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Background  Keratoconus (KTCN) is a progressive eye disease, characterized by changes in the shape and thickness of the cornea that results in loss of visual acuity. While numerous KTCN candidate genes have been identified, the genetic etiology of the disease remains undetermined. To further investigate and verify the contribution of particular genetic factors to KTCN, we assessed 45 candidate genes previously indicated as involved in KTCN etiology based on transcriptomic and genomic data.    Methods  The RealTime ready Custom Panel, covering 45 KTCN candidate genes and two reference transcripts, has been designed. Then, the expression profiles have been assessed using the RT-qPCR assay in six KTCN and six non-KTCN human corneas, obtained from individuals undergoing a penetrating keratoplasty procedure.    Results  In total, 35 genes exhibiting differential expression between KTCN and non-KTCN corneas have been identified. Among these genes were ones linked to the extracellular matrix formation, including collagen synthesis or the TGF-β, Hippo, and Wnt signaling pathways. The most downregulated transcripts in KTCN corneas were  CTGF, TGFB3, ZNF469, COL5A2, SMAD7 , and  SPARC , while  TGFBI  and  SLC4A11  were the most upregulated ones. Hierarchical clustering of expression profiles demonstrated almost clear separation between KTCN and non-KTCN corneas. The gene expression levels determined using RT-qPCR showed a strong correlation with previous RNA sequencing (RNA-Seq) results.    Conclusions  A strong correlation between RT-qPCR and earlier RNA-Seq data confirms the possible involvement of genes from collagen synthesis and the TGF-β, Hippo, and Wnt signaling pathways in KTCN etiology. Our data also revealed altered expression of several genes, such as  LOX ,  SPARC , and  ZNF469 , in which single nucleotide variants have been frequently identified in KTCN. These findings further highlight the heterogeneous nature of KTCN.

Further evaluation of differential expression of keratoconus candidate genes in human corneas