Liver X receptors (LXRs) α and β are transcriptional regulators of cholesterol homeostasis and potential targets for the development of antiatherosclerosis drugs. However, the specific roles of individual LXR isotypes in atherosclerosis and the pharmacological effects of synthetic agonists remain unclear. Previous work has shown that mice lacking LXRα accumulate cholesterol in the liver but not in peripheral tissues. In striking contrast, we demonstrate here that LXRα–/–apoE–/– mice exhibit extreme cholesterol accumulation in peripheral tissues, a dramatic increase in whole-body cholesterol burden, and accelerated atherosclerosis. The phenotype of these mice suggests that the level of LXR pathway activation in macrophages achieved by LXRβ and endogenous ligand is unable to maintain homeostasis in the setting of hypercholesterolemia. Surprisingly, however, a highly efficacious synthetic agonist was able to compensate for the loss of LXRα. Treatment of LXRα–/–apoE–/– mice with synthetic LXR ligand ameliorates the cholesterol overload phenotype and reduces atherosclerosis. These observations indicate that LXRα has an essential role in maintaining peripheral cholesterol homeostasis in the context of hypercholesterolemia and provide in vivo support for drug development strategies targeting LXRβ.
Michelle N. Bradley, Cynthia Hong, Mingyi Chen, Sean B. Joseph, Damien C. Wilpitz, Xuping Wang, Aldons J. Lusis, Allan Collins, Willa A. Hseuh, Jon L. Collins, Rajendra K. Tangirala, Peter Tontonoz
Usage data is cumulative from January 2024 through January 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 383 | 71 |
105 | 42 | |
Figure | 221 | 8 |
Table | 31 | 0 |
Citation downloads | 40 | 0 |
Totals | 780 | 121 |
Total Views | 901 |
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.