Gene network reveals LASP1, TUBA1C, and S100A6 are likely playing regulatory roles in multiple sclerosis

Abstract

IntroductionMultiple sclerosis (MS), a non-contagious and chronic disease of the central nervous system, is an unpredictable and indirectly inherited disease affecting different people in different ways. Using Omics platforms genomics, transcriptomics, proteomics, epigenomics, interactomics, and metabolomics database, it is now possible to construct sound systems biology models to extract full knowledge of the MS and recognize the pathway to uncover the personalized therapeutic tools.MethodsIn this study, we used several Bayesian Networks in order to find the transcriptional gene regulation networks that drive MS disease. We used a set of BN algorithms using the R add-on package bnlearn. The BN results underwent further downstream analysis and were validated using a wide range of Cytoscape algorithms, web based computational tools and qPCR amplification of blood samples from 56 MS patients and 44 healthy controls. The results were semantically integrated to improve understanding of the complex molecular architecture underlying MS, distinguishing distinct metabolic pathways and providing a valuable foundation for the discovery of involved genes and possibly new treatments.ResultsResults show that the LASP1, TUBA1C, and S100A6 genes were most likely playing a biological role in MS development. Results from qPCR showed a significant increase (P < 0.05) in LASP1 and S100A6 gene expression levels in MS patients compared to that in controls. However, a significant down regulation of TUBA1C gene was observed in the same comparison.ConclusionThis study provides potential diagnostic and therapeutic biomarkers for enhanced understanding of gene regulation underlying MS.

In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple Sclerosis

“…The S100A6 gene is expressed in a wide range of cell types, and appears to mainly contribute to cellular Ca 2+ signaling and play a role in stress responses in brain [ 81 ]. Although its biological activity has not been completely elucidated, S100A6 was found to be overexpressed in MS patients and has already been suggested as a potential biomarker of this disease [ 82 , 83 ]. Some studies suggest that S100A6 ’s increased expression may affect NFAT transcriptional activity, which has an established role in regulating the immune system [ 82 ].…”

“…Although its biological activity has not been completely elucidated, S100A6 was found to be overexpressed in MS patients and has already been suggested as a potential biomarker of this disease [ 82 , 83 ]. Some studies suggest that S100A6 ’s increased expression may affect NFAT transcriptional activity, which has an established role in regulating the immune system [ 82 ]. Our results overall showed an up-regulation of this gene, and support the observations in the literature regarding its use as a biomarker.…”