Extracellular regulated kinase 5 mediates osteoporosis through modulating viability and apoptosis of osteoblasts in ovariectomized rats

Introduction HIV mainly replicates in CD4+ T lymphocytes and monocyte/macrophages causing severe immunological impairment. In addition to the immune system, HIV infection affects tissues and organs such as kidney, liver, the central nervous system, heart and bone showing a complex pathogenesis [1]. The advent and widespread use of highly active antiretroviral therapy (HAART) in the last two decades has led to a marked improvement in the treatment of HIV disease even though viral infection cannot be eradicated because HAART does not completely eliminate the viral reservoirs [2]. HAART has dramatically changed the course of HIV infection from a fatal infection to a chronic and relatively manageable disease. The increased life expectancy of HIV patients and the effects of HAART have changed the management of HIV infection. Nowadays medical treatment is no longer focused solely on HIV infection, opportunistic diseases and monitoring immune derangement, but also includes the control of metabolic, cardiovascular, liver, bone and kidney complications. In particular, bone alterations have been observed in the course of HIV disease representing a pivotal clinical problem in the management of HIV patients especially for a possible development of bone fractures [3]. The major bone lesions detectable in HIV patients are related to bone demineralization (osteopenia/osteoporosis and osteomalacia) and osteonecrosis ([4] for a review). This report will discuss the pathogenesis, diagnosis and treatment of major bone complications represented by bone demineralization diseases during HIV infection and HAART treatment. Osteopenia/osteoporosis in HIV-infected patients Bone alterations have been observed in the course of HIV disease since for nearly two decades (Table 1). In particular, reduced bone mineral density (BMD) is the most common bone lesion found in HIV-infected individuals [5,6]. BMD is a parameter that predicts fracture risk, which in turn correlates with a shorter life expectancy [7]. BMD is measured by the dual X-ray absorptiometry scan (DXA). According to the WHO Classification, BMD is commonly reported in terms of DXA T-score, which represents the number of standard deviations below the mean of a young, sex-matched control population. T-score values are considered normal above the limit of −1. Values between −1 and −2.5 indicate osteopenia (low bone mass) whereas a T-score value below −2.5 signifies osteoporosis [8,9]. Osteoporosis is a systemic condition characterized by both quantitative and qualitative alterations that reduce bone strength [10].Table 1: Summary of HIV and HAART-related bone lesions.Several groups have used DXA to study BMD status during HIV infection. A meta-analysis of selected reports on bone loss in the whole HIV patient population (HAART treated plus naive) from 1994 to 2005 showed that these individuals had 6.4 fold increased odds of osteopenia and 3.7-fold increased odds of osteoporosis in comparison with uninfected individuals [11]. The relation between antiretroviral treatment and osteopenia/osteoporosis has been noted in several studies [12–18] although other reports failed to find any influence of HAART on bone loss, disclosing no major differences between naive and HAART treated patients [19–23]. A recent study on 492 patients belonging to the Aquitaine Cohort reported osteopenia in 50% and osteoporosis in 30% of HIV-positive cases but multivariate analysis did not show a significant correlation to bone loss and cumulative HAART or specific drug class [24]. In spite of these opposing findings, a meta-analysis of selected cross-sectional studies demonstrated that the odds of osteoporosis were increased 2.4 times in HAART-treated patients compared with naïve individuals [11]. In addition, the meta-analysis by Brown and Qaqish on 12 studies disclosed that patients treated with protease inhibitors have a higher prevalence of reduced BMD and the odds of osteoporosis in protease inhibitor-treated patients are 1.6 greater than in protease inhibitor-untreated individuals [11]. The controversy over the role of antiretroviral compounds in BMD decrease could be explained by shortcomings in some studies. HAART typically combines nucleoside analogue reverse transcriptase inhibitors (NRTIs) with either HIV protease inhibitors or nonnucleoside reverse transcriptase inhibitors (NNRTIs), thus, the antiretroviral cocktail composition may differ within the same cohort with conceivably different effects on bone. In addition, some DXA studies analysed only the spine (mainly confined to trabecular bone), or hip (mostly cortical bone) or both bone sites. The choice of bone for DXA assay is not negligible; the human skeleton is composed of two different types of bone tissue: trabecular bone (comprising around 20% of the bone and mainly involved in the maintenance of mineral homeostasis) and cortical bone (80% and responsible for most support functions). Plainly, high bone turnover states, such as HIV-induced osteoporosis, involve trabecular bone (spine) earlier and to a greater extent compromising cortical bone (hip) only much later [25]. Moreover, the effectiveness and duration of HAART treatment may also affect bone biology and hence the interaction between HAART and bone is noteworthy [26,27]. Mechanisms of HIV-associated osteopenia/osteoporosis The pathogenesis of reduced BMD in HIV-infected patients is probably multifactorial. Osteopenia and osteoporosis are bone lesions mainly correlated to risk factors such as sex, age, low body weight, malnutrition, immobility, lifestyle factors (smoking, alcohol abuse), glucocorticoid, hypogonadism and lipodystrophy [28]. The sum of traditional patient-related risk factors with HIV infection and HAART side effects can determine the onset of these bone lesions in HIV-infected patients. Bone cellular components Bone is a mineralized tissue composed of bone matrix and bone cells. Its homeostasis is mainly due to the tightly integrated contrasting activity of two major bone cell types: bone forming osteoblasts and bone resorbing osteoclasts. These cells are functionally connected and regulated by mediators such as hormones, vitamins and cytokines that strongly affect the skeletal biology throughout life [29]. Osteoblasts arise from mesenchymal stem cells and determine the formation and structural organization of bone extracellular matrix and its mineralization [30]. Mature osteoblasts synthesize several molecules involved either in bone formation or in regulating osteoclast activity such as type I collagen, osteocalcin, osteopontin, proteoglycans, receptor activator for nuclear factor κB ligand (RANKL) and osteoprotegerin (OPG) [31]. Notably, osteoblasts may also evolve to osteocytes when embedded in bone matrix, playing an important role in the control of architectural bone structure [32,33]. Osteoclasts are members of the monocyte/macrophage lineage originating from multiple cellular fusions of their precursors [34] that proliferate and differentiate towards mature osteoclasts by means of macrophage colony-stimulating factor (M-CSF) and RANKL [35]. M-CSF mainly induces precursor cell proliferation whereas RANKL plays a pivotal role in their differentiation, full functional activation and multiple cellular fusions of osteoclasts. Mature osteoclasts are able to resorb bone both by acid environment induction and secretion of lytic enzymes [36–38] such as cathepsin K and tartrate-resistant acid phosphatase (TRAP). The functional balance and cross-talk between osteoblasts and osteoclasts are crucial in determining bone mass (Fig. 1), which depends on the well tuned bone remodelling characterized by osteoclast bone resorption and osteoblast bone rebuilding phases [31]. An imbalance of the osteoblast/osteoclast interaction due to pathological conditions such as infection, hormonal, immunological and metabolic disorders, impairs both bone mass and structure impairment resulting in increased bone fragility and fracture risk.Fig. 1: Flow chart indicating bone mass loss after HIV infection. The well-tuned regulation between the bone resorption by osteoclasts and bone rebuilding by osteoblasts determines the bone homeostasis (a). When HIV infection occurs, this balance is impaired by increase of osteoclast differentiation and activity associated to apoptosis activation and biological activity inhibition of osteoblasts (b). Hence, HIV infection is able to elicit a preferential bone resorption with subsequent bone mass loss.The role of HIV infection As avian, feline and murine retroviruses are known to infect osteoblasts and osteocytes [39–41], early studies focused on the hypothesis that human osteoblasts may be a permissive target for HIV infection decreasing BMD through a direct viral mechanism. Some reports showed that HIV-1 transmission can occur during bone transplantation [42] and HIV-positive PCR assay has been observed in bone graft [43]. H9 cell line or peripheral blood mononuclear cells (PBMC) cocultivated with bone fragments from HIV-1-positive individuals displayed both a positive HIV RT activity and p24 detection in cell supernatants [44]. However, it was not clear whether blood or bone marrow HIV-positive cells contamination could be excluded in these studies. Mellert et al.[45] found that osteoblast-like cell lines were infected when challenged by HIV. Together, these data suggested that bone might be considered an HIV reservoir where the limited blood flow and the particular anatomical structure may also induce a poor antiretroviral concentration to tackle the HIV infection [46]. Moreover, the infection of osteoblasts may be closely related to the incomplete refilling of bone lacunae during bone remodelling with subsequent bone loss. In spite of these observations, further studies performed on human primary osteoblasts did not confirm the results obtained in osteoblast-like cell lines. The primary osteoblasts taken from HIV-positive individuals did not show viral DNA and RNA in PCR assays [47]. In addition, another study disclosed the failure of HIV productive infection when cultures of primary osteoblasts were challenged with classical HIV laboratory strains [48]. The lack of susceptibility may be partially explained by shortage of CD4 receptor and coreceptor proteins on osteoblast cell membrane [47,48]. In addition, as observed on CD34+ hematopoietic progenitor cell membrane [49], conceivably the CD4/CXCR4 complexes might be not so sterically closed to constitute the trimeric complex with gp120 essential for HIV entry. In addition to the direct effect of HIV replication, the apoptosis process plays a pivotal role in HIV pathogenesis. The progressive loss of CD4+ T lymphocytes is also related to apoptosis activated by the interaction between HIV gp120 and the CD4 receptor [50,51]. In addition, HIV-related apoptosis is a major mechanism involved in anaemia, thrombocytopenia and induction of neuronal cell death [52–54]. A recent paper showed an increased rate of apoptosis in primary osteoblasts treated by gp120 or challenged with heat-inactivated HIV laboratory strains [48]. Apoptosis activation occurs by a paracrin/autocrin mechanism due to TNF-α increase [48]. This finding may suggest that part of the bone loss detected in HIV-infected patients may be related both to apoptosis and the decreased biological activity of osteoblasts. The inhibitory effect of HIV gp120 on osteoblast function was confirmed by Cotter et al.[55] who found that gp120 (Fig. 2 and Table 2) reduces calcium deposition, alkaline phosphatase activity and bone specific Runt-related transcription factor 2 (RUNX-2) transcription factor expression after 24 h of treatment in primary osteoblast cultures. In agreement with these data, histomorphometric and serological analysis showed impairment in primary osteoblast functional activity and a consistent decrease of serum osteocalcin in HIV-infected patients [5,56,57].Fig. 2: Interaction between HIV and osteoblast lineage. (a) HIV gp120 determines Tumour necrosis factor alpha (TNF-α) expression increase in primary osteoblasts. TNF-α induces apoptosis activation in primary osteoblasts by paracrine/autocrine mechanisms. In addition, gp120 determines a downregulation of several osteoblast activity parameters inducing an inhibition of biological function of these cells. (b) The interaction between HIV and the osteoblast progenitor cells represented by the mesenchymal stem cells determines the inhibition of survival and proliferation by direct and indirect mechanisms. (c) HIV gp120 induces the inhibition of Runt-related transcription factor 2 (RUNX-2) protein and the activation of peroxisome proliferator-activated receptor gamma (PPAR-γ) with a preferential shift of mesenchymal cells differentiation from osteoblasts to fat cells.Table 2: HIV-related effects on bone cells.Osteoblasts are derived from bone marrow mesenchymal stem cells. Hence, some studies sought to establish whether mesenchymal stem cells and their differentiation towards osteoblasts are impaired by HIV infection (Fig. 2). Wang et al.[58] showed that bone marrow mesenchymal stem cells could be infected to a low extent by X4 tropic HIV strains leading to persistent harbouring of the virus inside these cells with subsequent inhibition of proliferation and survival. Several differentiation pathways from mesenchymal cells are also impaired by Tat through the upregulation of TNF-α and IL-1β expression. More recently, the interaction between specific HIV proteins and mesenchymal cells differentiating towards osteoblasts was analysed. In particular, p55gag and gp120 viral proteins elicited a derangement of specific transcription factors involved in the differentiation and activity of osteoblasts. HIV gp120 (Fig. 2) is also able to trigger the activation of peroxisome proliferator-activated receptor gamma (PPARγ) determining an MSC differentiation switch from osteoblasts to adipocytes [55,59]. Several reports have also analysed the influence of HIV on osteoclasts (Table 2). RANKL and M-CSF are key factors modulating the proliferation and differentiation of osteoclast lineage cells. A significant increase in plasma RANKL levels with an impairment of RANKL/OPG ratio was described in HIV-positive patients [60]. The RANKL increase correlated with high plasma viral RNA load indicating a direct relation between HIV infection status and RANKL synthesis [60–62]. Moreover, gp120 upregulated RANKL secretion (Fig. 3) in primary T cells [63] whereas Vpr synergized the glucocorticoid-mediated activation of RANKL in several cell systems such as primary T cells and Jurkat lymphoblastoid cell line [64]. In turn, RANKL upregulates HIV replication in acutely and chronically infected monocyte and T-lymphocyte lineages suggesting a feedback loop between HIV replication and RANKL production [65].Fig. 3: Description of main HIV-related mechanisms of osteoclast activation. HIV gp120 protein elicits the upregulation of receptor activator for nuclear factor kB ligand (RANKL) and macrophage colony-stimulating factor (M-CSF) in T lymphocytes and macrophages respectively determining the increase of osteoclast differentiation and activity.M-CSF is a haematopoietic growth factor controlling the survival, proliferation and differentiation of the monocyte-macrophage lineage and it is closely involved in the early phases of osteoclast differentiation. The pivotal involvement of M-CSF and its receptor in osteoclast differentiation was also confirmed by osteopetrosis and bone alterations in mice mutated in the CSF-1 or c-fms gene [66,67]. HIV infection of macrophages induces a significant increase in M-CSF production and secretion [68], which in turn promotes further HIV infection of macrophages through the increase in CD4/CCR5 receptors and virus gene expression [69–72]. M-CSF elicits osteoclast differentiation also enhancing the RANKL effect (Fig. 3). In addition, Yamada et al.[73] showed that bone marrow macrophages (BMMs) cultured without M-CSF produce a large amount of OPG compared with cells cultured with M-CSF. This finding suggests that M-CSF downregulates OPG production in BMMs. As OPG, a TNF receptor family secreting glycoprotein, inhibits osteoclast differentiation by acting as a decoy RANKL receptor, the increasing level of M-CSF during HIV infection impairs the balance between RANKL/RANK and OPG, increasing osteoclasts (Table 2). The role of HAART In 1995, the introduction of HAART in the treatment of HIV infection led to a dramatic and sustained decrease in HIV-related morbidity and mortality [74]. HAART typically combines nucleoside analogue reverse transcriptase inhibitors (NRTIs) with either HIV protease inhibitors or nonnucleoside reverse transcriptase inhibitors (NNRTIs). Despite controversial results regarding antiretroviral molecules and bone loss, several groups investigated the possible bone damage mechanisms of specific antiretroviral classes. The role of N(n)RTIs The nucleoside analogues (NRTIs) are antiretroviral molecules whose chemical structure is a modified nucleoside. These compounds suppress the replication of retroviruses by interfering with the reverse transcriptase enzyme activity causing premature termination of the proviral HIV DNA chain. Abacavir, didanosine, emtricitabine, lamivudine, stavudine, zalcitabine and zidovudine are currently used in HAART. Despite the major positive impact of these molecules in HIV therapy, clinical observations disclosed severe side effects such as mitochondrial toxicity, hyperlactataemia and lactic acidosis. To varying degrees, NRTIs inhibit the DNA polymerase-γ [75], the enzyme involved in the replication of mitochondrial DNA, leading to mitochondrial damage and dysfunction [76]. In-vitro studies disclosed some differences in the induction of specific NRTI-related mitochondrial DNA depletion. The so-called 'd-drugs' ddC (zalcitabine), ddI (didanosine), and d4T (stavudine) are relatively stronger inhibitors of polymerase-γ than other nucleoside analogues, called 'non-D drugs' [77,78]. In the presence of mitochondrial dysfunction or depletion, the metabolism of pyruvate is shifted the production of with a decrease in does not to lactic even though this condition is in individuals with virus and patients plus Several studies on patients demonstrated that hyperlactataemia is a relatively common in of individuals a whereas lactic is in than of patients et analysed patients by and found an between levels and reduced BMD (Table 3). These data suggest that lactic by NRTIs may osteopenia by a mechanism related to calcium loss as the bone to chronic acidosis. This damage mainly affects the trabecular which represents the of bone and is a of calcium than cortical bone. In addition the systemic effects of a paper by et (Table 3) showed a specific interaction between zidovudine and bone. the inducing osteopenia in a murine 3: and it is commonly with is a analogue with In-vitro studies demonstrated that the of to mitochondrial is low compared with other NRTIs studies have that is the primary of by a of secretion and and some of was noted in different This is related to dysfunction due to cell and correlates with an impaired The dysfunction may elicit the of whereas the reduced is associated with a decrease in the function of the an enzyme involved in metabolism Some and reports have described a with (Table 3) in HIV-infected patients in the presence of was mainly observed in patients treated with therapy or The impaired balance and metabolism related to may determine an in HIV some studies found an between use of and bone damage and a higher of fracture was also found in patients compared with individuals The between and was not confirmed by other studies. A cohort study in showed a in patients with normal but it was not significant with to patients. The and studies performed on a large number of patients with no of found the same of serum and in the and after 24 of treatment. The a over compared a treatment of and with a treatment of stavudine, and in patients the and These controversial results may be related to cohort as the patients in the studies did not show low is that the specific HAART and functional conditions of patients the interaction between and bone. The role of protease inhibitors inhibitors HIV replication by the viral protease a pivotal in the of the viral replication The viral obtained in the presence of protease cannot infect the target cells. and are the protease inhibitors used for antiretroviral The protease interaction has been in bone cell cultures (Table 3). The effects of protease inhibitors on osteoclasts were osteoclast activity in and showed activity whereas and did studies demonstrated that and osteoclast activity through the of a to RANKL represented by gamma of TNF receptor associated factor RANKL to the of resulting in the activation of nuclear factor of activated cells and protein pathways involved in the survival and differentiation of osteoclasts. A subsequent paper showed that had effects by This finding suggested a complex in the between protease inhibitors and the osteoclast lineage. inhibitors were also on the human mesenchymal stem cells differentiating to osteoblast lineage. 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The recent by the for the T-score with the value by WHO only for in data are it is that the same can be to over the of have major risk factor for individuals than diagnosis is the that the BMD with that of a and sex-matched population. However, the has no clear value for osteopenia and osteoporosis and the are patients with values than −1 are as low bone whereas a severe bone mass is by values than The may further analysis of BMD and a of this parameter in the of bone loss in HIV-infected can only be by bone that will large of bone As bone are the diagnosis of is indirect and is by DXA analysis with some blood Hence, DXA may the rate in this population as an number of patients may have been with a diagnosis be in to Osteoporosis is commonly treated with or whereas high of and spine are to be in patients with in the patients with marked and in patients with severe spine the in patients with a diagnosis of Bone biology parameters can be by laboratory and calcium calcium and In addition, bone formation osteocalcin or alkaline and bone resorption or or can with and may be obtained by and with a low inducing a decrease in the function of in the kidney and in and the of kidney function alterations may occur with normal and may an impairment of function for lactic monitoring and during may on the side effects of NRTIs on bone. et suggested that plasma RANKL and OPG may be in some cases of therapy as impairment of the RANKL/OPG is well described in patients protease HAART. though data indicate that and protease with and the RANKL/OPG and may to a in the bone resorption The of these cytokines is not part of the of HIV-infected patients. The management of osteopenia/osteoporosis in the course of HIV infection may be on a in risk calcium and and (Table and in HIV-related bone can be to and to control body In addition, patients have to an of calcium and However, be to HIV-infected patients The limit for is but this is below the that has been even with the of A of can be suggested to The only to is and when serum calcium is can be A low calcium has been demonstrated to reduce BMD and to increase the hip fracture risk The calcium for is between and but it is to this in it is important for to be to HIV-infected patients. 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Some in individuals indicate that the of osteoporosis after of between and and the fracture risk for a is greater than 50% These data suggest that the number of HIV patients with bone disease and fractures can be to increase dramatically in the because these patients also have two other HIV and antiretroviral Hence, antiretroviral therapy be by the clinical management of bone disease to reduce the risk of osteoporosis and fractures in these patients. This was by of the of the study for for selected of the of and the that have no or that may constitute a dual or

Article Figures and data Abstract Editor's evaluation eLife digest Introduction Results Discussion Methods Appendix 1 Appendix 2 Appendix 3 Data availability References Decision letter Author response Article and author information Abstract For the treatment of postmenopausal osteoporosis, several drug classes with different mechanisms of action are available. Since only a limited set of dosing regimens and drug combinations can be tested in clinical trials, it is currently unclear whether common medication strategies achieve optimal bone mineral density gains or are outperformed by alternative dosing schemes and combination therapies that have not been explored so far. Here, we develop a mathematical framework of drug interventions for postmenopausal osteoporosis that unifies fundamental mechanisms of bone remodeling and the mechanisms of action of four drug classes: bisphosphonates, parathyroid hormone analogs, sclerostin inhibitors, and receptor activator of NF-κB ligand inhibitors. Using data from several clinical trials, we calibrate and validate the model, demonstrating its predictive capacity for complex medication scenarios, including sequential and parallel drug combinations. Via simulations, we reveal that there is a large potential to improve gains in bone mineral density by exploiting synergistic interactions between different drug classes, without increasing the total amount of drug administered. Editor's evaluation The authors have developed a mathematical framework of drug interventions for postmenopausal osteoporosis using bisphosphonates, parathyroid hormone analogs, romosozumab, and denosumab. After calibrating and validating the model, authors demonstrated a predictive ability for complex clinical scenarios including sequential and parallel drug combinations. These data may be of great help in clinical practice. https://doi.org/10.7554/eLife.76228.sa0 Decision letter Reviews on Sciety eLife's review process eLife digest Our bones are constantly being renewed in a fine-tuned cycle of destruction and formation that helps keep them healthy and strong. However, this process can become imbalanced and lead to osteoporosis, where the bones are weakened and have a high risk of fracturing. This is particularly common post-menopause, with one in three women over the age of 50 experiencing a broken bone due to osteoporosis. There are several drug types available for treating osteoporosis, which work in different ways to strengthen bones. These drugs can be taken individually or combined, meaning that a huge number of drug combinations and treatment strategies are theoretically possible. However, it is not practical to test the effectiveness of all of these options in human trials. This could mean that patients are not getting the maximum potential benefit from the drugs available. Jörg et al. developed a mathematical model to predict how different osteoporosis drugs affect the process of bone renewal in the human body. The model could then simulate the effect of changing the order in which the therapies were taken, which showed that the sequence had a considerable impact on the efficacy of the treatment. This occurs because different drugs can interact with each other, leading to an improved outcome when they work in the right order. These results suggest that people with osteoporosis may benefit from altered treatment schemes without changing the type or amount of medication taken. The model could suggest new treatment combinations that reduce the risk of bone fracture, potentially even developing personalised plans for individual patients based on routine clinical measurements in response to different drugs. Introduction Osteoporosis, a disease characterized by porous bone prone to fractures, affects hundreds of millions of people worldwide (Cooper and Ferrari, 2019; Hernlund et al., 2013). Most recent estimates place the global annual incidence of bone fragility fractures at 9 million in the year 2000 (Cooper and Ferrari, 2019); projections for the year 2050 suggest between 7 and 21 million annual hip fractures (Gullberg et al., 1997). Osteoporosis-associated bone fractures lead to disabilities, pain, and increased mortality (Cooper and Ferrari, 2019). In the United States, medical cost for osteoporosis, including inpatient, outpatient, and long-term care costs, has been estimated at US$17 billion in 2005 (Burge et al., 2007); in the European Union, the total cost of osteoporosis, including pharmacological interventions and loss of quality-adjusted life-years (QALYs), is projected to rise from about €100 billion in 2010 to €120 billion in 2025 (Odén et al., 2013). Osteoporotic bone is the consequence of an imbalance of continuous bone resorption and bone formation, which—under close to homeostatic conditions—has the function to remove microfractures and renew the structural integrity of bone. Postmenopausal women are particularly at risk of osteoporosis: the rapid decline of systemic estrogen levels after menopause and other aging-related effects such as increased oxidative stress contribute to or drive the development of osteoporosis (Riggs et al., 1998; Manolagas, 2010). Moreover, osteoporosis can be a sequela of diseases affecting bone metabolism and remodeling such as primary hyperparathyroidism or gastrointestinal diseases (Painter et al., 2006). Osteoporosis can also be a side effect of treatments for other diseases; as a prime example, glucocorticoid administration is the most common cause of secondary osteoporosis (Weinstein, 2012). Over the last decades, an array of different osteoporosis treatments have emerged, from simple dietary supplementations such as calcium and vitamin D to specialized drugs targeting bone-forming and -resorbing cells and related signaling pathways (Tu et al., 2018). This entails a plethora of different medication options, including a large number of possible dosing schemes and combinations of drugs, administered in sequence or in parallel. Due to the huge number of such treatment schemes and the required time from study inception to completion, very few of them have been clinically tested so far when compared to the total number of available options. Concomitant with the development of new osteoporosis drugs, mathematical and biophysical modeling approaches capturing bone-related physiology have advanced our quantitative understanding of the biological principles governing bone mineral metabolism, bone turnover, and development of osteoporosis. Pioneering work by Lemaire et al., 2004 describes the dynamics of bone-forming and -resorbing cell populations coupled through signaling pathways and could qualitatively reproduce the effects of senescence, glucocorticoid excess, and estrogen and vitamin D deficiency on bone turnover. Since then, compartment-based descriptions of the mineral metabolism, bone-forming and -resorbing cell populations, and related signaling factors have elucidated the role of essential regulatory mechanisms underlying mineral balance and bone turnover (Komarova et al., 2003; Lemaire et al., 2004; Pivonka et al., 2008; Pivonka et al., 2010; Peterson and Riggs, 2010; Zumsande et al., 2011; Schmidt et al., 2011; Graham et al., 2013; Tanaka et al., 2014; Komarova et al., 2015; Berkhout et al., 2015). Coarse-grained as well as detailed spatially extended descriptions of bone geometry have also addressed the effects of mechanical forces and the propagation of the multicellular units responsible for bone turnover (Ryser et al., 2009; Buenzli et al., 2011; Scheiner et al., 2013; Buenzli et al., 2014; Pivonka et al., 2013), as well as the influence of secondary diseases such as multiple myeloma (Ayati et al., 2010). Detailed models of bone remodeling and calcium homeostasis have become versatile and widely used tools in hypothesis testing, such as the seminal model by Peterson and Riggs, 2010, which includes submodels for various organs such as gut, kidney, and the parathyroid gland. Pharmacokinetic and pharmacodynamic (PK/PD) models of therapeutic interventions have mostly focused on capturing the mechanisms of action of a single or a few drugs and testing their dosing regimens (Marathe et al., 2008; Marathe et al., 2011; Ross et al., 2012; Scheiner et al., 2014; Eudy et al., 2015; Lisberg et al., 2017; Martínez-Reina and Pivonka, 2019; Zhang and Mager, 2019). Recent modeling efforts have also started addressing the effects of drug combinations on bone-forming and -resorbing cells, pointing out the need for corresponding model frameworks to include clinically relevant variables like bone mineral density (BMD) and bone turnover biomarkers (BTMs) (Lemaire and Cox, 2019), as well as combination therapies of physical exercise and drug treatment (Lavaill et al., 2020). An integrated mathematical framework for multiple drugs, which can also be used to quantitatively predict the effects of drug combinations in sequence and in parallel is not yet available. Building on established mechanisms of bone turnover, we here present a quantitative model of bone turnover and postmenopausal osteoporosis treatment, unifying the description of multiple classes of drugs with different mechanisms of action, namely, bisphosphonates, parathyroid hormone (PTH) analogs, sclerostin antibodies, and receptor activator of NF-κB ligand (RANKL) antibodies. We calibrate the model using published population-level data from several clinical trials and assess its ability to predict the outcome of previously conducted clinical studies based on the medication scheme alone. We then use the model to demonstrate how medication schemes involving drug combinations can be optimized for a given medication load and discuss future model extensions. Mechanisms of bone turnover and its regulation Our model is based on a small set of key principles of bone turnover, which we briefly recapitulate here (Figure 1). As a composite tissue comprising hydroxyapatite, collagen, other proteins, and water (Boskey, 2013), bone is constantly turned over to renew its integrity and remove microdamage, at an average rate of about 4% per year in cortical bone and about 30% per year in trabecular bone (Manolagas, 2000). Figure 1 Download asset Open asset Schematic of the osteoporosis model describing the cell dynamics and signaling pathways within a 'representative bone remodeling unit (BRU)'. Regulatory interactions between different model components are indicated by colored boxes (see legend). TGFβ, transforming growth factor beta; BMP, bone morphogenetic protein; PDGF, platelet-derived growth factor; IGF, insulin-like growth factor; FGF, fibroblast growth factor. Bone-resorbing and -forming cells Bone resorption is performed by osteoclasts, multinucleated cells formed through the differentiation and fusion of their immediate precursors (pre-osteoclasts), which are derived from pluripotent hematopoietic stem cells via the myeloid lineage (Boyce and Xing, 2008). Osteoclasts attach to bone tissue and resorb it through the secretion of hydrogen ions and bone-degrading enzymes (Fuller and Chambers, 1995), which leads to the release of minerals and signaling factors stored in the bone matrix. New bone is formed by osteoblasts, a cell type derived from mesenchymal stem cells via several intermediate states that give rise to pre-osteoblasts and finally osteoblasts (Eriksen, 2010). Groups of osteoblasts organize into cell clusters (osteons) and collectively lay down an organic matrix (osteoid), which subsequently becomes mineralized over the course of months. Osteoblasts that are enclosed in the newly secreted bone matrix become osteocytes, nondividing cells with an average life span of up to several decades. Osteoclasts and osteoblasts organize into spatially defined local clusters termed 'bone remodeling units' (BRUs) (Figure 1), in which osteoblasts replenish the bone matrix previously resorbed by osteoclasts with a delay of several weeks. In cortical bone, the outer protective bone layer, BRUs migrate as a whole in 'tunnels,' whereas within the inner cancellous bone, BRUs propagate on the surfaces of the trabeculae, renewing the bone matrix in the process (Eriksen, 2010). Signaling pathways The differentiation and activity of osteoclasts and osteoblasts are regulated through several signaling pathways and hormones; recent reviews provide comprehensive descriptions of the various pathways (Siddiqui and Partridge, 2016). Osteoclast formation and activity are prominently regulated by RANKL and macrophage colony-stimulating factor (M-CSF) synthesized by bone marrow stromal cells. RANKL binds to receptor activator of NF-κB (RANK) on osteoclast precursors and promotes their differentiation into mature osteoclasts; osteoprotegerin (OPG) acts as a decoy receptor for RANKL and thus inhibits bone resorption (Boyce and Xing, 2008; Clarke, 2008). When laying down new bone, osteoblasts store signaling factors in the bone matrix, including transforming growth factor beta (TGFβ), bone morphogenetic protein (BMP), insulin growth factors (IGFs), platelet-derived growth factor (PDGF), and fibroblast growth factors (FGFs) (Solheim, 1998). Upon bone resorption, these factors are released and regulate cell fates and activity of osteoblasts and osteoclasts, thereby coupling bone resorption and formation (Houde et al., 2009; Eriksen, 2010). Osteocytes secrete sclerostin, a Wnt inhibitor interfering with extracellular binding of Wnt ligands (Li et al., 2005). Sclerostin inhibits bone formation and promotes resorption via downregulation of osteoblastogenesis and upregulation of osteoclastogenesis (Delgado-Calle et al., 2017; Maré et al., 2020). Since bone also acts as a mineral reservoir for the body, regulators of calcium homeostasis such as PTH and vitamin D also strongly affect the balance of bone formation and resorption alongside the intestinal absorption and renal reabsorption of calcium (Mundy and Guise, 1999). Estrogen The sex hormone estrogen inhibits bone resorption by inducing apoptosis of osteoclasts (Kameda et al., 1997) and lowering circulating sclerostin levels (Mödder et al., 2011). The rapid decline of estrogen levels after menopause is one known cause of postmenopausal osteoporosis (Riggs et al., 1998). Results Model overview The primary purpose of our model is to provide an efficient representation of bone turnover on multiple time scales from weeks to decades that allows for the quantitative description of drug interventions. Of particular interest are the consequences of pharmacological therapies on long-term dynamics of the BMD in specific bone sites and biochemical markers of bone formation and resorption. To this end, we considered a minimal set of physiologically relevant dynamic components (Figure 1) that are sufficient to capture a large range of clinically observed population-level data on drug interventions. Thus, our model describes a 'representative BRU' that abstracts from the vast set of intricate regulatory mechanisms underlying calcium homeostasis or the complex bone geometry. Our model comprises the following dynamic components to describe the bone turnover through a representative BRU: cell densities of (i) pre-osteoclasts, (ii) osteoclasts, (iii) pre-osteoblasts, (iv) osteoblasts, (v) osteocytes, (vi) sclerostin concentration, (vii) total bone density, and (viii) bone mineral content (BMC). The BMD is given by the product of bone density and BMC. Osteoblasts and osteoclasts can undergo apoptosis and are derived from pre-osteoblasts and pre-osteoclasts, respectively, with differentiation rates that depend on regulatory factors such as estrogen and sclerostin (Figure 1). Pre-osteoblasts and pre-osteoclasts are formed at constant rates and undergo apoptosis. These progenitor populations provide a dynamic reservoir for rapid differentiation and activation of osteoblasts and osteoclasts, respectively, which can be temporarily depleted if stimulated by a drug intervention. Osteocytes are derived from osteoblasts and provide a source of sclerostin, which has a regulatory effect on osteoblasts, osteoclasts, and thus, bone density change. The gain and loss rates of bone density are proportional to the density of osteoblasts and osteoclasts, respectively. The BMC has a steady state whose level can be temporarily shifted through drug administration, effectively accounting for more complex underlying dynamics such as promotion of secondary mineralization. All rates of cell formation, differentiation, apoptosis, and bone formation and resorption generally depend on the concentration of sclerostin, estrogen, and a 'resorption signal.' These dependencies also implicitly account for regulation of bone remodeling via other routes, for example, the RANK–RANKL–OPG pathway. The effects of aging and the onset of menopause are represented through an age-dependent serum estrogen concentration, which has been determined from the literature (Sowers et al., 2008; Appendix 1). The resorption signal corresponds to the melange of signaling factors stored in the bone matrix. Therefore, its release is proportional to the rate of bone resorption. The serum concentration of BTMs such as the resorption marker C-terminal telopeptide (CTX), the formation markers procollagen type 1 amino-terminal propeptide (P1NP), and bone-specific alkaline phosphatase (BSAP) were identified with elementary functions of the bone resorption and formation rates in the model (Appendix 1). We extended this core model of long-term bone turnover by a dynamic description of the mechanisms of action of several drug classes used in osteoporosis treatment: RANKL antibodies (denosumab), sclerostin antibodies (romosozumab), bisphosphonates (alendronate and others), and PTH analogs (teriparatide) (Appendix 2). We also included blosozumab, another sclerostin inhibitor, which was investigated in osteoporosis trials but not approved for osteoporosis treatment at the time the present work was conducted. PTH is known to exert anabolic or catabolic effects depending on whether administration is intermittent or continuous (Tam et al., 1982; Hock and Gera, 1992); PTH description in our model is restricted to the anabolic administration regimes relevant for osteoporosis treatment. A schematic overview of all model components, mechanisms, and regulatory interactions is given in Figure 1; a detailed formal description of the model and its extensions is provided in Appendix 1 and Appendix 2. Capturing clinical study results with the model The model and the corresponding medication modules rely on an array of physiological parameters (rates of cell formation, differentiation and death, concentration thresholds for signaling activity, medication efficacies and half-lives, etc.) many of which are not directly measureable. However, clinical measurements on physiological responses to medications with different mechanisms of action provide a wealth of indirect information about time scales of bone turnover and regulatory feedbacks. We calibrated the model using published clinical data from various seminal studies on both (i) long-term BMD age dependence and (ii) the response of BMD and BTMs to the administration of different drugs (see Appendix 3—table 2 for a comprehensive list of data sources). Although BMD constitutes the major target variable of our model, the dynamics of BTM concentrations carry important complementary information about the mode of action of the administered drugs (antiresorptive, anabolic, and combinations) that crucially informs the calibration procedure. To allow the model to capture the effects of medications as physiologically sensible modulations of the age-dependent bone mineral metabolism, we created hybrid datasets each of which comprised both aging-related BMD changes and the response to a treatment (see 'Methods' and Appendix 1—figure 1D). We then determined a single set of model parameters through a simultaneous fit of the free 31 model parameters to capture a specified set of hybrid aging/treatment datasets containing different drug responses (Appendix 3). Without constraining the average rate of skeletal bone turnover, model calibration yielded an inferred value of about 6% per year on average, of the same order of for cortical bone, which constitutes about of the (Manolagas, 2000). The model was to capture the BMD and BTM dynamics all calibration datasets with (Appendix 1), the structural To the of the we the mean between model and clinical the for BMD was for all calibration datasets (Appendix 3—table an between model and The of BTMs the of their from was in all calibration an description of the mode of action in the in the total of BTM observed for datasets were mostly due to in the of and and of the BTM as by different (Appendix 3 and Appendix 3—table 3). After the we to validate the calibrated model by its ability to predict the effects of drug dosing schemes that had not been used for Model included complex sequential and parallel drug combinations and the model to predict the effects of treatment schemes used in calibration (Appendix 3—table 2). To this end, the model only drug dosing information used in the clinical trials but was not by BMD or BTM which it had to the single set of previously determined the model showed a capacity to quantitatively the effects of a of medication both treatment and (Figure Figure 1). in scenarios including sequential treatments with up to three different drug types and parallel treatments with different drugs, respectively, the model was to predict the complex of both BMD and levels with a high of (Figure 2). all for BMD were (Appendix 3—table an predictive capacity of the In this provided a of the capacity to capture the physiological dynamics of bone turnover and the mechanisms of action of various drugs relevant to osteoporosis treatment using a single set of model Figure 2 with 1 all Download asset Open asset a single set of the calibrated model can quantitatively predict the effects of various drugs in different dosing and in of total hip bone mineral density and clinical data including aging and treatment of various sequential drug including romosozumab, and aging/treatment datasets were created data from et al., in in total and as well as et al., et al., and et al., in A and as into the treatment in including BMD and changes of the bone resorption marker C-terminal telopeptide and the bone formation marker procollagen type 1 amino-terminal propeptide the the medication scheme (see legend). Data average types and types as in the In both BMD is as a of its value at alternative treatment schemes established the predictive capacity of the model for the considered we to the model to study and drug dosing As an example, we considered a sequential treatment with three drugs of different the the sclerostin inhibitor romosozumab, and the RANKL inhibitor denosumab. In a clinical by et al., the sequence per for 1 by per for 1 by per for 1 had been (Figure 2). However, in there are different in which these drugs can be and A it is not whether synergistic or interactions between these drugs and the physiological state in which they the may lead to a and long-term of BMD and biomarkers between different medication all in a clinical present a and and of the study to treatment we these different treatment options using the present model (Figure To assess the clinical of different we compared clinically relevant different (i) the maximum BMD compared to at treatment of when it (Figure and (ii) the long-term effects of treatment on BMD as by the BMD after treatment (Figure Figure 3 Download asset Open asset The model for different of the same drugs at constant total medication of bone mineral density (BMD) and C-terminal telopeptide and procollagen type 1 amino-terminal propeptide concentrations for different of the three drugs and as treatment at age The total amount of drug administered is results on the sequence were in et al., also Figure 2. BMD to at treatment the course of treatment for different drug BMD after treatment to at treatment for different drug we that the of different medication were different the same total amount of drug administered (Figure as and a maximum BMD the course of the treatment, which to treatments to maximum BMD gain (Figure were to as by the maximum BMD treatment, they performed compared and with to long-term BMD as by model (Figure This that BMD gains may be limited as a for the clinical benefit of a treatment as a our modeling the for this is in effects after treatment of osteoclastogenesis leads to a of an osteoclast After treatment end, this becomes to and rise to a large osteoclast leading to resorption of the bone matrix that had been up treatment. In this specific drug lead to an of this for example, by osteoclast apoptosis such a thereby bone turnover in the In our model considerable potential in the of dosing regimens and drug in osteoporosis treatment, combination to achieve an optimal effect for a given medication These are possible because the mechanisms of action of one drug may or on the state of the bone mineral metabolism by the treatment with another Discussion of osteoporosis is and in many bone physiology as our we have a mathematical modeling framework that can quantitatively capture and predict the of osteoporosis in postmenopausal women with and without medical Our model is on a small set of essential mechanisms of bone turnover. The of this the of the bone mineral dynamics relevant for osteoporosis medications can be into only a few These components describe the of osteoblasts, osteoclasts, and osteocytes, as well as their cell populations and a few essential regulatory through and signaling factors such a

Dietary casein phosphopeptides prevent bone loss in aged ovariectomized rats.

Vitamin D insufficiency and sarcopenia are crucial risk factors for osteoporosis. In a study of noninstitutionalized elderly subjects, we investigated the simultaneous effect of vitamin D and sarcopenia on bone mineral density (BMD) and found that sarcopenia was associated with low BMD in the femur, especially in those with suboptimal vitamin D levels. Although vitamin D insufficiency and sarcopenia are prevalent in the elderly population worldwide, their possible influence on BMD has not been determined. We aimed to investigate the different effect of vitamin D insufficiency and sarcopenia on BMD in the elderly Korean population. Individuals aged 60 or older were selected from those who participated in the Fourth and Fifth Korea National Health and Nutrition Examination Surveys conducted in 2009 and 2010; 1,596 males and 1,886 females were analyzed. Appendicular skeletal muscle mass (ASM) and BMD were assessed by dual-energy X-ray absorptiometry; serum 25-hydroxyvitamin D [25(OH)D] and a panel of clinical and laboratory parameters were also measured. The study population was divided into four groups according to their vitamin D and sarcopenic status. BMD in total femur and in the femoral neck but not the lumbar spine was markedly decreased in sarcopenic subjects with vitamin D insufficiency [25(OH)D < 20ng/ml] comparing to other groups, regardless of gender. Multivariable linear regression models showed that BMD was significantly associated with ASM and high daily calcium intake as well as conventional risk factors such as age, body mass index (BMI), and history of fracture. Independent predictors for low femur BMD included sarcopenia, low daily calcium intake, low 25(OH)D levels, age, and BMI. These data showed that an association between vitamin D insufficiency and low BMD was more prominent in elderly subjects with sarcopenia.

OBJECTIVES/SPECIFIC AIMS: Persons living with HIV (PLWH) are at increased risk for fragility bone disease. Current osteoporosis screening guidelines do not account for HIV status, and clinical risk assessment tools are not sensitive in PLWH. We examined the value of traditional osteoporosis risk factors, HIV-specific indices, and bone turnover biomarkers in predicting low bone mineral density (BMD) in PLWH. METHODS/STUDY POPULATION: Demographic and clinical characteristics, dual energy x-ray absorptiometry (DXA)-derived BMD, HIV indices (viral load, CD4 count, antiretroviral therapy [ART]), and biomarkers of bone turnover (C-terminal telopeptide of collagen [CTx], osteocalcin [OCN]) were evaluated in a cross-sectional analysis of PLWH (n=248) and HIV- controls (n=183). The primary outcome was low BMD, defined as osteopenia or osteoporosis by WHO criteria. Multivariable logistic and modified Poisson regression models were used to assess associations between low BMD and covariates of interest. RESULTS/ANTICIPATED RESULTS: Overall, median age was 44 years, 48% were male, 88% were black, median body mass index (BMI) was 28 kg/m2, 72% smoked cigarettes, and 53% used alcohol; characteristics did not differ by HIV status. PLWH had a mean CD4 of 408 cells/mm3, 55% were ART-naïve, and 45% had viral suppression on ART. Overall, 25% (109/431) had low BMD, including 31% of PLWH compared to 16% of HIV- controls. In multivariable models, HIV was significantly associated with low BMD (aOR 2.46, 95%CI 1.39-4.34; aRR 1.90, 95%CI 1.18-3.07). Adjusting for HIV, three traditional risks– age, race, and BMI– were independently associated with low BMD in the full cohort. However, bone turnover markers, CTx and OCN, were better able to discriminate low vs. normal BMD in PLWH compared to HIV- controls. In PLWH, mean serum CTx was 23% higher in low vs. normal BMD (mean CTx difference=0.06 ug/mL); in HIV- controls, no association with BMD was observed (mean CTx difference=0 ug/mL). In PLWH, mean serum OCN was 38% higher in those with low vs. normal BMD (mean OCN difference=2.48 ug/mL); in HIV- controls, mean serum OCN was only 16% higher in those with low vs. normal BMD (mean OCN difference=1.08 ug/mL). DISCUSSION/SIGNIFICANCE OF IMPACT: In PLWH as opposed to HIV- controls, serum biomarkers reflecting a high bone turnover state, may discriminate individuals with low versus normal BMD. Because changes in biomarkers precede changes in BMD, these markers should be explored further either alone or in combination with traditional risk assessment tools to improve early screening for osteoporosis in PLWH.

In South Africa, appendicular and lumbar spine bone mineral density (BMD) have been found to be similar in black and white women. However, femoral BMD has been found to be higher in black than in white women. Two different techniques were used to recalculate BMD to eliminate the possible confounding influence of ethnic differences in height on areal BMD measurements. Volumetric bone mineral apparent density (BMAD) values were calculated and bone mineral content (BMC) was corrected for body and bone size. This report analyses differences in BMD (corrected for height and weight), BMAD, BMC (corrected for body and bone size), femoral neck axis length (FNAL), mineral homeostasis and bone turnover (BT) in a group of 20 to 49-year-old premenopausal (105 whites and 74 blacks) and 45 to 64-year-old postmenopausal (50 whites and 65 blacks) female South African nurses. The corrected BMD and BMC findings were congruous, showing that both pre- and postmenopausal blacks and whites have similar distal radius and lumbar spine bone mass but that whites have lower femoral neck bone mass than blacks. In contrast, BMAD findings suggest that pre- and postmenopausal whites have lower bone mass at the lumbar spine and femoral neck than blacks but similar bone mass at the distal radius to blacks. There is a greater rate of decline in BMD in postmenopausal whites than in blacks. BMD at the femoral neck was 12.1% lower in premenopausal whites and 16.5% lower in postmenopausal whites than in blacks. There was a positive association between femoral neck BMD and weight in premenopausal blacks (R2 = 0.5, p = 0.0001) but not in whites. Blacks had shorter FNAL than whites in both the pre- and post-menopausal groups. Blacks had lower serum 25-hydroxyvitamin D (25-(OH)D) and higher 1,25-dihydroxyvitamin D (1,25-(OH)2D) levels than whites. There were no ethnic differences in biochemical markers of bone formation (serum alkaline phosphatase and osteocalcin) or bone resorption (urine hydroxyproline and pyridinoline), or in dietary calcium intake in either the pre- or postmenopausal groups. In the postmenopausal group, whites had higher ionized serum calcium (p = 0.003), similar serum albumin, lower serum parathyroid hormone (p = 0.003) and higher urinary calcium excretion (p = 0.0001) than blacks. These results suggest that the higher peak femoral neck BMD in South African blacks than in whites might be determined by greater weight-bearing in blacks and that the significantly lower femoral neck BMD in postmenopausal whites than in blacks is determined by lower peak femoral neck BMD and a faster postmenopausal decline in BMD in whites. The higher incidence of femoral neck fractures in South African whites than in blacks is probably determined by the lower femoral neck BMD and longer FNAL in whites. The greater rate of decline in BMD in postmenopausal whites than in blacks is associated with an increase in urinary calcium excretion in whites. Measurement of biochemical markers of BT has not contributed to the understanding of ethnic differences in BMD and skeletal metabolism in our subjects.

Low bone mineral density (BMD) is a risk factor of osteoporosis and has strong genetic determination. Genes influencing BMD and fundamental mechanisms leading to osteoporosis have yet to be fully determined. Peripheral blood monocytes (PBM) are potential osteoclast precursors, which could access to bone resorption surfaces and differentiate into osteoclasts to resorb bone. Herein, we attempted to identify osteoporosis susceptibility gene(s) and characterize their function(s), through an initial proteomics discovery study on PBM in vivo, and multiscale validation studies in vivo and in vitro. Utilizing the quantitative proteomics methodology LC-nano-ESI-MS(E), we discovered that a novel protein, i.e. ANXA2, was up-regulated twofold in PBM in vivo in Caucasians with extremely low BMD (cases) versus those with extremely high BMD (controls) (n = 28, p < 0.05). ANXA2 gene up-regulation in low BMD subjects was replicated at the mRNA level in PBM in vivo in a second and independent case-control sample (n = 80, p < 0.05). At the DNA level, we found that SNPs in the ANXA2 gene were associated with BMD variation in a 3(rd) and independent case-control sample (n = 44, p < 0.05), as well as in a random population sample (n = 997, p < 0.05). The above integrative evidence strongly supports the concept that ANXA2 is involved in the pathogenesis of osteoporosis in humans. Through a follow-up cellular functional study, we found that ANXA2 protein significantly promoted monocyte migration across an endothelial barrier in vitro (p < 0.001). Thus, elevated ANXA2 protein expression level, as detected in low BMD subjects, probably stimulates more PBM migration through the blood vessel walls to bone resorption surfaces in vivo, where they differentiate into higher number of osteoclasts and resorb bone at higher rates, thereby decreasing BMD. In conclusion, this study identified a novel osteoporosis susceptibility gene ANXA2, and suggested a novel pathophysiological mechanism, mediated by ANXA2, for osteoporosis in humans.

To evaluate the roles or effects of oviductus ranae (OR) or oviductus ranae eggs (ORE) in preventing and treating postmenopausal osteoporosis. In vivo experiment: Sixty female adult Wistar rats were randomly divided into 5 groups of 12. To provide an osteoporosis model 4 groups of rats were ovariectomized (OVX), with the 5th being sham operated. Medication commenced 7 days after the operation and lasted continuously for 12 weeks. Sham operated and OVX groups were given equivalent volumes of 5% Tween-80. The other three groups intragastrically received conjugated estrogens (CE), OR or ORE of the corresponding doses. At the 12th week, serum estrogen, bone gla protein (BGP), serum calcium, phosphorus, and alkaline phosphatase (ALP) were assayed; bone mineral densities (BMD) were measured and bone scanning was conducted; uteri were weighed, and weight, volume and length of the femoral bones were determined; and cortical thickness of femoral heads and area of bone trabecula were measured by image analyzer. In vitro experiment: Eighty 10-month old SD rats, with equal numbers of males and females, were randomly divided into 8 groups. Osteoblasts were isolated from neonatal rat calvariae, and the cells were exposed to various concentrations of serum from OR and ORE groups to study the impact of these sera on osteoblastic proliferation, ALP activity and mineralization. Osteoclastic numbers were determined using tartrate resistant acid phosphatase (TRAP). In vivo experiment: The body weight of the four OVX groups increased significantly (P<0.01). Uterine weight of the CE group was the highest (P<0.01); Compared with the model group, estrogen level, BMD, bone scanning/bone imaging index weight of the femoral bones, cortical thickness of femoral heads in the OR and ORE groups increased significantly (P<0.05, P<0.01); femoral volume in the ORE group increased significantly (P<0.05); and the content of osteocalcin, phosphorus, and ALP in serum decreased significantly (P<0.05, P<0.01). In vitro experiment: Sera from OR and ORE groups had notable effects on the proliferation of osteoblasts (P<0.05 and P<0.01, repsectively) and stimulated the formation of calcium nodes (P<0.05, P<0.01), while the enhancement of ALP activity in osteoblasts was significant (P<0.05, P<0.01). The number of TRAP-positive cells was significantly reduced as well (P<0.01). OR and its eggs could effectively suppress OVX-induced osteoporosis in rats, and increase bone turnover possibly by both an increase in osteoblastic activity and a decrease in osteoclastic activity. The present study provides evidence that OR and its eggs could be considered a complementary and alternative medicine for the treatment of postmenopausal osteoporosis.

"The greatly compressed bodies of the vertebrae … were so soft they could easily be cut with a knife."—Harvey Cushing, 1932 THE ADVERSE EFFECTS OF HYPERCORTISOLISM on bone were recognized more than half a century ago,1 but today, the iatrogenic form of the disease has become far more common than Cushing's syndrome and glucocorticoid excess is the third leading cause of osteoporosis following loss of sex steroids and old age. It is estimated that as many as 50% of patients requiring glucocorticoids for the control of pulmonary, rheumatologic, autoimmune, hematopoietic, gastrointestinal disease, or to prevent transplant rejection will ultimately suffer fractures.2 The underlying cause of the fractures in glucocorticoid-induced osteoporosis, as in other forms of osteoporosis, is loss of bone. With glucocorticoid treatment, the loss of bone is biphasic with a rapid initial phase of approximately 12% during the first few months, followed by a slower phase of about 2–5% annually. Both cortical and cancellous bone are lost, but the adverse effects of steroids have a predilection for the axial skeleton. Hence, spontaneous fractures of the vertebrae or ribs are often presenting manifestations of the disorder. Besides these fractures, a frequent accompaniment of long-term glucocorticoid therapy is osteonecrosis—otherwise known as aseptic or avascular necrosis—which causes collapse of the femoral head in as many as 25% of patients.3 Because of the heterogeneity of the underlying conditions—some of which (e.g., rheumatoid arthritis, lymphoma, myeloma, Crohn's disease) independently contribute to skeletal deterioration—wide variations of dose and duration of treatment and lack of a faithful animal model, progress toward the elucidation of the mechanism(s) responsible for the adverse impact of glucocorticoids on the skeleton has been slow. As a result, the management of this condition has remained largely empirical. Recent advances in bone biology, in general, and elucidation of key mechanisms in glucocorticoid-induced osteoporosis, in particular, provide for the first time a convincing explanation of the pathogenesis of the disease and raise hope that more rational therapy may be forthcoming. The purpose of this editorial is to highlight these new developments and to point out their pharmacotherapeutic implications. To appreciate them better, however, one must first understand some basic principles of bone homeostasis. During life, the skeleton undergoes remodeling, a periodic replacement of old bone by new, which is responsible for the complete regeneration of the adult skeleton every 10 years. Remodeling is carried out by a team of juxtaposed osteoclasts (in the front) and osteoblasts (in the rear), comprising the basic multicellular unit (BMU). In cortical bone the BMUs tunnel through the tissue, while in cancellous bone they move across the trabecular surface forming a trench. In both situations the cellular components of the BMU maintain a well-orchestrated spatial and temporal relationship with each other. Osteoclasts attach to bone and subsequently remove it by acidification and proteolytic digestion. As the BMU advances, osteoclasts leave the resorption site and osteoblasts move in to cover the excavated area and begin the process of new bone formation by secreting osteoid, which is eventually mineralized. In healthy human adults, 3–4 million BMUs are initiated per year and about 1 million are operating at any moment.4 Even though millions of small packets of bone are constantly remodeled, bone mass is preserved thanks to a remarkably tight balance between the amount of bone resorbed and formed during each cycle of remodeling (Fig. 1, upper panel). Comparison of a normal cycle of bone remodeling (upper panel) with an abnormal one caused by glucocorticoid excess (lower panel); note the decreased number of osteoblasts and their premature apoptosis as well as the incomplete repair of bone in the latter. Old bone being replaced is indicated in red; newly formed bone is in light tan. Both osteoblasts and osteoclasts are derived from precursors originating in the bone marrow. The precursors of osteoblasts are multipotent mesenchymal stem cells, which also give rise to bone marrow stromal cells, chondrocytes, muscle cells, and adipocytes, while the precursors of osteoclasts are hematopoietic cells of the monocyte/macrophage lineage. The development of both osteoblasts and osteoclasts is controlled by growth factors and cytokines that are produced in the bone marrow microenvironment and is modulated by systemic hormones and probably by mechanical signals.5 Mesenchymal cell differentiation toward the osteoblast phenotype and osteoclastogenesis are inseparably linked because both are stimulated by the same factors, proceed simultaneously, and the former event is a prerequisite for the latter. It now seems quite clear that in the postnatal bone marrow, commitment of pluripotent mesenchymal precursors to the osteoblastic lineage is initiated by bone morphogenetic proteins (BMPs), the same proteins that are responsible for skeletal development during embryonic life and fracture healing.6 BMPs stimulate the transcription of the gene encoding Cbfa1/Osf2, an osteoblast transcription factor.7 In turn, Cbfa1/Osf2 activates osteoblast-specific genes such as osteopontin, bone sialoprotein, type I collagen, and osteocalcin. Lack of Cbfa1 prevents osteoblast development and remarkably also leads to a paucity of osteoclasts. The mechanistic basis of this phenomenon and the dependency of osteoclastogenesis on mesenchymal cell differentiation has recently been established by the discovery of a membrane-bound cytokine-like molecule, RANK ligand/osteoprotogerin ligand/TRANCE, which is expressed in committed preosteoblastic cells.8 The RANK ligand binds to a specific receptor (RANK) which is expressed in the hematopoietic osteoclast progenitors. This interaction is essential and, together with macrophage colony-stimulating factor (M-CSF), sufficient for osteoclastogenesis. Strong support for the above scenario has been provided by studies from the authors' group demonstrating that BMP-2 and BMP-4 and their receptors are expressed in the postnatal marrow and that they are indeed required for both osteoblast as well as osteoclast development.6 Moreover, the promoter of the RANK ligand gene contains two functional Cbfa1-binding sites.9 Hence, a BMP → Cbfa1 → RANK ligand gene expression cascade in cells of the bone marrow stromal/osteoblastic lineage may well constitute the molecular basis of the linkage between osteoblastogenesis and osteoclastogenesis, with BMPs providing the tonic baseline control of both processes, and thereby the rate of bone remodeling upon which other inputs (e.g. biomechanical, hormonal, etc.) operate (Fig. 2). The birth and fate of osteoblasts and osteoclasts. The autocrine actions of BMP-2/4 on uncommitted mesenchymal progenitors (illustrated by the circular arrows), the expression of CBFA-1 by stromal/osteoblast progenitors and the expression of RANK Ligand (RANKL) and RANK on stromal/osteoblastic and hematopoietic cells respectively, are depicted to indicate their critical contribution to the generation of these two cells. The BMU has an average life span of 6 months. The average life span of its executive cells, however, is much shorter. The average life span of a human osteoclast is 2 weeks and the average life span of an osteoblast is 3 months. Evidence accumulated during the last couple of years indicates that both osteoclasts and osteoblasts undergo apoptosis. Indeed, after osteoclasts have eroded to a particular distance, either from the central axis in cortical bone or to a particular depth from the surface in cancellous bone, they die by apoptosis and are quickly removed by phagocytes.10 The majority of osteoblasts (50–70%) also die by apoptosis once they have completed their bone-forming tasks.11 The remaining osteoblasts have one of two alternative fates: they can become elongated "lining cells" that cover the newly formed bone surface; or they can be entrapped in the mineralized matrix to become osteocytes, cells characterized by a striking stellate morphology, reminiscent of the dendritic network of the nervous system. Osteocytes represent the most common (∼90%) cell type in bone and are believed to be the sensors of the local need for bone augmentatioin or reduction during functional adaptation of the skeleton, the detection of microdamage, and the transmission of signals that lead to bone repair by remodeling.12 From this brief update of normal bone biology, it becomes clear that the rate of supply of new osteoblasts and osteoclasts and the timing of the death of these cells by apoptosis are critical determinants of the initiation of new BMUs and/or extension or shortening of the lifetime of existing ones. Strong support for this concept has been provided by the elucidation of the pathogenesis of postmenopausal and senile osteoporosis and, specifically, the realization that the bone loss underlying either form of the disease is due to changes in the birth13,14 as well as death rate of bone cells.10 As it will be discussed below, glucocorticoid-induced osteoporosis can also be explained by changes in the birth and death of bone cells. The cardinal histologic features of glucocorticoid-induced osteoporosis are decreased bone formation rate, decreased wall thickness of trabeculae, a strong indication of decreased work output by osteoblasts, and in situ death of portions of bone. Increased bone resorption, decreased osteoblast proliferation and biosynthetic activity, sex-steroid deficiency, as well as hyperparathyroidism resulting from decreased intestinal calcium absorption and hypercalciuria due to defective vitamin D metabolism, have all been proposed as mechanisms for the loss of bone that ensues with glucocorticoid excess.15 However, none of these mechanisms provides a satisfactory explanation for the cardinal histologic features of the condition. Moreover, the evidence put forward in support of each of these mechanisms has been weak and often conflicting. For example, while increased osteoclast surface has been shown in some histologic studies, others have not confirmed this finding and more recent ones have even shown that the number of osteoclasts is decreased.16 Likewise, elevated levels of parathyroid hormone (PTH) have not been a consistent finding in glucocorticoid-induced osteoporosis—and in fact, reduced levels have been reported in some studies.17,18 It is also very unlikely that the adverse effects of glucocorticoids on bone are mediated by sex-steroid deficiency, as they are readily manifested in both eugonadal and hypogonadal subjects. Finally, the circulating levels of vitamin D metabolites are usually normal in patients with glucocorticoid excess making improbable that a defect in vitamin D metabolism contributes in any significant degree to the development of this condition.19 Recent studies from our group provide evidence that the decreased bone formation and osteonecrosis can be accounted for by a suppressive effect of glucocorticoids on osteoblastogenesis (and as expected from the above discussion on osteoclastogenesis); as well as by promotion of apoptosis of osteoblasts and osteocytes.20 Moreover, our work has demonstrated that the mouse, unlike the rat and other previously examined laboratory animals, is a faithful animal model of the glucocorticoid-induced bone loss in humans. Indeed, mice receiving glucocorticoids for 4 weeks—a period equivalent to approximately 3–4 years in humans—exhibited decreased bone mineral density associated with a decrease in the number of osteoblast, as well as osteoclast, progenitors in the bone marrow and a dramatic reduction in cancellous bone area and trabecular width compared with placebo controls. These changes were associated with a significant reduction in osteoid area and a decrease in the rates of mineral apposition and bone formation. More strikingly, glucocorticoid administration to mice caused a 3-fold increase in the prevalence of osteoblast apoptosis in vertebrae and induced apoptosis in 28% of the osteocytes in metaphyseal cortical bone. Although there was a significant correlation between the severity of the bone loss and the extent of reduction in bone formation, some of the bone loss we observed was due to an early increase in bone resorption as evidenced by an increase in osteoclast perimeter by histomorphometric examination of vertebral cancellous bone after only 7 days of steroid treatment. The same histomorphometric changes seen in mice receiving glucocorticoids for 4 weeks were confirmed in biopsies from patients receiving long-term glucocorticoid therapy. Moreover, as in mice, an increase in osteoblast and osteocyte apoptosis was found in the human biopsies. Compared to osteoblast apoptosis, osteocyte apoptosis was far more prevalent, probably because of the anatomical isolation of osteocytes from scavenger cells. Consistent with these in vivo findings, we have more recently established that glucocorticoids promote osteoblast and osteocyte apoptosis in vitro.21 Decreased production of osteoclasts can explain the reduction in bone turnover with chronic glucocorticoid excess, whereas decreased production and apoptosis of osteoblasts can explain the decline in bone formation and trabecular width. Furthermore, accumulation of apoptotic osteocytes may contribute to osteonecrosis. Hence, as in the postmenopausal and senile form of osteoporosis the fundamental problem in the steroid-induced form of the disease is a change in the number of bone cells (Fig. 1, lower panel). In a follow-up study, the prevalence of osteocyte apoptosis was examined in whole femoral heads obtained from patients with glucocorticoid-induced osteoporosis who had undergone resection of the femoral head and prosthetic hip replacement because of the disease.22 Control specimens were obtained from patients with osteonecrosis due to other clinical disorders including femoral neck cores from five patients with sickle cell disease, a femoral head removed after traumatic fracture and rupture of ligamentum teres, and three femoral heads taken from patients with alcoholism. Abundant apoptotic osteocytes and cells lining cancellous bone were found in the proximal femoral heads resected from patients with glucocorticoid-induced avascular necrosis, whereas apoptotic bone cells were absent from specimens removed because of traumatic or sickle cell disease and were rare in alcohol-induced femoral necrosis. Furthermore, the apoptotic osteocytes were adjacent to the subchondral fracture crescent, whereas empty osteocytic lacunae, the cardinal sign of bone necrosis, were infrequent. Reduced cancellous bone area, increased marrow adipocytes, and decreased hematopoietic marrow were noted in the specimens of the glucocorticoid receiving patients. Although the function of osteocytes in bone is far from being understood, it is believed that these cells may participate in the detection of microdamage and the transmission of signals that lead to its repair by remodeling. In view of this, increased apoptosis of osteocytes may account for the so-called "bone necrosis" associated with glucocorticoid excess. In the past, glucocorticoid-induced osteonecrosis has been attributed to fat emboli, compression of the blood vessels of the femoral head by marrow fat or fluid retention, and poorly mending fatigue fractures. These new findings strongly support the contention that glucocorticoid-induced avascular necrosis is a misnomer; the bone is neither avascular nor necrotic, instead showing prominent apoptosis of cancellous lining cells and osteocytes. Glucocorticoid-induced osteocyte apoptosis, a cumulative and unrepairable defect, could uniquely disrupt the proposed mechanosensory role of the osteocyte network and thus promote collapse of the femoral head. At this stage, it is unknown whether changes in the regulation of osteocyte programmed cell death contribute to the bone loss associated with other forms of osteoporosis. However, it is worth noting that osteocyte apoptosis is increased in estrogen-deficient women and that a significant proportion of osteocytes gradually die with age.23,24 The precise mediators of the cellular changes caused by glucocorticoid excess remain a matter of conjecture. Nonetheless, there is evidence that glucocorticoids decrease the expression of the TGF-β type I receptor secondary to direct suppression of Cbfa125 and they antagonize the effects of BMP2 and insulin-like growth factor I.26,27 Further, the increased adipogenesis noted in the bone marrow of mice and humans with glucocorticoid excess might be due to increased expression of PPARγ2,28 a transcription factor that induces terminal adipocyte differentiation while suppressing osteoblast differentiation.29 In addition, the proapoptotic effect of glucocorticoids on osteoblasts can be prevented by overexpression of the Bcl-2 gene, suggesting that suppression of Bcl-2 or the ratio of Bcl-2 over BAX may also be key mechanisms21 (Table 1). Calcium, vitamin D and its metabolites, thiazide diuretics, fluoride, estrogen, testosterone, medroxyprogesterone, nandrolone decanoate, growth hormone, deflazacort—an oxazoline derivative of prednisolone—calcitonin, and bisphosphonates have all been proposed as therapy for glucocorticoid-induced osteoporosis. Unfortunately, with the only exception being the bisphosphonates, none of these drugs has been satisfactory and none has proven antifracture efficacy in glucocorticoid-induced osteoporosis. In fact, for most of them, the benefits of some modest increases in bone mineral density (BMD) have been outweighed by serious side effects. A calcium intake of 1500 mg/day is certainly safe if there is no history of renal calculi, but when used alone bone loss is not prevented. Sex-steroid replacement therapy is useful in hypogonadal patients, if not otherwise contraindicated. Calcitonin is seldom potent enough to have a clinically significant impact. Etidronate has been shown to improve spinal BMD, but must be given intermittently to avoid drug-induced defects in mineralization.30,31 Therapy with intravenous pamidronate or oral alendronate is more attractive because of greater safety, but the gain in BMD is still modest. Nonetheless, a small reduction in new vertebral fractures was recently reported in patients receiving alendronate (overall incidence, 2.3%; compared with the placebo group, 3.7%; relative risk, 0.6%; 95% confidence interval, 0.1–4.4).32 Bisphosphonates are most effective when started early, before the rapid, early bone loss, but their beneficial effects are less impressive in patients with established disease. In vitro studies in the authors' laboratory show that bisphosphonates prevent osteoblast and osteocyte apoptosis induced by glucocorticoid.33 In view of this evidence, it is theoretically possible that at least part of the antifracture efficacy of these drugs may be due to this mechanism. Considering our current understanding of the pathophysiology of glucocorticoid-induced osteoporosis, it is obvious that the ideal drug for this condition should be an anabolic agent which would increase bone mass. In a recent trial, Lane et al. reported that daily subcutaneous injections of PTH is a safe and effective treatment for corticosteroid-induced osteoporosis.34 Yet, as mentioned above, PTH has previously been thought of as one of the potential pathogenetic factors for the development of this condition. Can the new insights into the pathogenesis of glucocorticoid-induced osteoporosis and the evidence that intermittent PTH administration is an effective treatment be reconciled on a rational mechanistic basis? In direct contrast to the suppressive effect of glucocorticoids on bone formation, intermittent PTH administration increases bone mass in animals and humans, but the mechanism of this effect had remained an enigma for a long time. We have now obtained evidence that prevention of osteoblast and osteocyte apoptosis is the principal mechanism for the anabolic effect of PTH on bone.35 Thus, in mice, PTH increased the life span of mature osteoblasts by preventing apoptosis, an effect readily reproduced in vitro on osteoblasts and osteocytes, rather than by changing the rate of generation of new osteoblasts. Moreover, PTH prevents in vitro apoptosis induced by either etoposide or dexamethasone in primary cultures of calvaria cells, an osteocyte cell line, as well as in murine and human osteoblastic cell lines.36 Therefore, it seems that PTH and perhaps future PTH mimetics and nonpeptide inhibitors of apoptosis pathways in osteoblasts represent for the first time pathophysiology-based, i.e., rational as opposed to empirical, pharmacotherapies for osteoporosis, in particular, those in which osteoblast progenitor formation is suppressed, such as the osteoporoses associated with glucocorticoid excess and senility. Finally, it has been reported recently that glucocorticoid-induced apoptosis of thymocytes is mediated by a mechanism that requires the dimerization of the glucocorticoid receptor and direct binding of the receptor to glucocorticoid response element.37 In addition, synthetic glucocorticoids have been developed that exhibit anti-inflammatory activity in vivo as potently as classical glucocorticoids, without requiring glucocorticoid receptor–DNA binding and transactivation.38 The demonstration of osteoblast and osteocyte apoptosis in animals and humans with glucocorticoid-induced osteoporosis raises the possibility that these "designer glucocorticoids" might have bone sparing effects. The authors acknowledge the support of the National Institutes of Health (P01-AG13918 and R01-43003) and the Department of Veterans Affairs for their research; A. Michael Parfitt, Robert L. Jilka, and Teresita Bellido for helpful discussions; and Tonya Smith for the preparation of this manuscript.

THU0392 Bone Mineral Density Changes in Patients with Early Axial Spondyloarthritis

Is GSN significant for hip BMD in female Caucasians?

To evaluate the occurrence of low bone mineral density (BMD) and its relationship with clinical and laboratorial characteristics in children and young adults with sickle cell anaemia living in Northeast-Brazil, and to assess the role of radiography in diagnosing low BMD. Bone mineral density of lumbar spine was measured by dual energy X-ray absorptiometry (DXA) in 27 patients with Sickle cell anaemia (SCA) aged 7-28years. Clinical history, calcium and calorie intake, laboratory measurements, anthropometrics and pubertal development were assessed, and X-rays were obtained. Z-scores and T-scores for weight, height, Body Mass Index (BMI) and BMD were calculated using age and gender matched reference data. Mean lumbar spine BMD Z-scores and T-scores were -1.81 SD in boys and -0.80 SD in girls. BMD Z-scores were below -2 SD in 33.3% of girls and in 46.7% of boys. Low BMD (<-2 SD) occurred significantly more in patients with low height-for-age (P=0.02), low weight-for-age (P=0.001) and low BMI-for-age (P=0.006). No significant relationships were found between BMD and other clinical and laboratory parameters. Radiography had a sensitivity of 75% and a specificity of 36% to detect low BMD, and was considered not useful in this context. Patients with low height and/or low weight-for-age seem to be at high risk for developing low BMD.

The Role of RANKL/Osteoprotegerin and Wnt Signaling Pathways in the Development of Osteoporosis in Patients with Hemophilia

Patients with diabetes mellitus are known to develop osteopenia and osteoporosis, apparently as a reduction in the process of bone formation. In order to evaluate whether bone-modulating hormones--estradiol, testosterone, and 1,25(OH)(2)D(3)--have different effects on osteoblasts derived from diabetic and from normal non-diabetic rats, we studied the specific effects of these hormones on the differentiation and function of cultured osteoblasts derived from 1-year-old Cohen diabetic rats. (The Cohen diabetic model consists of a diabetic-sensitive strain [CDs; diabetic] and a diabetic-resistant strain [CDr; normal]). The CDs and CDr male and female rats were fed on a regular diet (RD) or a high-sucrose low-copper diet (HSD; diabetogenic). On the HSD diet, only CD rats develop type 2 diabetes, while CDr do not. Bones were removed for primary osteoblast cultures, and osteoblastic responses to the bone-modulation hormones--estradiol, testosterone, and 1,25(OH)(2)D(3)--were studied. In male rats fed RD, primary cultures of osteoblasts without hormone addition to the culture medium showed that alkaline phosphatase (ALP) activity was similar in the Cohen diabetic rats (both CDr and CDs) to that of the original Sabra strain. However, collagen synthesis was reduced in the CDr and CDs compared to the Sabra strain. The addition of the hormones to the culture medium did not change ALP activity or collagen synthesis in the male-derived osteoblasts, but increased mineralization in all strains. In female rats (studied only in CDs and CDr animals) there were no differences between animals fed the RD. HSD increased the basal activity of ALP in the CDr but not in the CDs rats, and decreased the rate of collagen synthesis in both CDr and CDs (diabetic) animals. The addition of the bone-modulation hormones to the culture medium further increased ALP activity in the osteoblasts derived from the CDr animals, while decreasing ALP activity in the CDs. These hormones also decreased collagen synthesis in both strains and increased mineralization in all osteoblasts. In conclusion, the metabolic status (HSD and diabetes) in rats prior to culture affected the phenotype of cultured osteoblasts, decreasing their response to bone-modulation hormones. This decreased response, especially to estradiol, may be a major cause of the osteopenia observed in diabetes.

Secondary Causes of Osteoporosis