Introduction
Adult skeleton constantly undergoes bone remodeling to replace old/damaged bones by new bones, which is required for the maintenance of bone shape and strength of adult skeleton. However, bone mass decreases and bone fragility increases with age in both men and women. Although an increase in bone resorption rate associated with menopause is the primary cause of low bone mass in postmenopausal women, a decline in bone formation rate may also contribute to the loss of bone mass in both postmenopausal and age-related osteoporosis.
In bone marrow, mesenchymal stem cell (bmMSC) is a small population of multipotent cells that are capable of self-renewal proliferation and differentiating into several cell lineages such as osteoblast, chondrocyte, and adipocyte [1]. Thus, bmMSC play a critical role in bone formation that occurs in the skeletal development and growth, in the maintenance of fully grown skeleton, and in fracture repair [2]. It is reasonable to assume that the osteogenic potential of bmMSC may decrease with age. Indeed, animal studies have shown that bmMSCs from aged rats are less responsive to growth factors than cells from adult rats, and that bmMSCs from old bone are defective in bone induction potential [3-6]. However, the effect of aging on human bmMSC is not clear, and the pathological role of bmMSC in the aging-related bone defects is still under debate. An understanding of the changes in gene expression of bmMSC with age may provide clues and give insights into the basic cause of bone defects during aging.
In this study, using Illumina bead chip expression microarray, we analyzed the gene expression profiles of bmMSC derived from 14 donors between 36 and 74 years old, including many patients with osteoarthritis (OA). We identified genes whose change in expression was highly associated with age or OA. Putative biological functions and molecular pathways corresponding to those identified genes were retrieved by bioinformatics analysis, through which a possible pathological role of bmMSC in the development of skeletal diseases in aging was proposed.
Patients and Methods
Isolation of bmMSC from bone marrow
Human bone marrows were either collected from osteoarthritis patients undergoing total knee replacement, or from the femurs of healthy donors receiving bone surgery because of trauma. Informed consent was obtained from each donor. The use of human bmMSCs in this study was approved by both the Institutional Review Board at National Health Research Institutes and Miaoli General Hospital. Bone marrows were subjected to ficoll density fractionation to collect the plastic-adherent mononuclear cells as described previously [7]. These cells were maintained in low glucose Dulbecco's modified Eagle's medium (GIBCO-BRL, California, USA) containing 20% fetal bovine serum (FBS) (Hyclone, Utah, USA), glutamine (GIBCO-BRL, California, USA), penicillin and streptomycin (GIBCO-BRL, California, USA), and maintained in a humidified atmosphere containing 5% CO2 at 37°C. After 10-14 days, colonies were dispersed and seeded at a density of 1.3 x 103 cells/cm2 (passage 1), and were passaged at 70%-80% confluence afterward. Cells of the fourth passage were maintained in medium containing 10% FBS for 4-7 days and subjected to flow cytometric analysis. Cultures that were CD31- and CD45-negative, but CD90- and CD105-positive were defined as bmMSCs and used for RNA extraction [7].
RNA extraction, microarray experiments, and RT-qPCR validation
Total RNA was isolated from cells using Trizol (Invitrogen, Califonia, USA) according to the protocol provided by the manufacturer. Methods for sample labeling, array experiments, and TaqMan probe-based RT-qPCR experiments, were as described elsewhere [8]. The probes and primers used in RT-qPCR are as listed in Supplemental Table SIV.
Statistical analysis
(1) Data normalization. To avoid possible unwanted technical variation between samples or batches of array, raw data from microarray experiments were subject to either quantile normalization [9] using preprocessCore package in the Bioconductor, or global normalization that linearly adjust signal intensity according to signal of those spike-in control probes in the Illumina arrays (see supplemental methods). Normalized data were subjected to the following statistical analysis.
(2) Neighborhood analysis. This analysis, developed by Golub et al. [10], was used to detect if there were genes, in our array data, showing strong correlation in their expression with age or OA. This analysis was performed as described in supplemental methods.
(3) Multiple regression/ criteria of probes selection. Multivariate linear regression was used to model the expression level of a gene and its relation with age, gender, or the presence of OA of each subject. This model is described as follows:
For probe, j = 1,…,J, let Yij be expression data of ith individual. For i = 1,…,N, let Ai, Gi and Di be the age, gender and OA respectively. In particular, Gi = 1 if and only if the ith individual is male; Di if and only if the ith individual has OA. Assume the gene expression
where αA, αD, αG and μj are the model parameters and εij is the error. Finally, a filter was applied to remove probes/genes having (i) average expression level < 300 arbitrary units or (ii) p>0.05 in multiple regression analysis, which then generated age-or OA-associated gene list. Since two normalization methods were applied, qualified probes/genes from either method that meet the above criteria were included in the candidate gene lists.
Measurement of DNA synthesis
DNA synthesis was assessed by measuring the incorporation of 5-bromo-2-deoxyuridine (BrdU) into DNA using BrdU Cell Proliferation Assay kit based on the protocol provided by manufacturer (Millipore, MA, USA). Briefly, cells were treated with BrdU or phosphate buffer saline (PBS, as background control) for 24 h. Cells were then fixed and DNAs were denatured using Fixing Solution. The BrdU label was detected by an anti-BrdU monoclonal antibody, and the signals were quantitated with a spectrophotometer microplate reader set at wavelength of 450/550 nm.
Bioinformatic analysis
We perform gene ontology and pathway analysis using Ingenuity Pathway Analysis 9.0 for enrichment of biological functions and pathways in which our selected genes of interest were involved.
Discussion
Aged bones are featured by decreased bone mass and increased fragility compared with young bones. Inadequate bone formation following excessive bone resorption is a major cause of age-related bone loss. Besides, aged skeleton is also commonly accompanied by inflammatory disease such as OA, as represented by the bone marrow donors in this study. Given that bmMSCs give rise to bone-forming cells, it is likely that the aging of bmMSC play an important role in the aging of skeleton, and may be even involved in the development of aging-associated skeletal diseases such as osteoporosis (OP) and OA. Unfortunately, molecular evidence that can support the above conjecture and link aging of bmMSC to OP/OA is still lacking. It is thus of great interest to understand the age-associated gene expression change to know the role of bmMSC in the pathogenesis of aging-related skeletal diseases. In this regard, we examined the transcriptome-wide changes of genes of bmMSCs derived from 14 donors of various age, and analyzed the array data by exploiting a multivariate linear regression model considering all known variables, i.e., age, presence of OA, and gender. This analytic platform allowed us to correct effects of the OA- and/or gender-related change of gene expression, to obtain a list of age-dependent genes (in the background of OA), and also a list of OA-associated genes (in the background of old age). As far as the age-associated genes are concerned, our data are in agreement with the results reported by Wagner et al. who demonstrated related effects of aging and replicative senescence on the gene expression profiles of human bmMSC/progenitors [11]. However, there is an overlap of only 8 genes between our and their data. These include the age-associated up-regulation of EPB41L3 and TCEAL7 involved in regulating cell proliferation; IL13RA2 involved in the signaling of transforming growth factor β1-mediated fibrosis; MFAP5 encoding a microfibrillar associated protein; ROBO1 involved in axon guidance; S100A4 encoding a calcium binding protein; STEAP3 involved in iron metabolism; and UBE2E2 involved in protein degradation. The little overlap might be due in part to the differences in the populations studied, cell culture conditions, array data processing, or analytical platform used. In addition to the above mentioned genes, we report novel findings about the age- and OA-associated changes in the gene expression profiles of bmMSC.
Our data point out that cell growth, proliferation, and migration are the cellular functions that most possibly change with age in human bmMSC. Among the genes involved in these cellular functions are the cell cycle regulators-encoding CCND2, CCNE1, and CDKN2B. The former two genes encode D- and E-type cyclins, whereas CDKN2B encodes a cyclin-dependent kinase (CDK) inhibitor p15INK4b which arrests cell cycle by inhibiting the D-type cyclin-dependent kinase CDK4 activity. We observed that CCND2 and CDKN2B are up-regulated, but CCNE1 is down-regulated with age. Given the findings that CDK inhibitors play an important role in regulating the renewal proliferation of mice hematopoietic stem cells [13-15], and that there is a strong link between p16INK4a and cellular aging [13-16], our results suggest that regulation of CDKN2B expression may play an important role in the renewal proliferation as well as aging of human bmMSC. Besides the cell cycle regulators, we found the up-regulation of DCN, PODN, TP53INP1, and DRAM1, and down-regulation of ERCC2 and TGM2 with age. DCN encodes a proteoglycan which down-regulates the proliferation and migration of mammalian cells [17]. PODN encodes an extracellular matrix (ECM) component which inhibits cell growth and migration [18]. ERCC2 encodes a nucleotide excision repair enzyme critical for removal of damaged DNA fragments, while TP53INP1 and DRAM1 participate in the DNA damage-triggered growth arrest and apoptosis [19, 20]. As for TGM2, it was found to enhance cell growth and survival through anti-apoptosis signaling [21]. Interestingly, TGFBR3, RPS6KA2, PTGER4, FBXO32, SULF1, DBC1, TCEAL7, and EPB41L3 are up-regulated with age (supplemental Table SI). These genes have been reported to negatively control cancer cell proliferation [22-29]. Thus, up-regulation of these ‘tumor suppressor genes’ is likely to decrease the proliferation rate of human bmMSC. Data described above might underlie the aging-associated decrease in the proliferation rate of bmMSCs, an aging phenotype of mammalian bmMSCs [3, 30, 31]. Since our data are in agreement with the current findings regarding the deleterious effect of aging to the proliferation of stem cells, it is conceivable that our results can also reveal the other important age-associated functional changes in human bmMSC. Among them, as revealed by our analyses, are those involved in glycobiology.
Glycosylation is a cellular process that links glycans to macromolecules such as proteins and lipids by different types of glycosidic bonds. N-linked glycans (N-glycans), for example, are the polysaccharides that link to the peptides or proteins by N-glycosidic bond. Mature glycoproteins and glycolipids not only form the architecture of cell membrane but also participate in cellular signaling. Our results show that several genes involved in the modification of glycan are up-regulated with age (Table IV and Figure 3). Since modification of glycan is a pivotal process in the synthesis and catabolism of glycoproteins and glycolipids, up-regulation of these genes with age suggests that aging of human bmMSC may be accompanied by alterations in membrane homeostasis and in the glycosylation of membrane components, which may result in the alteration in cellular signaling. For example, hexosaminidase has been implicated in local hydrolysis of glycosphingolipids at cell membranes [32]. Given that glycosphingolipid is the major component of lipid rafts which play an important role in a variety of cellular processes including signal transduction and cell proliferation, elevated expression of HEXA and HEXB might enhance the degradation of glycosphingolipids at aged bmMSC surface, impact the formation of lipid rafts, and affect signaling. For another example, sulfatase 1 is able to desulfate the sulfated proteoglycans at the cell membrane, inhibits their co-receptor functions in the signaling of several growth factors. Accordingly, elevated expression of SULF1 in aged bmMSC is likely to impair cellular response to growth factors. In fact, we show that Na2SO4 is able to induce DNA synthesis in bmMSCs from adult and aged donors, and the induction is stronger in bmMSCs from aged donors than in bmMSCs from adult donors (Figure 4). Based on these findings, we postulate that alterations in the cellular functions regulating membrane homeostasis and glycosylation of membrane components are very likely to alter the proliferative capacity of bmMSC, and play an important role in the aging of bmMSC.
Table IV. Genes involved in glycan modification
Gene symbol | Product | Function |
---|
GLT8D2 | Glycosyltransferase 8 domain containing 2 | glycosyltransferase |
---|
FUCA1 | Tissue alpha-L-fucosidase 1 | fucosidases |
---|
FUCA2 | Tissue alpha-L-fucosidase 2 | fucosidases |
---|
MAN1A1 | Mannosidase, alpha, class 1A, member 1 | mannosidases |
---|
MAN2B2 | Mannosidase, alpha, class 2A, member 2 | mannosidases |
---|
MANBA | Lysosomal mannosidase, beta A | mannosidases |
---|
NEU1 | Lysosomal sialidase 1 | Sialidase |
---|
HEXA | Hexosaminidase A (α-polypeptide) | hexosaminidase (glycosylhydrolase) |
---|
HEXB | Hexosaminidase B (β-polypeptide) | hexosaminidase (glycosylhydrolase) |
---|
GM2A | GM2 ganglioside activator | cofactor of hexosaminidase |
---|
ARSB | Arylsulfatase B | sulfatases |
---|
IDS | Iduronate 2-sulfatase | sulfatases |
---|
SULF1 | Sulfatase 1 | sulfatases |
In addition, our results have provided clues to address the involvement of bmMSC in aging-associated skeletal diseases. OA is an inflammatory disease featured by the degeneration of cartilage matrix, which is due in part to excessive degradation of the matrix components aggrecan, collagen II and GAG [33-35]. It has been reported that hexosaminidase and sulfatase 1 which are involved in the degradation of GAG are the dominant enzymes in the synovial fluid and cartilage of OA patients [36, 37]. Inhibition of hexosaminidase activity has been proposed for preventing or even reversing cartilage degradation in OA patients [34]. ADAMTS5, an aggrecanase, was also found highly expressed in human OA cartilages [38]. Deletion of active ADAMTS5 has been shown to prevent cartilage degradation in a murine OA model [39]. As to the degradation of collagen II, cathepsin K was found involved in the cleavage of collagen II in articular cartilages in certain OA patients, suggesting that it might play a role in OA pathology [33]. Our data show that genes encoding these enzymes in bmMSCs are all up-regulated with age. In addition, COL8A2 and GPNMB, two OA candidate genes [40], are also up-regulated with age in bmMSCs. Given that bmMSCs are the primary source of cartilage chondrocytes, our data suggest a pathological role of aged bmMSC in aging-associated OA.
Moreover, the age-associated genes also cover genes participating in regulating bone resorption and formation. Data show that RPL29 is down-regulated with age in human bmMSC. RPL29 encodes a ribosomal protein. Mice lacking this gene display a short stature phenotype and exhibit increased bone fragility, which is due to delayed entry of osteoprogenitors into cell cycle and altered matrix protein synthesis rates [40]. In addition, we show that TNFAIP6 is up-regulated with age. This gene has been found down-regulated during osteoblastic differentiation; overexpression of this gene inhibits osteoblastic differentiation of human MSCs [41]. Thus, down-regulation of RPL29 and up-regulation of TNFAIP6 with age may represent a mechanism underlying the aging-associated defects in bone formation and osteoblastic differentiation of human bmMSC. As mentioned above, cathepsin K may play a role in OA pathology, and is up-regulated with age. In fact, there are evidences showing that capthesin K is also implicated in the pathogenesis of OP: (i) cathepsin K has been considered as a target for the pharmacological treatment of OP, and (ii) overexpression of CTSK has been shown to cause spontaneous development of synovial hyperplasia and fibrosis, cartilage degeneration, and bone destruction in transgenic mice upon aging [42]. Therefore, it is conceivable that osteoprogenitors/osteoblasts with elevated expression of CTSK may jeopardize their osteogenic activity. With these in mind, it is not surprising to find that SPP1, an OP susceptibility gene [43], is up-regulated with age in bmMSC (supplemental Table SI). Thus, our findings provide compelling molecular evidences to suggest a role of aged bmMSC in the pathogenesis of OP. Meanwhile, it has to be mentioned that there is a moderate overlap between age- and OA-associated gene lists though, the age-associated genes discussed above are only present in the former gene list. Taken together, it is tempting to postulate that by associating with the forming of pathological gene expression profile described above, increase of age may act as an intrinsic promoting factor to the development of aging-associated skeletal diseases.
Our analyses of the OA-associated genes have shown interesting findings regarding the etiology of OA. Based on current theory, OA is the consequence of long term mechanical stress on the articular cartilage. In response, the cartilage chondrocytes produce inflammatory cytokines and matrix metalloproteinases, which eventually causes destruction of articular cartilage. But recently, a genome-wide association study (GWAS) identified two single nucleotide polymophisms (SNPs) which are in a region containing HLA class genes including HLA-DRB4, associated with susceptibility to knee OA [44]. This finding suggests that immunological mechanism may be implicated in the etiology of OA. Here, we show that antigen presentation and signaling of immune cells are the top pathways enriched by OA-associated genes, and that CD74 and a list of HLA class genes including HLA-DRB4 are down-regulated with OA (Table III). Thus, coinciding with that GWAS result, our results also suggest an immunological issue associated with OA. Accordingly, we propose that bmMSC with altered immunological property might play an important role in the etiology of OA. On the other hand, we found that DAXX which encodes a pro-apoptotic factor in primary cells [45] is up-regulated with OA. Oppositely, GAS6, SKI, and RAD51 are down-regulated with OA (supplemental Table SII). Gas6 can promote cell proliferation, survival, and migration [46]. Ski can bind to the histone deacetylase SIRT1 and inactivate p53 [47]. Rad51 is the major recombinase involved in the repair of DNA double strand breaks. So, our results suggest that the presence of OA might associate with deficient DNA repair, and decreased proliferation and survival of bmMSC.
In summary, we have reported novel findings regarding to the age- and OA-associated changes in the gene expression profiles of human bmMSC. We show that increase of age and the presence of OA may independently associate with changes in gene expression profile that may hinder the proliferation and survival of bmMSC. In particular, our results suggest a pathological role of aged bmMSC in the development of OP and/or aging-associated OA, and also suggest a role of bmMSC with altered immunological property in the etiology of ‘adult-onset’ OA.
bmMSC: bone marrow-derived mesenchymal stem cell;
OA: osteoarthritis;
OP: osteoporosis.
This work was supported by National Science Council, Taiwan (NSC-99-3112-B-400-011, NSC 99-3112-B-400-012, and NSC-100-3112-B-400-002) and Department of Health, Taiwan (DOH100-TD-C-111-004), and NHRI (CS-098-PP08 and CS-099-PP07).