Your eyes can reveal your true biological age – and your risk of disease and death

Bionic eye concept

Difference between the biological age of the retina and the actual age of the person linked to an increased risk of death.

Potential use of ‘retinal age gap’ as a screening tool, researchers suggest.

According to research published online in the British Journal of Ophthalmology.

This “retinal age gap” could be used as a screening tool, the researchers suggest.

A growing body of evidence suggests that the network of small vessels (microvessels) in the retina may be a reliable indicator of the overall health of the circulatory system of the body and the brain.

Although the risks of disease and death increase with age, it is clear that these risks vary considerably among people of the same age, implying that “biological aging” is unique to the individual and may be a better indicator of current and future health, say the researchers.

Several tissue, cellular, chemical and imaging indicators have been developed to detect biological aging that is out of step with chronological aging. But these techniques run into issues of ethics and privacy, while often being invasive, expensive and time-consuming, researchers say.

So they turned to deep learning to see if it could accurately predict a person’s retinal age from images of the fundus, the inner back surface of the eye, and to Seeing if there was a difference between this and a person’s actual age, called the ‘retinal age gap’, could be linked to an increased risk of death.

Deep learning is a type of machine learning and artificial intelligence (AI) that mimics the way people acquire certain types of knowledge. But unlike classical machine learning algorithms which are linear, deep learning algorithms are stacked in a hierarchy of increasing complexity.

The researchers relied on 80,169 fundus images taken by 46,969 adults aged 40 to 69, all of whom were part of the UK Biobank, a large population-based study of over half a million of middle-aged and older British residents.

Some 19,200 fundus images of the right eye of 11,052 relatively healthy participants at the initial Biobank health checkup were used to validate the precision of the deep learning model for retinal age prediction.

This showed a strong association between predicted retinal age and actual age, with overall accuracy within 3.5 years.

Retinal age difference was then assessed in the remaining 35,917 participants over an average follow-up period of 11 years.

During this period, 1,871 (5%) participants died: 321 (17%) from cardiovascular disease; 1018 (54.5%) of cancers; and 532 (28.5%) from other causes, including dementia.

The proportions of “rapid aging” – those whose retinas appeared older than their actual age – with retinal age discrepancies of more than 3, 5 and 10 years were, respectively, 51%, 28% and 4.5 %.

Large retinal age gaps in years were significantly associated with 49% to 67% higher risks of death other than cardiovascular disease or cancer.

And every one-year increase in retinal age difference was associated with a 2% increased risk of death from any cause and a 3% increased risk of death from a specific cause. other than cardiovascular disease and cancer, after controlling for influencing factors, such as high blood pressure, weight (BMI), lifestyle and ethnicity.

The same process applied to the left eyes produced similar results.

This is an observational study, and as such cannot establish cause. The researchers also acknowledge that the retinal images were captured at one point in time and the participants may not be representative of the UK population as a whole.

Nevertheless, they write: “Our new findings have determined that retinal age discrepancy is an independent predictor of increased risk of mortality, particularly non-[cardiovascular disease]/ non-cancer mortality. These findings suggest that retinal age may be a clinically significant biomarker of aging.

They add: “The retina provides a unique and accessible ‘window’ to assess the pathological processes underlying vascular and neurological systemic diseases associated with increased risks of mortality.

“This hypothesis is supported by previous studies, which have suggested that retinal imaging contains information about cardiovascular risk factors, chronic kidney disease, and systemic biomarkers.”

The new findings, combined with previous research, add weight to “the hypothesis that the retina plays an important role in the aging process and is susceptible to the cumulative damage of aging that increases mortality risk,” they explain. .

Reference: “Retinal Age Difference as a Predictive Biomarker of Mortality Risk” by Zhuoting Zhu, Danli Shi, Peng Guankai, Zachary Tan, Xianwen Shang, Wenyi Hu, Huan Liao, Xueli Zhang, Yu Huang, Honghua Yu , Wei Meng, Wei Wang, Zongyuan Ge, Xiaohong Yang and Mingguang He, January 18, 2022, British Journal of Ophthalmology.
DOI: 10.1136/bjophthalmol-2021-319807

Funding: Key State Ophthalmology Laboratory; National Natural Science Foundation of China; Guangzhou Science and Technology Program, China

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