Comparative Transcriptome and Network Biology Analyses Demonstrate Antiproliferative and Hyperapoptotic Phenotypes in Human Keratoconus Corneas

Abstract

To decipher the biological pathways involved in keratoconus pathophysiology by determining the patterns of differential gene expression between keratoconus and control corneas. RNA was extracted from surgically removed corneas of 10 keratoconus patients and from normal corneas of 10 control patients who had undergone enucleation of an eye for ocular melanoma. Several hundred thousand RNA transcripts were assessed using exon microarrays. Statistical comparison and identification of differentially regulated and differentially spliced RNA transcripts was performed by comparing keratoconus cases and controls. In addition, relevant biological pathways were identified by information extraction using network biology. Eighty-seven genes showed significant differences in expression levels. Among these, 69 were downregulated in keratoconus patients, particularly partners of the transcription factor AP-1. The 18 overexpressed genes include mucins, keratins, and genes involved in fibroblast proliferation. In addition, 36 genes were shown to be differentially spliced, including 9 among those that were differentially expressed. Network biology and analysis using Gene Ontology descriptors suggest that many members of both groups belong to pathways of apoptosis and regulation of the balance between cellular differentiation and proliferation. This work constitutes the first genome-wide transcriptome analysis of keratoconus patient corneas that include all currently known genes and exons. Differential expression suggests that mechanisms of cell loss resulting from antiproliferative and hyperapoptotic phenotypes may be responsible for the pathogenesis of keratoconus. Array information, experimental design, raw intensities, and processed log(2) ratios were deposited at the European Bioinformatic Institute's ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/). The accession number is E-MEXP-2777.