Usage Information
Citation Information: J Clin Invest. 2018;128(12):5251-5266. https://doi.org/10.1172/JCI99044.
Abstract
Bone marrow mesenchymal stem cells (BMSCs) exhibit an age-related lineage switch between osteogenic and adipogenic fates, which contributes to bone loss and adiposity. Here we identified a long noncoding RNA, Bmncr, which regulated the fate of BMSCs during aging. Mice depleted of Bmncr (Bmncr-KO) showed decreased bone mass and increased bone marrow adiposity, whereas transgenic overexpression of Bmncr (Bmncr-Tg) alleviated bone loss and bone marrow fat accumulation. Bmncr regulated the osteogenic niche of BMSCs by maintaining extracellular matrix protein fibromodulin (FMOD) and activation of the BMP2 pathway. Bmncr affected local 3D chromatin structure and transcription of Fmod. The absence of Fmod modified the bone phenotype of Bmncr-Tg mice. Further analysis revealed that Bmncr would serve as a scaffold to facilitate the interaction of TAZ and ABL, and thus facilitate the assembly of the TAZ and RUNX2/PPARG transcriptional complex, promoting osteogenesis and inhibiting adipogenesis. Adeno-associated viral-mediated overexpression of Taz in osteoprogenitors alleviated bone loss and marrow fat accumulation in Bmncr-KO mice. Furthermore, restoring BMNCR levels in human BMSCs reversed the age-related switch between osteoblast and adipocyte differentiation. Our findings indicate that Bmncr is a key regulator of the age-related osteogenic niche alteration and cell fate switch of BMSCs.
Authors
Chang-Jun Li, Ye Xiao, Mi Yang, Tian Su, Xi Sun, Qi Guo, Yan Huang, Xiang-Hang Luo
Usage data is cumulative from February 2024 through February 2025.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 751 | 193 |
| 95 | 73 | |
| Figure | 463 | 6 |
| Supplemental data | 49 | 9 |
| Citation downloads | 71 | 0 |
| Totals | 1,429 | 281 |
| Total Views | 1,710 | |
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.
Copyright © 2025 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)