Retinal scans provide a non-invasive, inexpensive method to track aging

Researchers developed models to predict diabetic retinopathy from retinal images and have gone on to use retinal images to identify at least 39 eye diseases, including glaucoma, diabetic retinopathy, and AMD. (Image courtesy of Adobe Stock/WavebreakMediaMicro)

A team of researchers, led by Buck Institute professor Pankaj Kapahi, PhD, believe the eye is a window to aging. Kapahi’s lab, in tandem with Google Health and Zuckerberg San Francisco General Hospital, has shown how imaging of the fundus, the blood vessel-rich tissue in the retina, can be used to track human aging, in a way that is noninvasive, less expensive and more accurate than other aging clocks that are currently available.1

According to a Buck Institute news release, researchers also did a genome-wide association study (GWAS) to establish the genetic basis for such a clock, which they call eyeAge.

“This type of imaging could be really valuable in tracking the efficacy of interventions aimed at slowing the aging process,” Kapahi, a senior co-author of the study, said in the news release. “The results suggest that potentially, in less than one year we should be able to determine the trajectory of aging with 71% accuracy by noting discernable changes in the eyes of those being treated, providing an actionable evaluation of gero-protective therapeutics.”

Moreover, Kapahi noted in the release that retinal scans most probably can prove to be more reliable due to the fact that changes in the human eye are less susceptible to day-to-day fluctuations compared to biomarkers from the blood which are more dynamic and can be influenced by something as simple as eating a meal or a current infection.

Mounting evidence also points to the fact that the microvasculature in the retina could probe to be a reliable indicator of the overall health of the body’s circulatory system and the brain. The Buck Institute release noted changes in the eye accompany aging and many age-related diseases including age-related macular degeneration (AMD), diabetic retinopathy, and Parkinson’s and Alzheimer’s disease. Ophthalmologists can often detect early symptoms of AIDS, chronic high blood pressure and tumors in the eyes, a utility that is not surprising given that any subtle changes in the vascular system first appear in the smallest blood vessels, and capillaries in the retina are among the smallest in the body.

Buck Institute noted in the release that the smallest changes in the small blood vessels can go undetected by even the most sophisticated instruments, necessitating the use of deep learning, an effort spearheaded by Google Research.

According to the news release, researchers from Google and elsewhere developed models to predict diabetic retinopathy from retinal images and have gone on to use retinal images to identify at least 39 eye diseases, including glaucoma, diabetic retinopathy, and AMD, as well as several non-eye diseases, including chronic kidney disease and cardiovascular disease.

Google researchers trained and tuned the model for eyeAge using their well-studied EyePACS data set which involves more than 100,00 patients and applied it to patients from the UK Biobank, which involved more than 64,000 patients.

Sara Ahadi, PhD, co-corresponding author and a former Fellow at Google Research who is now senior computational biologist at Alkahest, pointed out in the news release the study emphasizes the value of longitudinal data for analyzing accurate aging trajectories.

“Through EyePACS longitudinal dataset involving multiple scans from individual people over time our results show a more accurate positive prediction ratio for two consecutive visits of individual rather than random, time-matched individuals,” Noting that eyeAge is independent from phenotypic age (a well-established aging clock based on blood markers), Ahadi added in the news release. “We are looking at aging through a different lens and bringing more information to the table. We hope eyeAge will be utilized along with other clocks to make tracking aging more robust, powerful and comprehensive.”

According to the news release, the GWAS was done at the Buck Institute utilizing biological samples available from the UK Biobank. Kenneth Wilson, a postdoc at the Buck Institute, validated some of the genes that were highlighted in the analysis, building upon previous Buck research that found a link between diet, eye health and lifespan in Drosophila. Wilson identified nearly 30 genes from patient samples that are associated with visual decline, diabetes, hearing loss, Alzheimer’s disease, cardiovascular disease and stroke.

One of the genes, ALKAL2, has been previously shown to extend lifespan in Drosophila (via the fly homolog ALK). When Wilson knocked down the gene in the flies, it improved their vision later in life and extended their lifespan.

Kapahi says results from the research are ripe for more study. “It would be really informative to understand how these genes, which are already linked to other age-related diseases, are affecting the changes we are seeing in the eye,” he says. “This is human data that provides targets for potential treatments for age-related diseases. The fact that we might be able to track their efficacy in such a low cost, non-invasive way is a huge plus.”

This study is supported by grants from the National Institutes of Health, T32AG000266-23; R01 Ago38688, AG045835, the Larry L. Hillblom Foundation and the Reta Haynes Foundation. The authors have declared no competing interest.

Reference

Sara Ahadi, Kenneth A. Wilson Jr., Boris Babenko, Cory Y. McClean, Drew Bryant, Orion Pritchard, Ajay Kumar, Enrique M. Carrera, Ricardo Lamy, et.al. Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock. Computational and Systmes Biology. Published March 28, 2023. doi: https://doi.org/10.7554/eLife.82364