Bibliometric analysis highlights lesser-studied pathways in bone remodeling

Bibliometric analysis highlights lesser-studied pathways in bone remodeling | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Bibliometric analysis highlights lesser-studied pathways in bone remodeling Emily M. Davis, Jacob A. Snyder, Basil S. Mustaklem, Hailey L. Brown, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4768994/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Oct, 2025 Read the published version in Clinical & Translational Metabolism → Version 1 posted 7 You are reading this latest preprint version Abstract Bone mass is determined by the relative balance of action between osteoblasts, which deposit bone matrix, and osteoclasts, which resorb bone matrix. Imbalance in these actions leads to conditions of high or low bone mass. Osteoporosis, i.e. , low bone mass, is a common medical condition that places individuals at elevated risk of fracture and greater likelihood of disability, loss of independence, and death. Both anti-resorptive and anabolic medications are available and are generally successful at stabilizing and/or promoting gains in bone mass. However, each current medication has significant drawbacks which present considerable challenges for the long-term management of this chronic condition. Unfortunately, there are few new candidate therapies in the drug development pipeline. This underscores a need for identifying new treatment targets for increasing bone mass, particularly for novel pathways lacking a therapeutic modality in development. However, a report from 2018 identified a striking lack of heterogeneity among molecular pathways studied in the bone remodeling field, with just three pathways accounting for more than 50% of publications and 46% of United States National Institutes of Health-funded grants. Here, we update the prior analysis to 2018-2022 to a) examine the heterogeneity of molecular pathways studied in the bone remodeling field in that time and b) determine if new functional evidence has emerged for additional lesser-known pathways which might hold therapeutic potential. Our results reveal a sustained lack of diversity in research that may restrict discovery of novel therapeutic approaches. We call for an expansion into lesser-studied pathways to broaden the collective focus of the field and highlight several pathways for which functional evidence supports a role in the regulation of bone remodeling. Future work is required to determine therapeutic potential and elucidate the mechanism(s) by which these pathways intersect with the complicated signal transduction network underlying bone remodeling. Osteoporosis bone remodeling cell signaling osteoblast osteoclast Figures Figure 1 Figure 2 Introduction Bone mass is determined by the relative balance of action between osteoblasts, which deposit bone matrix, and osteoclasts, which resorb bone matrix. In humans, bone mass generally declines after age thirty due to the rate of bone resorption exceeding the rate of bone formation [ 1 ]. Osteoporosis, i.e. , low bone mass, is a common medical condition that places individuals at elevated risk of fracture and greater likelihood of disability, loss of independence, and death [ 2 ]. Estimates suggest that up to 49 million individuals have osteoporosis in North America, Europe, Japan, and Australia alone [ 3 ]. In the US, hospitalizations for osteoporotic fractures exceed those for heart attack, stroke, and breast cancer [ 4 ]. And, by 2025 the number of fractures due to osteoporosis may increase to nearly three million in the US alone, creating a $ 25 billion financial burden [ 5 ]. Given the relationship between bone mass and osteoporosis – i.e., “an increase of [bone mass] by one standard deviation would reduce the fracture risk by 50% [ 6 ]” – therapies aimed at increasing bone mass are crucial for adequate management of this disease. Both anti-resorptive and anabolic medications are available and are generally successful at stabilizing and/or promoting gains in bone mass. However, each current medication has significant drawbacks (including counter-indications, short therapeutic windows, and the potential need for drug holiday) which present considerable challenges for the long-term management of this chronic condition [ 7 , 8 ]. Unfortunately, there are few new candidate therapies in the drug development pipeline. This presents an urgent and unmet need for identifying new treatment targets for increasing bone mass – particularly for those novel pathways that do not yet have a therapeutic modality in development. However, in a 2018 report, we identified a striking lack of heterogeneity among molecular pathways studied in the bone remodeling field, with just three pathways (Wnt, Mitogen-activated protein (MAP) kinase, and the Transforming Growth Factor (TGF)-beta superfamily) accounting for more than 50% of publications (2699 out of 4826 publications) and 46% of United States National Institutes of Health (NIH)-funded grants (862 out of 1850) between 2008–2017 [ 9 ]. Further, adding Parathyroid Hormone (PTH), this list of four pathways accounts for nearly 55% of United States National Institutes of Health (NIH) grants funded during that period (1012 out of 1850 grants) [ 9 ]. Our prior report highlighted several lesser-studied pathways that garnered limited attention by the field but for which functional evidence (genetic, pharmacological, etc.) was available implicating a role in bone remodeling in vivo [ 9 ]. Here, we update the prior analysis to the time period of 2018–2022 to a) examine the heterogeneity of molecular pathways studied in the bone remodeling field in that time and b) determine if new functional evidence has emerged for additional lesser-known pathways which might hold therapeutic potential. Our results confirm a lack of diversity in research that may restrict discovery of novel therapeutic approaches. Additionally, we detail several pathways for which functional evidence supports a role in the regulation of osteoblasts and/or osteoclasts in vivo and call for an expansion into lesser-studied pathways to broaden the collective focus of the field. Materials & Methods Searches were performed on PubMed ( https://pubmed.ncbi.nlm.nih.gov/ ) or the NIH Research Portfolio Online Reporting Tools Expenditures and Results (RePORTER, https://reporter.nih.gov ) using the search phrase (("skeleton" or "bone") and ("signaling" or "pathway")) and ("osteoblast" or "osteocyte" or "osteoclast")) with results restricted to the five year period between January 1, 2018, and December 31, 2022. This yielded a total of 3,835 publications and 1239 grants on PubMed and RePORTER, respectively. We then added search terms relating to specific signaling pathways (Table S1 ) to identify the number of publications or grants that mention those pathways. We used PubMed to identify lesser-studied pathways in bone remodeling by excluding pathways for which the search returned fifty or more publications in the last five years. Then, to narrow down those lesser-studied pathways to those highlighted in this narrative, we sought to identify particularly notable pathways using the following inclusion criteria: 1) functional evidence (knock-out genetic model, pharmacological intervention, etc.) published in a peer-reviewed journal and indexed in PubMed.gov; 2) fewer than five review articles published about actions of the pathway in the skeleton in the last five years; and 3) identifiable as a distinct signaling pathway rather than a downstream effector of a different pathway. Results Most popular pathways by publications Search of the PubMed database generated a set of 3835 publications in the bone remodeling field from 2018–2022; this closed set was the basis for all subsequent bibliometric analyses below. These publications represent an average rate of 767 publications per year from 2018–2022, which is accelerated nearly 60% compared to 482.6 per year from 2008–2017. Adding specific terms to this search detailed the relative popularity of 145 pathways (Table S2). The top ten most popular pathways from 2018–2022 and their rank from 2008–2017 are shown in Table 1 . In both time periods, the RANK Ligand (RANKL) pathway had the greatest frequency of publications (32.5% in 2018–2022 and 29.2% in 2008–2017). Similarly, the TGF-beta superfamily was the second most popular pathway in both periods (26.6% in 2018–2022 and 26.4% in 2008–2017). Changes in the ranking were noted for other pathways in the former top ten – most notably with the Wnt pathway and Androgen Receptor pathway falling from third and fifth in 2008–2017 to fifth and tenth in 2018–2022, respectively (Table 1 ). Similarly, Osteocalcin and Osteoprotegerin – which were eighth and ninth in 2008–2017, respectively – fell from the top ten in 2018–2022 (Table S2). Two pathways were newcomers to the top ten in 2018–2022, with the transcription factor Oct4 and the Ak strain transforming (AKT) family moving from eleventh to eighth and twelfth to ninth, respectively (Table 1 ). Table 1 Top ten most popular pathways based on publication between 2018–2022 compared to their status between 2008–2017. 2018–2022 2008–2017 Term Rank Count Percentage of Total Rank Count Percentage of Total Change in Rank RANKL 1 1246 32.49% 1 1411 29.24% 0 TGF-beta 2 1019 26.57% 2 1273 26.38% 0 MAPK 3 851 22.19% 4 974 20.18% 1 Fos/Jun 4 841 21.93% 6 778 16.12% 2 Wnt 5 813 21.20% 3 1077 22.32% -2 NFATc 6 554 14.45% 10 479 9.93% 4 Runx 7 544 14.19% 7 638 13.22% 0 Oct4 8 519 13.53% 11 385 7.98% 3 AKT 9 422 11.00% 12 355 7.36% 3 AR 10 418 10.90% 5 883 18.30% -5 Our one-by-one pathway search method was unable to distinguish overlapping publications – i.e., a single publication that included terms from more than one pathway. Thus, we combined search terms for the top five pathways by publication to determine the percentage of the bone remodeling literature examining these pathways. This revealed that these top five pathways alone account for 75.3% of publications in the bone remodeling field from 2018–2022 (2889 of 3835), which represents sustained popularity compared to the 2008–2017 time period (78.4%, 3785 of 4826). Expanding the search terms to include all top ten pathways raises the representation of these pathways to 86.2% of publications (3309 of 3835) from 2018–2022 compared to 89.2% for these pathways from 2008–2017 (4309 of 4826). Most popular pathways by US NIH funding Search of the NIH RePORTER database generated a set of 1239 funded grants in the bone remodeling field from 2018–2022; it is important to note that the methodology of RePORTER generally counts each year of multi-year grants individually rather than just the project overall – i.e., an award that spans three fiscal years is counted three times instead of once. This closed set was the basis for all subsequent bibliometric analyses below. The grants awarded in 2018–2022 represent an average rate 247.8 per year, which is accelerated nearly 34% compared to the 185 grants per year from 2008–2017 [ 9 ]. Adding specific terms to this search detailed the relative popularity of the pathways examined above (Table S3). The top ten most popular pathways by NIH grant funding from 2018–2022 and their rank from 2008–2017 are shown in Table 2 . In both time periods, the Wnt pathway had the greatest frequency of grants (25.2% in 2018–2022 and 28.1% in 2008–2017). Similarly, the second, third, and fourth most popular pathways in both time periods were the RANKL, TGF-beta superfamily, and PTH pathways, respectively (Table 2 ). Changes in the ranking were noted for other pathways in the top ten – most notably with Runx2, the MAP kinase family, Estrogen, Osterix, and Nfatc1, which were fifth, sixth, seventh, eighth, and tenth in 2008–2017, respectively, falling out of the top ten entirely (Table S3). The Tumor Necrosis Factor (TNF)-alpha pathway climbed to fifth in 2018–2022 from ninth in 2008–2017 (Table 2 ). Five pathways were newcomers to the top ten in 2018–2022: Osteoprotegerin, Cadherin superfamily, Insulin, Interleukin superfamily, and Osteocalcin (Table 2 ). Table 2 Top ten most popular pathways based on United States National Institutes of Health grants between 2018–2022 compared to their status between 2008–2017. 2018–2022 2008–2017 Term Rank Count Percentage of Total Rank Count Percentage of Total Change in Rank Wnt 1 312 25.18% 1 520 28.11% 0 RANKL 2 199 16.06% 2 376 20.32% 0 BMP/TGF 3 165 13.32% 3 342 18.49% 0 PTH 4 154 12.43% 4 304 16.43% 0 TNF 5 142 11.46% 9 105 5.68% 4 OPG 6 94 7.59% 11 88 4.76% 5 Cadherin 7 89 7.18% 62 8 0.43% 55 Insulin 8 88 7.10% 13 75 4.05% 5 Interleukin 9 77 6.21% 25 40 2.16% 16 Osteocalcin 10 67 5.41% 17 61 3.30% 7 We then combined search terms for the top five pathways by funding to determine the percentage of NIH funding in the bone remodeling field that examined these pathways in 2018–2022. This revealed that these top five pathways alone account for 53.1% of grants in the bone remodeling field in this time period (658 of 1239). Moreover, just the top four pathways (Wnt, RANKL, TGF-beta superfamily, and PTH) account for approximately half of NIH funding in bone remodeling in 2018–2022 (619 of 1239), which represents sustained popularity compared to the 2008–2017 time period (62.25%) [ 9 ]. Expanding the search terms to include all top ten pathways raises the representation of these pathways to 60.5% of grants (749 of 1239) from 2018–2022 compared to 67.5% for those same pathways from 2008–2017 [ 9 ]. Comparing publications and funding Figure 1 shows the relative percentage for the top 25 most popular pathways based on grants and their popularity in NIH grants. We were interested to examine the potential correlation between frequency of publication and frequency of NIH funding for bone remodeling pathways. After removing those pathways for which there were no publications and no NIH grants in 2018–2022, we found a R-squared value of 0.4336 by simple linear regression analysis (p < 0.0001) for the remaining 121 pathways (Fig. 2 ). Notable yet lesser-studied pathways In our prior report, we developed a search method in PubMed involving a combination of exclusion and inclusion criteria to identify notable yet lesser-studied pathways in bone remodeling [ 9 ]. This produced a refined set of nine pathways (Apolipoprotein D (ApoD), Aryl Hydrocarbon Receptor (AhR), Lysophosphatidic Acid (LPA), Osteoclast Inhibitory Factor (OIP)-1, Oxytocin, Taste Receptor Type 1 (Tas1R) Family, Neuromedin U (NMU), Tyro3, and Type 1 Equilibrative Nucleoside Transporter (ENT1)) for which there was functional evidence to implicate a role in the regulation of osteoblasts and/or osteoclasts in vivo . The number of publications for these pathways between 2018–2022 compared to 2008–2017 is presented in Table 3 . Among these, the AhR and NMU pathways have received considerably greater attention between 2018–2022 compared to the ten years prior. Additionally, only the AhR, LPA, NMU, and OIP-1 pathways are subjects of NIH-funded grants: AhR, R01AR074930; LPA, R21AR055192, R01DK121776, R03HD042066; NMU: 1R03AG081947; OIP, R01DE012603. Table 3 Publication rate between 2018–2022 compared to 2008–2017 for pathways highlighted in 2018 study using the narrow search terms described in the methods section. 2018–2022 2008–2017 Term Rank Count Percentage of Total Rank Count Percentage of Total Change in Rank AhR 69 16 0.42% 95 7 0.15% 26 LPA 97 5 0.13% 91 9 0.19% -6 NMU 107 3 0.08% ND ND Oxytocin 116 1 0.03% 92 9 0.19% -24 TAS1R 116 1 0.03% 113 3 0.06% -3 ApoD ND 0 0.00% 122 1 0.02% ND ENT1 ND 0 0.00% 127 1 0.02% ND OIP ND 0 0.00% 119 2 0.04% ND Tyro3 ND 0 0 132 1 0.0002 ND To identify additional notable yet lesser-studied pathways, we searched PubMed to exclude pathways for which there were fifty or more publications in the last five years (Table S2), resulting in a refined set of 232 publications. Among these, twelve publications examined pathways highlighted in our previous report [ 9 ]. We screened the remaining 220 publications using the same inclusion criteria as our prior report [ 9 ]. This produced a refined list of 20 lesser-studied pathways for which there was functional evidence (knock-out genetic model, pharmacological intervention, etc.) reported between 2018–2022 implicating an endogenous role in bone remodeling (Table S4); some of these details are discussed below. Discussion To us, the findings above demonstrate a striking lack of heterogeneity in the pathways studied by the bone remodeling field overall. Moreover, given the heavy enrichment for just a few pathways over the last fifteen years, the lack of diversity may limit paradigm-changing discoveries and restrict novel therapeutic approaches for osteoporosis. In 2018, we called for an expansion into lesser-studied pathways to broaden the collective focus of the field [ 9 ]. We additionally highlighted nine pathways for which there was functional evidence to implicate a role in the regulation of bone remodeling in vivo [ 9 ]. Among these, two (the AhR and NMU pathways) have received considerably greater attention while four (the AhR, LPA, NMU, and OIP-1 pathways) are subjects of NIH-funded grants. However, relatively little progress has been made in the understanding and/or therapeutic potential of the other pathways we highlighted. Here, we identified an additional twenty pathways for which functional evidence was reported between 2018–2022 implicating a role in bone remodeling in vivo . In the sections below, we highlight several pathways that, to us, are particularly noteworthy as potential “low-hanging fruit” for future study. CD82 Conditional deletion of the transmembrane scaffolding protein CD82 in the osteoclast lineage leads to increased trabecular bone mass with deficits in osteoclast differentiation [ 10 ]. However, it is important to note that a separate study using global knockout of CD82 revealed this protein is involved in both osteoblast and osteoclast compartments and the net effect of knockout is smaller bones with no change in bone mineral density [ 11 ]. Thus, translational studies aimed at targeting this factor in bone metabolism may require selectively inhibiting its action in osteoclasts while preserving its function in osteoblasts. Chemerin Chemerin, encoded by RARRES2 , is an adipokine which signals through chemokine-like receptor 1 (CMKLR1) and is expressed by adipocytes, mesenchymal stem cells, osteoblasts, and osteoclasts [ 12 – 14 ]. Numerous studies in healthy adults or populations with specific diseases/conditions [ 15 – 21 ] [ 22 ] and animal models [ 23 , 24 ] report that serum chemerin levels are inversely related to bone mass [ 25 ]. Moreover, chemerin is required for osteoclastic differentiation [ 26 ] and targeting chemerin via neutralizing antibodies in vivo results in near complete loss of osteoclastogenesis with correspondingly high bone mass [ 14 ]. This raises the possibility of translational studies aimed at pharmacological inhibition of chemerin to increase bone mass. However, it is important to note that CMKLR1 is involved in regulating testosterone production by Leydig Cells in the male gonads [ 27 ], which may complicate systemic targeting of chemerin activity and require more targeted strategies. FAM210A Several genetic variations at the FAM210A locus in humans are associated with bone mineral density and fracture. And, global loss of FAM210A expression in mice is associated with low bone mass due to reduced bone formation and increased bone resorption [ 28 ]. Yet, this factor is not abundantly expressed in the bone microenvironment and skeletal muscle-specific loss of FAM210A also leads to low bone mass [ 28 ], suggesting that it may play an indirect role in bone metabolism. Menin Menin is a nuclear protein encoded by the MEN1 gene and is involved in transcription regulation and chromatin remodeling, and genome stability. Deleterious mutations in MEN1 are associated with the rare autosomal dominant disorder Multiple Endocrine Neoplasia type 1, which is characterized by the development of tumors in multiple endocrine glands, including the parathyroid glands, pancreatic islet cells, and the anterior pituitary. The location of these tumors and endocrinological interaction with the skeleton underlies symptoms of bone pain and early-onset osteoporosis found in this disease. However, several lines of evidence support a direct role for menin in bone metabolism through regulating osteoblast differentiation and/or activity. For instance, conditional knockout of menin in various stages of mesenchymal stem cells or the osteoblast lineage is associated with intense reduction of bone mass and concurrent decrease in number of osteoblasts [ 29 – 32 ]. These data are consistent with evidence that menin controls expression of type 1 collagen, alkaline phosphatase, and osteocalcin through interaction with the BMP and/or TGF-beta pathways [ 33 – 36 ]. Collectively, these data raise the possibility that strategies aimed at increasing menin production in the osteoblast lineage may hold therapeutic potential for raising bone mass; indeed, mice overexpressing menin in osteoblasts from had increased bone volume [ 31 ]. NMU NMU is an evolutionarily conserved peptide that is expressed in two major molecular forms, both of which are derived from the same mRNA and display similar receptor affinity for the heterotrimeric Gq/11-protein-coupled receptors NMU Receptor 1 (NMUR1) and NMU Receptor 2 (NMUR2) to regulate similar downstream targets [ 37 – 39 ]. NMUR1 is more broadly expressed than NMUR2 (see the Human Protein Atlas, proteinatlas.org) yet both are expressed in the bone microenvironment [ 39 ]. Two independent studies in mice implicate NMU as a negative regulator of bone formation [ 39 , 40 ]. Many of the effects of NMU are attributed to its actions in the hypothalamus; indeed, this was initially proposed to be the mechanism by which NMU regulates bone metabolism since over-activation of the NMU pathway in this location reduces bone remodeling in the appendicular skeleton [ 40 ]. However, interpretation of those findings is complicated by the non-wildtype genetic background and “rescue” design of the experiment. Moreover, hypothalamus-specific knockdown of endogenous Nmu expression does not impact bone mass despite > 92% knockdown efficiency [ 41 ] and NMU has direct effects on suppressing osteoblastic differentiation of osteoprogenitor cells in vitro [ 39 ]. Given that NMU and its receptors are expressed in bone in vivo [ 39 ], these findings leave open the possibility that the negative effects of NMU on bone formation are accomplished in the bone microenvironment itself and could be targeted as a potential anabolic therapy for increasing bone mass. Sirtuin-6 Sirtuin-6 is a sirtuin family protein that plays a vital role in genomic stability, aging, metabolism, and stress response via NAD + -dependent deacetylase activity. Functional evidence has indicated Sirt-6 plays a vital role in promoting osteoblastogenesis and preventing bone resorption. Several in vitro experiments have revealed that microRNAs – specifically miR-545-3p, miR-186, and miR-128 – bind to Sirt-6-3’UTR to downregulate its activity, resulting in decreased expression of osteoblastic markers and increased expression of osteoclastic markers [ 42 – 44 ]. Additionally, osteoblast/osteocyte-specific knockout of Sirtuin-6 has been shown to promote the phosphorylation of NF-kappaB, increasing RANKL-induced osteoclastogenesis, bone resorption, and expression of inflammatory cytokines as well as decreasing mature osteoblast function [ 45 – 49 ]. Restoration of Sirt-6 expression significantly reverses the increased expression of RANKL and proinflammatory cytokines [ 47 ]. In vivo experiments also revealed decreased trabecular bone mass/cortical bone thickness in homozygous Sirt-6 mutant mice [ 50 ], cavitation of femoral heads in mice with decreased Sirt-6 expression due to glucocorticoid-induced osteonecrosis [ 51 ], and decreased bone mass and apoptosis in aged Sirt-6 knockout mice. Reintroduction of Sirt-6 expression in the aforementioned Sirt-6 knockout models restores apoptosis of osteoclasts [ 52 ], increases osteoblast viability [ 53 ], and is associated with improved bone formation and calcification of tissues [ 49 ]. These studies call to mind studies aimed at increasing expression of Sirtuin-6 as an anabolic strategy to increase bone mass. Tas1R At least two of the Taste Receptor Tas1R family of heterotrimeric G-protein coupled receptors, which function in non-gustatory tissues as nutritional sensors, regulates bone metabolism as knock-out of Tas1R2 or Tas1R3 leads to high bone mass [ 54 , 55 ]. These two receptors are capable of heterodimerizing with one another as a means of monitoring extracellular glucose levels and, given that the serum marker of osteoclastic activity CTx is dramatically reduced in Tas1R3 knockout mice[ 55 ], is possible that pharmacological targeting of this pathway could disrupt osteoclast function. Vangl2 Vang-like protein 2 (Vangl2) is an essential component of the planar cell polarity (PCP) signaling pathway and is involved in various developmental and physiological functions. Vangl2 mutations are associated with skeletal patterning defects including malformed digit development [ 56 ]. Additionally, a specific role for Vangl2 in the negative regulation of osteoblasts comes from a report involving conditional deletion of this factor in the embryonic limb bud, which is associated with enhanced osteoblast differentiation of precursors and high bone mass in the postnatal skeleton [ 57 ]. This model also revealed increased bone formation rate in the absence of Vangl2 expression with no defects in bone resorption, suggesting that strategies aimed at limiting this factor in the osteoblastic lineage may hold promise as an anabolic therapy for increasing bone mass. Miscellaneous In addition to the above pathways, there are several others for which functional evidence indicates an endogenous role in bone remodeling and potential opportunity for therapeutic modulation. For instance, galectin-8 mediates coupling between osteoclasts and osteoblasts and global loss of this factor results in accelerated age-related bone loss [ 58 ]. Similarly, conditional deletion of the gene encoding Lysine (K)-specific demethylase 4B (KDM4B) in the embryonic limb bud is associated with enhanced age-related bone loss with selective defects in osteoblast activity (but not osteoclast activity) and increased bone marrow adipocity [ 59 ]. On the other hand, global loss of expression of Adaptor protein containing pleckstrin homology domain, phosphotryosine binding domain and leucine zipper motif (APPL1) – which plays an important role in intracellular signaling and vesicle trafficking and is an adaptor protein of the adiponectin receptor – leads to high bone mass associated with higher number of osteoblasts and reduced bone marrow adipocity [ 60 ]. Engulfment and Cell Motility Protein 1 (ELMO1) plays a significant role in osteoclast function as global loss of this factor reduces bone resorption in two mouse models of osteoporosis [ 61 ]; importantly, this study provided details on a peptide capable of disrupting ELMO1 function and reducing osteoclast activity in vitro , thus providing rationale for future studies examining this or other inhibitors as a means of dampening bone resorption. Finally, global loss of Transient Receptor Potential Cation Channel, Subfamily C, Member 6 (TRPC6) expression results in low bone mass with increased osteoclastic activity [ 62 ]. Conclusion The primary aim of this report is to detail a striking lack of diversity in research published in the bone remodeling field. This causes us concern as it may restrict discovery of novel therapeutic approaches in metabolic bone disease. Yet, there are myriad pathways for which there is solid evidence pinpointing a functional role in the regulation of bone metabolism – but many of these are understudied or remain obscure within the literature. Thus, a secondary aim of this report is to detail several lesser-studied pathways that are particularly compelling for us and call for broadening the collective focus of the field to enhance the likelihood of future therapy development. Declarations Author Contributions Conceptualization, EMD and JWL; Methodology, EMD and JWL; Formal Analysis, JWL; Investigation, EMD, JAS, BSM, HLB, MMS, CMW, EAD, GB, SS, and JWL; Resources, JWL.; Data Curation, EMD and JWL; Writing – Original Draft Preparation, EMD, JAS, BSM, HLB, MMS, CMW, EAD, GB, SS, and JWL.; Writing – Review & Editing, EMD, JAS, BSM, HLB, MMS, CMW, EAD, GB, SS, and JWL.; Visualization, JWL; Supervision, JWL.; Project Administration, JWL.; Funding Acquisition, JWL. All authors have read and agreed to the published version of the manuscript. Funding Funding was provided by intramural funds issued to JWL. Institutional Review Board Statement This study did not involve human subjects and IRB approval is not applicable. Informed Consent Statement Not applicable. Data Availability Statement Datasets used and/or analyzed are available from the corresponding author on reasonable request. Acknowledgments We wish to acknowledge the support and helpful feedback from members of the Marian University Bone & Muscle Research Group and the Indiana Center for Musculoskeletal Health. Conflict of Interest Competing Interest: JWL is Editor-in-Chief of Clinical and Translational Metabolism and is financially compensated for this role. Other authors have no financial or propiertary interests to disclose. References Raisz, L.G., Pathogenesis of osteoporosis: concepts, conflicts, and prospects. J Clin Invest, 2005. 115 (12): p. 3318-25. Leboime, A., et al., Osteoporosis and mortality. Joint Bone Spine, 2010. 77 Suppl 2 : p. S107-12. Wade, S.W., et al., Estimating prevalence of osteoporosis: examples from industrialized countries. Arch Osteoporos, 2014. 9 : p. 182. Singer, A., et al., Burden of illness for osteoporotic fractures compared with other serious diseases among postmenopausal women in the United States. Mayo Clin Proc, 2015. 90 (1): p. 53-62. 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Zhao, F., et al., Chemerin/ChemR23 signaling mediates the effects of ultra-high molecular weight polyethylene wear particles on the balance between osteoblast and osteoclast differentiation. Ann Transl Med, 2021. 9 (14): p. 1149. Zhao, H., et al., Chemokine-like receptor 1 deficiency leads to lower bone mass in male mice. Cell Mol Life Sci, 2019. 76 (2): p. 355-367. Tanaka, K.I., et al., FAM210A is a novel determinant of bone and muscle structure and strength. Proc Natl Acad Sci U S A, 2018. 115 (16): p. E3759-E3768. Abi-Rafeh, J., et al., Genetic Deletion of Menin in Mouse Mesenchymal Stem Cells: An Experimental and Computational Analysis. JBMR Plus, 2022. 6 (5): p. e10622. Troka, I., et al., Effect of Menin Deletion in Early Osteoblast Lineage on the Mineralization of an In Vitro 3D Osteoid-like Dense Collagen Gel Matrix. Biomimetics (Basel), 2022. 7 (3). Kanazawa, I., et al., Osteoblast menin regulates bone mass in vivo. J Biol Chem, 2015. 290 (7): p. 3910-24. 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Davenport, Emerging pharmacology and physiology of neuromedin U and the structurally related peptide neuromedin S. Br J Pharmacol, 2009. 158 (1): p. 87-103. Zeng, H., et al., Neuromedin U receptor 2-deficient mice display differential responses in sensory perception, stress, and feeding. Mol Cell Biol, 2006. 26 (24): p. 9352-63. Hsiao, Y.T., et al., Neuromedin U (NMU) regulates osteoblast differentiation and activity. Biochem Biophys Res Commun, 2020. 524 (4): p. 890-894. Sato, S., et al., Central control of bone remodeling by neuromedin U. Nat Med, 2007. 13 (10): p. 1234-40. Born-Evers, G., et al., Examining the Role of Hypothalamus-Derived Neuromedin-U (NMU) in Bone Remodeling of Rats. Life (Basel), 2023. 13 (4). Wu, M., et al., lncRNA SERPINB9P1 Regulates SIRT6 Mediated Osteogenic Differentiation of BMSCs via miR-545-3p. Calcif Tissue Int, 2023. 112 (1): p. 92-102. Zhao, J., et al., MiR-128 inhibits the osteogenic differentiation in osteoporosis by down-regulating SIRT6 expression. Biosci Rep, 2019. 39 (9). Xiao, J., et al., Osteogenic differentiation of rat bone mesenchymal stem cells modulated by MiR-186 via SIRT6. Life Sci, 2020. 253 : p. 117660. Zhang, D., et al., Evidence for excessive osteoclast activation in SIRT6 null mice. Sci Rep, 2018. 8 (1): p. 10992. Kim, S.J., et al., Loss of Sirtuin 6 in osteoblast lineage cells activates osteoclasts, resulting in osteopenia. Bone, 2020. 138 : p. 115497. Zhang, Z., et al., Osteoblasts/Osteocytes sirtuin6 Is Vital to Preventing Ischemic Osteonecrosis Through Targeting VDR-RANKL Signaling. J Bone Miner Res, 2021. 36 (3): p. 579-590. Mu, W., et al., Metformin promotes the proliferation and differentiation of murine preosteoblast by regulating the expression of sirt6 and oct4. Pharmacol Res, 2018. 129 : p. 462-474. Sun, H., et al., SIRT6 regulates osteogenic differentiation of rat bone marrow mesenchymal stem cells partially via suppressing the nuclear factor-kappaB signaling pathway. Stem Cells, 2014. 32 (7): p. 1943-55. Sugatani, T., et al., SIRT6 deficiency culminates in low-turnover osteopenia. Bone, 2015. 81 : p. 168-177. Jo, E.A., et al., The appearance of C1q deposition in transplanted kidney allografts and its clinical and histopathologic features. Korean J Transplant, 2022. 36 (3): p. 180-186. Moon, Y.J., et al., Sirtuin 6 in preosteoclasts suppresses age- and estrogen deficiency-related bone loss by stabilizing estrogen receptor alpha. Cell Death Differ, 2019. 26 (11): p. 2358-2370. Fang, L., et al., SIRT6 Prevents Glucocorticoid-Induced Osteonecrosis of the Femoral Head in Rats. Oxid Med Cell Longev, 2022. 2022 : p. 6360133. Simon, B.R., et al., Sweet taste receptor deficient mice have decreased adiposity and increased bone mass. PLoS One, 2014. 9 (1): p. e86454. Eaton, M.S., et al., Loss of the nutrient sensor TAS1R3 leads to reduced bone resorption. J Physiol Biochem, 2018. 74 (1): p. 3-8. Wang, B., et al., Disruption of PCP signaling causes limb morphogenesis and skeletal defects and may underlie Robinow syndrome and brachydactyly type B. Hum Mol Genet, 2011. 20 (2): p. 271-85. Gong, Y., et al., Vangl2 limits chaperone-mediated autophagy to balance osteogenic differentiation in mesenchymal stem cells. Dev Cell, 2021. 56 (14): p. 2103-2120 e9. Vinik, Y., et al., Ablation of the mammalian lectin galectin-8 induces bone defects in mice. FASEB J, 2018. 32 (5): p. 2366-2380. Deng, P., et al., Loss of KDM4B exacerbates bone-fat imbalance and mesenchymal stromal cell exhaustion in skeletal aging. Cell Stem Cell, 2021. 28 (6): p. 1057-1073 e7. Lin, Y.Y. and L.Q. Dong, APPL1 negatively regulates bone mass, possibly by controlling the fate of bone marrow mesenchymal progenitor cells. Proc Jpn Acad Ser B Phys Biol Sci, 2020. 96 (8): p. 364-371. Arandjelovic, S., et al., ELMO1 signaling is a promoter of osteoclast function and bone loss. Nat Commun, 2021. 12 (1): p. 4974. Klein, S., et al., Modulation of Transient Receptor Potential Channels 3 and 6 Regulates Osteoclast Function with Impact on Trabecular Bone Loss. Calcif Tissue Int, 2020. 106 (6): p. 655-664. Additional Declarations Competing interest reported. Competing Interest: JWL is Editor-in-Chief of Clinical and Translational Metabolism and is financially compensated for this role. Other authors have no financial or propiertary interests to disclose. Supplementary Files DavisetalSupplementalMaterial.pdf Supplementary Materials Table S1. List of multiple terms related to a given signaling pathway (if utilized for search). Table S2. Relative popularity of 145 pathways based on publication between 2018-2022 compared to their status between 2008-2017. Table S3. Relative popularity of 145 pathways based on US NIH grants between 2018-2022 compared to their status between 2008-2017. Table S4. Pathways for which search produced study(ies) from 2018-2022 providing functional evidence implicating an endogenous role in bone remodeling. Cite Share Download PDF Status: Published Journal Publication published 30 Oct, 2025 Read the published version in Clinical & Translational Metabolism → Version 1 posted Editorial decision: Revision requested 27 Sep, 2024 Reviews received at journal 24 Sep, 2024 Reviewers agreed at journal 06 Sep, 2024 Reviewers invited by journal 24 Jul, 2024 Editor assigned by journal 23 Jul, 2024 Submission checks completed at journal 23 Jul, 2024 First submitted to journal 19 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4768994","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":339870629,"identity":"d23e8a1d-5985-4731-ac06-8d38235cd363","order_by":0,"name":"Emily M. Davis","email":"","orcid":"","institution":"Marian University","correspondingAuthor":false,"prefix":"","firstName":"Emily","middleName":"M.","lastName":"Davis","suffix":""},{"id":339870632,"identity":"1fd55437-0038-4c72-ba28-396febe34a28","order_by":1,"name":"Jacob A. Snyder","email":"","orcid":"","institution":"Marian University","correspondingAuthor":false,"prefix":"","firstName":"Jacob","middleName":"A.","lastName":"Snyder","suffix":""},{"id":339870636,"identity":"021116e8-05ce-4f27-b2c1-e29596d237b3","order_by":2,"name":"Basil S. Mustaklem","email":"","orcid":"","institution":"Marian University","correspondingAuthor":false,"prefix":"","firstName":"Basil","middleName":"S.","lastName":"Mustaklem","suffix":""},{"id":339870637,"identity":"607e2b64-f221-419c-92cb-0140d9311452","order_by":3,"name":"Hailey L. Brown","email":"","orcid":"","institution":"Marian University","correspondingAuthor":false,"prefix":"","firstName":"Hailey","middleName":"L.","lastName":"Brown","suffix":""},{"id":339870638,"identity":"a8f1fb00-8519-43f4-afcd-a883064003e2","order_by":4,"name":"Madeline M. Sasse","email":"","orcid":"","institution":"Marian University","correspondingAuthor":false,"prefix":"","firstName":"Madeline","middleName":"M.","lastName":"Sasse","suffix":""},{"id":339870639,"identity":"14850917-0676-431b-bf96-b67b1037dc78","order_by":5,"name":"Connor M. Wakefield","email":"","orcid":"","institution":"Marian University","correspondingAuthor":false,"prefix":"","firstName":"Connor","middleName":"M.","lastName":"Wakefield","suffix":""},{"id":339870640,"identity":"0c958355-2cce-456e-88d2-9ccab121d876","order_by":6,"name":"Elicza A. Day","email":"","orcid":"","institution":"Marian University","correspondingAuthor":false,"prefix":"","firstName":"Elicza","middleName":"A.","lastName":"Day","suffix":""},{"id":339870641,"identity":"9937a600-da0f-4181-b81f-92c88246b597","order_by":7,"name":"Gabriella Battiston","email":"","orcid":"","institution":"Marian University","correspondingAuthor":false,"prefix":"","firstName":"Gabriella","middleName":"","lastName":"Battiston","suffix":""},{"id":339870642,"identity":"88f53aea-5fce-4f9f-8eed-5ddc0f437655","order_by":8,"name":"Sierra Street","email":"","orcid":"","institution":"Marian University","correspondingAuthor":false,"prefix":"","firstName":"Sierra","middleName":"","lastName":"Street","suffix":""},{"id":339870643,"identity":"ca1a1344-b672-4a71-b4c5-7f735f6d1325","order_by":9,"name":"Jonathan W. Lowery","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYBACxnYILQciDjAgSDxamiG0MfFaGJghVGIDXISQFuZm5mMSH/ccTl/bfvbhgZ87GOT4biQQchhbmuSMZ4dzt51JNzjYe4bBWJKwFh6z2zwHgFoOpDEc4G1jSNxAlJY/Bw6nm51/xnDwbxtDPXFaGA4cTjC7kcZwGGhLggERfkn/2XMg3XDbjWcMh2XbJAxnnnmAX4the/Nhgx8HrOXNzqcxf3zbZiPPd5yALYYNYKoZxpfArxwE5CFUHWGVo2AUjIJRMHIBAIyhTG7oNyeXAAAAAElFTkSuQmCC","orcid":"","institution":"Marian University","correspondingAuthor":true,"prefix":"","firstName":"Jonathan","middleName":"W.","lastName":"Lowery","suffix":""}],"badges":[],"createdAt":"2024-07-19 18:06:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4768994/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4768994/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12018-025-09313-x","type":"published","date":"2025-10-30T15:57:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62837687,"identity":"38d3599e-50ba-4002-ae34-48fe723b05d1","added_by":"auto","created_at":"2024-08-20 05:42:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30580,"visible":true,"origin":"","legend":"\u003cp\u003eRelative percentage for the top 25 most popular pathways based on grants and their popularity in NIH grants between 2018-2022.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4768994/v1/ccb9c6a757472bbd66fd5e9e.png"},{"id":62837689,"identity":"84fce26d-3845-4b18-a88c-97c343236cc4","added_by":"auto","created_at":"2024-08-20 05:42:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":22078,"visible":true,"origin":"","legend":"\u003cp\u003eX-Y scatter plot of relationship between frequency of publication and frequency of NIH funding for bone remodeling pathways. Those pathways for which there were no publications or grants in 2018-2022 were removed, allowing analysis on 121 pathways by simple linear regression.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4768994/v1/97fdad3521174957e428be48.png"},{"id":95040431,"identity":"d6122f81-daa8-44e5-af83-282300a930f6","added_by":"auto","created_at":"2025-11-03 16:08:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1055897,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4768994/v1/5329f73a-d2cd-434f-b962-e6361d11b271.pdf"},{"id":62838125,"identity":"af2c71a2-2ee6-4bc4-9f23-ef383ce11841","added_by":"auto","created_at":"2024-08-20 05:50:59","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":242908,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable S1. List of multiple terms related to a given signaling pathway (if utilized for search).\u003c/p\u003e\n\u003cp\u003eTable S2. Relative popularity of 145 pathways based on publication between 2018-2022 compared to their status between 2008-2017.\u003c/p\u003e\n\u003cp\u003eTable S3. Relative popularity of 145 pathways based on US NIH grants between 2018-2022 compared to their status between 2008-2017.\u003c/p\u003e\n\u003cp\u003eTable S4. Pathways for which search produced study(ies) from 2018-2022 providing functional evidence implicating an endogenous role in bone remodeling.\u003c/p\u003e","description":"","filename":"DavisetalSupplementalMaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4768994/v1/27c535c1b44c8601e07d94cf.pdf"}],"financialInterests":"Competing interest reported. Competing Interest: JWL is Editor-in-Chief of Clinical and Translational Metabolism and is financially compensated for this role. Other authors have no financial or propiertary interests to disclose.","formattedTitle":"Bibliometric analysis highlights lesser-studied pathways in bone remodeling","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBone mass is determined by the relative balance of action between osteoblasts, which deposit bone matrix, and osteoclasts, which resorb bone matrix. In humans, bone mass generally declines after age thirty due to the rate of bone resorption exceeding the rate of bone formation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Osteoporosis, \u003cem\u003ei.e.\u003c/em\u003e, low bone mass, is a common medical condition that places individuals at elevated risk of fracture and greater likelihood of disability, loss of independence, and death [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Estimates suggest that up to 49\u0026nbsp;million individuals have osteoporosis in North America, Europe, Japan, and Australia alone [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In the US, hospitalizations for osteoporotic fractures exceed those for heart attack, stroke, and breast cancer [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. And, by 2025 the number of fractures due to osteoporosis may increase to nearly three million in the US alone, creating a \u003cspan\u003e$\u003c/span\u003e25\u0026nbsp;billion financial burden [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Given the relationship between bone mass and osteoporosis \u0026ndash; i.e., \u0026ldquo;an increase of [bone mass] by one standard deviation would reduce the fracture risk by 50% [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u0026rdquo; \u0026ndash; therapies aimed at increasing bone mass are crucial for adequate management of this disease.\u003c/p\u003e \u003cp\u003eBoth anti-resorptive and anabolic medications are available and are generally successful at stabilizing and/or promoting gains in bone mass. However, each current medication has significant drawbacks (including counter-indications, short therapeutic windows, and the potential need for drug holiday) which present considerable challenges for the long-term management of this chronic condition [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Unfortunately, there are few new candidate therapies in the drug development pipeline. This presents an urgent and unmet need for identifying new treatment targets for increasing bone mass \u0026ndash; particularly for those novel pathways that do not yet have a therapeutic modality in development. However, in a 2018 report, we identified a striking lack of heterogeneity among molecular pathways studied in the bone remodeling field, with just three pathways (Wnt, Mitogen-activated protein (MAP) kinase, and the Transforming Growth Factor (TGF)-beta superfamily) accounting for more than 50% of publications (2699 out of 4826 publications) and 46% of United States National Institutes of Health (NIH)-funded grants (862 out of 1850) between 2008\u0026ndash;2017 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Further, adding Parathyroid Hormone (PTH), this list of four pathways accounts for nearly 55% of United States National Institutes of Health (NIH) grants funded during that period (1012 out of 1850 grants) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur prior report highlighted several lesser-studied pathways that garnered limited attention by the field but for which functional evidence (genetic, pharmacological, etc.) was available implicating a role in bone remodeling \u003cem\u003ein vivo\u003c/em\u003e [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Here, we update the prior analysis to the time period of 2018\u0026ndash;2022 to a) examine the heterogeneity of molecular pathways studied in the bone remodeling field in that time and b) determine if new functional evidence has emerged for additional lesser-known pathways which might hold therapeutic potential. Our results confirm a lack of diversity in research that may restrict discovery of novel therapeutic approaches. Additionally, we detail several pathways for which functional evidence supports a role in the regulation of osteoblasts and/or osteoclasts \u003cem\u003ein vivo\u003c/em\u003e and call for an expansion into lesser-studied pathways to broaden the collective focus of the field.\u003c/p\u003e"},{"header":"Materials \u0026 Methods","content":"\u003cp\u003eSearches were performed on PubMed (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) or the NIH Research Portfolio Online Reporting Tools Expenditures and Results (RePORTER, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://reporter.nih.gov\u003c/span\u003e\u003cspan address=\"https://reporter.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) using the search phrase ((\"skeleton\" or \"bone\") and (\"signaling\" or \"pathway\")) and (\"osteoblast\" or \"osteocyte\" or \"osteoclast\")) with results restricted to the five year period between January 1, 2018, and December 31, 2022. This yielded a total of 3,835 publications and 1239 grants on PubMed and RePORTER, respectively. We then added search terms relating to specific signaling pathways (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) to identify the number of publications or grants that mention those pathways.\u003c/p\u003e \u003cp\u003eWe used PubMed to identify lesser-studied pathways in bone remodeling by excluding pathways for which the search returned fifty or more publications in the last five years. Then, to narrow down those lesser-studied pathways to those highlighted in this narrative, we sought to identify particularly notable pathways using the following inclusion criteria: 1) functional evidence (knock-out genetic model, pharmacological intervention, etc.) published in a peer-reviewed journal and indexed in PubMed.gov; 2) fewer than five review articles published about actions of the pathway in the skeleton in the last five years; and 3) identifiable as a distinct signaling pathway rather than a downstream effector of a different pathway.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMost popular pathways by publications\u003c/h2\u003e \u003cp\u003eSearch of the PubMed database generated a set of 3835 publications in the bone remodeling field from 2018\u0026ndash;2022; this closed set was the basis for all subsequent bibliometric analyses below. These publications represent an average rate of 767 publications per year from 2018\u0026ndash;2022, which is accelerated nearly 60% compared to 482.6 per year from 2008\u0026ndash;2017. Adding specific terms to this search detailed the relative popularity of 145 pathways (Table S2). The top ten most popular pathways from 2018\u0026ndash;2022 and their rank from 2008\u0026ndash;2017 are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In both time periods, the RANK Ligand (RANKL) pathway had the greatest frequency of publications (32.5% in 2018\u0026ndash;2022 and 29.2% in 2008\u0026ndash;2017). Similarly, the TGF-beta superfamily was the second most popular pathway in both periods (26.6% in 2018\u0026ndash;2022 and 26.4% in 2008\u0026ndash;2017). Changes in the ranking were noted for other pathways in the former top ten \u0026ndash; most notably with the Wnt pathway and Androgen Receptor pathway falling from third and fifth in 2008\u0026ndash;2017 to fifth and tenth in 2018\u0026ndash;2022, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Similarly, Osteocalcin and Osteoprotegerin \u0026ndash; which were eighth and ninth in 2008\u0026ndash;2017, respectively \u0026ndash; fell from the top ten in 2018\u0026ndash;2022 (Table S2). Two pathways were newcomers to the top ten in 2018\u0026ndash;2022, with the transcription factor Oct4 and the Ak strain transforming (AKT) family moving from eleventh to eighth and twelfth to ninth, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop ten most popular pathways based on publication between 2018\u0026ndash;2022 compared to their status between 2008\u0026ndash;2017.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e2018\u0026ndash;2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e2008\u0026ndash;2017\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTerm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage of Total\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePercentage of Total\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eChange in Rank\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRANKL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e29.24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTGF-beta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.57%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26.38%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMAPK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.19%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFos/Jun\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.93%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.12%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWnt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e813\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22.32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNFATc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.45%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.93%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRunx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.19%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOct4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.53%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.36%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e18.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOur one-by-one pathway search method was unable to distinguish overlapping publications \u0026ndash; i.e., a single publication that included terms from more than one pathway. Thus, we combined search terms for the top five pathways by publication to determine the percentage of the bone remodeling literature examining these pathways. This revealed that these top five pathways alone account for 75.3% of publications in the bone remodeling field from 2018\u0026ndash;2022 (2889 of 3835), which represents sustained popularity compared to the 2008\u0026ndash;2017 time period (78.4%, 3785 of 4826). Expanding the search terms to include all top ten pathways raises the representation of these pathways to 86.2% of publications (3309 of 3835) from 2018\u0026ndash;2022 compared to 89.2% for these pathways from 2008\u0026ndash;2017 (4309 of 4826).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMost popular pathways by US NIH funding\u003c/h2\u003e \u003cp\u003eSearch of the NIH RePORTER database generated a set of 1239 funded grants in the bone remodeling field from 2018\u0026ndash;2022; it is important to note that the methodology of RePORTER generally counts each year of multi-year grants individually rather than just the project overall \u0026ndash; i.e., an award that spans three fiscal years is counted three times instead of once. This closed set was the basis for all subsequent bibliometric analyses below.\u003c/p\u003e \u003cp\u003eThe grants awarded in 2018\u0026ndash;2022 represent an average rate 247.8 per year, which is accelerated nearly 34% compared to the 185 grants per year from 2008\u0026ndash;2017 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Adding specific terms to this search detailed the relative popularity of the pathways examined above (Table S3).\u003c/p\u003e \u003cp\u003eThe top ten most popular pathways by NIH grant funding from 2018\u0026ndash;2022 and their rank from 2008\u0026ndash;2017 are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In both time periods, the Wnt pathway had the greatest frequency of grants (25.2% in 2018\u0026ndash;2022 and 28.1% in 2008\u0026ndash;2017). Similarly, the second, third, and fourth most popular pathways in both time periods were the RANKL, TGF-beta superfamily, and PTH pathways, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Changes in the ranking were noted for other pathways in the top ten \u0026ndash; most notably with Runx2, the MAP kinase family, Estrogen, Osterix, and Nfatc1, which were fifth, sixth, seventh, eighth, and tenth in 2008\u0026ndash;2017, respectively, falling out of the top ten entirely (Table S3). The Tumor Necrosis Factor (TNF)-alpha pathway climbed to fifth in 2018\u0026ndash;2022 from ninth in 2008\u0026ndash;2017 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Five pathways were newcomers to the top ten in 2018\u0026ndash;2022: Osteoprotegerin, Cadherin superfamily, Insulin, Interleukin superfamily, and Osteocalcin (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop ten most popular pathways based on United States National Institutes of Health grants between 2018\u0026ndash;2022 compared to their status between 2008\u0026ndash;2017.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e2018\u0026ndash;2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e2008\u0026ndash;2017\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTerm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage of Total\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePercentage of Total\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eChange in Rank\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWnt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e28.11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRANKL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.06%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMP/TGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e18.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePTH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.43%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.43%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.46%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.68%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOPG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.59%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.76%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCadherin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.43%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.05%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterleukin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOsteocalcin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe then combined search terms for the top five pathways by funding to determine the percentage of NIH funding in the bone remodeling field that examined these pathways in 2018\u0026ndash;2022. This revealed that these top five pathways alone account for 53.1% of grants in the bone remodeling field in this time period (658 of 1239). Moreover, just the top four pathways (Wnt, RANKL, TGF-beta superfamily, and PTH) account for approximately half of NIH funding in bone remodeling in 2018\u0026ndash;2022 (619 of 1239), which represents sustained popularity compared to the 2008\u0026ndash;2017 time period (62.25%) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Expanding the search terms to include all top ten pathways raises the representation of these pathways to 60.5% of grants (749 of 1239) from 2018\u0026ndash;2022 compared to 67.5% for those same pathways from 2008\u0026ndash;2017 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eComparing publications and funding\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the relative percentage for the top 25 most popular pathways based on grants and their popularity in NIH grants. We were interested to examine the potential correlation between frequency of publication and frequency of NIH funding for bone remodeling pathways. After removing those pathways for which there were no publications and no NIH grants in 2018\u0026ndash;2022, we found a R-squared value of 0.4336 by simple linear regression analysis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) for the remaining 121 pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eNotable yet lesser-studied pathways\u003c/h2\u003e \u003cp\u003eIn our prior report, we developed a search method in PubMed involving a combination of exclusion and inclusion criteria to identify notable yet lesser-studied pathways in bone remodeling [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This produced a refined set of nine pathways (Apolipoprotein D (ApoD), Aryl Hydrocarbon Receptor (AhR), Lysophosphatidic Acid (LPA), Osteoclast Inhibitory Factor (OIP)-1, Oxytocin, Taste Receptor Type 1 (Tas1R) Family, Neuromedin U (NMU), Tyro3, and Type 1 Equilibrative Nucleoside Transporter (ENT1)) for which there was functional evidence to implicate a role in the regulation of osteoblasts and/or osteoclasts \u003cem\u003ein vivo\u003c/em\u003e. The number of publications for these pathways between 2018\u0026ndash;2022 compared to 2008\u0026ndash;2017 is presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Among these, the AhR and NMU pathways have received considerably greater attention between 2018\u0026ndash;2022 compared to the ten years prior. Additionally, only the AhR, LPA, NMU, and OIP-1 pathways are subjects of NIH-funded grants: AhR, R01AR074930; LPA, R21AR055192, R01DK121776, R03HD042066; NMU: 1R03AG081947; OIP, R01DE012603.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePublication rate between 2018\u0026ndash;2022 compared to 2008\u0026ndash;2017 for pathways highlighted in 2018 study using the narrow search terms described in the methods section.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e2018\u0026ndash;2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e2008\u0026ndash;2017\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTerm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage of Total\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePercentage of Total\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eChange in Rank\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAhR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.42%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.19%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNMU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOxytocin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.19%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAS1R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApoD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOIP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTyro3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo identify additional notable yet lesser-studied pathways, we searched PubMed to exclude pathways for which there were fifty or more publications in the last five years (Table S2), resulting in a refined set of 232 publications. Among these, twelve publications examined pathways highlighted in our previous report [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. We screened the remaining 220 publications using the same inclusion criteria as our prior report [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This produced a refined list of 20 lesser-studied pathways for which there was functional evidence (knock-out genetic model, pharmacological intervention, etc.) reported between 2018\u0026ndash;2022 implicating an endogenous role in bone remodeling (Table S4); some of these details are discussed below.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo us, the findings above demonstrate a striking lack of heterogeneity in the pathways studied by the bone remodeling field overall. Moreover, given the heavy enrichment for just a few pathways over the last fifteen years, the lack of diversity may limit paradigm-changing discoveries and restrict novel therapeutic approaches for osteoporosis. In 2018, we called for an expansion into lesser-studied pathways to broaden the collective focus of the field [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. We additionally highlighted nine pathways for which there was functional evidence to implicate a role in the regulation of bone remodeling in vivo [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Among these, two (the AhR and NMU pathways) have received considerably greater attention while four (the AhR, LPA, NMU, and OIP-1 pathways) are subjects of NIH-funded grants. However, relatively little progress has been made in the understanding and/or therapeutic potential of the other pathways we highlighted. Here, we identified an additional twenty pathways for which functional evidence was reported between 2018\u0026ndash;2022 implicating a role in bone remodeling \u003cem\u003ein vivo\u003c/em\u003e. In the sections below, we highlight several pathways that, to us, are particularly noteworthy as potential \u0026ldquo;low-hanging fruit\u0026rdquo; for future study.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCD82\u003c/h2\u003e \u003cp\u003eConditional deletion of the transmembrane scaffolding protein \u003cem\u003eCD82\u003c/em\u003e in the osteoclast lineage leads to increased trabecular bone mass with deficits in osteoclast differentiation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, it is important to note that a separate study using global knockout of \u003cem\u003eCD82\u003c/em\u003e revealed this protein is involved in both osteoblast and osteoclast compartments and the net effect of knockout is smaller bones with no change in bone mineral density [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Thus, translational studies aimed at targeting this factor in bone metabolism may require selectively inhibiting its action in osteoclasts while preserving its function in osteoblasts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eChemerin\u003c/h2\u003e \u003cp\u003eChemerin, encoded by \u003cem\u003eRARRES2\u003c/em\u003e, is an adipokine which signals through chemokine-like receptor 1 (CMKLR1) and is expressed by adipocytes, mesenchymal stem cells, osteoblasts, and osteoclasts [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Numerous studies in healthy adults or populations with specific diseases/conditions [\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19 CR20\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and animal models [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] report that serum chemerin levels are inversely related to bone mass [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Moreover, chemerin is required for osteoclastic differentiation [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and targeting chemerin via neutralizing antibodies \u003cem\u003ein vivo\u003c/em\u003e results in near complete loss of osteoclastogenesis with correspondingly high bone mass [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This raises the possibility of translational studies aimed at pharmacological inhibition of chemerin to increase bone mass. However, it is important to note that CMKLR1 is involved in regulating testosterone production by Leydig Cells in the male gonads [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], which may complicate systemic targeting of chemerin activity and require more targeted strategies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFAM210A\u003c/h2\u003e \u003cp\u003eSeveral genetic variations at the \u003cem\u003eFAM210A\u003c/em\u003e locus in humans are associated with bone mineral density and fracture. And, global loss of FAM210A expression in mice is associated with low bone mass due to reduced bone formation and increased bone resorption [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Yet, this factor is not abundantly expressed in the bone microenvironment and skeletal muscle-specific loss of FAM210A also leads to low bone mass [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], suggesting that it may play an indirect role in bone metabolism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMenin\u003c/h2\u003e \u003cp\u003eMenin is a nuclear protein encoded by the \u003cem\u003eMEN1\u003c/em\u003e gene and is involved in transcription regulation and chromatin remodeling, and genome stability. Deleterious mutations in \u003cem\u003eMEN1\u003c/em\u003e are associated with the rare autosomal dominant disorder Multiple Endocrine Neoplasia type 1, which is characterized by the development of tumors in multiple endocrine glands, including the parathyroid glands, pancreatic islet cells, and the anterior pituitary. The location of these tumors and endocrinological interaction with the skeleton underlies symptoms of bone pain and early-onset osteoporosis found in this disease. However, several lines of evidence support a direct role for menin in bone metabolism through regulating osteoblast differentiation and/or activity. For instance, conditional knockout of \u003cem\u003emenin\u003c/em\u003e in various stages of mesenchymal stem cells or the osteoblast lineage is associated with intense reduction of bone mass and concurrent decrease in number of osteoblasts [\u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. These data are consistent with evidence that menin controls expression of type 1 collagen, alkaline phosphatase, and osteocalcin through interaction with the BMP and/or TGF-beta pathways [\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Collectively, these data raise the possibility that strategies aimed at increasing menin production in the osteoblast lineage may hold therapeutic potential for raising bone mass; indeed, mice overexpressing menin in osteoblasts from had increased bone volume [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eNMU\u003c/h2\u003e \u003cp\u003eNMU is an evolutionarily conserved peptide that is expressed in two major molecular forms, both of which are derived from the same mRNA and display similar receptor affinity for the heterotrimeric Gq/11-protein-coupled receptors NMU Receptor 1 (NMUR1) and NMU Receptor 2 (NMUR2) to regulate similar downstream targets [\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. NMUR1 is more broadly expressed than NMUR2 (see the Human Protein Atlas, proteinatlas.org) yet both are expressed in the bone microenvironment [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Two independent studies in mice implicate NMU as a negative regulator of bone formation [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Many of the effects of NMU are attributed to its actions in the hypothalamus; indeed, this was initially proposed to be the mechanism by which NMU regulates bone metabolism since over-activation of the NMU pathway in this location reduces bone remodeling in the appendicular skeleton [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. However, interpretation of those findings is complicated by the non-wildtype genetic background and \u0026ldquo;rescue\u0026rdquo; design of the experiment. Moreover, hypothalamus-specific knockdown of endogenous \u003cem\u003eNmu\u003c/em\u003e expression does not impact bone mass despite \u0026gt;\u0026thinsp;92% knockdown efficiency [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] and NMU has direct effects on suppressing osteoblastic differentiation of osteoprogenitor cells \u003cem\u003ein vitro\u003c/em\u003e [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Given that NMU and its receptors are expressed in bone in vivo [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], these findings leave open the possibility that the negative effects of NMU on bone formation are accomplished in the bone microenvironment itself and could be targeted as a potential anabolic therapy for increasing bone mass.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSirtuin-6\u003c/h2\u003e \u003cp\u003eSirtuin-6 is a sirtuin family protein that plays a vital role in genomic stability, aging, metabolism, and stress response via NAD\u003csup\u003e+\u003c/sup\u003e-dependent deacetylase activity. Functional evidence has indicated Sirt-6 plays a vital role in promoting osteoblastogenesis and preventing bone resorption. Several \u003cem\u003ein vitro\u003c/em\u003e experiments have revealed that microRNAs \u0026ndash; specifically miR-545-3p, miR-186, and miR-128 \u0026ndash; bind to Sirt-6-3\u0026rsquo;UTR to downregulate its activity, resulting in decreased expression of osteoblastic markers and increased expression of osteoclastic markers [\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Additionally, osteoblast/osteocyte-specific knockout of \u003cem\u003eSirtuin-6\u003c/em\u003e has been shown to promote the phosphorylation of NF-kappaB, increasing RANKL-induced osteoclastogenesis, bone resorption, and expression of inflammatory cytokines as well as decreasing mature osteoblast function [\u003cspan additionalcitationids=\"CR46 CR47 CR48\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Restoration of Sirt-6 expression significantly reverses the increased expression of RANKL and proinflammatory cytokines [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. \u003cem\u003eIn vivo\u003c/em\u003e experiments also revealed decreased trabecular bone mass/cortical bone thickness in homozygous \u003cem\u003eSirt-6\u003c/em\u003e mutant mice [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], cavitation of femoral heads in mice with decreased Sirt-6 expression due to glucocorticoid-induced osteonecrosis [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], and decreased bone mass and apoptosis in aged \u003cem\u003eSirt-6\u003c/em\u003e knockout mice. Reintroduction of Sirt-6 expression in the aforementioned \u003cem\u003eSirt-6\u003c/em\u003e knockout models restores apoptosis of osteoclasts [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], increases osteoblast viability [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], and is associated with improved bone formation and calcification of tissues [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. These studies call to mind studies aimed at increasing expression of Sirtuin-6 as an anabolic strategy to increase bone mass.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eTas1R\u003c/h2\u003e \u003cp\u003eAt least two of the Taste Receptor Tas1R family of heterotrimeric G-protein coupled receptors, which function in non-gustatory tissues as nutritional sensors, regulates bone metabolism as knock-out of \u003cem\u003eTas1R2\u003c/em\u003e or \u003cem\u003eTas1R3\u003c/em\u003e leads to high bone mass [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. These two receptors are capable of heterodimerizing with one another as a means of monitoring extracellular glucose levels and, given that the serum marker of osteoclastic activity CTx is dramatically reduced in \u003cem\u003eTas1R3\u003c/em\u003e knockout mice[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], is possible that pharmacological targeting of this pathway could disrupt osteoclast function.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eVangl2\u003c/h2\u003e \u003cp\u003eVang-like protein 2 (Vangl2) is an essential component of the planar cell polarity (PCP) signaling pathway and is involved in various developmental and physiological functions. \u003cem\u003eVangl2\u003c/em\u003e mutations are associated with skeletal patterning defects including malformed digit development [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Additionally, a specific role for Vangl2 in the negative regulation of osteoblasts comes from a report involving conditional deletion of this factor in the embryonic limb bud, which is associated with enhanced osteoblast differentiation of precursors and high bone mass in the postnatal skeleton [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. This model also revealed increased bone formation rate in the absence of Vangl2 expression with no defects in bone resorption, suggesting that strategies aimed at limiting this factor in the osteoblastic lineage may hold promise as an anabolic therapy for increasing bone mass.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMiscellaneous\u003c/h2\u003e \u003cp\u003eIn addition to the above pathways, there are several others for which functional evidence indicates an endogenous role in bone remodeling and potential opportunity for therapeutic modulation. For instance, galectin-8 mediates coupling between osteoclasts and osteoblasts and global loss of this factor results in accelerated age-related bone loss [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Similarly, conditional deletion of the gene encoding Lysine (K)-specific demethylase 4B (KDM4B) in the embryonic limb bud is associated with enhanced age-related bone loss with selective defects in osteoblast activity (but not osteoclast activity) and increased bone marrow adipocity [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. On the other hand, global loss of expression of Adaptor protein containing pleckstrin homology domain, phosphotryosine binding domain and leucine zipper motif (APPL1) \u0026ndash; which plays an important role in intracellular signaling and vesicle trafficking and is an adaptor protein of the adiponectin receptor \u0026ndash; leads to high bone mass associated with higher number of osteoblasts and reduced bone marrow adipocity [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEngulfment and Cell Motility Protein 1 (ELMO1) plays a significant role in osteoclast function as global loss of this factor reduces bone resorption in two mouse models of osteoporosis [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]; importantly, this study provided details on a peptide capable of disrupting ELMO1 function and reducing osteoclast activity \u003cem\u003ein vitro\u003c/em\u003e, thus providing rationale for future studies examining this or other inhibitors as a means of dampening bone resorption. Finally, global loss of Transient Receptor Potential Cation Channel, Subfamily C, Member 6 (TRPC6) expression results in low bone mass with increased osteoclastic activity [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe primary aim of this report is to detail a striking lack of diversity in research published in the bone remodeling field. This causes us concern as it may restrict discovery of novel therapeutic approaches in metabolic bone disease. Yet, there are myriad pathways for which there is solid evidence pinpointing a functional role in the regulation of bone metabolism \u0026ndash; but many of these are understudied or remain obscure within the literature. Thus, a secondary aim of this report is to detail several lesser-studied pathways that are particularly compelling for us and call for broadening the collective focus of the field to enhance the likelihood of future therapy development.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, EMD and JWL; Methodology, EMD and JWL; Formal Analysis, JWL; Investigation, EMD, JAS, BSM, HLB, MMS, CMW, EAD, GB, SS, and JWL; Resources, JWL.; Data Curation, EMD and JWL; Writing – Original Draft Preparation, EMD, JAS, BSM, HLB, MMS, CMW, EAD, GB, SS, and JWL.; Writing – Review \u0026amp; Editing, EMD, JAS, BSM, HLB, MMS, CMW, EAD, GB, SS, and JWL.; Visualization, JWL; Supervision, JWL.; Project Administration, JWL.; Funding Acquisition, JWL. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding was provided by intramural funds issued to JWL.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not involve human subjects and IRB approval is not applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDatasets used and/or analyzed are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe wish to acknowledge the support and helpful feedback from members of the Marian University Bone \u0026amp; Muscle Research Group and the Indiana Center for Musculoskeletal Health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompeting Interest: JWL is Editor-in-Chief of \u003cem\u003eClinical and Translational Metabolism\u003c/em\u003e and is financially compensated for this role. Other authors have no financial or propiertary interests to disclose.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRaisz, L.G., \u003cem\u003ePathogenesis of osteoporosis: concepts, conflicts, and prospects.\u003c/em\u003e J Clin Invest, 2005. \u003cstrong\u003e115\u003c/strong\u003e(12): p. 3318-25.\u003c/li\u003e\n\u003cli\u003eLeboime, A., et al., \u003cem\u003eOsteoporosis and mortality.\u003c/em\u003e Joint Bone Spine, 2010. \u003cstrong\u003e77 Suppl 2\u003c/strong\u003e: p. 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Dong, \u003cem\u003eAPPL1 negatively regulates bone mass, possibly by controlling the fate of bone marrow mesenchymal progenitor cells.\u003c/em\u003e Proc Jpn Acad Ser B Phys Biol Sci, 2020. \u003cstrong\u003e96\u003c/strong\u003e(8): p. 364-371.\u003c/li\u003e\n\u003cli\u003eArandjelovic, S., et al., \u003cem\u003eELMO1 signaling is a promoter of osteoclast function and bone loss.\u003c/em\u003e Nat Commun, 2021. \u003cstrong\u003e12\u003c/strong\u003e(1): p. 4974.\u003c/li\u003e\n\u003cli\u003eKlein, S., et al., \u003cem\u003eModulation of Transient Receptor Potential Channels 3 and 6 Regulates Osteoclast Function with Impact on Trabecular Bone Loss.\u003c/em\u003e Calcif Tissue Int, 2020. \u003cstrong\u003e106\u003c/strong\u003e(6): p. 655-664.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"clinical-and-translational-metabolism","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Clinical \u0026 Translational Metabolism](https://link.springer.com/journal/12018)","snPcode":"12018","submissionUrl":"https://submission.springernature.com/new-submission/12018/3","title":"Clinical \u0026 Translational Metabolism","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Osteoporosis, bone remodeling, cell signaling, osteoblast, osteoclast ","lastPublishedDoi":"10.21203/rs.3.rs-4768994/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4768994/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBone mass is determined by the relative balance of action between osteoblasts, which deposit bone matrix, and osteoclasts, which resorb bone matrix. Imbalance in these actions leads to conditions of high or low bone mass. Osteoporosis, \u003cem\u003ei.e.\u003c/em\u003e, low bone mass, is a common medical condition that places individuals at elevated risk of fracture and greater likelihood of disability, loss of independence, and death. Both anti-resorptive and anabolic medications are available and are generally successful at stabilizing and/or promoting gains in bone mass. However, each current medication has significant drawbacks which present considerable challenges for the long-term management of this chronic condition. Unfortunately, there are few new candidate therapies in the drug development pipeline. This underscores a need for identifying new treatment targets for increasing bone mass, particularly for novel pathways lacking a therapeutic modality in development. However, a report from 2018 identified a striking lack of heterogeneity among molecular pathways studied in the bone remodeling field, with just three pathways accounting for more than 50% of publications and 46% of United States National Institutes of Health-funded grants. Here, we update the prior analysis to 2018-2022 to a) examine the heterogeneity of molecular pathways studied in the bone remodeling field in that time and b) determine if new functional evidence has emerged for additional lesser-known pathways which might hold therapeutic potential. Our results reveal a sustained lack of diversity in research that may restrict discovery of novel therapeutic approaches. We call for an expansion into lesser-studied pathways to broaden the collective focus of the field and highlight several pathways for which functional evidence supports a role in the regulation of bone remodeling. Future work is required to determine therapeutic potential and elucidate the mechanism(s) by which these pathways intersect with the complicated signal transduction network underlying bone remodeling.\u003c/p\u003e","manuscriptTitle":"Bibliometric analysis highlights lesser-studied pathways in bone remodeling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-20 05:42:55","doi":"10.21203/rs.3.rs-4768994/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-27T09:10:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-24T10:39:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"92787540818974193897428297763955985703","date":"2024-09-06T08:37:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-24T13:48:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-24T02:57:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-23T23:49:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"Clinical \u0026 Translational Metabolism","date":"2024-07-19T18:05:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"clinical-and-translational-metabolism","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Clinical \u0026 Translational Metabolism](https://link.springer.com/journal/12018)","snPcode":"12018","submissionUrl":"https://submission.springernature.com/new-submission/12018/3","title":"Clinical \u0026 Translational Metabolism","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d524ba39-5210-4b40-8acc-3f5bfc377a10","owner":[],"postedDate":"August 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-03T16:04:12+00:00","versionOfRecord":{"articleIdentity":"rs-4768994","link":"https://doi.org/10.1007/s12018-025-09313-x","journal":{"identity":"clinical-and-translational-metabolism","isVorOnly":false,"title":"Clinical \u0026 Translational Metabolism"},"publishedOn":"2025-10-30 15:57:44","publishedOnDateReadable":"October 30th, 2025"},"versionCreatedAt":"2024-08-20 05:42:55","video":"","vorDoi":"10.1007/s12018-025-09313-x","vorDoiUrl":"https://doi.org/10.1007/s12018-025-09313-x","workflowStages":[]},"version":"v1","identity":"rs-4768994","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4768994","identity":"rs-4768994","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}