Xing-Bo Mo1,2,3, Shu-Feng Lei1,2,3, Qi-Yu Qian1,3, Yu-Fan Guo4, Yong-Hong Zhang1,3, Huan Zhang5,6. 1. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, 199 Renai Road, Suzhou, 215123, Jiangsu, People's Republic of China. 2. Center for Genetic Epidemiology and Genomics, School of Public Health, Soochow University, 199 Renai Road, Suzhou, 215123, Jiangsu, People's Republic of China. 3. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Department of Epidemiology, School of Public Health, Soochow University, 199 Renai Road, Suzhou, 215123, Jiangsu, People's Republic of China. 4. Department of Rheumatology, The First Affiliated Hospital of Soochow University, Suzhou, 215000, Jiangsu, People's Republic of China. 5. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, 199 Renai Road, Suzhou, 215123, Jiangsu, People's Republic of China. hzhang3@suda.edu.cn. 6. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Department of Epidemiology, School of Public Health, Soochow University, 199 Renai Road, Suzhou, 215123, Jiangsu, People's Republic of China. hzhang3@suda.edu.cn.
Abstract
OBJECTIVE: Many genomic loci have been identified for multiple sclerosis (MS) by genome-wide association studies (GWAS). Discrimination of the most functionally relevant genes in these loci remains challenging. The aim of this study was to highlight potential causal genes for MS. METHODS: We detected potential causal DNA methylations and gene expressions for MS by integrating data from large scale GWAS and quantitative trait locus (QTL) studies using the summary data-based Mendelian randomization method. Potential functional SNPs in the identified genes were searched. RESULTS: We found 178 DNA methylation sites and mRNA expressions of 29 genes that were causally associated with MS. The identified genes enriched in 21 specific KEGG pathways and 80 GO terms (e.g., antigen processing and presentation, interferon gamma mediated signaling pathway). Among the identified non-MHC genes, METTL21B, METTL1 and TSFM were strongly connected. MS-associated SNPs in DDR1 were strongly associated with plasma MHC class I polypeptide-related sequence B (MICB) and Granzyme A levels. And plasma MICB and Granzyme A levels were causally associated with MS. Many SNPs in the causal genes showed QTL effects. The association between m6A-SNPs rs923829 and METTL21B expression level was validated in 40 unrelated Chinese Han individuals. CONCLUSIONS: This study identified many DNA methylations and genes as important risk factors for MS and provided novel evidence on the association between circulating MICB and Granzyme A and MS. We also showed that the interaction among DDR1, MICB and GZMA and interaction among METTL21B, METTL1 and TSFM may participate in the pathogenesis of MS.
OBJECTIVE: Many genomic loci have been identified for multiple sclerosis (MS) by genome-wide association studies (GWAS). Discrimination of the most functionally relevant genes in these loci remains challenging. The aim of this study was to highlight potential causal genes for MS. METHODS: We detected potential causal DNA methylations and gene expressions for MS by integrating data from large scale GWAS and quantitative trait locus (QTL) studies using the summary data-based Mendelian randomization method. Potential functional SNPs in the identified genes were searched. RESULTS: We found 178 DNA methylation sites and mRNA expressions of 29 genes that were causally associated with MS. The identified genes enriched in 21 specific KEGG pathways and 80 GO terms (e.g., antigen processing and presentation, interferon gamma mediated signaling pathway). Among the identified non-MHC genes, METTL21B, METTL1 and TSFM were strongly connected. MS-associated SNPs in DDR1 were strongly associated with plasma MHC class I polypeptide-related sequence B (MICB) and Granzyme A levels. And plasma MICB and Granzyme A levels were causally associated with MS. Many SNPs in the causal genes showed QTL effects. The association between m6A-SNPs rs923829 and METTL21B expression level was validated in 40 unrelated Chinese Han individuals. CONCLUSIONS: This study identified many DNA methylations and genes as important risk factors for MS and provided novel evidence on the association between circulating MICB and Granzyme A and MS. We also showed that the interaction among DDR1, MICB and GZMA and interaction among METTL21B, METTL1 and TSFM may participate in the pathogenesis of MS.
Entities:
Keywords:
Genome-wide association study; Mendelian randomization; Methylation; Multiple sclerosis
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