Investigative Ophthalmology & Visual Science Cover Image for Volume 65, Issue 7
June 2024
Volume 65, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2024
Metabolic signatures of retinal photoreceptor layer reveal underpinnings of eye-body association and predict multi-disease risk
Author Affiliations & Notes
  • Shaopeng Yang
    Sun Yat-Sen University Zhongshan Ophthalmic Center State Key Laboratory of Ophthalmology, Guangzhou, Guangdong, China
  • Zhuoyao Xin
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
    F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
  • Lingyi Liang
    Sun Yat-Sen University Zhongshan Ophthalmic Center State Key Laboratory of Ophthalmology, Guangzhou, Guangdong, China
  • Mingguang He
    Experimental Ophthalmology, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
  • Wei Wang
    Sun Yat-Sen University Zhongshan Ophthalmic Center State Key Laboratory of Ophthalmology, Guangzhou, Guangdong, China
  • Footnotes
    Commercial Relationships   Shaopeng Yang None; Zhuoyao Xin None; Lingyi Liang None; Mingguang He None; Wei Wang None
  • Footnotes
    Support  National Natural Science Foundation of China 82371086
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 5120. doi:
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      Shaopeng Yang, Zhuoyao Xin, Lingyi Liang, Mingguang He, Wei Wang; Metabolic signatures of retinal photoreceptor layer reveal underpinnings of eye-body association and predict multi-disease risk. Invest. Ophthalmol. Vis. Sci. 2024;65(7):5120.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The role of the retinal photoreceptor layer in systemic health is intriguing but not fully understood. This prospective, observational clinical study aims to elucidate the eye-body association and inform health promotion strategies.

Methods : We employed optical coherence tomography and metabolomics data from two ethnically diverse cohorts: the UK Biobank (UKB) and the Guangzhou Diabetic Eye Study (GDES). We examined the prospective association between photoreceptor layer thickness and multi-system health outcomes in 35,830 UKB and 2,975 GDES participants. Additionally, we identified and validated plasma metabolites linked to photoreceptor layer thickness in 7,824 UKB and 638 GDES participants. The prospective association of these photoreceptor-related metabolites with multi-disease risk and their added predictability were assessed in a further 86,014 UKB participants.

Results : The photoreceptor layer was associated with risk of 16 multi-system health outcomes, including all-cause mortality, type 2 diabetes, coronary artery disease, myocardial infarction, heart failure, stroke, peripheral arterial disease, abdominal aortic aneurysm, kidney disease, liver disease, chronic obstructive pulmonary disease, asthma, lung cancer, cancer mortality, and other-cause mortality (all false discovery rate [FDR] P < 0.05). We identified 109 metabolic signatures associated with the photoreceptor layer, comprising 96 metabolites with positive and 13 with negative associations (all FDR P < 0.05). Metabolites positively associated with the layer generally indicated a lower risk of multi-system outcomes, whereas those negatively associated indicated increased risk (all FDR P < 0.05). Incorporating metabolic signatures of photoreceptor layer consistently enhanced prediction of multi-system health outcomes beyond established models (all P < 0.05).

Conclusions : The photoreceptor layer is significantly associated with risk of multi-system health outcomes, with circulating metabolomics playing a pivotal role in this eye-body association. These profiles might help refine the integrated prediction of systemic health, though further validation studies are required.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.

 

a) Identification of metabolic signatures of photoreceptor layer. b) Associations of photoreceptor layer and photoreceptor layer-related metabolites with risk of multi-system health outcomes.

a) Identification of metabolic signatures of photoreceptor layer. b) Associations of photoreceptor layer and photoreceptor layer-related metabolites with risk of multi-system health outcomes.

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