Dual PPARα/γ agonists that were developed to target hyperlipidemia and hyperglycemia in patients with type 2 diabetes caused cardiac dysfunction or other adverse effects. We studied the mechanisms that underlie the cardiotoxic effects of a dual PPARα/γ agonist, tesaglitazar, in wild-type and diabetic (leptin receptor–deficient, db/db) mice. Mice treated with tesaglitazar-containing chow or high-fat diet developed cardiac dysfunction despite lower plasma triglycerides and glucose levels. Expression of cardiac PPARγ coactivator 1-α (PGC1α), which promotes mitochondrial biogenesis, had the most profound reduction among various fatty acid metabolism genes. Furthermore, we observed increased acetylation of PGC1α, which suggests PGC1α inhibition and lowered sirtuin 1 (SIRT1) expression. This change was associated with lower mitochondrial abundance. Combined pharmacological activation of PPARα and PPARγ in C57BL/6 mice reproduced the reduction of PGC1α expression and mitochondrial abundance. Resveratrol-mediated SIRT1 activation attenuated tesaglitazar-induced cardiac dysfunction and corrected myocardial mitochondrial respiration in C57BL/6 and diabetic mice but not in cardiomyocyte-specific Sirt1–/– mice. Our data show that drugs that activate both PPARα and PPARγ lead to cardiac dysfunction associated with PGC1α suppression and lower mitochondrial abundance, likely due to competition between these 2 transcription factors.
Charikleia Kalliora, Ioannis D. Kyriazis, Shin-ichi Oka, Melissa J. Lieu, Yujia Yue, Estela Area-Gomez, Christine J. Pol, Ying Tian, Wataru Mizushima, Adave Chin, Diego Scerbo, P. Christian Schulze, Mete Civelek, Junichi Sadoshima, Muniswamy Madesh, Ira J. Goldberg, Konstantinos Drosatos
Usage data is cumulative from May 2020 through May 2021.
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.