Identification of osteoclast-osteoblast coupling factors in humans reveals links between bone and energy metabolism

Abstract

Bone remodeling consists of resorption by osteoclasts followed by formation by osteoblasts, and osteoclasts are a source of bone formation-stimulating factors. Here we utilize osteoclast ablation by denosumab (DMAb) and RNA-sequencing of bone biopsies from postmenopausal women to identify osteoclast-secreted factors suppressed by DMAb. Based on these analyses, LIF, CREG2, CST3, CCBE1, and DPP4 are likely osteoclast-derived coupling factors in humans. Given the role of Dipeptidyl Peptidase-4 (DPP4) in glucose homeostasis, we further demonstrate that DMAb-treated participants have a significant reduction in circulating DPP4 and increase in Glucagon-like peptide (GLP)-1 levels as compared to the placebo-treated group, and also that type 2 diabetic patients treated with DMAb show significant reductions in HbA1c as compared to patients treated either with bisphosphonates or calcium and vitamin D. Thus, our results identify several coupling factors in humans and uncover osteoclast-derived DPP4 as a potential link between bone remodeling and energy metabolism.

Fig. 1. Baseline participant characteristics and effects of DMAb on bone metabolism.

a Baseline clinical and biochemical data in the study participants. b Correlations at baseline between markers of bone formation (PINP, μg/L; OCN, ng/mL) and resorption (CTX, ng/mL; TRAP5b, U/L) demonstrating coupling of bone formation and resorption at the systemic level (N = 48 participants); Spearman’s correlation coefficient was used to determine strength of relationships. c Changes in markers of bone resorption (top panels) and bone formation (bottom panels) over 3 months (% change from baseline, N = 24 participants per group). Individual values are plotted with mean and error bars represent SD. Significance was determined using the Mann–Whitney test. Source data are provided as a Source Data file.

Fig. 2. Correlation of osteoclast and osteoblast genes and secreted factors altered by DMAb.

a Heat maps showing the osteoclast and osteoblast normalized gene expression in placebo and DMAb-treated participant bone biopsies. Normalized gene expression (CQN values) were ranked for each gene across the placebo and DMAb participant biopsies (N = 15 participant biopsies/group). Red denotes higher expression and blue denotes lower expression. b Rank mean values for DMAb-suppressed osteoclast and osteoblast gene sets were plotted for the placebo participants. c DMAb-suppressed secreted factor genes, but not d DMAb-upregulated secreted factor genes correlate with osteoblast and osteoclast marker genes in the placebo participants (N = 15 participant biopsies); Spearman’s correlation coefficient was used to test the strength of the relationship between rank mean gene sets in b–d. Source data are provided as a Source Data file.

Fig. 3. Identification of osteoclast-derived secreted factors involved in coupling.

a Flow chart describing processing of the bone biopsy samples to select for osteocyte- and osteoblast-enriched fractions. b Overlap of DMAb-suppressed secreted factor genes in centrifuged bone vs. the osteocyte-enriched fraction (N = 15 participant biopsies/group). For both sample sets, differential gene expression was determined using the R package edgeR. Ingenuity Pathway Analysis was used to identify differentially expressed secreted genes. c Heat map comparison of gene expression in osteoblast-enriched vs. bone marrow-derived osteoclast cultures. Red denotes higher expression and blue denotes lower expression. The Wilcoxon’s signed-rank test was used to determine significance between osteoblast-enriched (Ob) and bone marrow-derived osteoclast (Oc) gene expression. *P < 0.05; **p < 0.01; NS not significant. Significance between osteoblast-enriched (Ob) and osteoclast (Oc) gene expression is shown in the Ob vs. Oc column (N = 9 participant samples/group). Significant change in osteocyte gene expression by DMAb compared to placebo is shown in the osteocyte-enriched column (N = 15 participant biopsies/group); differential expression of RNA-sequencing osteocyte data was performed with the R program edgeR. Source data are provided as a Source Data file.

Fig. 4. Bone marrow plasma DPP4 protein linked to bone remodeling.

a Bone marrow plasma DPP4 levels in the placebo- vs. DMAb-treated participants as measured by Olink Proteomics (N = 24 participant samples/group). Bone marrow DPP4 is measured in NPX (normalized protein eXpression), an arbitrary, relative unit in log 2 scale; values were converted to linear scale and p value was calculated by the Kruskal–Wallis test. Individual values are plotted with mean and error bars represent SD. b Bone marrow plasma DPP4 levels (assessed by the Olink Proteomics) correlate with osteoblast and osteoclast gene sets in the placebo participants; Spearman’s correlation coefficient was used to determine strength of relationships (N = 15 participant samples). c Change in serum DPP4 over 3 months in the placebo- vs. DMAb-treated participants (% change from baseline, N = 24 placebo, N = 22 DMAb participant samples [see Methods]); individual values are plotted with mean and error bars represent SD. Significance was determined using the Mann–Whitney test. d In situ hybridization (ISH) staining in human bone showing the presence of DPP4 mRNA in osteoclasts, but not other cell types. Staining for DPP4 mRNA (red stain) was abundant in osteoclasts (OC) on eroded surfaces (ES) of cancellous bone and intracortical canals. Osteoblasts on osteoid surfaces (OS) and bone lining cells on quiescent surfaces (QS) showed no staining. Dotted lines represent separation of bone surfaces. Scale bars = 50 µm. e Changes in serum GLP-1 (top) and glucose and insulin (bottom) levels in the placebo- and DMAb-treated participants (% change from baseline, N = 24 placebo, N = 22 DMAb participant samples). Individual values of percent change GLP-1 are plotted with mean and error bars represent SD. Significance was determined using the Mann–Whitney test. Source data are provided as a Source Data file.

Fig. 5. Analysis of type 2 diabetic/prediabetes patients treated with DMAb.

a HbA1c, b fasting plasma glucose (FPG), and c BMI are plotted for patients treated with calcium plus vitamin D (C/VitD, black solid line and circles), bisphosphonate (BP, red squares), or DMAb (blue triangles) (N = 115 patients per group). The y-axis shows percent change from baseline. Analysis of covariance (ANCOVA) was used to test for differences in continuous measures among the three groups. Bonferroni correction was used for post hoc pairwise comparisons. Mean percent change from baseline is presented at 6 and 12 months. Error bars represent SD. Source data are provided as a Source Data file.

Fig. 6. Proposed mechanism for coupling of bone remodeling to energy metabolism.

RANKL signaling in osteoclasts induces (directly or indirectly) the expression of key coupling factors, identified in our human study as LIF, CREG2, CST3, CCBE1, and DPP4 (note that LIF and CST3 are known to have effects on osteoblasts and thus are likely osteoclast–osteoblast-coupling factors (solid arrows)^,,, whereas DPP4, CREG2, and CCBE1 are potential coupling factors identified by our study that require further characterization (dashed arrows)). Increases in circulating DPP4 lead to a decrease in GLP-1 levels, leading in turn to reduced insulin and increased glucagon secretion, resulting in hyperglycemia. These actions of RANKL-induced DPP4 appear to be synergistic with other effects of RANKL (denoted by red arrows and text) on glucose metabolism, which are to induce insulin resistance and increase circulating glucose levels. These findings may be of particular interest in the context of previous findings from the Long laboratory demonstrating that Wnt signaling in osteoblasts favors glycolysis over oxidative phosphorylation (Warburg effect) and that glycolytic intermediates may be particularly important for the process of osteoblast differentiation. As such, in addition to RANKLinducing osteoclast differentiation and osteoclast-derived osteoblast-coupling factors, the ability to make glucose available to differentiating osteoblasts may also be a key component of RANKL-induced energy coupling at a systemic level. We should note that this is a working model and, for example, it remains to be shown that antagonism of RANKL by DMAb regulates the insulin/glucagon ratio in humans, not only under fasting but also postprandial conditions, given what is known about the mechanisms of action of DPP4 inhibitors.