The increasing expression of TNFSF10 was observed in peripheral blood mononuclear cells of patients with multiple sclerosis. TNFSF10 belongs to the tumor necrosis factor/nerve growth factor superfamily, and can induce cell death or apoptosis of inflammatory cells. Blockade of TNFSF10 expressed in CD4+ myelin-specific T cells reduces caspase-dependent neuronal cell death in an experimental animal model for multiple sclerosis. TNFSF10 involves both in cell death and other immunoregulatory mechanisms. According to Kikuchi et al., the presence of the CC genotype in the coding region of TNFSF10 at position 1595 in exon 5 associated with a higher risk of multiple sclerosis in Japanese patients. Also, more than 80% of the top 30 most significant genes in multiple sclerosis were categorized into apoptosis signaling-related genes, and among them TNFSF10 was one of the significantly up-regulated genes. In addition, a more recent candidate gene case-control study in the Spanish population finds an association of 3 SNPs in TRAIL, genes with susceptibility to multiple sclerosis. Besides TNFSF10, the rest 7 genes showed markedly differential expression SR 57227 hydrochloride between multiple sclerosis patients and controls, appearing to be functionally related to apoptosis. TRPS1 executes multiple functions in proliferating chondrocytes and activates proliferation in columnar cells according to the function annotations from the GeneCards database. TRPS1 was also suggested to be an apoptosis-associated gene that acts as a TC-T 6000 death-signaling gene to induce the elimination of cells via apoptosis. GPS1 is known to suppress survival-associated mitogen-activated protein kinase-mediated signal transduction. Hspbap1 is believed to inhibit the neuroprotective effects of heat shock protein 27, and is found extensively in the anterior temporal neocortex of patients with intractable epilepsy. MRVI1 and SMCHD1 are respectively linked to blood coagulation and chromosome organization. Several studies had explored gene expression patterns in multiple sclerosis. Brynedal et al. evaluated the association between transcripts and group specificity using t-tests to detect differentially expressed genes, and estimated the fold change of genes between different groups. However, these studies identified a large amount of differentially regulated transcripts between different groups. Indeed, it is important to apply more effective approaches to analyze microarray data, where there are many thousands of features, and a few tens to hundreds of samples.