Age-related macular degeneration (AMD) damages the retinal pigment epithelium (RPE), the tissue that safeguards photoreceptor health, leading to irreversible vision loss. Polymorphisms in cholesterol and complement genes are implicated in AMD, yet mechanisms linking risk variants to RPE injury remain unclear. We sought to determine how allelic variants in the apolipoprotein E cholesterol transporter modulate RPE homeostasis and function. Using live-cell imaging, we show that inefficient cholesterol transport by the AMD risk-associated ApoE2 increases RPE ceramide, leading to autophagic defects and complement-mediated mitochondrial damage. Mitochondrial injury drives redox state–sensitive cysteine-mediated phase separation of ApoE2, forming biomolecular condensates that could nucleate drusen. The protective ApoE4 isoform lacks these cysteines and is resistant to phase separation and condensate formation. In Abca–/– Stargardt macular degeneration mice, mitochondrial dysfunction induces liquid-liquid phase separation of p62/SQSTM1, a multifunctional protein that regulates autophagy. Drugs that decrease RPE cholesterol or ceramide prevent mitochondrial injury and phase separation in vitro and in vivo. In AMD donor RPE, mitochondrial fragmentation correlates with ApoE and p62 condensates. Our studies demonstrate that major AMD genetic and biological risk pathways converge upon RPE mitochondria, and identify mitochondrial stress-mediated protein phase separation as an important pathogenic mechanism and promising therapeutic target in AMD.
Nilsa La Cunza, Li Xuan Tan, Thushara Thamban, Colin J. Germer, Gurugirijha Rathnasamy, Kimberly A. Toops, Aparna Lakkaraju
Usage data is cumulative from September 2022 through September 2023.
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.