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Analysis
of genetic insights and molecular pathways in age-related macular
degeneration: A functional enrichment
Loya Geeta Anusha1,
N. Uday Kumar2*, E.V. Ravikanth3, K. Farzia4
and U. Adiga4
1Department
of Ophthalmology, Apollo Institute of Medical Sciences and Research Chittoor,
Murukambattu - 517 127, India
2Department
of General Surgery, Apollo Institute of Medical Sciences and Research
Chittoor, Murukambattu - 517 127, India
3Department
of Dermatology, Apollo Institute of Medical Sciences and Research Chittoor,
Murukambattu - 517 127, India
4Department
of Biochemistry, Apollo Institute of Medical Sciences and Research Chittoor,
Murukambattu - 517 127, India
Received: 29 November
2025 Revised: 04 May 2026 Accepted: 04
June 2026
*Corresponding Author Email: udaykumar_n@aimsrchittoor.edu.in
*ORCiD: https://orcid.org/0000-0002-7207-3458
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Abstract
Aim: Age-related macular
degeneration (AMD) is a leading cause of vision loss in older adults, with
genetic factors strongly influencing onset and progression. This study aimed
to analyse GWAS data to identify AMD-associated genetic variants and explore
their biological and regulatory significance.
Methodology:
Publicly
available GWAS datasets were analysed using Gene Ontology (GO), KEGG, and
Reactome databases to identify functional pathways. MicroRNA enrichment
analysis assessed regulatory control, whilst MetaboAnalyst linked genetic
variation to metabolic alterations. Unsupervised machine learning approaches,
including principal component analysis (PCA), K-means, and hierarchical
clustering, identified biological patterns among single nucleotide
polymorphisms (SNPs).
Results:
Strong
associations were observed at known susceptibility loci, particularly CFH,
with additional genes including INHBB, GLI2, and TYR implicated in immune
regulation and retinal development. Enrichment analyses highlighted
complement activation, lipid metabolism, and oxidative stress as key
biological processes. MicroRNA analysis revealed regulators influencing
inflammatory and immune pathways, whilst clustering identified three distinct
SNP groups supported by hierarchical patterns.
Interpretation:
By
integrating genetic, functional and regulatory data, this study advances
molecular understanding of AMD, identifying complement dysregulation, immune
dysfunction, and metabolic imbalance as central contributors, alongside novel
candidate biomarkers and therapeutic targets with potential implications for
precision medicine in AMD management.
Key
words: Age-related
macular degeneration, Functional enrichment, Genome wide association study,
Genetic variants, Molecular pathways
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