The In-depth Analysis Of Genome-wide Association Data On Multiple Sclerosis

Multiple Sclerosis(MS) is an inflammatory and demyelinating disease of central nervous system. It threatens public health seriously. MS is a classical complex disease affected by both genetic and environmental factors simultaneously, but genetic factors contribute markedly to the susceptibility to MS. Its heritability is up to 50%. It was found that 80% of the heritability is attributed to common variants among genome-wide association data. However, representing a small portion with less risk, most of the genetic variants identified by genome-wide association study(GWAS) only explain a limited susceptibility. On the other hand, they just have statistical associations with MS, and their functional mechanisms are still unknown. According to the status and problem of GWAS and based on the available GWAS data and results, this study deeply mined the genetic information to further identify novel susceptible genes and explore the pathogenesis of MS. This study consists of two parts: 1) Using the high efficient gene-based association study method to identify novel susceptible genes; 2) Combining the annotation information from multiple datasets including m RNA and protein levels to identify functional relevance and explore their functional mechanisms.Purpose:The aim of this study was to identify novel genes associated with MS(Part Ι), and possible functional relevance followed by research on exploring their functional mechanisms(Part II).Methods:The methods had two parts. Part Ι: Based on the publicly available data of the SNP-based genome-wide association study(GWAS), this study conducted a powerful gene-based GWAS in an initial sample with 931 family trios, and a replication study sample with 978 cases and 883 controls. For the interesting genes, integrative analyses including differential gene expression, protein-protein interaction(PPI) and functional annotation clustering analyses were conducted.Part II: Utilizing the publically available datasets, the study carried out expression quantitative trait loci(e QTLs) analyses to identify e QTL SNPs/target genes. Further, functional prediction for SNPs, differential gene expression, and functional annotation clustering analyses for genes were conducted to explore their functional relevance to MS.Results:Part Ι: Twenty novel genes significantly associated with MS(P<1.40×10–4) were identified by gene-based GWAS, in which 16 novel genes were supported by replicated association and/or differential expression. The associations between five novel genes and MS, which encode myelin oligodendrocyte glycoprotein(MOG), coiled-coil alpha-helical rod protein 1(CCHCR1), human leukocyte antigen complex group 22(HCG22), and major histocompatibility complex, class II, DM alpha(HLA-DMA), were highlighted through integrative analyses.Part II: e QTLs analyses showed that 45 SNPs act as cis-effect regulators on 19 MS-associated genes. Among those, 15 of 45 SNPs were predicted most likely located in transcription factor(TF) binding sites, and 14 of 19 e QTL target genes showed significantly differential expressions in MS-related cells. The functional evidence, taken together, highlighted the functional relevance of the six SNPs(rs3095329 of TUBB, rs9469220/rs2647046 of HLA-DQB1, rs11154801 of AHI1, rs1062158 of NDFIP1 and rs7194 of HLA-DRA) to MS, which may exert allelic-specific influence on gene expression through TF-mediated transcriptional regulation. Moreover, rs7194 may also influence HLA-DRA expression level through micro RNA-mediated post-transcriptional regulation.Conclusions:This study identified 20 novel MS-associated genes, and the associations between five novel genes and MS, namely MOG, CCHCR1, HCG22 and HLA-DMA, were highlighted through integrative analyses. The functional relevance of the six SNPs to MS, which may influence the expression of their target genes through TF or micro RNA were also explored. This study greatly enriched research on MS. The results not only provided the direct study contents and directions in further functional experiments, but some clues for the genetic molecular mechanism underlying MS.