Two coding variants of apolipoprotein L1 (APOL1), called G1 and G2, explain much of the excess risk of kidney disease in African Americans. While various cytotoxic phenotypes have been reported in experimental models, the proximal mechanism by which G1 and G2 cause kidney disease is poorly understood. Here, we leveraged 3 experimental models and a recently reported small molecule blocker of APOL1 protein, VX-147, to identify the upstream mechanism of G1-induced cytotoxicity. In HEK293 cells, we demonstrated that G1-mediated Na+ import/K+ efflux triggered activation of GPCR/IP3–mediated calcium release from the ER, impaired mitochondrial ATP production, and impaired translation, which were all reversed by VX-147. In human urine-derived podocyte-like epithelial cells (HUPECs), we demonstrated that G1 caused cytotoxicity that was again reversible by VX-147. Finally, in podocytes isolated from APOL1 G1 transgenic mice, we showed that IFN-γ–mediated induction of G1 caused K+ efflux, activation of GPCR/IP3 signaling, and inhibition of translation, podocyte injury, and proteinuria, all reversed by VX-147. Together, these results establish APOL1-mediated Na+/K+ transport as the proximal driver of APOL1-mediated kidney disease.
Somenath Datta, Brett M. Antonio, Nathan H. Zahler, Jonathan W. Theile, Doug Krafte, Hengtao Zhang, Paul B. Rosenberg, Alec B. Chaves, Deborah M. Muoio, Guofang Zhang, Daniel Silas, Guojie Li, Karen Soldano, Sarah Nystrom, Davis Ferreira, Sara E. Miller, James R. Bain, Michael J. Muehlbauer, Olga Ilkayeva, Thomas C. Becker, Hans-Ewald Hohmeier, Christopher B. Newgard, Opeyemi A. Olabisi
Usage data is cumulative from January 2024 through May 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 2,754 | 82 |
881 | 40 | |
Figure | 327 | 0 |
Supplemental data | 312 | 8 |
Citation downloads | 89 | 0 |
Totals | 4,363 | 130 |
Total Views | 4,493 |
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.