Although cardiovascular disease (CVD) is the leading cause of morbimortality worldwide, promising new drug candidates are lacking. We compared the arterial high-resolution proteome of patients with advanced versus early-stage CVD to predict, from a library of small bioactive molecules, drug candidates able to reverse this disease signature. Of the approximately 4000 identified proteins, 100 proteins were upregulated and 52 were downregulated in advanced-stage CVD. Arachidonyl trifluoromethyl ketone (AACOCF3), a cytosolic phospholipase A2 (cPLA2) inhibitor was predicted as the top drug able to reverse the advanced-stage CVD signature. Vascular cPLA2 expression was increased in patients with advanced-stage CVD. Treatment with AACOCF3 significantly reduced vascular calcification in a cholecalciferol-overload mouse model and inhibited osteoinductive signaling in vivo and in vitro in human aortic smooth muscle cells. In conclusion, using a systems biology approach, we have identified a potentially new compound that prevented typical vascular calcification in CVD in vivo. Apart from the clear effect of this approach in CVD, such strategy should also be able to generate novel drug candidates in other complex diseases.
Joost P. Schanstra, Trang T.D. Luong, Manousos Makridakis, Sophie Van Linthout, Vasiliki Lygirou, Agnieszka Latosinska, Ioana Alesutan, Beate Boehme, Nadeshda Schelski, Dirk Von Lewinski, William Mullen, Stuart Nicklin, Christian Delles, Guylène Feuillet, Colette Denis, Florian Lang, Burkert Pieske, Jean-Loup Bascands, Harald Mischak, Jean-Sebastien Saulnier-Blache, Jakob Voelkl, Antonia Vlahou, Julie Klein
Usage data is cumulative from February 2024 through February 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 1,653 | 151 |
73 | 35 | |
Figure | 136 | 9 |
Table | 65 | 0 |
Supplemental data | 89 | 9 |
Citation downloads | 44 | 0 |
Totals | 2,060 | 204 |
Total Views | 2,264 |
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.