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
Proteomic analysis of urinary biomarkers in low and high-risk diabetic retinopathy patients
Author Affiliations & Notes
  • Dean P Hainsworth
    Ophthalmology, University of Missouri System, Columbia, Missouri, United States
  • Varsha Srinivasan
    Medical Pharmacology and Physiology, University of Missouri System, Columbia, Missouri, United States
  • Abilash Gangula
    Radiology, University of Missouri System, Columbia, Missouri, United States
  • Raghuraman Kannan
    Radiology, University of Missouri System, Columbia, Missouri, United States
    Bioengineering, University of Missouri System, Columbia, Missouri, United States
  • Anandhi Upendran
    Medical Pharmacology and Physiology, University of Missouri System, Columbia, Missouri, United States
  • Footnotes
    Commercial Relationships   Dean Hainsworth None; Varsha Srinivasan None; Abilash Gangula None; Raghuraman Kannan None; Anandhi Upendran None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 3217. doi:
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      Dean P Hainsworth, Varsha Srinivasan, Abilash Gangula, Raghuraman Kannan, Anandhi Upendran; Proteomic analysis of urinary biomarkers in low and high-risk diabetic retinopathy patients. Invest. Ophthalmol. Vis. Sci. 2024;65(7):3217.

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

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Abstract

Purpose : Diabetic retinopathy (DR) is the leading cause of blindness among adults in the United States. Regular screening of the retina is essential to facilitate early treatment and preserve useful vision. Unfortunately, 40-60% of diabetic patients avoid the annual eye exam due to several factors, including cost, discomfort, and accessibility. To improve the rates of DR screening, we have previously developed a low-cost, gold nanoparticle-based lateral flow immune assay (LFIA) for the detection of a urinary biomarker 8-hydroxy-2′-deoxyguanosine for DR screening. Incorporation of additional DR-specific biomarkers would aid in developing a multiplex LFIA with enhanced sensitivity for DR screening. Herein, we have performed a mass spectrometry-based label-free proteomics analysis of urine samples from low and high risk DR patients to identify additional biomarkers for integrating in LFIA.

Methods : Proteomic analysis was performed on urine samples collected from two groups: i) Low-risk DR comprising of No DR (n=5) and mild non-proliferative DR (n=5); ii) High-risk DR comprising of moderate (n=5) and severe non-proliferative (n=5) DR. Differential abundance testing between the groups was performed using unpaired t-tests. A threshold of q-value < 0.05, and an absolute average log2 (fold change)>0.58 were used to identify significant candidates.

Results : 303 proteins were found to be differentially expressed between low-and high-risk DR groups (fold difference ≥ 1.5). Functional annotation and pathway analysis using DAVID bioinformatics tool suggests that the upregulated proteins are involved in inflammatory pathways, angiogenesis, tissue remodeling, lipid metabolism, transport, and hemostasis. Additionally, vision-related markers such as transthyretin, retinol-binding protein 4, prolactin-inducible protein, and cystatin-s were significantly upregulated in the high-risk group. Based on the association with DR pathogenesis, we identified four major proteins as potential biomarkers for integrating in LFIA for DR screening.

Conclusions : Urine proteomic analysis between low and high-risk DR groups identified 303 differentially expressed proteins that could be potential biomarkers for DR. The identified proteins were annotated to pathways which have been implicated in the pathophysiology of DR. The future work entails the validation of these biomarkers for translation into a multiplexed LFIA for DR screening.

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

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