Coupling is the process that links bone resorption to bone formation in a temporally and spatially coordinated manner within the remodeling cycle. Several lines of evidence point to the critical roles of osteoclast-derived coupling factors in the regulation of osteoblast performance. Here, we used a fractionated secretomic approach and identified the axon-guidance molecule SLIT3 as a clastokine that stimulated osteoblast migration and proliferation by activating β-catenin. SLIT3 also inhibited bone resorption by suppressing osteoclast differentiation in an autocrine manner. Mice deficient in Slit3 or its receptor, Robo1, exhibited osteopenic phenotypes due to a decrease in bone formation and increase in bone resorption. Mice lacking Slit3 specifically in osteoclasts had low bone mass, whereas mice with either neuron-specific Slit3 deletion or osteoblast-specific Slit3 deletion had normal bone mass, thereby indicating the importance of SLIT3 as a local determinant of bone metabolism. In postmenopausal women, higher circulating SLIT3 levels were associated with increased bone mass. Notably, injection of a truncated recombinant SLIT3 markedly rescued bone loss after an ovariectomy. Thus, these results indicate that SLIT3 plays an osteoprotective role by synchronously stimulating bone formation and inhibiting bone resorption, making it a potential therapeutic target for metabolic bone diseases.
Beom-Jun Kim, Young-Sun Lee, Sun-Young Lee, Wook-Young Baek, Young Jin Choi, Sung Ah Moon, Seung Hun Lee, Jung-Eun Kim, Eun-Ju Chang, Eun-Young Kim, Jin Yoon, Seung-Whan Kim, Sung Ho Ryu, Sun-Kyeong Lee, Joseph A. Lorenzo, Seong Hee Ahn, Hyeonmok Kim, Ki-Up Lee, Ghi Su Kim, Jung-Min Koh
Usage data is cumulative from November 2018 through November 2019.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.