Big data differential analysis of microglial cell responses in neurodegenerative diseases.

Microarray technology has become an indispensable tool for monitoring the levels of gene expression in a given organism through organization, analysis, interpretation, and utilization of biological sequences. Importantly, preliminary microarray gene expression differs from experimentally validated gene expression. Generally, microarray analysis of gene expression in microglial cells is used to identify genes in the brain and spinal cord that are responsible for the onset of neurodegenerative diseases; these genes are either upregulated or downregulated. In the present study, 770 genes identified in prior publications, including experimental studies, were analyzed to determine whether these genes encode novel disease genes. Among the genes published, 340 genes were matched among multiple publications, whereas 430 genes were mismatched; the matched genes were presumed to have the greatest likelihood of contributing to neurodegenerative diseases and thus to be potentially useful target genes for treatment of neurodegenerative diseases. In protein and mRNA expression studies, matched and mismatched genes showed 99% and 97% potentiality, respectively. In addition, some genes identified in microarray analyses were significantly different from those in experimentally validated expression patterns. This study identified novel genes in microglial cells through comparative analysis of published microarray and experimental data on neurodegenerative diseases.