Microarray Analysis for Differential Gene Expression in Multiple Sclerosis *Habibi N [1], Mustafa AS [1,2], Al-Shammari S [3], Shaheed F [1] OMICS Research Unit, Research Core Facility, Health Sciences Centre [1]; Department of Microbiology [2], and Department of Medicine [3], Faculty of Medicine [2], Kuwait University INTRODUCTION CONCLUSIONS Multiple sclerosis (MS) is an immune-mediated inflammatory demyelinating disease of the central nervous system. The peripheral blood mononuclear cells (PBMCs, i.e. lymphocytes and monocytes), induce active nerve demyelination in MS. Therefore, differential gene expression analysis in PBMCs of MS patients may be helpful in a better understanding of disease pathogenesis. In this study, the microarray technology was used to identify the genes expressed differentially in MS patients. The microarray analysis is a useful tool to study global gene expression in cells. It provides important information about the up or down regulation of genes that may have a potential role in disease pathogenesis. Table 1: List of upregulated genes (P <0.05) MATERIALS AND METHODS PBMCs were isolated from the blood of newly diagnosed and drug naïve patients with relapsing-remitting MS and healthy subjects. Total RNA was purified from the cells by TRIzoI reagent (Ambion) and quantified spectrophotometrically (Epoch, Biotek). The quality of purified RNA was assessed using Bioanalyzer 2100 (Agilent). The GeneChip 3’ IVT Express kit (Affymetrix) was used for target RNA preparation and hybridized to HG-U133_plus_2 array (Affymetrix). The chips were scanned using the GeneChip scanner 3000 7G(Fig.1) The raw CEL files were scanned visually and quality control was done by the Expression Console Software. The *.chp files were exported to the Transcriptome Analysis Console (Affymetrix) for fold change estimation in gene expression. Fig 2: Summary of Data Analysis on Transcriptome Analytical Console (TAC) a b RESULTS REFERENCES The purity and quality of all the RNA samples were within the specified range. Out of the total 54,613 transcripts studied, 1098 transcripts were differentially expressed; 774 transcripts were up-regulated and 324 transcripts were down-regulated in MS patients (Fig. 2,4). Principal component analysis and hierarchical clustering (Fig. 3) revealed that the healthy and the diseased samples formed separate clusters. Interestingly, the majority of transcripts showing significant changes in MS PBMCs were associated with immune responses (Table 1). Ratzer R, Søndergaard HB, Christensen JR, Börnsen L, Borup R, Sørensen PS, Sellebjerg F. 2013. Gene expression analysis of relapsing-remitting, primary progressive and secondary progressive multiple sclerosis. Multiple Sclerosis; 14:1841-1848. Taha S, AljishI M, Alsharoqi I, Bakhiet M. 2015. Differential up regulation of the hypothetical transmembrane protein 66 (TMEM66) in multiple sclerosis patients with potential inflammatory response. Biomedical Reports; 3:98-104. Fig 3: Clustering Analysis (a) PCA and (b) Heirarchial reveals clear grouping of Healthy and MS patients a b ACKNOWLEDGEMENTS Fig 4: (a)Scatter plots and (b) Volcano plots showing significantly expressed genes (-10 log 10 p-Value) The authors would like to thank the Research Core Facility & OMICS Research Unit (Grant no. SRUL02/13) and MM 03/09 for support to carry out this work. Fig 1: Affymetrix microarray platform in OMICSRU/RCF Correspondence: nazima@hsc.edu.kw, abusalim@hsc.edu.kw