; Tian, M.; Ding, Y.; Li, J. Bmal1 knockout aggravates Porphyromonas gingivalis-induced periodontitis by activating the NF-kappaB pathway. J. Appl. Oral Sci. 2025, 33, e20240388. [] [ CrossRef] McElderry, J.-D.P.; Zhao, G.; Khmaladze, A.; Wilson, C.G.; Franceschi, R.T.; Morris, M.D. Tracking circadian rhythms of bone mineral deposition in murine calvarial organ cultures. J. Bone Miner. Res. 2013, 28, 1846–1854. [] [ CrossRef] Kikyo, N. Circadian Regulation of Bone Remodeling. Int. J. Mol. Sci. 2024, 25, 4717. [] [ CrossRef] [ PubMed] Liu, A.C.; Welsh, D.K.; Ko, C.H.; Tran, H.G.; Zhang, E.E.; Priest, A.A.; Buhr, E.D.; Singer, O.; Meeker, K.; Verma, I.M.; et al. Intercellular coupling confers robustness against mutations in the SCN circadian clock network. Cell 2007, 129, 605–616. [] [ CrossRef] [ PubMed] Balsalobre, A.; Damiola, F.; Schibler, U. A serum shock induces circadian gene expression in mammalian tissue culture cells. Cell 1998, 93, 929–937. [] [ CrossRef] Abe, Y.O.; Yoshitane, H.; Kim, D.W.; Kawakami, S.; Koebis, M.; Nakao, K.; Aiba, A.; Kim, J.K.; Fukada, Y. Rhythmic transcription of Bmal1 stabilizes the circadian timekeeping system in mammals. Nat. Commun. 2022, 13, 4652. [] [ CrossRef] Li, L.; Zhang, M.; Zhao, C.; Cheng, Y.; Liu, C.; Shi, M. Circadian clock gene Clock-Bmal1 regulates cellular senescence in Chronic obstructive pulmonary disease. BMC Pulm. Med. 2022, 22, 435. [] [ CrossRef] Yang, W.; Kang, X.; Liu, J.; Li, H.; Ma, Z.; Jin, X.; Qian, Z.; Xie, T.; Qin, N.; Feng, D.; et al. Clock Gene Bmal1 Modulates Human Cartilage Gene Expression by Crosstalk with Sirt1. Endocrinology 2016, 157, 3096–3107. [] [ CrossRef] Soejima, Y.; Iwata, N.; Nakano, Y.; Yamamoto, K.; Suyama, A.; Nada, T.; Otsuka, F. Biphasic Roles of Clock Genes and Bone Morphogenetic Proteins in Gonadotropin Expression by Mouse Gonadotrope Cells. Int. J. Mol. Sci. 2021, 22, 11186. [] [ CrossRef] Min, H.Y.; Kim, K.M.; Wee, G.; Kim, E.J.; Jang, W.G. Bmal1 induces osteoblast differentiation via regulation of BMP2 expression in MC3T3-E1 cells. Life Sci. 2016, 162, 41–46. [] [ CrossRef] [ PubMed] Samsa, W.E.; Vasanji, A.; Midura, R.J.; Kondratov, R.V. Deficiency of circadian clock protein BMAL1 in mice results in a low bone mass phenotype. Bone 2016, 84, 194–203. [] [ CrossRef] Schroder, A.; Alefeld, A.; Forneck, A.; Spanier, G.; Deschner, J.; Proff, P.; Kirschneck, C. Impact of melatonin on periodontal ligament fibroblasts during mechanical strain. Eur. J. Orthod. 2022, 44, 659–668. [] [ CrossRef] [ PubMed] Xu, C.; Ochi, H.; Fukuda, T.; Sato, S.; Sunamura, S.; Takarada, T.; Hinoi, E.; Okawa, A.; Takeda, S. Circadian Clock Regulates Bone Resorption in Mice. J. Bone Miner. Res. 2016, 31, 1344–1355. [] [ CrossRef] Gaspar, L.; Brown, S.A. Measuring circadian clock function in human cells. Methods Enzymol. 2015, 552, 231–256. [] [ CrossRef] Joseph, F.; Chan, B.Y.; Durham, B.H.; Ahmad, A.M.; Vinjamuri, S.; Gallagher, J.A.; Vora, J.P.; Fraser, W.D. The circadian rhythm of osteoprotegerin and its association with parathyroid hormone secretion. J. Clin. Endocrinol. Metab. 2007, 92, 3230–3238. [] [ CrossRef] [ PubMed] Swanson, C.; Shea, S.A.; Wolfe, P.; Markwardt, S.; Cain, S.W.; Munch, M.; Czeisler, C.A.; Orwoll, E.S.; Buxton, O.M. 24-hour profile of serum sclerostin and its association with bone biomarkers in men. Osteoporos. Int. 2017, 28, 3205–3213. [] [ CrossRef] Zhu, X.; Han, X.; Li, Z.; Zhou, X.; Yoo, S.H.; Chen, Z.; Ji, Z. CircaKB: A comprehensive knowledgebase of circadian genes across multiple species. Nucleic Acids Res. 2025, 53, D67–D78. [] [ CrossRef] Ehnert, S.; Gao, X.; Heßlinger, M.; Braun, N.R.; Schulz, K.A.; Jahn, D.; Springer, F.; Nussler, A.K. In Vitro Modeling of Diurnal Changes in Bone Metabolism. Int. J. Mol. Sci. 2025, 26, 7699. [] [ CrossRef] [ PubMed] Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. © 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Share and Cite MDPI and ACS Style Gao, X.; Cai, X.; Nussler, A.K. Modeling the Clockwork of Bone: A Narrative Review of Experimental Approaches to Circadian Rhythm in Bone Metabolism. Int. J. Mol. Sci. 2026, 27, 5167. https://doi.org/10.3390/ijms27125167 AMA Style Gao X, Cai X, Nussler AK. Modeling the Clockwork of Bone: A Narrative Review of Experimental Approaches to Circadian Rhythm in Bone Metabolism. International Journal of Molecular Sciences. 2026; 27(12):5167. https://doi.org/10.3390/ijms27125167 Chicago/Turabian Style Gao, Xiang, Xinyuan Cai, and Andreas K. Nussler. 2026. "Modeling the Clockwork of Bone: A Narrative Review of Experimental Approaches to Circadian Rhythm in Bone Metabolism" International Journal of Molecular Sciences 27, no. 12: 5167. https://doi.org/10.3390/ijms27125167 APA Style Gao, X., Cai, X., & Nussler, A. K. (2026). Modeling the Clockwork of Bone: A Narrative Review of Experimental Approaches to Circadian Rhythm in Bone Metabolism. International Journal of Molecular Sciences, 27(12), 5167. https://doi.org/10.3390/ijms27125167 Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details . Article Metrics Article metric data becomes available approximately 24 hours after publication online.
Modeling the Clockwork of Bone: A Narrative Review of Experimental Approaches to Circadian Rhythm in Bone Metabolism
