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Published in final edited form as: Biogerontology. 2022 Sep 2;23(5):629–640. doi: 10.1007/s10522-022-09986-7

Alterations in Bone Metabolites with Age in C57BL/6 mice Model

Dhara Patel 1, Tae Jin Lee 2, Sandeep Kumar 3, Sagar Vyavahare 3, Alison Worth 4, William D Hill 5, Mark Hamrick 3,6, Carlos M Isales 1,6, Rahul S Shinde 4, Sadanand Fulzele 1,3,6,*
PMCID: PMC10918568  NIHMSID: NIHMS1940627  PMID: 36056226

Abstract

Understanding the pathophysiology behind age-related diseases is an urgent need as the elderly population continues to grow. With age, there is a high risk of musculoskeletal deterioration and associated morbidity and mortality. Although the exact mechanism behind age-related degeneration is unknown, it is well established that alteration in cellular metabolism is one of the important contributing factors. Alteration in signaling pathways with age leads to the accumulation or depletion of several metabolites that play a vital role in musculoskeletal pathophysiology. This study aimed to identify age-related changes in bone tissue metabolites in C57BL/6 mice. We then correlated the differentially expressed metabolites with their functions in bone biology. In both aged males and females, hydroxyproline, glutamine, and alpha-linolenic acid levels were decreased. In aged females, Ornithine (pvalue=0.001), L-Proline (pvalue=0.008), Uridine (pvalue=0.001), Aspartic Acid (pvalue=0.004) levels were significantly decreased, and glutamate (pvalue=0.002) was elevated. In aged males, N-acetyl-D-glucosamine (pvalue=0.010), Adrenic acid (pvalue=0.0099), Arachidonic acid (pvalue=0.029) and Allantoin (pvalue=0.004) levels were decreased. Metabolic pathway analysis revealed that purine and D-glutamine and D-glutamate metabolism were significantly altered in both sexes, while arginine biosynthesis in females and lipid metabolism in males were highly affected. These differences in metabolic signaling might be one of the reasons for the discrepancy in musculoskeletal disease manifestation between the two sexes. Understanding the role of these metabolites play in the aging bone will allow for new sex-specific targeted therapies against the progression of musculoskeletal diseases.

Introduction

As the elderly population in the United States continues to grow, it is becoming more imperative to understand the pathophysiology behind age-related diseases. By the year 2030, one in every five Americans will be over the age of 65, and projections estimate this number will increase to 95 million by the year 2060 (Vespa, Armstrong, & Medina, 2018). The growth of the elderly population is expected to burden the healthcare system significantly. Medicare expenditures will nearly triple in less than ten years as the aging cohort continues to increase life expectancy (Thorpe & Howard, 2006).

Age-related musculoskeletal complications, such as osteoporosis are costly to treat and elevate the risk of severe acute events, like fractures, which can potentially be debilitating and even fatal (Burge et al., 2007; Center, Nguyen, Schneider, Sambrook, & Eisman, 1999; Chrischilles, Butler, Davis, & Wallace, 1991). Along with the financial burden of osteoporotic fractures, fragility fractures also lead to disability, psychological decline, and mortality (Bliuc et al., 2009; Braithwaite, Col, & Wong, 2003; Dolan et al., 2000; Lenze et al., 2007). There has been significant attention focused on post-menopausal women and bone loss. Most hip fractures occur in women, who have a lifetime risk of 11.4% of having a femur/hip fracture and about 53.2% risk of a fracture at any other site (De Laet, van Hout, Burger, Hofman, & Pols, 1997; van Staa, Dennison, Leufkens, & Cooper, 2001). Men have lower risk with an estimated 20.7% lifetime risk of developing a fracture and a 3.1% hip/femur fracture (van Staa et al., 2001). Although there are differences between the sexes, hip fractures are particularly devastating to both, increasing all-cause mortality and 1-year mortality by up to 25% (Braithwaite et al., 2003; Katsoulis et al., 2017). Given the multifactorial nature of osteoporosis and the increasing prevalence in both men and women, it is becoming imperative to elucidate its root cause of pathophysiology.

Although age-related bone deterioration affects a significant percentage of the population, its mechanism is still unknown. It is well established that altered metabolism is associated with the aging process. Several studies suggested age-related dysfunction of the signaling pathways, leading to the decrease or accumulation of specific metabolites. For example, our previous studies have demonstrated the accumulation of tryptophan metabolites (kynurenine) with age is responsible for bone loss (Patel et al., 2021; Refaey et al., 2017) . Tintut et al. (2003) reported that hyperlipidemia might contribute to osteoporosis via increased osteoclastic bone resorption (Tintut, Morony, & Demer, 2004). Several studies suggested long-chain polyunsaturated fatty acids and their metabolites play critical roles in bone homeostasis (Kesavalu et al., 2006; Kruger, Coetzer, de Winter, Gericke, & van Papendorp, 1998; Maurin, Chavassieux, & Meunier, 2005; Poulsen, Moughan, & Kruger, 2007). In this study, we identified bone-related metabolites that modulated with age and investigated male and female differences. We hypothesize that sex-specific alterations in bone metabolites will occur with age. Identifying differentially altered metabolites with age and understanding their roles in bone biology will potentially offer new targets for therapies for musculoskeletal diseases like osteoporosis.

Material Method:

Animals:

C57BL/6 mice were obtained from the NIH. All methods were carried out in accordance with the approved guidelines of Augusta University. Four-month-old and twenty-month-old C57BL/6 male (n=4-5/group) and female (n=5/group) mice were used in the experiments.

Preparation of bone extracts for metabolomics:

Young and aged mice were sacrificed. The soft tissue was carefully removed from the hind limb, and long bones (femur and tibia) were isolated under sterile conditions. The bone marrow was flushed, and bone segments were cut into small pieces (chips). The cellular components on the bone surface were removed by incubating bone chips with 0.25% trypsin at 37 °C for 10 min, followed by digestion with 0.1% type I collagenase at 37 °C for 20 min to remove the remaining cells attached to bone chips. After digestion, bone segments were washed with PBS two times and centrifuged at 1000 rpm for 10 min, and then crushed to powder by grinding with liquid nitrogen. Polar metabolites were extracted from ~15mg of the bone powder with ice-cold 80% methanol. Samples were homogenized on dry ice for 1-2 minutes using a Presells 24 tissue grinder (Bertin Technologies, Ampere Montigny-le-Bretonneux, France) and placed at −80°C overnight. Samples were centrifuged at maximum speed (>13,000 rpm) for 15 minutes at 4°C, and supernatants were stored at −80°C.

Metabolomics profiling:

Metabolomics assessment was conducted at Proteomics and Metabolomics facility at The Wistar Institute (https://wistar.org/research-discoveries/shared-resources/proteomics-metabolomics-facility). Non-targeted polar metabolite profiling was performed on bone extracts as described previously (Giron et al., 2021). Briefly, polar metabolites were extracted from bone crushed samples with 250μl ice-cold 80% methanol, and deproteinated supernatants were stored at −80 °C prior to analysis. A quality control (QC) sample was generated by pooling equal volumes of all samples after extraction (Giron et al., 2021). LC-MS analysis was performed on a Thermo Scientific Q-Exactive HF-X mass spectrometer with HESI II probe and Vanquish Horizon UHPLC system. An equivalent fraction of each extract was injected in a pseudorandomized order, and a sample pool was run periodically throughout the sequence. Data analysis was performed using Compound Discoverer 3.1 (ThermoFisher Scientific). Metabolites were quantified relatively based on integrated MS peak area, and these quantifications were corrected for instrument drift based on the sample pool runs. Metabolites were identified either by accurate mass and retention time using a database generated from pure standards or by accurate mass and MS2 fragmentation spectra using the mzCloud spectral database (https://www.mzCloud.org) with identifications having identity search match factors of 50 or greater. Results were manually processed to remove entries with apparent peak mis-integrations and correct commonly misannotated metabolites. Positive and negative data sets of identified compounds were merged, and the preferred polarity was selected for compounds identified in both polarities. When a compound was identified at multiple retention times, a single entry was selected with priority given to standards database matches, followed by higher confidence mzCloud match factors and larger peak areas. Compound quantifications were normalized per amount tissue injected on column, which was equivalent for all samples. These values were further normalized to the summed area of identified metabolites in each sample.

Bioinformatics and Statistical analysis:

Differential expression analysis was performed using the LIMMA R package (3.50.0). The P values were adjusted using Benjamini and Hochberg’s approach. Metabolites with a P value less than 0.05 were differentially expressed. The enrichment analysis was performed by MetaboAnalyst 5.0 (Pang et al., 2021).

Results

Aging alters bone metabolite expression.

In this study, we performed metabolomics analysis on bone tissue. The principal component analysis (PCA) plot suggests a clear separation of differentially expressed metabolites in both male and female young versus old mice (Figure.1). Furthermore, the combined (young vs. old) PCA plot suggests a clear separation of differentially expressed metabolites with age (Figure.1). The heat map clustering also showed a clear separation between the aged bone in both sexes (Figure.1b). In both male and female mice, 13 metabolites were common that altered with age. Of significance, 4-Hydroxyproline, Oleamide, Guanosine, Guanine, L-Threonine, Hypoxanthine, Phenyl-lactic acid, Pseudouridine, L-Glutamine, Acrylic acid, Alpha-Linolenic acid, and L-Lactic acid were downregulated, and L-iditol was significantly elevated in both sexes in aged bone (Figure.1b).

Figure. 1;

Figure. 1;

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Differential expression of bone metabolites in aged male and female mice. Principle component analysis (PCA) (a) combined male and female young vs old mice, b) female young vs old mice and c) male young vs old mice. Young group (indicated by red color) was clustered distinctly from old group (indicated by blue). The heat-map showing the differential expression pattern of metabolites in d) female and e) male young vs old group; Deference between young and old bone metabolites were examined using Student’s t-test, and only those that were significantly different at the p value 0.05 level were selected (n = 4-5 each group).

Changes in Metabolomics between Sexes.

Sex-related alterations in metabolites with age were also identified. In females, 39 metabolites were differentially expressed, whereas 21 metabolites in males aged bones. Specifically, amino acids glutamate (pvalue=0.002), cysteine (pvalue=0.009), serine (pvalue=0.008), and aspartate (pvalue=0.004) were significantly elevated in aged female mice along with malic acid (pvalue=0.006), and cis-Aconitic acid (pvalue=0.006) (Figure.2). Amino acids arginine (pvalue=0.014), lysine (pvalue=0.018), and proline (pvalue=0.0083) were downregulated along with creatine (pvalue=0.006), adenosine (pvalue=0.016), myo-inositol (pvalue=0.023), and deoxyinosine (pvalue=0.004) in aged females (Figure.3). In aged males, N-acetyl-D-glucosamine (pvalue=0.023), allantoin (pvalue=0.0001), and adrenic acid (pvalue=0.007) were downregulated (Figure.4).

Figure 2.

Figure 2.

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Common bone metabolites altered with age in male and female mice. (a) Hydroxyproline, (b) glutamine, (c) alpha-linolenic acid, (d) L-Iditol and (e) Oleamide. Differences between young and old mice bone were examined using Student’s t-test (female young, n = 5, female Old, n = 5), male young, n = 4, male Old, n = 5), * p = 0.04, # p = 0.01.

Figure 3.

Figure 3.

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Alteration in the bone metabolites with age in female mice. (a) Glutamate, (b) Cystine, (c) Serine, (d) Aspartic Acid, (e) cis-Aconitic, (f) Adenosine, (g) Creatine, (h) Malic Acid, (i) L-Lysine, (j) L-Arginine, (k) Ornithine, and (i) L-Proline. Differences between young and old mice bone were examined using Student’s t-test (female young, n = 5, female Old, n = 5), male young, n = 4, male Old, n = 5), * p = 0.04, # p = 0.01.

Figure 4.

Figure 4.

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Alteration in the bone metabolites with age in male mice. (a) N-acetyl-D-glucosamine, (b) Allantoin, (c) Adrenic Acid, (d) Arachidonic acid. Differences between young and old mice bone were examined using Student’s t-test (female young, n = 5, female Old, n = 5), male young, n = 4, male Old, n = 5), * p = 0.04, # p = 0.01.

Bioinformatic analysis revealed that several metabolic pathways were altered between the sexes at different degrees (Figure.5). In females, purine, aminoacyl-tRNA biosynthesis, arginine, and proline metabolism were the four most differentially regulated. In males, along with purine and pyruvate, D-glutamine and D-glutamate, and biosynthesis of unsaturated fatty acids was altered.

Figure 5.

Figure 5.

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Metabolomics Signaling pathways alter with age in bones of a) female and b) males

Discussion

Postmenopausal women have a higher risk of bone loss than men; however, the mechanism behind this disparity is not fully understood. This study analyzed the differences in metabolite levels with age in males and females. We hypothesized that there would be distinct differences in the metabolomics profiling between females and males and aged versus young mice. Overall, similar trends (upregulation and downregulation) were noted between aged male and female mice; however, the degree to which the metabolite was expressed varied between sexes. We also noted that the female-aged bones had more metabolites altered (up and down) than males.

Our data showed that 4-hydroxyproline was significantly decreased in aged bone in both sexes. Hydroxyproline is a major component of collagen that stabilizes the helical structure and is often measured as an indicator of collagen content (Ignat’eva et al., 2007). Decreased hydroxyproline levels may contribute to compromised structural integrity found in aged bone. Low hydroxyproline contributes to decreased bone density and strength through type I collagen degradation found in osteoporosis (Kuo & Chen, 2017). Hydroxyproline supplementation enhances bone density, fracture healing, and wound healing in mice (Tsuruoka, Yamato, Sakai, Yoshitake, & Yonekura, 2007; Wu, Fujioka, Sugimoto, Mu, & Ishimi, 2004; Zhang, Wang, Ding, Dai, & Li, 2011). Thus, the decrease in hydroxyproline we found supports previous studies that it may contribute to the phenotypic bone loss associated with age through oxidative damage or impaired collagen synthesis.

Another metabolite affected with age is L-glutamine. Our data showed that this amino acid had significantly reduced levels in aged bone in both males and females. Glutamine enhances fracture healing (Polat, Kilicoglu, & Erdemli, 2007) and is necessary for osteoblast differentiation and bone mineralization (Brown, Hutchison, & Crockett, 2011; Polat, Kilicoglu, & Erdemli, 2007). A recent study showed that bone marrow stromal cells increase glutamine metabolism during osteoblast differentiation and impaired metabolism leads to decrease bone mass and increased marrow fat (Yu et al., 2019). In vitro studies demonstrated that glutamine directly stimulates collagen transcription in human fibroblasts (Bellon, Chaqour, Wegrowski, Monboisse, & Borel, 1995). Glutamine is an important amino acid that plays a vital role in stem cell differentiation and bone formation, and reduced levels with age might be one of the factors for bone degeneration.

The metabolite alpha-linolenic acid (ALA) was also found to be decreased in both males and females in aged bone. ALA is abundantly found in flaxseeds and is converted into ω-3 derivatives (Kim & Ilich, 2011). Some studies have found that flaxseed supplementation improved bone health in postmenopausal women on estrogen therapy (Sacco et al., 2009a; Sacco et al., 2009b). Furthermore, higher levels of ALA compared to linoleic acid (LA) correlated with higher hip bone mineral density in older adults, both men and women (Weiss, Barrett-Connor, & von Mühlen, 2005). Using ALA-rich oils has been shown to significantly increase femoral strength, bone mineral density, and lower urinary bone resorption markers (Nielsen, 2004; Sun et al., 2004). Overall, ALA has been shown to benefit bone health, especially for individuals with osteoporosis, although the exact mechanism is unclear.

We also analyzed differentially expressed metabolites between males and females with age. Several metabolites were significantly up-regulated in female bones but not in aged males, such as glutamate, cysteine, and serine. L-serine is essential for osteoclastogenesis (Ogawa et al., 2006), and high serine profiles were found in osteolytic bone metastasis (Pollari et al., 2011). Cystine accumulation within cells disturbs normal cell bioactivity and eventually leads to apoptotic cell death (Park, Pejovic, Kerisit, Junius, & Thoene, 2006). In nephropathic cystinosis, a lysosomal storage disease in which cystine accumulates intracellularly, clinical manifestations include bone defects and conditions like rickets, osteomalacia, and growth retardation (Antoniazzi et al., 1997; Haffner et al., 1999; Klusmann, van’t Hoff, Monsell, & Offiah, 2014). Mesenchymal stem cells from a nephropathic cystinosis patient displayed lower proliferation and osteogenic differentiation. These abnormalities were ameliorated by cystine depletion (Conforti et al., 2015), suggesting the pathological effect of cystine accumulation on bone health. L-glutamate is released by osteoclasts along with bone degradation products (Morimoto et al., 2006). In rheumatoid arthritis, a disease characterized by systemic inflammation and bone and cartilage degradation, glutamate levels were significantly increased in synovial fluid (McNearney, Speegle, Lawand, Lisse, & Westlund, 2000). There is a direct relationship between the amino acids (glutamate, cysteine, and serine), as serine and glycine can be derived from glutamine (Bonifácio, Pereira, Serpa, & Vicente, 2021). Previously, Auro and group (2014) demonstrated significantly higher concentrations of amino acids glutamine in postmenopausal women (Auro et al., 2014). Elevated glutamate levels, along with serine and cysteine, could provide insight into the discrepancy between female and male osteoporotic conditions as these amino acids have detrimental effects on bone health.

On the other hand, amino acids like arginine, ornithine, proline, and lysine levels decreased significantly in the aged female mice. Arginine is involved in the synthesis of proline and polyamine, substrates for collagen synthesis (Chevalley, Rizzoli, Manen, Caverzasio, & Bonjour, 1998). A study previously found that arginine stimulates the production of bone matrix synthesis in human osteoblasts (Torricelli et al., 2002). L-arginine is an amino acid that is vital in repairing tissue, muscle, and bone. It has been previously shown to stimulate growth hormone and insulin-like growth factor-1 release, mediate bone remodeling and osteoblastic bone formation, as well as induce nitric oxide release, which inhibits osteoclast activity (Baecker, Boese, Schoenau, Gerzer, & Heer, 2005; Clementi et al., 2001). We previously reported that the expression of the Arginase 1 enzyme is up-regulated in bone and bone marrow stromal cells in the diabetic condition/oxidative stress (Bhatta et al., 2016) and with age in muscle (Pandya et al., 2019). Arginase is an enzyme that metabolizes L-arginine to form urea and L-ornithine in the urea cycle (M. Li, Qin, Xiong, Jiang, & Zhang, 2021). Elevated levels of Arginase I expression with age might be one of the factors for decreased arginine levels in bones. Arginine supplementation in ovariectomized rats enhanced bone mineral density (Hanaa, Ahmed, & Hamza, 2009), suggesting its role in preventing bone loss. Thus, downregulation of arginine biosynthesis may contribute to osteopenia in elderly females.

It is well established that proline is a critical component of cartilage and contributes to the integrity and structure of collagen (Smith & Phang, 1978). Lower levels of proline, observed in our study in females, could impair collagen production and compromise bone integrity with age. L-lysine plays an important role in promoting calcium absorption and renal conservation, thus maintaining bone health (Civitelli et al., 1992). Furthermore, lysine is involved in the cross-linking process of collagen, adding to bone strength (Oxlund, Barckman, Ørtoft, & Andreassen, 1995). Along with L-arginine, L-lysine enhances the activity and proliferation of osteoblasts and promotes collagen production (Fini et al., 2001; Torricelli et al., 2002). Thus, deficiencies in these amino acids may lead to adverse effects on bone homeostasis and increase women’s risk of developing osteoporosis and other musculoskeletal diseases.

The metabolite adenosine was also downregulated in aged female bone. Adenosine promotes osteogenic differentiation of human mesenchymal stem cells by binding to A2b adenosine receptors (Carroll et al., 2012; Costa et al., 2011; Shih et al., 2014). Activation of this receptor stimulates bone mineralization, Runx2 expression, and alkaline phosphatase activity (Gharibi, Abraham, Ham, & Evans, 2011). Lower extracellular adenosine levels in bone marrow have been associated with post-menopausal osteoporotic bone loss (Shih et al., 2019). Our study also supports this hypothesis as we found adenosine levels decreased in females with aging. Moreover, creatine levels were also reduced in aged female bone. Creatine supplementation increases muscle mass and correlates with increased bone mineral density in those who resistance train (Chilibeck, Chrusch, Chad, Shawn Davison, & Burke, 2005). The increase in muscle mass puts a strain on bone and increases bone formation (Chilibeck, Sale, & Webber, 1995). When supplemented to cell cultures, creatine enhances osteoblast activity and osteogenic differentiation (Gerber, ap Gwynn, Alini, & Wallimann, 2005). In postmenopausal women, long-term creatine supplementation and resistance training preserved femoral bone mineral density (Chilibeck, Candow, Landeryou, Kaviani, & Paus-Jenssen, 2015). Therefore, it is possible that reduced creatine levels, as our data showed, could contribute to osteoporotic conditions in aging females by lowering osteogenic activity and bone mineral density. Of note, in old male bone, N-acetyl-D-glucosamine (NAG) was downregulated; however, the same result was not observed in females. NAG has been reported to enhance chondroblast proliferation and promote the healing of cartilaginous injuries (Tamai et al., 2003).

Bioinformatics analysis revealed several metabolic pathways altered with age Figure. 5). In both males and females, the metabolites guanosine, guanine, and hypoxanthine were downregulated with age. These metabolites are involved in purine metabolism, an essential substrate for DNA and RNA, and promoting cell survival and proliferation. The final common product of purine metabolism is uric acid, which has previously been shown to have a positive correlation with bone mineral density in post-menopausal women and older men (Ahn et al., 2013; Bonaccorsi et al., 2019; Nabipour et al., 2011). Our study confirms the relationship between low purine metabolism and aged bone, suggesting that decreased purine metabolism plays a role in the pathogenesis of osteoporosis in both male and female mice. Our study also showed arginine biosynthesis, histidine metabolism, and aminoacyl-tRNA biosynthesis were affected in female aged bones. Previous studies reported purine metabolism, arginine biosynthesis, histidine metabolism (Wei et al., 2022), and aminoacyl-tRNA biosynthesis (X. Li et al., 2022) metabolic pathways dysregulated in postmenopausal Sarco-Osteoporosis (ovariectomized) mice model. In aged males, we found biosynthesis of unsaturated fatty acids metabolic pathway were altered. Our data showed that arachidonic acid, adrenic acid, 8,11,14-Eicosatrienoic acid, and crotonic acid were significantly downregulated in aged males. A previous study has shown that men who took a high arachidonic acid supplementation were at a lower risk of hip fracture than those with low arachidonic acid intake (Farina et al., 2011). Our study elucidates the role of essential metabolites in bone health and musculoskeletal diseases and offers new targets for future therapies.

Our study has some limitations; first and most importantly, a small sample size was used. Additional studies are needed to validate these findings with a larger sample size. Another limitation is that this study used a mouse model, which may have limited translation to human therapeutics. Further functional studies are needed to investigate the loss and gain of function of differentially expressed metabolites with age and subsequent effects on bone health. Overall, our study showed that certain metabolites were differentially regulated in bone with age. We also discovered notable differences between male and female bone metabolites, which may help to explain why older females are at a higher risk for musculoskeletal deterioration.

Funding:

This publication is based upon work supported in part by the National Institutes of Health NIA00059 (SF), 1R21CA259240-01 (R.S.S.) and AG036675 (National Institute on Aging-AG036675 S.F, W.D.H, M.H, C.I,). The above-mentioned funding did not lead to any conflict of interests regarding the publication of this manuscript.

Footnotes

Conflict of interest: The authors also declare that there is no other conflict of interest regarding the publication of this manuscript.

Data Availability statement:

The data that support the findings of this study will be available from the corresponding author upon reasonable request.

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Associated Data

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Data Availability Statement

The data that support the findings of this study will be available from the corresponding author upon reasonable request.

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