Stanford Medicine researchers build an eye "aging clock" that could lead to treatments for ocular diseases
Using a technique they developed for studying eye fluid, Stanford Medicine researchers and their collaborators have found a way to measure ocular aging, opening avenues for treatment of numerous eye diseases.
The scientists looked at nearly 6,000 proteins in the fluid and found that they can use 26 of them to predict aging. Using artificial intelligence, they developed an eye-aging “clock,” indicating which proteins accelerate aging in each disease and revealing new potential targets for therapies.
The study was published Oct. 19 in Cell. Vinit Mahajan, M.D., Ph.D., a professor of ophthalmology, is the senior author, and Julian Wolf, M.D., a postdoctoral scholar in Mahajan’s lab, is the lead author of the paper.
Mahajan and his colleagues intend to apply the clock method to other bodily fluids to develop more effective drugs for a variety of diseases.
To glean the most information possible with small, renewable samples, Mahajan and his team developed a technique — TEMPO, or tracing expression of multiple protein origins. By tracing proteins to a type of cell where the RNA that creates the proteins resides, TEMPO enables the scientists to understand the cellular origin of disease-driving proteins with the hope that eventually they can target the cells with personalized medical treatments.
Vinit Mahajan and colleagues at Stanford University used artificial intelligence to identify a subset of proteins that can predict the age of the human eye. Clocks were also created that predict the age of specific cells. In a study of human eye fluid, they found that eye diseases accelerated the eye's biological age.