Paradoxical Sost gene expression response to mechanical unloading in metaphyseal bone

The Sost gene encodes Sclerostin, an inhibitor of Wnt-signaling, generally considered a main response gene to mechanical loading in bone. Several papers describe that unloading leads to upregulation of Sost, which in turn may lead to loss of bone. These studies were based on whole bone homogenates or cortical bone. By serendipity, we noted an opposite response to unloading in the proximal rat tibia. Therefore, we hypothesized that Sost-expression in response to changes in mechanical load is bone site specific. One hind limb of male, 3 month old rats was unloaded by paralyzing the extensors with Botulinium toxin A (Botox) injections. A series of experiments compared the expression of Sost mRNA in the unloaded and contralateral, loaded limbs, after 3 or 10 days, in metaphyseal cancellous bone, metaphyseal cortical bone, and diaphyseal cortical bone. We also conducted μCT to confirm changes in bone volume density related to unloading. Sost mRNA expression in the cancellous metaphyseal bone was downregulated almost 2-fold, both 3 days and 10 days after unloading (P<0.05). A similar tendency was seen in the metaphyseal cortical bone, in which Sost was 1.5-fold downregulated (P<0.05) after 10days, but not significantly changed after 3days. In contrast, diaphyseal cortical Sost expression was instead upregulated 1.4-fold (P<0.05) following 3-day unloading, while there was no significant change after 10days. Cancellous bone volume density was 58% lower (P<0.001, compared to cage controls) in the unloaded limb but not significantly affected in the loaded limb. The results suggest that Sost mRNA expression in metaphyseal bone responds to mechanical unloading in an opposite direction to that observed in diaphyseal cortical bone. This proposes a more complex expression pattern for Sost in response to unloading. Therapeutics that target Sclerostin during altered loading conditions may result in local bone mass changes that are difficult to predict.