Fight Aging!

Blood vessel density declines with age, alongside other detrimental changes in the microvasculature, such as small areas of tissue damage following microbleeds. All of this can be readily imaged in the retina, and retinal imaging is already in widespread use in clinical practices. Thus it is interesting to see progress towards an aging clock that uses this aspect of degenerative aging as a marker. A number of potential therapeutic strategies may meaningfully increase angiogenesis and thus microvascular density in later life, such as increased circulating VEGF via gene therapy, or use of existing FDA-approved CLCX12 agonists, all of which have yet to be robustly assessed as better or worse than the effects of, say, six months of a structured exercise program. A good, accessible way to measure results will hopefully speed up progress here.

The blood vessel-rich tissue in the retina, can be used to track human aging in an aging clock called eyeAge, in a way that is noninvasive, less expensive and more accurate than other aging clocks that are currently available. A growing body of evidence suggests that the microvasculature in the retina might be a reliable indicator of the overall health of the body's circulatory system and the brain. 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 certain 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.

But subtle changes in these small blood vessels often go undetected by even the most sophisticated instruments, necessitating the use of deep learning, an effort spearheaded by Google Research. 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 non-eye diseases such as 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.

"This type of imaging could be really valuable in tracking the efficacy of interventions aimed at slowing the aging process. 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 geroprotective therapeutics. Our 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."

Link: https://www.buckinstitute.org/news/retinal-scans-a-non-invasive-inexpensive-method-to-track-human-aging/