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Integrative analysis and knowledgebase construction of key candidate genes and pathways in age-related macular degeneration. | LitMetric

AI Article Synopsis

  • - Age-related macular degeneration (AMD) is a vision-impairing disease predominantly affecting older adults, with complex genetic variations complicating effective treatment and understanding.
  • - The AMDGKB online platform consolidates genetic data from multiple sources, allowing users to access personalized information and insights about AMD and its subtypes across different ethnicities.
  • - Research indicates that specific genes (like VEGFA and MT2A) contribute differently to AMD based on ethnic background, emphasizing the need for customized approaches in diagnosis and treatment due to this genetic diversity.

Article Abstract

Age-related macular degeneration is a retinal disease that severely impacts vision in the older population. Its gene-related heterogeneity has not been fully studied, increasing the burden of precise treatment, prevention and prognosis. Genetic variation and related information were collected, annotated and expanded from multiple related websites, and all the data were integrated into the online platform AMDGKB. Users can visit this database via the following link: http://amdgd.bioinf.org.cn/for their personalized applications knowledge-guided modeling and applications. This study also explored the heterogeneity of ethnicity and AMD subtypes via genetic variation, functional enrichment analysis and protein‒protein interactions. These results suggest that VEGFA, MT2A, CCL2 and SERPINF1 play different roles in the development of AMD in different ethnic groups. The enrichment analysis also revealed differences in the pathogenesis pathways of different ethnic groups and AMD subtypes. This study highlights that genetic heterogeneity needs to be considered in the process of diagnosis and treatment. AMDGKB provides information for investigating the transformation of genetic variation during AMD progression, as well as for future personalized applications in the diagnosis and prognosis of AMD.

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Source
http://dx.doi.org/10.1016/j.exer.2024.110177DOI Listing

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