Bone cell mechanosensitivity, estrogen deficiency, and osteoporosis

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Bone cell mechanosensitivity, estrogen deficiency, and osteoporosis J. Klein-Nulend, R.F.M. van Oers, A.D. Bakker, R. G. Bacabac

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Accepted date: 26 November 2014 Cite this article as: J. Klein-Nulend, R.F.M. van Oers, A.D. Bakker, R.G. Bacabac, Bone cell mechanosensitivity, estrogen deficiency, and osteoporosis, Journal of Biomechanics, http://dx.doi.org/10.1016/j.jbiomech.2014.12.007 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

BONE CELL MECHANOSENSITIVITY, ESTROGEN DEFICIENCY, AND OSTEOPOROSIS

J. Klein-Nulend1, R.F.M. van Oers1,2, A.D. Bakker1, R.G. Bacabac3

1

Department of Oral Cell Biology, ACTA-University of Amsterdam and VU University Amsterdam, MOVE Research Institute Amsterdam, Amsterdam, The Netherlands

2

Department of Dental Materials Science, ACTA-University of Amsterdam and VU University Amsterdam, MOVE Research Institute Amsterdam, Amsterdam, The Netherlands

3

Department of Physics, Medical Biophysics Group, University of San Carlos, Cebu City, Philippines

Corresponding author: Jenneke Klein-Nulend, PhD Department of Oral Cell Biology ACTA-VU University Amsterdam MOVE Research Institute Amsterdam Amsterdam, The Netherlands tel

+31 20 5980881

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+31 20 5980333

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[email protected]

Key words: Mechanical loading; Osteocytes; Estrogen deficiency; Osteoporosis; Computer simulation

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ABSTRACT Adaptation of bone to mechanical stresses normally produces a bone architecture that combines a proper resistance against failure with a minimal use of material. This adaptive process is governed by mechanosensitive osteocytes that transduce the mechanical signals into chemical responses, i.e. the osteocytes release signaling molecules, which orchestrate the recruitment and activity of bone forming osteoblasts and/or bone resorbing osteoclasts. Computer models have shown that the maintenance of a mechanically-efficient bone architecture depends on the intensity and spatial distribution of the mechanical stimulus as well as on the osteocyte response. Osteoporosis is a condition characterized by a reduced bone mass and a compromized resistance of bone against mechanical loads, which has led us to hypothesize that mechanotransduction by osteocytes is altered in osteoporosis. One of the major causal factors for osteoporosis is the loss of estrogen, the major hormonal regulator of bone metabolism. Loss of estrogen may increase osteocyte-mediated activation of bone remodeling, resulting in impaired bone mass and architecture. In this review we highlight current insights on how osteocytes perceive mechanical stimuli placed on whole bones. Particular emphasis is placed on the role of estrogen in signaling pathway activation by mechanical stimuli, and on computer simulation in combination with cell biology to unravel biological processes contributing to bone strength.

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GENERAL INTRODUCTION Osteoporosis is a common disorder of aging. It is a skeletal disease characterized by low bone mass and micro-architectural deterioration of bone tissue leading to increased bone fragility and susceptibility to fractures. Osteoporosis is a major health problem, as it is estimated that over 200 million people worldwide suffer from this disease (Cooper et al., 1992). It manifests itself by fractures of the lower forearm, the humerus, the lower thoracic and lumbar vertebrae, the proximal femur, and the hip. However, fragility fractures can occur in many other sites. The incidence of hip fractures rises exponentially after the age of 50 years, i.e. it doubles every 6 years in both sexes. Worldwide 1.6 million elderly are admitted to the hospital per year for hip fracture. Usually they are operated and subsequently rehabilitated in a nursing home. The long-term outcome is moderate. One year after hip fracture 25% of the patients have died, 40% can walk poorly or is wheelchairbound, and 60% can walk more or less as before the fracture. Vertebral fractures also cause considerable morbidity, such as pain, decrease of physical function, immobility, and social and emotional problems. Osteoporosis is caused by hormonal changes and decreased mobility with aging, superimposed on a genetic susceptibility. It is aggravated by other chronic and aging diseases (Raisz, 2007). In view of the importance of mechanical stress for maintaining bone strength, mechanical stimuli have great potential for prevention and even treatment of osteoporosis (Lock et al., 2006; Rubin and McLeod, 1996). In contrast to systemic, pharmaceutical agents such as estrogen or bisphosphonates, the attribute of mechanical prophylaxis is that it is native to the bone tissue, safe at low intensities, and targets all cell types involved in the remodeling cycle. It will ultimately induce lamellar bone at those locations where it contributes most to mechanical strength, while the relative amplitude of the stimulus will subside as bone formation persists. However, the widespread use of mechanical stimuli in the prevention or treatment of osteoporosis is hampered because we do not fully understand how these signals work, and whether they still work as efficiently in the elderly and in postmenopausal women. The separate effects of impaired 3

mechanosensitivity and estrogen insufficiency have been related with mechanical failure of bone tissue (Raisz, 2007; Riggs et al., 2002; Turner et al., 1994). However new and more effective approaches to treat osteoporosis are likely to emerge from a better understanding of the combined effect of these regulators of bone cell function. Only if the separate roles of estrogen and mechanical stress in maintaining adequate bone architecture and density are clarified, can the interaction between both preventive measures be studied in a rational manner. The quantitative relationship between stress magnitude and frequency, and bone cell responses has been investigated (Bacabac et al., 2004; Bacabac et al., 2006, Bacabac 2009). To prevent, or even cure, osteoporosis by mechanical loading, possibly in combination with estrogen mimetic therapy, validated computer simulation models offer good opportunities to test the expected efficacy of a combination therapy, even before costly and time-consuming animal studies are performed (van Rietbergen et al., 1998). The combination of cell biological and computersimulation studies has provided a framework based on experimental observations to explain these interactions and their effect in terms of bone strength (Ruimerman et al., 2005).

HISTORICAL PERSPECTIVE ON BONE CELL MECHANOSENSITIVITY, ESTROGEN DEFICIENCY, AND OSTEOPOROSIS Osteoporosis has probably existed throughout human history, but only more recently became a major clinical problem as human lifespan increased. In the early 19th century, Sir Astley Cooper, a distinguished English surgeon, noted “the lightness of bone …favors much the production of fractures” (Cooper and Cooper, 1822). The cause of the disease is not yet completely understood, but is likely multifactorial (Cummings et al., 1995; Delmas, 1996). One factor very often involved is sex hormone deficiency, in particular estrogen deficiency in postmenopausal osteoporosis. Several clinical studies have demonstrated the beneficial effect of estrogen replacement therapy in preventing bone loss following menopause (Kanis, 1995; Lindsey, 1995). However, epidemiological studies point to other risk factors, some of which are genetically determined, 4

others relating to mobility (Cummings et al., 1995). Bone turnover is controlled by mechanical usage in a hormonal environment (Rodan, 1996). The complexity of the regulatory processes has precluded complete unraveling of the causes for bone deterioration in osteoporosis. Bone tissue adapts its mass and structure to changes in mechanical loading (Wolff’s Law). During the last decades it has been well established that lack of physical exercise, or disuse, can lead to osteopenia (Heinonen et al., 1995; Leblanc et al., 1990), while mechanical stimulation can prevent the negative effect of disuse (Lanyon, 1992). The first isolation and culture of osteocytes (Van der Plas and Nijweide, 1992; Aarden et al., 1996) allowed in vitro studies showing that osteocytes from human and animal bone are very sensitive to mechanical stress. Cultured osteocytes respond to stress with a rapid release of prostaglandins and nitric oxide (NO) (Ajubi et al., 1999; Klein-Nulend et al., 1995a; Klein-Nulend et al., 1995b; Klein-Nulend et al., 2002), followed by induction of cyclooxygenase-2 (COX-2) (Bakker et al., 2003; Klein-Nulend et al., 1997). Cyclooxygenase (COX), in particular COX-2, the inducible isoform of the enzyme, has been suggested to be involved in the osteogenic response to mechanical stress in vivo (Forwood, 1996). ecNOS has been suggested to be an enzyme involved in the adaptive response of the vasculature to (blood) fluid shear stress (Busse et al., 1995), and to play a role in bone adaptation as well (Helfrich et al., 1997; Klein-Nulend et al., 1995b; Klein-Nulend et al., 1998; Turner et al., 1996). These observations indicated that mechanical stress is a direct regulator of bone cell activity (Ajubi et al., 1996; Klein-Nulend et al., 1995a; Klein-Nulend et al., 1995b; Klein-Nulend et al., 2002; Bakker et al., 2003), and that disuse-related bone loss results from a lack of mechanical activation of bone cells. In the field of bone biomechanics, many attempts have been made to relate the stresses and strains applied to bone quantitatively to bone mass and architecture (Huiskes et al., 1993). Already more than twenty years ago, empirical mathematical models of the mechanically driven regulatory processes were combined with finite element methods, to capture the potential relationships in computer-simulation models (Carter, 1987; Cowin, 1993; Weinans et al., 1992). 5

Validation studies using animal and human material have confirmed the value of this approach (Mullender and Huiskes, 1995; Mullender and Huiskes, 1997). Based on these early analyses, the normal architecture of trabecular bone could be explained as the result of a continuous mechanical adaptation process, controlled by mechanosensitive osteocytes (Mullender and Huiskes, 1997). These findings predicted that osteoporosis may result from impaired bone cell mechanosensitivity, even if the loading patterns are normal. This strengthens the validity of hypotheses formulated by cell biologists and endocrinologists, the most well known being the “mechanostat” theory. Harold Frost first introduced this “mechanostat” theory in which he proposed the existence of a homeostatic regulatory mechanism in bone with two strain “setpoints”, above or below which bone formation or resorption occurs (Frost, 1987). Disease such as postmenopausal osteoporosis might change these “setpoints”, resulting in a lack of bone formation or excess bone resorption at mechanical loading intensities that would normally maintain bone mass. Indeed, early studies report that in osteoporosis the effectiveness of mechanical stress for eliciting a cellular response may be impaired (Sterck et al., 1998). Bone cells from patients with established osteoporosis showed an abnormal response to fluid shear stress in vitro (Bakker et al., 2006; Sterck et al., 1998). Notably, the stress-stimulated release of prostaglandins, important mediators of the induction of bone formation by mechanical stress (Chow and Chambers, 1994; Forwood, 1996), was low or absent in these patients, in contrast to the age-matched control group (Bakker et al., 2006; Sterck et al., 1998). These observations indicated that an intrinsic, genetically determined lack of mechanosensitivity may be present in osteoporotic patients. Around the same time that the first experiments with bone cells from osteoporotic donors were performed, it was found that estrogen deficiency by itself interacts with the anabolic effect of mechanical stress (Cheng et al., 1996). In a study using rat caudal vertebrae submitted to loading, estrogen acted primarily not on the strain sensing mechanism itself, but on the osteogenic response to signals from strain-sensitive cells (Jagger et al., 1996). These studies suggested that 6

the bone loss following estrogen withdrawal may result from a reduced effectiveness of the loading-related stimulus on osteoblast activity. The combination of intrinsically impaired mechanosensitivity and estrogen deficiency might then lead to fragile bone. In the ensuing decades evidence has accumulated that this may indeed be the case. This will be addressed in the following paragraph. How bone fragility relates to bone density and trabecular architecture has been subject of several studies (Goldstein et al., 1993; Hodgskinson and Currey, 1990; Mullender and Huiskes, 1995). It has been known for a long time that bone density alone is an imperfect predictor of fracture risk (Johnston and Melton, 1995; Recker, 1993). Fracture characteristics not only depend on the magnitude, but also on the directionality of the load. Therefore, fracture risk is also determined by morphological characteristics, i.e. the architectural efficacy of trabecular bone to cope with high loads, such as during falls. Although architecture has been characterized by several kinds of morphometric parameters (Goldstein et al., 1993; Mullender and Huiskes, 1997; Odgaard et al., 1997; Parfitt, 1982; Van Rietbergen et al., 1996a; Weinans and Prendergast, 1996; e.g. volume fraction, mean intercept length, volume orientation, trabecular width, trabecular connectivity, trabecular separation), a reliable, generic relationship with strength has not yet been found. Although bone strength can be measured ex vivo in destructive mechanical tests, these tests are known to be unreliable, particularly for small specimens (Linde and Hvid, 1989). Moreover multi-directional destructive tests are impossible in principle. A way out of this impasse was first reached through the application of large-scale micromechanical finite-element (FE) models (Van Rietbergen et al., 1996b). These models can be used to simulate multi-axial strength tests in the computer, based on a three-dimensional (3D) computer-graphics reconstruction of a bone specimen. At that time the 3D reconstructions were generated with micro-CT scanners, but the same principles still hold for modern day 3D in vivo scan techniques. The FE analysis provides stress distributions at the trabecular tissue level for each external loading case selected,

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from which failure risks can be estimated. In this way, the inherent mechanical failure resistance of a bone specimen can be established (Van Rietbergen et al., 1998; Weinans et al., 1997).

CURRENT INSIGHTS IN BONE CELL MECHANOSENSITIVITY AND MECHANICAL ADAPTATION OF BONE

Osteocytes sense mechanical stimuli and direct mechanical adaptation of bone Osteocytes sense physical stimuli derived from mechanical forces exerted on bone (reviewed in: Klein-Nulend et al., 2012) (Figure 1). They comprise 90% of the bone cells, and are embedded in the calcified bone matrix. They form many cell-cell contacts through their long slender cell processes, forming a syncytium capable of rapid signal transduction. Osteocytes are highly mechanosensitive; after mechanical stimulation they alter the production of a range of signaling molecules, such as bone morphogenetic proteins (BMPs), Wnts, PGE2, and NO (reviewed in: Klein-Nulend et al., in press), which modulate recruitment, differentiation, and activity of osteoblasts and osteoclasts (Robling et al., 2006; Santos et al., 2009; Tan et al., 2007; You et al., 2008). Osteocytes are theoretically capable of orchestrating the cellular process of bone adaptation in response to mechanical loading (Burger and Klein-Nulend, 1999; Burger et al., 2003; Smit et al., 2002). They have been shown to be essential mediators of osteoclastic bone resorption in response to unloading of bone (Tatsumi et al., 2007). The bone loss after hind limb unloading was prevented when 80% of the osteocytes were ablated. Osteocytes thus seem to stimulate osteoclast activity in the absence of daily mechanical loads, a capability that has been confirmed by in vitro studies (Kulkarni et al., 2010; You et al., 2008). RANKL produced by osteocytes determines bone mass in adult mice, demonstrating the importance of osteocytes in the regulation of bone mass (Nakashima et al., 2011; Xiong et al., 2011). Interestingly the anabolic response of bone to (re)loading did not require living

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osteocytes (Tatsumi et al., 2007), which does not eliminate a role of osteocytes in mediating the anabolic response of bone to loading under normal conditions.

Mechanical stimulation of osteocytes Whole bone loads result in matrix strains, which in theory could be sensed directly by the osteocytes (Nicolella et al., 2006). Osteocytes might indeed respond to matrix strains directly (Bonivtch et al., 2007). Substrate deformations as low as 3,400 microstrain increase signalling molecule production by osteoblasts (Robinson et al., 2006), and osteocytes are more mechanosensitive than osteoblasts (Klein-Nulend et al., 1995a). The matrix strains also stimulate the interstitial fluid surrounding the osteocyte cell processes to flow across a pressure gradient (Weinbaum et al., 1994). Deformations of the bone matrix have been shown to drive interstitial fluid flow in sheep tibia (Knothe-Tate et al., 1998; Knothe-Tate et al., 2000), and canalicular fluid flow has been correlated with mechanical loading in mouse tibia (Price et al., 2011). This fluid flow “amplifies” local strains, and is thereby a likely mechanical signal that is sensed by the osteocytes (Fritton and Weinbaum, 2009). Numerous studies have shown that osteocytes in vitro are sensitive to fluid flow when seeded as a monolayer of cells on flat, 2-dimensional (2D) substrates (Ajubi et al., 1996; Bacabac et al., 2004; Bakker et al., 2001; Bakker et al., 2009; Juffer et al., 2012; Klein-Nulend et al., 1995a; Klein-Nulend et al., 1995b; Kulkarni et al., 2012; Litzenberger et al., 2010). Using a Stokesian fluid stimulus probe it has been shown that electrical signaling is provoked when applied to an osteocytic cell process in vitro on a 2D surface (Wu et al., 2011). Interstitial fluid flow within the canaliculi is driven only over osteocyte processes in vivo, while a laminar fluid flow over cells seeded in a parallel plate flow chamber deforms both the cell body and the cell processes. In theory this could elicit a response that otherwise would not be provoked (Fritton and Weinbaum, 2009; McGarry et al., 2005a). Yet, so far virtually all experiments performed with bone cells on glass slides and in vivo show comparable biochemical responses. It has been 9

suggested that fluid flow over the osteocyte processes in the lacuno-canalicular porosity induces strains in the actin filament bundles of the cytoskeleton that are more than an order of magnitude larger than tissue level strains (You et al., 2001). A more recent theoretical model predicts that integrin-based attachment complexes along osteocyte cell processes dramatically and focally amplifiy small tissue-level strains (Wang et al., 2007). The theoretical model predicts that the tensile forces acting on αvβ3 integrins (McNamara et al., 2009) are <15 pN, and that axial strains caused by the sliding of actin microfilaments along the fixed integrin attachments are an order of magnitude larger than the radial strains in the earlier proposed strainamplification theory (Wang et al., 2007). Based on recent 3D reconstruction of a human osteocyte canaliculus using high-voltage EM, new and realistic models can be developed that will even further enhance our understanding of how whole bone loads are transduced into a signal that can be sensed by osteocytes (Kamioka et al., 2012). Interestingly, the morphology of the canalicular network may be altered in osteoporosis (Sharma et al., 2012), which makes it possible that loads placed on whole bones are less efficiently transduced to the osteocytes. Recently it has been been shown that bone changes resulting from reduced estrogen levels alter interstitial fluid flow around osteocytes in cancellous rat bone (Ciani et al., 2014). The altered interstitial fluid flow around osteocytes is likely related to nanostructural matrix-mineral level differences at the lacuno-canalicular surface after estrogen deprivation, which could affect the transmission of mechanical loads to the osteocyte. Not only the morphology of the canalicular network may affect the transmission of mechanical signals towards the osteocytes, but also the morphology of the osteocyte cell bodies and lacunae may be involved in this process. Since direct mechanosensing of matrix strain likely occurs by the cell bodies, the differences in osteocyte morphology and their lacunae might indicate differences in osteocyte mechanosensitivity. Indeed, the mechanosensitivity of osteocytes appears to be strongly influenced by their morphology (Bacabac et al., 2008). Osteocyte morphology might play a role in various bone pathologies such as osteoporosis, 10

since it has been observed in cortical bone of the tibia of patients with different BMD (osteoarthritis, osteopenia, and osteopetrosis), that there are significant differences in the morphology of osteocytes as well as their lacunae (Figures 2 and 3). These differences in 3D osteocyte morphology may be a consequence of the differences in matrix strain in these bones in response to similar external physiological mechanical loading. However, differences in 3D osteocyte morphology also cause a change in sensitivity of the osteocytes to mechanical signals, thereby making osteocyte shape a potential causative factor for changes in bone mass.

Osteocyte mechanosensing Sensing of mechanical signals at the cellular level is enabled by force-induced conformational changes in cellular structures, e.g. stretch-activated ion channels, integrin complexes, primary cilia, gap junctions, and cell-cell adhesions (Zhang et al., 2011). The conformational changes enable ion influx and efflux or the activation of signaling cascades, resulting in altered protein activity and production (Hoffman et al., 2011). Integrins anchor to the extracellular matrix and mechanically link the cell exterior to the cytoskeleton, forming transmembrane complex structures. These complexes are often clustered in focal adhesions, and likely function as mechanotransducers (Litzenberger et al., 2010; Santos et al., 2010). The cytoskeleton, a composite gel-like material of actin, microtubules, intermediate filaments and their cross-linkers, is the scaffold determining cellular shape and stiffness (Sugawara et al., 2008). The importance of anchoring mechanotransduction complexes that connect the extracellular matrix to the cytoskeleton predicts that the osteocyte cytoskeleton plays a key role in osteocyte mechanotransduction. The osteocyte is able to discern different stimuli applied at different frequencies (Li, Rose et al., 2012). The highly dynamic nature of the attachment sites and the cytoskeleton, which are continuously undergoing turnover, likely explains how mechanical stimuli of varying magnitude and frequency regulate distinct signaling pathways (Hoffman et al., 2011). The 11

viscoelastic properties of the cytoskeletal structure provide cells with resistance to shear or compression, enable cell migration and transport of intracellular molecules, determine the cell’s mechanical properties, and allow for mechanosensing (reviewed in: Klein-Nulend et al., 2012). The distribution of cytoskeletal structures (actin, intermediate filaments, and microtubules) changes when osteoblasts differentiate into osteocytes. Moreover osteoblast stiffness decreases during differentiation towards osteocytes (Sugawara et al., 2008). Microtubules are limited to the proximal region of osteocyte processes but extend the entire length of cell processes of osteoblasts grown in 3D (Murshid et al., 2007). Microtubules are essential for the integrity and formation of osteoblast cell processes grown in 3D, but processes of primary osteocytes in 3D are dependent on actin (Murshid et al., 2007). Actin filaments are also crucial for maintaining the shape of osteocytes cultured on flat substrates (Tanaka-Kamioka et al., 1998). Osteocytes also contain actin-bundling proteins distinctive of that in osteoblasts. Fimbrin and α-actinin are predominantly found in osteocyte processes (Kamioka et al., 2004), whereas villin is abundantly present in the cytoplasm but not in the processes. Disruption of both the actin and microtubule cytoskeleton inhibits mechanical stimulation-mediated release of PGE2 in osteocytes (McGarry et al., 2005b). In osteoblasts, which depend on microtubules rather than actin for their cytoskeletal integrity, inhibition of actin polymerization does not inhibit intracellular calcium mobilization or PGE2 release in response to a mechanical stimulus (Malone et al., 2007; McGarry et al., 2005b). In contrast, disruption of the actin cytoskeleton in chicken calvarial osteoblasts strongly inhibits mechanical loading-stimulated PGE2 release (Ajubi et al., 1996). Whether the osteocyte cytoskeleton is altered in osteoporosis is unknown, but it is striking that a mutation in the actin binding protein plastin 3 has been linked recently to osteoporosis and bone fracture in humans (van Dijk et al., 2013). Various bone cell types and fibroblasts exhibit different mechanosensitivity and mechano-activity. Fibroblasts typically demonstrate force traction of larger magnitude than bone cells probed using a two-particle microrheology assay (Bacabac et al., 2008; Mizuno et al. 12

2009). Furthermore, actin-cytoskeletal activity induces force fluctuations in fibroblasts reflective of motility, which is expected to be less in osteocytes. This two-particle assay allows the monitoring of NO release in response to minute sinusoidal forces as low as 5 pN, which is exhibited by MLO-Y4 osteocytes in round morphology (Bacabac et al., 2008). Flat-adherent MLO-Y4 osteocytes respond with less NO release despite forces at nN range, suggesting the relevance of cellular geometry on mechanosensation. It is noted that integrins can be deformed at force scales around 10 pN. Hence, the observation for round cells implies direct stimulation via trans-membrane proteins, agreeing with the theoretical model that requires forces less than 15 pN to act on αvβ3 integrins to stimulate mechanosensation (Wang et al., 2007). These observations contribute to the notion that mechanosensation is pre-conditioned by the cytoskeletal structure, which determines the overall cell morphology. Furthermore, one possible mechanosensation strategy may require cellular force traction, where the cell actively interacts with its perceived mechanical environment. This activity is causally linked to molecular signaling, exhibited using our two-particle assay where we observed that NO release by MLOY4 cells coincides with force induction. Taken together, evidence has been provided demonstrating that the cytoskeleton and the extracellular environment of the osteocytes affect the osteocyte response to stress, implying that the cytoskeleton is directly involved in cellular mechanotransduction. Osteocytes in the skull might have a different sensitivity to mechanical stimulation than the osteocytes in long bones based on their difference in mechanical environment. However different mechanosensitivity of skull and long bone osteocytes could not be confirmed in vitro (Soejima et al., 2001), where osteocytes were cultured on flat and stiff substrates and perhaps unable to replicate their site-specific cytoskeletal arrangement and thus mechanosensitivity (Vatsa et al., 2008). Osteocytes were also not grown on their native extracellular matrix before being mechanically stimulated. The extracellular matrix of skull bones differs from that of long bones, and changes in the extracellular matrix drive cytoskeletal changes that possibly affect 13

osteocyte mechanosensing. Osteoporosis is a bone disease leading to an increased risk of fracture in long bones and vertebrae, but not in the skull bones. So far osteoporosis has not been connected to a difference in extracellular matrix composition, but further studies on the response of skull and long bone osteocytes could shed light on this issue. Besides cell-matrix interactions, the osteocyte mechanosensitivity might be altered during osteoporosis by the enhanced circulating levels of cytokines present in postmenopausal osteoporosis, since cytokines can modulate the response of osteocytes to mechanical loading (Bakker et al., 2009). The cytokines TNFα and IL-1β inhibit the increase in NO production and intracellular calcium that is normally observed in cultured osteocytes after mechanical stimulation by fluid flow (Bakker et al., 2009). Another molecular pathway through which osteocyte mechanosensing may be altered in osteoporosis is the Wnt pathway. Several bone mass disorders have been linked to mutations in a Wnt receptor and in a Wnt antagonist that is more or less specifically expressed by osteocytes (Little et al., 2002; van Bezooijen et al., 2007). Hence, molecules involved in Wnt signaling are of interest to the field of osteocyte biology. The Wnt proteins are a family of secreted glycoproteins with members that activate various intracellular pathways after binding to frizzled receptors or to a complex comprised of frizzled and LDL receptor-related proteins 5/6 (LRP5/6). The anabolic response of bone to mechanical loading is enhanced in ulnae of mice lacking the Wnt inhibitor Sfrp3 (Lories et al., 2007). The best studied Wnt pathway is the Wnt/β-catenin pathway (Johnson et al., 2004; Lai et al., 2009; Li, Ng et al., 2012). β-catenin has been suggested to alter the sensitivity of bone cells to mechanical loading (Robinson et al., 2006). When bone cells are treated with molecules that stabilize β-catenin and then subjected to mechanical loading, a synergistic up-regulation of Wnt gene expression is observed (Robinson et al., 2006), suggesting that activation of the Wnt signaling cascade enhances the mechanosensitivity of bone cells. Mechanical loading increases Wnt protein production by osteocytes, which activates the canonical Wnt signaling pathway in a paracrine fashion (Santos et al., 2009; Tu et al., 2012). Mechanical loading might thus lead to 14

Wnt production by osteocytes, thereby tuning their own sensitivity to mechanical loading in a feedback loop. Whether β-catenin/Sfrp3 levels change due to estrogen deprivation, osteoporosis, or with age is however unknown.

ESTROGEN AS MODULATOR OF THE OSTEOGENIC RESPONSE TO STRESS

Mechanical loading and estrogen Both mechanical loading and estrogen play an important role in bone homeostasis. Estrogen, similar to mechanical loading, stimulates the production of NO and PGE2 by human bone cells in culture (Bakker et al., 2005), and both NO and PGE2 are known to affect osteoclasts and osteoblasts. Mechanical loading suppresses bone resorption and stimulates bone formation, while estrogen suppresses both resorption and formation. Estrogen is able to affect bone mass by changing the balance between resorption and formation, and loss of estrogen can also lead to irreversible loss of thin trabecular elements. Since thin trabecular elements will rarely be oriented along the trajectories of principal strain, estrogen can affect bone architecture in addition to bone mass. Consequently, estrogen withdrawal will result in a reduced bone mass, a less structurally effective bone architecture and an increased incidence of fracture. It has been suggested that estrogen modulates the mechanoresponsiveness of bone cells, and that loss of estrogen during menopause alters the response of bone cells to mechanical loading, thereby contributing to the rapid loss of bone. Loss of estrogen might thus cause a change in the strain “setpoint” in Frost’s mechanostat mechanism (Frost, 1987). Since estrogen receptor alpha (ERα) is known to be involved in the osteogenic response to mechanical strain (Windahl et al., 2012), it is possible that mechanical strain and estrogen thereby share a common pathway. Several animal studies have shown that estrogen suppresses the loading response in cortical and trabecular bone (Li et al., 2003; Chen et al., 2001; Jarvinen et al., 2001; Saxon and 15

Turner, 2006). However, there are a number of animal studies showing that estrogen status has no effect on the responsiveness to mechanical loading (Hagino et al., 1993; Honda et al., 2003; Tromp et al., 2006; Umemura et al., 2008). Others have shown that the combination of estrogen and mechanical loading increases trabecular bone formation (Li et al., 2003), and osteoblast proliferation (Cheng et al., 1996). Interestingly estrogen status has different effects on different stages of the adaptive process (Jagger et al., 1996). Estrogen treatment of rats initiated on the same day, or 1 day post-loading, reduces the osteogenic response in trabecular bone formation, but when estrogen administration starts 3 days post-loading, estrogen enhances the osteogenic response (Jagger et al., 1996). This suggests that estrogen stimulates the activity of osteoblasts that were already forming bone, while it inhibits the induction of new sites of bone formation. Human exercise data suggest an ambiguous role for estrogen in the response of bone to mechanical loading. Young men and pre-pubertal girls with low estrogen have a greater responsiveness to loading based on measures of periosteal expansion, than women who are estrogen replete. Post-menopausal women have an adaptive response to an increased loading challenge that is not substantially different from that pre-menopausally. Nevertheless, their response to continued habitual loading is insufficient to provide structural protection against fragility fracture. The insufficiency as reflected by bone loss might be related to declining estrogen levels (Riggs et al., 2002).

Estrogen receptor There is accumulating evidence that estrogen receptor-α (ERα) is involved in mechanical loading-related osteogenesis in vivo (Lee et al., 2003; Windahl et al., 2013), and in the response of osteoblasts and osteocytes to mechanical stimulation in vitro (Aguirre et al., 2007; Armstrong et al., 2007; Galea et al., 2013; Sunters et al., 2010;). The potential role of ERα in estrogen deficiency-related bone loss in humans is still unknown, but could involve ER downregulation,

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resulting from reduced estrogen concentrations, to an extent that insufficient ERs in the bone cells are available to facilitate mechanically related signaling pathways. An association study in humans suggests that genetic variants at the ERα locus modulate the mechanosensitivity of bone (Suuriniemi et al., 2004). This supports the hypothesis that ERα number and/or function in bone cells may affect bone adaptation to mechanical loading. The in vivo data concerning the role of ERβ for the osteogenic response to loading is conflicting, since mice deficient in ERβ either display a reduced (Lee et al., 2004) or enhanced osteogenic response to loading (Saxon et al., 2007). The ER is not essential for bone cells to respond to mechanical strain, but it contributes to a range of signaling pathways activated by mechanical stimulation (Zaman et al., 2010). ERα contributes to the response of bone cells to mechanical strain through both genomic and nongenomic actions. Nongenomic contributions of ERα include its desensitization of insulin-like growth factor 1 receptor (IGF-1R) signaling through a direct interaction with this receptor (Sunters et al., 2010), which facilitates upregulation of early strain target genes such as COX-2 (Liedert et al., 2010). IGF-1 signaling is a key component of the early stages of the adaptive response of bone to loading (Sunters et al., 2010). The actual source of IGF-1 remains controversial, although osteocytes have clearly been shown to increase IGF-1 expression after mechanical loading of rat tibiae (Reijnders et al., 2007). Mechanical strain sensitizes the osteoblast response to endogenous IGF-1 (Sunters et al., 2010). ERα regulates β1 integrin, which is required for loading-related bone formation and bone loss resulting from disuse in vivo, which might provide a mechanism by which estrogen affects the response of osteocytes to mechanical stimuli.

THE EFFECT OF ALTERED OSTEOCYTE MECHANOSENSITIVITY AND OSTEOBLAST RESPONSIVENESS ON BONE ARCHITECTURE

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So far we have discussed how osteocytes sense mechanical loads and direct bone remodeling, and how this capability of osteocytes may be hampered in osteoporosis or after estrogen withdrawal. In order to link changes in osteocyte mechanosensitivity to changes in bone mass and architecture, computer models provide an invaluable tool. Trabecular bone strength is determined by bone mass and architectural efficacy (Wang et al. , 2012; Ulrich et al., 2001). Bone mass and architectural efficacy are independent parameters, determined by different cellular activities. Bone mass results from the overall metabolic activity of the osteoblasts and osteoclasts, while architectural efficacy results from local osteoblast and/or osteoclast recruitment. The capacity of the osteocytes to steer local osteoblast/osteoclast recruitment, and the metabolic capacity of the osteoblasts and osteoclasts together determine the mass and architecture of bone. Mechanical stress regulates the steering activity of the osteocytes, and therefore affects both mass and architecture. If estrogen modulates osteocyte mechanosensitivity as described in the previous paragraph, then both bone mass and architectural efficacy may be expected to be affected in postmenopausal osteoporosis. Using a computer model, Huiskes and coworkers (Mullender and Huiskes, 1995; Mullender and Huiskes, 1997; Weinans et al., 1998, Huiskes et al., 2000; Ruimerman et al., 2003; Ruimerman et al., 2005a) demonstrated that osteocytes, sensing local tissue strains and sending local signals, can direct the alignment of trabeculae to global load directions. Tanck et al. (2006) used this model to explain how bone under the growth plate could develop into porous trabecular bone or solid cortical bone, depending on variations in the loading magnitude. This indicates that cortical and cancellous bone share the same regulatory mechanisms, operating under different loading conditions. An extension of the model, explicitly simulating tunneling osteoclasts, reproduces osteonal remodeling in cortical bone (Smit and Burger, 2000; van Oers et al., 2008a; van Oers et al., 2008b). Here again, osteocytes sensing local tissue strains guide the development of osteons along global load directions. In this model, regions of

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osteocyte death cause nearby osteoclasts to redirect their course and resorb the damaged bone (van Oers et al., 2008a; van Oers et al. 2011b). Postmenopausal osteoporosis leads to increased remodeling rates, i.e. both osteoclast and osteoblast activities are enhanced (Chambers, 1998). While estrogen is known to have an inhibitory effect on bone resorbing osteoclasts (Riggs et al., 2002), it is still debated whether it has a direct effect on osteoblasts. Moreover estrogen deficiency has been implicated in osteocyte mechanosensitivity and viability. The question is whether computational models can provide a means to differentiate between the effects of estrogen on these different aspects of bone remodeling. Ruimerman et al. (2005b) simulated the effect of estrogen deficiency in postmenopausal osteoporosis via increased osteoclast activity, since estrogen inhibits osteoclast activity (Riggs et al., 2002). Upon rapid initial bone loss, osteoblast activity increased through mechanical coupling with resorption, establishing a new osteoporotic equilibrium with increased remodeling rates (Figure 4). Postmenopausal osteoporosis indeed leads to increased remodeling rates (Chambers, 1998). A direct effect of estrogen on osteoblasts was not needed to explain the increased osteoblast activity. Conversely, osteoporosis can also be simulated by reducing osteoblast activity. However this would cause a reduction in remodeling rate, unlike postmenopausal osteoporosis. Mullender et al. (1998) simulated osteoporosis by reducing osteocyte mechanosensitivity, i.e. by increasing the mechanical setpoint at which osteocytes emit an osteogenic signal. In this study the osteocyte signal controlled the change in bone density directly, without separating osteoclast and osteoblast activity, which makes it difficult to relate the dynamics of this simulation to postmenopausal osteoporosis. In another bone adaptation model, osteoporosis has been simulated by reducing the number of viable osteocytes (Liotier et al., 2013). This choice is not unreasonable, since estrogen deficiency has been associated with osteocyte apoptosis (Manalogas, 2006). However, to correctly simulate the effect of reduced osteocyte mechanosensitivity, the right assumptions must be made about osteocyte signaling to 19

osteoclasts and osteoblasts. Vital osteocytes actively repel osteoclasts, while apoptotic osteocytes attract osteoclasts (Tan et al., 2007; Kogianni et al., 2008). With these regulation mechanisms, both a decrease in mechanosensitivity (which effectively works as disuse) and a decrease in osteocyte viability would increase osteoclast activity. Osteocyte signaling to osteoblasts has more complex results. Mechanically stimulated osteocytes stimulate osteoblast activity (Taylor et al., 2007; Vezeridis et al., 2006), while osteocytes in disuse inhibit osteoblast activity with signals like sclerostin (Robling et al., 2006). We speculate that a decrease in osteocyte mechanosensitivity would inhibit osteoblast activity, while a reduction in the number of osteocytes enhances bone formation through a lack of sclerostin (van Oers et al., 2011a). Thus the biological mechanisms underlying a computer model must be correct, to predict the dynamics of estrogen deficiency correctly.

CONCLUSION Together, biological models and computer simulation models allow to link modulations of cellular behaviour in bone by mechanical stimuli with the trabecular morphologies it produces, and the changes in bone strength that accompany these changes in morphology. Osteocyte mechanosensitivity may be intrinsically low in patients that develop osteoporosis, and estrogen deficiency may further reduce the bone cell response to stress. A correlation between osteocyte mechanosensitivity and bone architecture may exist, as has been demonstrated using a multilevel approach ranging from in vivo and in vitro models to micro-mechanical finite element models and computer-simulation models of the bone remodeling process. The tremendous progress in insight in osteocyte function in relation to osteoporosis has been made since researchers from different disciplines have joined hands. The future looks full of new discoveries with regards to osteocyte mechanosensation and bone adaptation. Rik Huiskes was our collaborator on joint projects related to unraveling the link between bone cell mechanosensitivity, estrogen deficiency, and osteoporosis. More than that, he was 20

truly a colleague extraordinaire, who led with his actions and inspired others. He challenged us continuously with critical questions which touched the fundamental biomechanical issues of our cell biological research. Rik loved lively discussions to keep himself and us on our toes when it came to the understanding of cell behavior, in order to improve his models. Rik’s standards were unwavering, and he set an example of how to think about and conduct science. We truly miss Rik.

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ACKNOWLEDGEMENTS The authors would like to acknowledge the pioneering leadership in the field of osteocyte biology of Drs Elisabeth H. Burger and Peter J. Nijweide, and in the field of osteoporosis of Dr. Paul Lips, collaborators of the authors. Specifically Elisabeth Burger and Rik Huiskes laid the foundation upon which the present authors have founded their research on bone cell mechanosensitivity, estrogen deficiency, and osteoporosis. The work of R.F.M. van Oers is supported by a grant from the University of Amsterdam for the stimulation of a research priority area Oral Regenerative Medicine.

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FIGURE LEGENDS

Figure 1. Modeling and cell biology complement each other when decomposing the complete cascade of events responsible for mechanical adaptation of bone. Cell biologists have made valuable discoveries regarding which cellular features enable the sensing of mechanical stimuli by osteocytes, how the expression of signaling molecules by osteocytes is altered by mechanical stimuli, and how these signaling molecules affect osteoclasts and osteoblasts (3 white arrows, left). Computer models aid in tying the whole process together, by helping us to understand how a mechanical load placed on bone as an organ is translated into a mechanical stimulus that is felt by the osteocytes, and how modification of osteoblast and osteoclast recruitment and activity in response to mechanical signals can affect bone mass and architecture (2 white arrows, right). Estrogen (E2) may affect the magnitude of the mechanical stimulus exerted on the osteocyte by altering the canalicular architecture, by changing the intrinsic sensitivity of the osteocytes to mechanical stimuli, by altering the production of signaling molecules by mechanically stimulated osteocytes, and by directly affecting osteoclast and osteoblast formation and activity. These concepts are described in detail throughout this manuscript.

Figure 2. Maximal 2D projection (upper row) and 3D reconstruction (lower row) of single osteocytes in osteoarthritic, osteopenic and osteopetrotic cortical bone of the proximal tibia using confocal laser scanning microscopy scans. A) Osteoarthritic bone, showing relatively elongated osteocytes. B) Osteopenic bone, showing relatively round osteocytes. C) Osteopetrotic bone, showing relatively small and round osteocytes. All types of bone show the presence of the intercellular osteocyte network. Bar, 15 µm. (Reprinted from Bone 45, Van Hove, R.P., Nolte, P.A., Vatsa, A., Semeins, C.M., Salmon, P.L., Smit, T.H., Klein-Nulend, J., Osteocyte morphology in human tibiae of different bone pathologies with different bone mineral 48

density – is there a role for mechanosensing? pp. 321-329, 2009, with permission from Elsevier).

Figure 3. 3D reconstruction of osteocyte lacunae in osteoarthritic, osteopenic and osteopetrotic cortical bone of the proximal tibia using nano-CT scanning. A) Osteoarthritic bone, showing relatively small, aligned osteocyte lacunae. B) Osteopenic bone, showing relatively large, aligned osteocyte lacunae. C) Osteopetrotic bone, showing relatively intermediate sized osteocyte lacunae without any obvious alignment. Bar, 15 µm. (Reprinted from Bone 45, Van Hove, R.P., Nolte, P.A., Vatsa, A., Semeins, C.M., Salmon, P.L., Smit, T.H., Klein-Nulend, J., Osteocyte morphology in human tibiae of different bone pathologies with different bone mineral density – is there a role for mechanosensing? pp. 321-329, 2009, with permission from Elsevier).

Figure 4. In a simulated trabecular architecture (A), postmenopausal osteoporosis was simulated by increased osteoclast activity, via either increased resorption depth (B), or increased osteoclast activation frequencies (C). After initial bone loss, osteoblast activity picks up through mechanical coupling with resorption, and the osteoporotic structures reach a new equilibrium. Adapted from Ruimerman et al. (2005b).

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