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RESEARCH PAPER / 2025-05-04

Latent retinal structural patterns with aging.

Kei Sano, Kota Fukai, Ryo Terauchi, Yuko Furuya, Shoko Nakazawa, Kosuke Sakai, Toru Honda, Yuya Watanabe, Takeshi Hayashi, Toru Nakagawa, Tadashi Nakano, Masayuki Tatemichi

Department of Preventive Medicine, Tokai University School of Medicine, Isehara, Japan.Department of Preventive Medicine, Tokai University School of Medicine, Isehara, Japan. · pubmed

Abstract

Optical coherence tomography (OCT) is an efficient tool for non-invasively evaluating retinal structures. Retinal thinning changes assessed using OCT are recognized as potential biomarkers for systemic conditions such as Alzheimer's disease, Parkinson's disease, and chronic kidney disease. However, age-related retinal changes remain largely unexplored, complicating the differentiation between physiological and pathological alterations. Here, we introduced a highly granular approach to assess age-related spatial changes in the inner retina using latent retinal archetypes, identifying 36 retinal archetypes of macula and peripapillary sector images from 189,387 OCTs of 22,494 individuals. Subsequently, we evaluated the associations between these archetypes and age; age-related archetypes are characterized by total or superior thinning in the macula sector. Among individuals with myopia, the inferior thinning pattern in the macula ganglion cell-inner plexiform layer was associated with aging. The age-related effects in the peripapillary sector were primarily reflected in the shape of retinal artery trajectories. Overall, latent retinal archetypes would offer new avenues for the effective utilization of retinal biomarkers in age-related diseases.

The following analysis is generated by AI and may contain errors. It is separate from the authors’ abstract and is not peer review.

Research summary

The paper identifies age-related retinal archetypes that correlate with structural changes in the retina. This research is relevant as it explores the physiological changes associated with aging, potentially contributing to our understanding of age-related diseases and biomarkers.

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