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SPECIAL FOCUS ON AGE-RELATED MACULAR DEGENERATION, ORIGINAL ARTICLE
Year : 2021  |  Volume : 69  |  Issue : 3  |  Page : 647-654

Proteomics-based approach for differentiation of age-related macular degeneration sub-types


1 L&T Opthalmic Pathology, Vision Research Foundation, Sankara Nethralaya; Centre for Biotechnology, Anna University, Chennai, India
2 L&T Opthalmic Pathology, Vision Research Foundation, Sankara Nethralaya, Chennai, India
3 Institute of Bioinformatics, International Technology Park, Bangalore, India
4 Radheshyam Kanoi Stem Cell Laboratory, Vision Research Foundation, Sankara Nethralaya, Chennai, India
5 Sri Sankaradeva Nethralaya, Beltola, Guwahati, Assam, India
6 Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, Karnataka, India
7 Centre for Biotechnology, Anna University, Chennai, India
8 Shri Bhagwan Mahavir Vitreoretinal Services, Sankara Nethralaya, Chennai, India
9 Department of Nanobiotechnology, Vision Research Foundation, Sankara Nethralaya, Chennai, India
10 L&T Opthalmic Pathology, Vision Research Foundation; Department of Uvea, Sankara Nethralaya, Chennai, India

Correspondence Address:
Dr. Subramanian Krishnakumar
L&T Opthalmic Pathology, Vision Research Foundation, Sankara Nethralaya, Chennai, Tamil Nadu
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijo.IJO_470_20

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Purpose: Age-related macular degeneration (AMD) is one of the leading causes of irreversible central vision loss in the elderly population. The current study aims to find non-invasive prognostic biomarkers in the urine specimens of the AMD patients. Methods: Peripheral blood and urine samples were collected from 23 controls and 61 AMD patients. Genomic DNA was extracted from the buffy coat of peripheral blood. Allele specific PCR was used to assay SNPs in complement factor H (CFH), complement component 3 (C3). Comparative proteomic analysis of urine samples from early AMD, choroidal neovascular membrane (CNVM), geographic atrophy (GA), and healthy controls was performed using isobaric labelling followed by mass spectrometry. Validation was performed using enzyme-linked immunosorbent assay (ELISA). Results: Comparative proteomic analysis of urine samples identified 751 proteins, of which 383 proteins were found to be differentially expressed in various groups of AMD patients. Gene ontology classification of differentially expressed proteins revealed the majority of them were involved in catalytic functions and binding activities. Pathway analysis showed cell adhesion molecule pathways (CAMs), Complement and coagulation cascades, to be significantly deregulated in AMD. Upon validation by ELISA, SERPINA-1 (Alpha1 antitrypsin), TIMP-1 (Tissue inhibitor of matrix metaloprotease-1), APOA-1 (Apolipoprotein A-1) were significantly over-expressed in AMD (n = 61) patients compared to controls (n = 23). A logistic model of APOA-1 in combination with CFH and C3 polymorphisms predicted the risk of developing AMD with 82% accuracy. Conclusion: This study gives us a preliminary data on non-invasive predictive biomarkers for AMD, which can be further validated in a large cohort and translated for diagnostic use.


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