Increased PLEKHO1 within osteoblasts suppresses Smad-dependent BMP signaling to inhibit bone formation during aging
Emerging evidence indicates that the dysregulation of protein ubiquitination plays a crucial role in aging-associated diseases. Smad-dependent canonical BMP signaling pathway is indispensable for osteoblastic bone formation, which could be disrupted by the ubiquitination and subsequent proteasomal degradation of Smad1/5, the key molecules for BMP signaling transduction. However, whether the dysregulation of Smad1/5 ubiquitination and disrupted BMP signaling pathway is responsible for the age-related bone formation reduction is still underexplored. Pleckstrin homology domain-containing family O member 1 (PLEKHO1) is a previously identified ubiquitination-related molecule that could specifically target the linker region between the WW domains of Smurf1 to promote the ubiquitination of Smad1/5. Here, we found an age-related increase in the expression of PLEKHO1 in bone specimens from either fractured patients or aging rodents, which was associated with the age-related reduction in Smad-dependent BMP signaling and bone formation. By genetic approach, we demonstrated that loss of Plekho1 in osteoblasts could promote the Smad-dependent BMP signaling and alleviated the age-related boneformation reduction. In addition, osteoblast-specific Smad1 overexpression had beneficial effect on bone formation during aging, which could be counteracted after overexpressing Plekho1 within osteoblasts. By pharmacological approach, we showed that osteoblast-targeted Plekho1siRNA treatment could enhance Smad-dependent BMP signaling and promote bone formation in aging rodents. Taken together, it suggests that the increased PLEKHO1 could suppress Smad-dependent BMP signaling to inhibit bone formation during aging, indicating the translational potential of targeting PLEKHO1 in osteoblast as a novel bone anabolic strategy for reversing established osteoporosis during aging.
Authors: Liu J1,2,3, Liang C1,2,3, Guo B1,2,3, Wu X1,2,3, Li D1,2,3, Zhang Z4, Zheng K1,5, Dang L1,2,3, He X1,2,3,5, Lu C1,6, Peng S1,7, Pan X1,8, Zhang BT4, Lu A1,2,3, Zhang G1,2,3.
Influence Factor: 3.357
Citation: Aging Cell 16, 360-376 (2017).