Hypertriglyceridemia is an independent risk factor for cardiovascular disease, and plasma triglycerides (TGs) correlate strongly with plasma apolipoprotein C-III (ApoC-III) levels. Antisense oligonucleotides (ASOs) for ApoC-III reduce plasma TGs in primates and mice, but the underlying mechanism of action remains controversial. We determined that a murine-specific ApoC-III–targeting ASO reduces fasting TG levels through a mechanism that is dependent on low-density lipoprotein receptors (LDLRs) and LDLR-related protein 1 (LRP1). ApoC-III ASO treatment lowered plasma TGs in mice lacking lipoprotein lipase (LPL), hepatic heparan sulfate proteoglycan (HSPG) receptors, LDLR, or LRP1 and in animals with combined deletion of the genes encoding HSPG receptors and LDLRs or LRP1. However, the ApoC-III ASO did not lower TG levels in mice lacking both LDLR and LRP1. LDLR and LRP1 were also required for ApoC-III ASO–induced reduction of plasma TGs in mice fed a high-fat diet, in postprandial clearance studies, and when ApoC-III–rich or ApoC-III–depleted lipoproteins were injected into mice. ASO reduction of ApoC-III had no effect on VLDL secretion, heparin-induced TG reduction, or uptake of lipids into heart and skeletal muscle. Our data indicate that ApoC-III inhibits turnover of TG-rich lipoproteins primarily through a hepatic clearance mechanism mediated by the LDLR/LRP1 axis.
Philip L.S.M. Gordts, Ryan Nock, Ni-Huiping Son, Bastian Ramms, Irene Lew, Jon C. Gonzales, Bryan E. Thacker, Debapriya Basu, Richard G. Lee, Adam E. Mullick, Mark J. Graham, Ira J. Goldberg, Rosanne M. Crooke, Joseph L. Witztum, Jeffrey D. Esko
Usage data is cumulative from May 2023 through May 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 654 | 277 |
142 | 72 | |
Figure | 248 | 24 |
Supplemental data | 30 | 8 |
Citation downloads | 17 | 0 |
Totals | 1,091 | 381 |
Total Views | 1,472 |
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.