Discovering diagnostic gene targets for early diagnosis of acute GVHD using methods of computational intelligence on gene expression data

This is an application paper of applying standard methods of computational intelligence to identify diagnostic gene targets and to use them for a successful diagnosis of a medical problem - acute graft-versus-host disease (aGVHD). This is the major complication after allogeneic haematopoietic stem cell transplantation (HSCT) in which functional immune cells of donor, recognize the recipient as ”foreign” and mount an immunologic attack. In this paper we analyzed gene-expression profiles of 47 genes associated with allo-reactivity in 59 patients submitted to HSCT. We have applied different dimensionality reduction techniques of the variable space, combined with different classifiers to detect the aGVHD at onset of clinical signs. This is a preliminary study which utilises both computational and biological evidence for the involvement of a limited number of genes for the diagnosis of aGVHD. Directions for further studies are also outlined in this paper.