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. Author manuscript; available in PMC: 2018 Nov 2.
Published in final edited form as: Toxicol Pathol. 2017 Nov 2;45(7):887–893. doi: 10.1177/0192623317737065

Energy Metabolism of Bone

Katherine J Motyl 1, Anyonya R Guntur 2, Adriana Lelis Carvalho 3, Clifford J Rosen 2
PMCID: PMC5777524  NIHMSID: NIHMS909065  PMID: 29096593

Abstract

Biological processes utilize energy and therefore must be prioritized based on fuel availability. Bone is no exception to this, and the benefit of remodeling when necessary outweighs the energy costs. Bone remodeling is important for maintaining blood calcium homeostasis, repairing micro cracks and fractures, and modifying bone structure so that it is better suited to withstand loading demands. Osteoclasts, osteoblasts and osteocytes are the primary cells responsible for bone remodeling, although bone marrow adipocytes and other cells may also play an indirect role. There is a renewed interest in bone cell energetics because of the potential for these processes to be targeted for osteoporosis therapies. In contrast, due to the intimate link between bone and energy homeostasis, pharmaceuticals that treat metabolic disease or have metabolic side effects often have deleterious bone consequences. In this brief review, we will introduce osteoporosis, discuss how bone cells utilize energy to function, evidence for bone regulating whole body energy homeostasis, and some of the unanswered questions and opportunities for further research in the field.

Keywords: Musculoskeletal system, Bone, Energy Balance, Endocrine system

Osteoporosis

Osteoporosis is a major public health condition commonly related to aging. It is a skeletal disorder characterized by reduced bone mineral density (BMD) and microarchitecture deterioration of bone tissue (Kanis et al., 2013). The reduction of BMD is caused by an imbalance between osteoclast mediated bone resorption and osteoblast mediated bone formation (i.e. uncoupled remodeling). Osteoporosis compromises bone strength leading to an increased susceptibility to fractures. In the United States, it is expected that the number of fractures and its costs will increase almost 50% by the year of 2025 (Burge et al., 2007). In addition to occurring with aging and after menopause, osteoporosis can be attributed to many clinical conditions that impact whole-body energy metabolism, such as diabetes mellitus and anorexia nervosa.

Postmenopausal Osteoporosis

Postmenopausal osteoporosis is associated with increased low BMD and changes in body composition. Postmenopausal women are predisposed to fracture, in particular at the hip and wrist regions (Burge et al., 2007). During menopausal transition, women usually experience an accelerated bone loss, mostly due to changes in sex hormone levels. Estrogen deficiency is an important factor that contributes to postmenopausal osteoporosis development. The drop in estrogen levels induces osteoclast recruitment and activation by increasing receptor activator of nuclear factor kappa β ligand (RANKL) production by osteoblastic cells which favors bone resorption activity and consequently a rapid bone loss (Clarke and Khosla, 2010). The onset of postmenopausal osteoporosis is also associated with age-related changes in body composition. Lean mass, which exerts a positive influence on the skeleton, decreases with age and becomes more evident in women over 65 years (Zhang et al., 2013, Chen et al., 2015). On the other hand, there is an increase in body fat with advancing age (Ho et al., 2010, Sornay-Rendu et al., 2012). However, the increase of adipose tissue may have different effects on bone mass (Compston, 2015). Fat mass can have a positive association with BMD in postmenopausal women (Chain et al., 2017, Ho-Pham et al., 2010), suggesting that a slight accumulation of body fat may be advantageous for these women and it would not induce bone loss (Chain et al., 2017). However, low trauma fracture is observed in obese postmenopausal women with normal bone mineral density (BMD) (Premaor et al., 2010, Compston, 2015). Obesity is associated with the production of a specific set of cytokines and adipokines by visceral (VAT) and subcutaneous (SAT) adipose tissue that may have a negative or positive effect on bone mass (Russell et al., 2010). Thus, it needs to be taken into consideration that not only the amount of fat mass, but also VAT/SAT proportion is important to postmenopausal women bone health as it will determine the type of cytokines and adipokines secreted having a diverse impact on bone mass.

Anorexia Nervosa

Anorexia nervosa (AN) is a psychiatric disease characterized by a voluntary food restriction leading to severe weight loss and, consequently, bone loss with increased fracture risk. Bone loss is caused by decrease in mechanical loading as these patients exhibit a loss of lean and fat mass compartments. Concomitantly, marrow adipose tissue (MAT) expands in AN and has a negative association with bone mass. This increase in MAT is an evident feature of anorexia nervosa and it might represent a compensatory mechanism related to the lack of peripheral fat or a shift towards fat lineage instead of bone cell as result of impaired osteoblastogenesis (Bredella et al., 2009). Curiously, MAT content is decreased in women who had begun to recover their nutritional status. Therefore, this may indicate that MAT is more susceptible to nutritional changes than the other fat depots and its reduction can induce a bone mass improvement in these patients (Fazeli et al., 2012).

Diabetes Mellitus

Diabetes mellitus (DM) is a metabolic disease characterized by a hyperglycemic state. Bone loss is one of the classical complications of type 1 DM patients (McCabe, 2007, Starup-Linde et al., 2016, Vestergaard, 2007). Conversely, type 2 DM patients usually have an adequate or increased BMD (Vestergaard, 2007, Starup-Linde et al., 2016, de Araujo et al., 2017). However, fracture risk is increased in both types of diabetes even though there are discrepancies in bone phenotype (Starup-Linde et al., 2016). Nutritional status is one factor that differs between types of diabetes: unlike type 1 DM, type 2 DM patients are overweight or obese with visceral fat accumulation (de Araujo et al., 2017). Higher body weight exerts a greater mechanical loading on the skeleton (Reid, 2010), and it can explain the absence of bone loss in these individuals. On the other hand, adipose tissue produces certain cytokines and adipokines, which have a deleterious effect on bone (Russell et al., 2010) and predispose obese patients to fracture. In type 1 DM animal models, as in caloric restriction models, trabecular bone mass reduction is associated with an increase in MAT (Botolin and McCabe, 2007). However, MAT expansion is not observed in type 1 DM condition in humans (Slade et al., 2012). Likewise, some have reported that increased MAT is not a feature in obese type 2 DM subject (de Araujo et al., 2017). Yet, others have described a greater MAT content in lumbar spine and femoral metaphysis of morbid obese subjects with type 2 DM using insulin therapy or anti-diabetic oral agents (Yu et al., 2017). This highlights that MAT function and its determinants in diabetes condition needs to be better understood. In addition to aging, MAT was related to serum lipid levels in type 1 diabetes subjects (Slade et al., 2012) and hyperglycemia has shown to be a determinant factor of MAT in type 2 diabetes condition (Yu et al., 2017). Moreover, available data in the literature did not observe any association between MAT and insulin resistance (HOMA-IR) (Yu et al., 2017, de Paula et al., 2015, de Araujo et al., 2017). Another important aspect to be considered is the relationship between saturated and unsaturated lipids of the MAT and bone mass. Saturated lipids are higher in type 2 DM subjects with previous fractures (Patsch et al., 2013), suggesting that the lipid profile of MAT might be a predictive marker of bone health (Patsch et al., 2013, Yeung et al., 2005).

Bone Cell Energetics

Due to the impact of metabolic diseases on bone health, it is not surprising that changes in bone cell energy metabolism modify differentiation and function. Osteoblasts, osteocytes and marrow adipocytes all originate from common progenitor mesenchymal stem cells. Osteoclasts, which are bone-resorbing cells, have a monocytic origin (Bianco and Robey, 2004, Xiao et al., 2015). The fuel sources and pathways that are utilized by these cells to generate adenosine 5’-triphosphate (ATP) are currently under intense scrutiny. ATP is the most widely used nucleoside triphosphate to provide chemical energy for biochemical reactions. It is generated in the cytoplasm through glycolysis and in the mitochondria through oxidative phosphorylation. The specialized cells that make up bone need to generate substantial amounts of ATP to maintain a normal healthy skeleton. During development, osteoblasts produce and secrete alpha-1 type 1 collagen and mineralize bone (Rodan, 1992). Osteocytes, which are embedded in mineralized bone, secrete a number of osteokines like sclerostin and function in a highly hypoxic environment as mechanical sensors (Weivoda et al., 2017). Osteoclasts, on the other hand, need to generate H+ to acidify and help resorb bone, hydrolyzing ATP to generate resorption pits. In this section we will review the current understanding of the exogenous fuel sources and bioenergetics pathways that are utilized by cells in the skeleton to meet this ATP need.

Osteoblasts

Recent studies have shown that bone marrow stromal cells utilize oxidative phosphorylation to generate ATP preferably over glycolysis, while concomitantly increasing antioxidant enzymes generated to combat the detrimental effects of reactive oxygen species (ROS) (Chen et al., 2008, Shum et al., 2016). In contrast to some of these data, Wnt3a, a known osteogenic factor specifically induces glycolysis through an mTORC2-dependent pathway (Esen et al., 2013). There is an increase in Glut1, the insulin-independent glucose transporter, along with several glycolytic pathway enzymes, in a number of pre-calvarial osteoblasts and bone marrow stem cell lines at the later stages of osteoblast differentiation. The preferential use of glycolysis to generate ATP is akin to the Warburg effect that has been described in a variety of cancer cells (Diaz-Ruiz et al., 2011). The reasons for this seem to be multifold, namely, need for 1) generating NAD+ when lactate is generated from pyruvate, 2) generating ribose precursors and NADPH through pentose phosphate pathway, and 3) generating ATP at a faster rate. However, which of these are relevant for osteoblasts is currently not clear.

Early studies using ex vivo techniques to measure bone cell energetics in the 1950’s identified that parathyroid hormone (PTH) induces lactate via aerobic glycolysis. More recently, it was shown that this mechanism is through induction of IGF-1 and glycolytic gene upregulation (Neuman et al., 1978, Esen et al., 2015). However, others have shown increases in both oxidative phosphorylation and glycolysis during the late stages of in vitro osteoblast differentiation in calvarial derived osteoblast cells (Guntur et al., 2014).

The substrates that have been used in these studies have used exogenously added glucose, pyruvate and glutamine (Guntur et al., 2014, Komarova et al., 2000). All of these substrates are metabolized and processed through glycolysis and Krebs cycle. Glutamine, used by osteoblasts as an alternate fuel source, is converted to α-ketoglutarate to enter the Krebs cycle through the process of glutaminolysis. Karner et al. have shown that this process is also Wnt signaling mediated and is essential for osteoblast differentiation (Karner et al., 2015). However, the transporters and enzymes involved in this pathway in osteoblasts still need to be identified. Furthermore, more recent studies have also identified that early osteoblast differentiation in BMSCs require intracellular fatty acids as energy sources. Other studies have shown that oxidation of fatty acids by osteoblasts for generating energy is controlled by Wnt-Lrp5 signaling and a loss in this process will result in decreased bone mass along with increases in whole body fat mass (Rendina-Ruedy et al., 2017, Frey et al., 2015).

Osteocytes

Osteocytes make up close to 95% of the cells in the adult skeleton (Bonewald, 2011). There are currently no studies that have identified the bioenergetic pathways in these cells. Osteocytes are embedded in a hypoxic environment. This, combined with the fact that they are terminally differentiated osteoblasts, leads to the hypothesis that they would be highly glycolytic in their energy production. These cells have been shown to generate protons and acidify their microenvironment (Jahn et al., 2017), though there are currently no published studies that have examined energy metabolism in osteocytes.

Osteoclasts

The origin of the osteoclast is the bone marrow macrophage. The fully differentiated osteoclast forms a sealing zone between its ruffled membrane and the area it needs to resorb. It then proceeds to generate an acidic environment within the sealing zone containing cathepsin K (CtsK), and matrix metalloproteases (MMP) to initiate remodeling (Boyle et al., 2003). There are two studies that have identified the bioenergetic pathways in osteoclasts. The first study identified the need for glycolysis for normal osteoclast differentiation; which seems to be an underlying theme for all the different cells in the skeleton (Indo et al., 2013). The authors observed an increase in Glut1 and other glycolytic enzymes with osteoclast differentiation. The same study also identified an increase in glutaminolysis as seen with osteoblast differentiation in response to Wnt signaling. Modulating either pathway leads to a decrease in osteoclast differentiation and function. In a more recent study, Lemma et al., showed that there is increased oxidative phosphorylation with differentiation in osteoclasts with an increase in mitochondrial mass and biogenesis (Lemma et al., 2016). This is followed by a need for glycolysis to properly function during resorption.

The sequence of events described in these studies suggests that the need to shift to glycolysis might be based on the function of these specialized cells. The generation of ATP for pumping protons into the sealing zone may need to occur at a rate that exceeds the ability of the cells to promote mitochondrial biogenesis. Thus, glycolysis in the cytoplasm might be a more readily available source of ATP than if it is generated through oxidative phosphorylation in the mitochondria and transported out through ADP/ATP transporters.

Relevance of studying energy metabolism

Metabolic pathways can control gene expression through epigenetic modifications as most of the substrates and cofactors that are necessary for epigenetic modifications are generated through bioenergetic pathways. For example, nicotinamide dinucleotide, (NAD+ (oxidized form)) is an essential electron acceptor for a number of dehydrogenases to generate NADH. In the mitochondria, NADH functions as the electron donor in the electron transport chain to generate a ΔpH and the mitochondrial membrane potential necessary for ATP generation. NAD+ is also absolutely essential for the enzymatic activity as a cofactor for sirutinin enzyme mediated deacetylations (Imai et al., 2000). The effects of NAD+ on bone metabolism are currently not know though there is a keen interest in using nicotinamide mononucleotide (NAM) or nicotinamide riboside (NR) which are precursors that have been shown to affect the aging process. More importantly, long term treatment of wildtype C57BL/6J mice with NAM showed significantly higher bone mineral density compared to age matched controls, suggesting that there could be a beneficial effect of these compounds on bone mass (Mills et al., 2016).

Acetyl-CoA generated in the Krebs cycle in the mitochondria is also a crucial cofactor and substrate for acetylation reactions. It is used by histone acetyltransferases as an acetyl donor and known to exist in two separate pools: one in the mitochondria and the other in the cytoplasm. Karner et al. have recently shown that reduced nuclear acetyl-CoA leads to suppression of osteoblast gene expression. This could be one potential explanation for the need for the cells to switch to glycolysis with osteoblast differentiation (Mills et al., 2016). Therefore control of metabolic pathways and the flux through which these substrates can be increased or decreased has far reaching consequences not only in controlling ATP generation but also controlling gene expression. These are in turn controlled by substrate availability and cellular ATP demand, setting the tone for which pathway needs to be upregulated or downregulated.

Missing pieces

One of the crucial pieces of data that is lacking from most of these studies is the status of mitochondrial respiration and mitochondrial membrane potential, which at any point of time is a good indicator of cellular energetic pathways. The switch to glycolysis that is observed with osteoblasts and osteoclasts would indicate that there is a defect or insufficiency in mitochondrial metabolism, but whether this is because of some dysfunction that occurs with differentiation or due to specific programming is not clear. Studying ATP generation and mitochondrial dynamics with differentiation and identifying the amount of ATP that is generated from these pathways will be crucial for obtaining a complete bioenergetic picture.

Current studies have focused on identifying the pathways during normal osteoblast differentiation, so there needs to be a push to study the role of these energetic pathways in pathophysiological conditions. More careful study of bioenergetic pathways at the molecular level may identify novel mechanisms of pathological bone loss, and subsequently novel pathways to target for therapies.

Regulation of Energy Metabolism by Peripheral Tissues

Energy balance is defined by the regulation of food intake, nutrient storage, and energy expenditure. These processes are all controlled by central mechanisms; and feedback from peripheral tissues is an essential part of these regulatory networks. Leptin, for example, is secreted from adipocytes that are storing lipids and acts in the hypothalamus to reduce food intake and increase energy expenditure (Roh et al., 2016). On the other hand, during exercise, IL-6 is secreted from skeletal muscle and promotes sympathetic nervous system (SNS) mediated mobilization of fat stores. Intracerebroventricular administration of IL-6 increases energy expenditure, and deletion of IL-6 promotes obesity (Febbraio and Pedersen, 2002, Roh et al., 2016). Alternately, low glucose levels in the blood (lowered by utilization or storage by tissues), stimulate the hypothalamic-pituitary-adrenal axis and the SNS to mobilize glucose and fatty acids (Routh et al., 2014). The latter example, however, is a more passive way in which peripheral tissues modify energy metabolism (i.e. simply by using energy). Bone will certainly use energy, causing a reduction in available fuel and further stimulation to eat or mobilize fuel stores, but active mechanisms through which bone regulates energy metabolism are currently being investigated. Although we have not currently identified ways in which the bone can feedback directly to the brain, there is evidence that bone can regulate insulin secretion and sensitivity, which we will summarize below.

Involvement of Bone in the Regulation of Energy Metabolism

Osteocalcin is the second most abundant protein in bone, after type 1 collagen, and its serum levels have long been used as a marker for bone turnover. However, a role for osteocalcin in regulating insulin sensitivity has been established and is well reviewed (Booth et al., 2013, Motyl et al., 2010, Wei and Karsenty, 2015). These findings were initiated by the observation osteocalcin knockout mice were overweight, with high blood glucose (Lee et al., 2007). However, these mice also had lower insulin levels, suggesting they were not simply prone to the classical obesity-induced insulin resistance, in which insulin levels are generally high (Lee et al., 2007). Instead, the authors did indeed find insulin resistance (marked by impaired insulin tolerance test, and reduced glucose infusion rate in hyperinsulinemic euglycemic clamp studies) in the osteocalcin knockout mice, along with the intriguing finding that osteocalcin protein itself could stimulate insulin secretion from pancreatic beta cells (Lee et al., 2007). More recently, Ferron et al. demonstrated that undercarboxylated osteocalcin (ucOC) release from bone during resorption stimulates insulin production in the pancreas (Ferron et al., 2010). This combined with the known role of insulin in promoting bone remodeling suggests a bone-pancreas feed forward loop regulating bone and insulin secretion. Although studies in humans point to the carboxylated form of OC as having a more prominent role in glucose metabolism, these studies nonetheless suggest that metabolic homeostasis is can be modified by hormones released from bone (Booth et al., 2013).

More recently, non-osteocalcin mediated mechanisms have been proposed for bone in the regulation of energy homeostasis. Ablation of osteoblasts with diphtheria toxin expression under control of the osteocalcin-Cre promoter resulted in hypoinsulinemia, hyperglycemia and impaired insulin sensitivity (Yoshikawa et al., 2011). This finding is similar to the metabolic phenotype of the osteocalcin knockout mice; however, the authors also observed increased energy expenditure and reduced gonadal fat mass, which could not be rescued with osteocalcin administration. This suggests that osteoblasts or osteocytes produce another hormone(s) that contribute to the regulation of energy metabolism. Furthermore, increasing evidence suggests that neuropeptide Y (NPY) expressed from osteoblasts, is one of these essential molecules mediating changes in energy expenditure (reviewed in this issue) (Rodriguez-Carballo et al., 2015, Baldock et al., 2007, Lundberg et al., 2007, Lee et al., 2015). The above examples modulated energy expenditure and glucose homeostasis, but it is becoming evident that bone can have impacts on brown/beige adipose tissue as well. In a recent study by Brun, et al., deletion of PPARγ in osteocytes (utilizing the Dmp1-Cre mouse) resulted in high bone mass, improved glucose tolerance and insulin sensitivity, as well as increased beiging of white adipose tissue (Brun et al., 2017). These mice were also resistant to high fat diet-induced obesity and steatosis, also could not be explained by changes in osteocalcin. The authors postulated that osteokines under the control of PPARγ were responsible for the effects, and although not tested directly, they identified BMP7 as a candidate molecule (Brun et al., 2017).

In addition to bone cells themselves regulating energy metabolism, bone marrow adipocytes within the bone marrow niche have also been demonstrated to be important contributors to glucose control. In particular, marrow adipocytes expand in size and number during metabolic diseases, such as anorexia nervosa and diabetes mellitus. In part, this is thought to be due to altered mesenchymal lineage selection toward the adipogenic lineage at the expense of the osteogenic lineage. However, marrow adipose tissue is the major source of adiponectin in calorie restriction models, suggesting it too has a role in modifying insulin sensitivity (Cawthorn et al., 2014). Furthermore, stimulation of the SNS through cold exposure, or treatment with antipsychotic drugs, promotes marrow fat loss, suggesting fat is lipolyzed for fuel in these cases (Scheller et al., 2015, Motyl et al., 2015). How such acute changes in marrow fat globally modulate energy metabolism, however, is unknown.

Summary and Conclusions

Bone remodeling is a dynamic process that, when uncoupled, leads to osteoporosis. Although osteoporosis occurs with conditions such as aging and menopause, it can also occur secondary to metabolic diseases such as diabetes mellitus, and secondary to treatment with pharmaceuticals that impact metabolism. Bone requires a significant portion of the available fuel of an organism, thus it is not surprising that glucose homeostasis, adipose tissue metabolism and bone remodeling appear to be tightly linked. There is increasing evidence that bone can regulate organismal energy metabolism through pathways other than just osteocalcin-mediated alone. However, we have not yet seen strong evidence that bone regulates central control of energy balance. The importance of studying these pathways is at least two-fold. First, treatments that modulate energy metabolism may have unexpected impacts on bone and visa versa. For example, atypical antipsychotic drugs have known metabolic side effects, and in rodent models these lead to trabecular bone loss. Alternately, osteoporotic therapies may in turn have deleterious metabolic side effects. Second, studying the energetics of bone cells themselves will lead to a better understanding of the etiology of pathologic conditions like diabetes and the mechanism of action of bone therapies like PTH. In conclusion, understanding the energy metabolism of bone may lead to novel treatment regimes and/or therapeutics with improved efficacy and reduced side effects.

Acknowledgments

ALC received financial support from FAPESP (2013/09853-6 and 2014/14505-0). Additional financial support was from the following National Institutes of Health awards: NIAMS award number K01 AR067858 to KJM, NIGMS award number P20 GM121301 to KJM, and NIAMS award number R03 AR068095 to ARG. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

References

  1. Baldock PA, Allison SJ, Lundberg P, Lee NJ, Slack K, Lin EJ, Enriquez RF, McDonald MM, Zhang L, During MJ, Little DG, Eisman JA, Gardiner EM, Yulyaningsih E, Lin S, Sainsbury A, Herzog H. Novel role of Y1 receptors in the coordinated regulation of bone and energy homeostasis. The Journal of biological chemistry. 2007;282:19092–19102. doi: 10.1074/jbc.M700644200. [DOI] [PubMed] [Google Scholar]
  2. Bianco P, Robey PG. Handbook of Stem Cells. Academic Press; Burlington: 2004. 39 - Skeletal Stem Cells; pp. 415–424. [Google Scholar]
  3. Bonewald LF. The amazing osteocyte. Journal of Bone and Mineral Research. 2011;26:229–238. doi: 10.1002/jbmr.320. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Booth SL, Centi A, Smith SR, Gundberg C. The role of osteocalcin in human glucose metabolism: marker or mediator? Nature reviews. Endocrinology. 2013;9:43–55. doi: 10.1038/nrendo.2012.201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Botolin S, McCabe LR. Bone loss and increased bone adiposity in spontaneous and pharmacologically induced diabetic mice. Endocrinology. 2007;148:198–205. doi: 10.1210/en.2006-1006. [DOI] [PubMed] [Google Scholar]
  6. Boyle WJ, Simonet WS, Lacey DL. Osteoclast differentiation and activation. Nature. 2003;423:337–342. doi: 10.1038/nature01658. [DOI] [PubMed] [Google Scholar]
  7. Bredella MA, Fazeli PK, Miller KK, Misra M, Torriani M, Thomas BJ, Ghomi RH, Rosen CJ, Klibanski A. Increased bone marrow fat in anorexia nervosa. The Journal of clinical endocrinology and metabolism. 2009;94:2129–2136. doi: 10.1210/jc.2008-2532. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Brun J, Berthou F, Trajkovski M, Maechler P, Foti M, Bonnet N. Bone Regulates Browning and Energy Metabolism Through Mature Osteoblast/Osteocyte PPARgamma Expression. Diabetes. 2017 doi: 10.2337/db17-0116. [DOI] [PubMed] [Google Scholar]
  9. Burge R, Dawson-Hughes B, Solomon DH, Wong JB, King A, Tosteson A. Incidence and economic burden of osteoporosis-related fractures in the United States, 2005–2025. J Bone Miner Res. 2007;22:465–475. doi: 10.1359/jbmr.061113. [DOI] [PubMed] [Google Scholar]
  10. Cawthorn WP, Scheller EL, Learman BS, Parlee SD, Simon BR, Mori H, Ning X, Bree AJ, Schell B, Broome DT, Soliman SS, DelProposto JL, Lumeng CN, Mitra A, Pandit SV, Gallagher KA, Miller JD, Krishnan V, Hui SK, Bredella MA, Fazeli PK, Klibanski A, Horowitz MC, Rosen CJ, MacDougald OA. Bone marrow adipose tissue is an endocrine organ that contributes to increased circulating adiponectin during caloric restriction. Cell metabolism. 2014;20:368–375. doi: 10.1016/j.cmet.2014.06.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Chain A, Crivelli M, Faerstein E, Bezerra FF. Association between fat mass and bone mineral density among Brazilian women differs by menopausal status: The Pró-Saúde Study. Nutrition. 2017;33:14–19. doi: 10.1016/j.nut.2016.08.001. [DOI] [PubMed] [Google Scholar]
  12. Chen CT, Shih YR, Kuo TK, Lee OK, Wei YH. Coordinated changes of mitochondrial biogenesis and antioxidant enzymes during osteogenic differentiation of human mesenchymal stem cells. Stem cells (Dayton, Ohio) 2008;26:960–968. doi: 10.1634/stemcells.2007-0509. [DOI] [PubMed] [Google Scholar]
  13. Chen Y, Xiang J, Wang Z, Xiao Y, Zhang D, Chen X, Li H, Liu M, Zhang Q. Associations of Bone Mineral Density with Lean Mass, Fat Mass, and Dietary Patterns in Postmenopausal Chinese Women: A 2-Year Prospective Study. PLoS One. 2015;10:e0137097. doi: 10.1371/journal.pone.0137097. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Clarke BL, Khosla S. Physiology of bone loss. Radiol Clin North Am. 2010;48:483–495. doi: 10.1016/j.rcl.2010.02.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Compston J. Obesity and fractures in postmenopausal women. Curr Opin Rheumatol. 2015;27:414–419. doi: 10.1097/BOR.0000000000000182. [DOI] [PubMed] [Google Scholar]
  16. de Araujo IM, Salmon CE, Nahas AK, Nogueira-Barbosa MH, Elias J, Jr, de Paula FJ. Marrow adipose tissue spectrum in obesity and type 2 diabetes mellitus. Eur J Endocrinol. 2017;176:21–30. doi: 10.1530/EJE-16-0448. [DOI] [PubMed] [Google Scholar]
  17. de Paula FJ, de Araújo IM, Carvalho AL, Elias J, Salmon CE, Nogueira-Barbosa MH. The Relationship of Fat Distribution and Insulin Resistance with Lumbar Spine Bone Mass in Women. PLoS One. 2015;10:e0129764. doi: 10.1371/journal.pone.0129764. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Diaz-Ruiz R, Rigoulet M, Devin A. The Warburg and Crabtree effects: On the origin of cancer cell energy metabolism and of yeast glucose repression. Biochimica et biophysica acta. 2011;1807:568–576. doi: 10.1016/j.bbabio.2010.08.010. [DOI] [PubMed] [Google Scholar]
  19. Esen E, Chen J, Karner CM, Okunade AL, Patterson BW, Long F. WNT-LRP5 signaling induces Warburg effect through mTORC2 activation during osteoblast differentiation. Cell metabolism. 2013;17:745–755. doi: 10.1016/j.cmet.2013.03.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Esen E, Lee SY, Wice BM, Long F. PTH Promotes Bone Anabolism by Stimulating Aerobic Glycolysis via IGF Signaling. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research. 2015;30:2137. doi: 10.1002/jbmr.2714. [DOI] [PubMed] [Google Scholar]
  21. Fazeli PK, Bredella MA, Freedman L, Thomas BJ, Breggia A, Meenaghan E, Rosen CJ, Klibanski A. Marrow fat and preadipocyte factor-1 levels decrease with recovery in women with anorexia nervosa. J Bone Miner Res. 2012;27:1864–1871. doi: 10.1002/jbmr.1640. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Febbraio MA, Pedersen BK. Muscle-derived interleukin-6: mechanisms for activation and possible biological roles. FASEB journal : official publication of the Federation of American Societies for Experimental Biology. 2002;16:1335–1347. doi: 10.1096/fj.01-0876rev. [DOI] [PubMed] [Google Scholar]
  23. Ferron M, Wei J, Yoshizawa T, Del Fattore A, DePinho RA, Teti A, Ducy P, Karsenty G. Insulin signaling in osteoblasts integrates bone remodeling and energy metabolism. Cell. 2010;142:296–308. doi: 10.1016/j.cell.2010.06.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Frey JL, Li Z, Ellis JM, Zhang Q, Farber CR, Aja S, Wolfgang MJ, Clemens TL, Riddle RC. Wnt-Lrp5 signaling regulates fatty acid metabolism in the osteoblast. Molecular and cellular biology. 2015;35:1979–1991. doi: 10.1128/MCB.01343-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Guntur AR, Le PT, Farber CR, Rosen CJ. Bioenergetics during calvarial osteoblast differentiation reflect strain differences in bone mass. Endocrinology. 2014;155:1589–1595. doi: 10.1210/en.2013-1974. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Ho SC, Wu S, Chan SG, Sham A. Menopausal transition and changes of body composition: a prospective study in Chinese perimenopausal women. Int J Obes (Lond) 2010;34:1265–1274. doi: 10.1038/ijo.2010.33. [DOI] [PubMed] [Google Scholar]
  27. Ho-Pham LT, Nguyen ND, Lai TQ, Nguyen TV. Contributions of lean mass and fat mass to bone mineral density: a study in postmenopausal women. BMC Musculoskelet Disord. 2010;11:59. doi: 10.1186/1471-2474-11-59. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Imai S, Armstrong CM, Kaeberlein M, Guarente L. Transcriptional silencing and longevity protein Sir2 is an NAD-dependent histone deacetylase. Nature. 2000;403:795–800. doi: 10.1038/35001622. [DOI] [PubMed] [Google Scholar]
  29. Indo Y, Takeshita S, Ishii KA, Hoshii T, Aburatani H, Hirao A, Ikeda K. Metabolic regulation of osteoclast differentiation and function. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research. 2013;28:2392–2399. doi: 10.1002/jbmr.1976. [DOI] [PubMed] [Google Scholar]
  30. Jahn K, Kelkar S, Zhao H, Xie Y, Tiede-Lewis LM, Dusevich V, Dallas SL, Bonewald LF. Osteocytes Acidify Their Microenvironment in Response to PTHrP In Vitro and in Lactating Mice In Vivo. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research. 2017;32:1761–1772. doi: 10.1002/jbmr.3167. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Kanis JA, McCloskey EV, Johansson H, Cooper C, Rizzoli R, Reginster JY (IOF), S.A.B.o.t.E.S.f.C.a.E.A.o.O.a.O.E.a.t.C.o.S.A.o.t.I.O.F. European guidance for the diagnosis and management of osteoporosis in postmenopausal women. Osteoporos Int. 2013;24:23–57. doi: 10.1007/s00198-012-2074-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Karner CM, Esen E, Okunade AL, Patterson BW, Long F. Increased glutamine catabolism mediates bone anabolism in response to WNT signaling. The Journal of clinical investigation. 2015;125:551–562. doi: 10.1172/JCI78470. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Komarova SV, Ataullakhanov FI, Globus RK. Bioenergetics and mitochondrial transmembrane potential during differentiation of cultured osteoblasts. American journal of physiology. Cell physiology. 2000;279:C1220–1229. doi: 10.1152/ajpcell.2000.279.4.C1220. [DOI] [PubMed] [Google Scholar]
  34. Lee NJ, Nguyen AD, Enriquez RF, Luzuriaga J, Bensellam M, Laybutt R, Baldock PA, Herzog H. NPY signalling in early osteoblasts controls glucose homeostasis. Molecular metabolism. 2015;4:164–174. doi: 10.1016/j.molmet.2014.12.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Lee NK, Sowa H, Hinoi E, Ferron M, Ahn JD, Confavreux C, Dacquin R, Mee PJ, McKee MD, Jung DY, Zhang Z, Kim JK, Mauvais-Jarvis F, Ducy P, Karsenty G. Endocrine regulation of energy metabolism by the skeleton. Cell. 2007;130:456–469. doi: 10.1016/j.cell.2007.05.047. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Lemma S, Sboarina M, Porporato PE, Zini N, Sonveaux P, Di Pompo G, Baldini N, Avnet S. Energy metabolism in osteoclast formation and activity. The international journal of biochemistry & cell biology. 2016;79:168–180. doi: 10.1016/j.biocel.2016.08.034. [DOI] [PubMed] [Google Scholar]
  37. Lundberg P, Allison SJ, Lee NJ, Baldock PA, Brouard N, Rost S, Enriquez RF, Sainsbury A, Lamghari M, Simmons P, Eisman JA, Gardiner EM, Herzog H. Greater bone formation of Y2 knockout mice is associated with increased osteoprogenitor numbers and altered Y1 receptor expression. The Journal of biological chemistry. 2007;282:19082–19091. doi: 10.1074/jbc.M609629200. [DOI] [PubMed] [Google Scholar]
  38. McCabe LR. Understanding the pathology and mechanisms of type I diabetic bone loss. Journal of cellular biochemistry. 2007;102:1343–1357. doi: 10.1002/jcb.21573. [DOI] [PubMed] [Google Scholar]
  39. Mills KF, Yoshida S, Stein LR, Grozio A, Kubota S, Sasaki Y, Redpath P, Migaud ME, Apte RS, Uchida K, Yoshino J, Imai SI. Long-Term Administration of Nicotinamide Mononucleotide Mitigates Age-Associated Physiological Decline in Mice. Cell metabolism. 2016;24:795–806. doi: 10.1016/j.cmet.2016.09.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Motyl KJ, DeMambro VE, Barlow D, Olshan D, Nagano K, Baron R, Rosen CJ, Houseknecht KL. Propranolol attenuates risperidone-induced trabecular bone loss in female mice. Endocrinology. 2015:en20151099. doi: 10.1210/en.2015-1099. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Motyl KJ, McCabe LR, Schwartz AV. Bone and glucose metabolism: a two-way street. Arch Biochem Biophys. 2010;503:2–10. doi: 10.1016/j.abb.2010.07.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Neuman WF, Neuman MW, Brommage R. Aerobic glycolysis in bone: lactate production and gradients in calvaria. The American journal of physiology. 1978;234:C41–50. doi: 10.1152/ajpcell.1978.234.1.C41. [DOI] [PubMed] [Google Scholar]
  43. Patsch JM, Li X, Baum T, Yap SP, Karampinos DC, Schwartz AV, Link TM. Bone marrow fat composition as a novel imaging biomarker in postmenopausal women with prevalent fragility fractures. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research. 2013;28:1721–1728. doi: 10.1002/jbmr.1950. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Premaor MO, Pilbrow L, Tonkin C, Parker RA, Compston J. Obesity and fractures in postmenopausal women. J Bone Miner Res. 2010;25:292–297. doi: 10.1359/jbmr.091004. [DOI] [PubMed] [Google Scholar]
  45. Reid IR. Fat and bone. Arch Biochem Biophys. 2010;503:20–27. doi: 10.1016/j.abb.2010.06.027. [DOI] [PubMed] [Google Scholar]
  46. Rendina-Ruedy E, Guntur AR, Rosen CJ. Intracellular lipid droplets support osteoblast function. Adipocyte. 2017:1–9. doi: 10.1080/21623945.2017.1356505. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Rodan GA. Introduction to bone biology. Bone. 1992;(13 Suppl 1):S3–6. doi: 10.1016/s8756-3282(09)80003-3. [DOI] [PubMed] [Google Scholar]
  48. Rodriguez-Carballo E, Gamez B, Mendez-Lucas A, Sanchez-Freutrie M, Zorzano A, Bartrons R, Alcantara S, Perales JC, Ventura F. p38alpha function in osteoblasts influences adipose tissue homeostasis. FASEB journal : official publication of the Federation of American Societies for Experimental Biology. 2015;29:1414–1425. doi: 10.1096/fj.14-261891. [DOI] [PubMed] [Google Scholar]
  49. Roh E, Song DK, Kim MS. Emerging role of the brain in the homeostatic regulation of energy and glucose metabolism. Experimental & molecular medicine. 2016;48:e216. doi: 10.1038/emm.2016.4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Routh VH, Hao L, Santiago AM, Sheng Z, Zhou C. Hypothalamic glucose sensing: making ends meet. Frontiers in systems neuroscience. 2014;8:236. doi: 10.3389/fnsys.2014.00236. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Russell M, Mendes N, Miller KK, Rosen CJ, Lee H, Klibanski A, Misra M. Visceral fat is a negative predictor of bone density measures in obese adolescent girls. J Clin Endocrinol Metab. 2010;95:1247–1255. doi: 10.1210/jc.2009-1475. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Scheller EL, Doucette CR, Learman BS, Cawthorn WP, Khandaker S, Schell B, Wu B, Ding SY, Bredella MA, Fazeli PK, Khoury B, Jepsen KJ, Pilch PF, Klibanski A, Rosen CJ, MacDougald OA. Region-specific variation in the properties of skeletal adipocytes reveals regulated and constitutive marrow adipose tissues. Nature communications. 2015;6:7808. doi: 10.1038/ncomms8808. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Shum LC, White NS, Mills BN, Bentley KL, Eliseev RA. Energy Metabolism in Mesenchymal Stem Cells During Osteogenic Differentiation. Stem cells and development. 2016;25:114–122. doi: 10.1089/scd.2015.0193. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Slade JM, Coe LM, Meyer RA, McCabe LR. Human bone marrow adiposity is linked with serum lipid levels not T1-diabetes. J Diabetes Complications. 2012;26:1–9. doi: 10.1016/j.jdiacomp.2011.11.001. [DOI] [PubMed] [Google Scholar]
  55. Sornay-Rendu E, Karras-Guillibert C, Munoz F, Claustrat B, Chapurlat RD. Age determines longitudinal changes in body composition better than menopausal and bone status: the OFELY study. J Bone Miner Res. 2012;27:628–636. doi: 10.1002/jbmr.1469. [DOI] [PubMed] [Google Scholar]
  56. Starup-Linde J, Lykkeboe S, Gregersen S, Hauge EM, Langdahl BL, Handberg A, Vestergaard P. Bone structure and predictors of fracture in type 1 and type 2 diabetes. J Clin Endocrinol Metab. 2016:jc20153882. doi: 10.1210/jc.2015-3882. [DOI] [PubMed] [Google Scholar]
  57. Vestergaard P. Discrepancies in bone mineral density and fracture risk in patients with type 1 and type 2 diabetes--a meta-analysis. Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2007;18:427–444. doi: 10.1007/s00198-006-0253-4. [DOI] [PubMed] [Google Scholar]
  58. Wei J, Karsenty G. An overview of the metabolic functions of osteocalcin. Current osteoporosis reports. 2015;13:180–185. doi: 10.1007/s11914-015-0267-y. [DOI] [PubMed] [Google Scholar]
  59. Weivoda MM, Youssef SJ, Oursler MJ. Sclerostin expression and functions beyond the osteocyte. Bone. 2017;96:45–50. doi: 10.1016/j.bone.2016.11.024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Xiao Y, Zijl S, Wang L, de Groot Daniel C, van Tol Maarten J, Lankester Arjan C, Borst J. Identification of the Common Origins of Osteoclasts, Macrophages, and Dendritic Cells in Human Hematopoiesis. Stem Cell Reports. 2015;4:984–994. doi: 10.1016/j.stemcr.2015.04.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Yeung DK, Griffith JF, Antonio GE, Lee FK, Woo J, Leung PC. Osteoporosis is associated with increased marrow fat content and decreased marrow fat unsaturation: a proton MR spectroscopy study. Journal of magnetic resonance imaging : JMRI. 2005;22:279–285. doi: 10.1002/jmri.20367. [DOI] [PubMed] [Google Scholar]
  62. Yoshikawa Y, Kode A, Xu L, Mosialou I, Silva BC, Ferron M, Clemens TL, Economides AN, Kousteni S. Genetic evidence points to an osteocalcin-independent influence of osteoblasts on energy metabolism. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research. 2011;26:2012–2025. doi: 10.1002/jbmr.417. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Yu EW, Greenblatt L, Eajazi A, Torriani M, Bredella MA. Marrow adipose tissue composition in adults with morbid obesity. Bone. 2017;97:38–42. doi: 10.1016/j.bone.2016.12.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Zhang H, Chai X, Li S, Zhang Z, Yuan L, Xie H, Zhou H, Wu X, Sheng Z, Liao E. Age-related changes in body composition and their relationship with bone mineral density decreasing rates in central south Chinese postmenopausal women. Endocrine. 2013;43:643–650. doi: 10.1007/s12020-012-9833-6. [DOI] [PubMed] [Google Scholar]

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