Identification of Candidate Genes Responsible for Age-related Macular Degeneration using Microarray Data

Abstract

A DNA microarray can measure the expression of thousands of genes simultaneously, and this enables us to study the molecular pathways underlying Age-related Macular Degeneration. Previous studies have not determined which genes are responsible for the process of AMD. The authors address this deficiency by applying modern data mining and machine learning feature selection algorithms to the AMD microarray dataset. In this paper four methods are utilized to perform feature selection: Naïve Bayes, Random Forest, Random Lasso, and Ensemble Feature Selection. Functional Annotation of 20 final selected genes suggests that most of them are responsible for signal transduction in an individual cell or between cells. The top seven genes, five protein-coding genes and two non-coding RNAs, are explored from their signaling pathways, functional interactions and associations with retinal pigment epithelium cells. The authors conclude that Pten/PI3K/Akt pathway, NF-kappaB pathway, JNK cascade, Non-canonical Wnt Pathway, and two biological processes of cilia are likely to play important roles in AMD pathogenesis.