Duchenne muscular dystrophy (DMD) is a progressive hereditary muscular disease caused by a lack of dystrophin, leading to membrane instability, cell damage, and inflammatory response. However, gene-editing alone is not enough to restore the healthy phenotype and additional treatments are required. In the present study, we have first conducted a meta-analysis of three microarray datasets, GSE38417, GSE3307, and GSE6011, to identify the differentially expressed genes (DEGs) between healthy donors and DMD patients. We have then integrated this analysis with the knowledge obtained from DisGeNET and DIAMOnD, a well-known algorithm for drug–gene association discoveries in the human interactome. The data obtained allowed us to identify novel possible target genes and were used to predict potential therapeutical options that could reverse the pathological condition.
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