Investigative Ophthalmology & Visual Science Cover Image for Volume 61, Issue 7
June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
Blood metabolomics and major eye diseases: the Singapore Epidemiology of Eye Diseases Study
Author Affiliations & Notes
  • Simon Nusinovici
    Singapore Eye Research Institute, Singapore, Singapore
  • Zhou Lei
    Singapore Eye Research Institute, Singapore, Singapore
  • Caroline Fajoles Vasseneix
    Singapore Eye Research Institute, Singapore, Singapore
  • Baskaran Mani
    Singapore Eye Research Institute, Singapore, Singapore
  • Yih Chung Tham
    Singapore Eye Research Institute, Singapore, Singapore
  • Gavin SW Tan
    Singapore Eye Research Institute, Singapore, Singapore
  • Gemmy Cheung
    Singapore Eye Research Institute, Singapore, Singapore
  • Charumathi Sabanayagam
    Singapore Eye Research Institute, Singapore, Singapore
  • Tien Y Wong
    Singapore Eye Research Institute, Singapore, Singapore
  • Ching-Yu Cheng
    Singapore Eye Research Institute, Singapore, Singapore
  • Footnotes
    Commercial Relationships   Simon Nusinovici, None; Zhou Lei, None; Caroline Vasseneix, None; Baskaran Mani, None; Yih Chung Tham, None; Gavin Tan, None; Gemmy Cheung, None; Charumathi Sabanayagam, None; Tien Wong, None; Ching-Yu Cheng, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 757. doi:
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      Simon Nusinovici, Zhou Lei, Caroline Fajoles Vasseneix, Baskaran Mani, Yih Chung Tham, Gavin SW Tan, Gemmy Cheung, Charumathi Sabanayagam, Tien Y Wong, Ching-Yu Cheng; Blood metabolomics and major eye diseases: the Singapore Epidemiology of Eye Diseases Study. Invest. Ophthalmol. Vis. Sci. 2020;61(7):757.

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

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Abstract

Purpose : The objective was to identify and quantify the variations of metabolic profile associated with the risk of diabetic retinopathy (DR), early age-related macular degeneration (AMD), age-related cataract and primary open-angle glaucoma (POAG).

Methods : Cross-sectional population-based study comprised of 10,033 Singaporeans (Chinese, Indians and Malays). A total of 150 metabolites were quantified from serum (Chinese and Indians) and plasma (Malay) samples using high-throughput proton NMR metabolomics platform (Nightingale Health Ltd). The metabolites associated with each disease were first identified in each of the three ethnic cohorts, independently of age and gender using penalized regression. Then, the associations between these metabolites and each disease were estimated using logistic regression, adjusting for age, gender, smoking status, BMI, diabetes, hypertension, alcohol drinking, IOP and socio-economic status (+HbA1c and duration of diabetes for DR). Finally, the effect of each metabolite in the overall population was calculated using a random-effect meta-analysis.

Results : The overall prevalences of the eye diseases were 29.8% for DR (in people with diabetes), 6.0% for early AMD, 35.9% for cataract, and 2.1% for POAG. Increases in tyrosine (OR=0.74 [0.64, 0.87]) and triglycerides in HDL (OR=0.70 [0.51, 0.96]) were associated with a decrease risk of DR. Half of the metabolites associated with the risk of early AMD were amino-acids, suggesting that this disease mainly involved a disorder of amino-acid metabolism. However, these effects varied according to the ethnicity. Tyrosine was also a protective factor for the risk of cataract (OR=0.88 [0.81, 0.95]), supposedly by reducing free radical formation. Finally, increases in concentrations of cholesterol and phospholipids in HDL were associated with a decreased (OR=0.68 [0.53, 0.86]) and increased (OR=1.33 [1.02, 1.73]) risks of POAG, respectively, reflecting complex lipoprotein mechanisms leading to neurodegeneration.

Conclusions : This study shows a comparative overview of metabolic profile associated with the four major eye diseases, allowing a better understanding of the disease pathways and the identification of potentially new biomarkers.

This is a 2020 ARVO Annual Meeting abstract.

 

 

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