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Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility locus discovery, this univariate approach has limitations in detecting complex genotype-phenotype correlations. Multivariate analysis is essential to identify shared genetic risk factors acting through common biological mechanisms of autoimmune/autoinflammatory diseases. In this study, GWAS summary statistics, including 41,274 single nucleotide polymorphisms (SNPs) located in 11,516 gene regions, were analyzed to identify shared variants of seven autoimmune/autoinflammatory diseases using the metaCCA method. Gene-based association analysis was used to refine the pleiotropic genes. In addition, GO term enrichment analysis and protein-protein interaction network analysis were applied to explore the potential biological functions of the identified genes. A total of 4,962 SNPs (P < 1.21 × 10 −6) and 1,044 pleotropic genes (P < 4.34 × 10 −6) were identified by metaCCA analysis. By screening the results of gene-based P-values, we identified the existence of 27 confirmed pleiotropic genes and highlighted 40 novel pleiotropic genes that achieved statistical significance in the metaCCA analysis and were also associated with at least one autoimmune/autoinflammatory in the VEGAS2 analysis. Using the metaCCA method, we identified novel variants associated with complex diseases incorporating different GWAS datasets. Our analysis may provide insights for the development of common therapeutic approaches for autoimmune/autoinflammatory diseases based on the pleiotropic genes and common mechanisms identified.

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19Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility 20 locus discovery, this univariate approach has limitation in detecting complex genotype-21 phenotype correlations. It is essential to identify shared genetic risk factors acting through 22 common biological mechanisms of autoimmune diseases with a multivariate analysis. In this 23 study, the GWAS summary statistics including 41,274 single nucleotide polymorphisms 24 (SNPs) located in 11,516 gene regions was analyzed to identify shared variants of seven 25 autoimmune diseases using metaCCA method. Gene-based association analysis was used to 26 refine the pleiotropic genes. In addition, GO term enrichment analysis and protein-protein 27 interaction network analysis were applied to explore the potential biological function of the 28 identified genes. After metaCCA analysis, 4,962 SNPs (P<1.21×10 −6 ) and 1,044 pleotropic 29 genes (P<4.34×10 −6 ) were identified. By screening the results of gene-based p-values, we 30 identified the existence of 27 confirmed pleiotropic genes and highlighted 40 novel pleiotropic 31 genes which achieved significance threshold in metaCCA analysis and were also associated 32 with at least one autoimmune disease in the VEGAS2 analysis. The metaCCA method could 33 identify novel variants associated with complex diseases incorporating different GWAS 34 datasets. Our analysis may provide insights for some common therapeutic approaches of 35 autoimmune diseases based on the pleiotropic genes and common mechanisms identified. 36Author summary 37 Although previous researches have clearly indicated varying degrees of overlapping genetic 38 sensitivities in autoimmune diseases, it has proven GWAS only explain small percent of 39 heritability. Here, we take advantage of recent technical and methodological advances to 40 identify pleiotropic genes that act on common biological mechanisms and the overlapping 41 pathophysiological pathways of autoimmune diseases. After selection using multivariate 3 42 analysis and verification using gene-based analyses, we successfully identified a total of 67 43 pleiotropic genes and performed the functional term enrichment analysis. In particularly, 27 44 genes were identified to be pleiotropic in previous different types of studies, which were 45 validated by our present study. Forty significant genes (16 genes were associated with one 46 disease earlier, and 24 were novel) might be the novel pleiotropic candidate genes for seven 47 autoimmune diseases. The improved detection not only yielded the shared genetic components 48 but also provided better understanding for exploring the potential common biological 49 pathogenesis of these major autoimmune diseases. 4 50 51 Autoimmune diseases are chronic conditions initiated by loss of immunological tolerance to 52 self-antigens[1]. An estimated incidence of autoimmune diseases is about 90 cases per 100,000 53 person-year and the prevalence is about 7.6-9.4% in Europe and North America[2]. The chronic 54 nature of such di...

The mitochondrial DNA (mtDNA) copy number is a vital component in maintaining normal mitochondrial function. It is affected by environmental and occupational exposures, as well as polymorphisms in nuclear genes. Nonetheless, the specific roles of polymorphisms in cell-cycle genes and mtDNA copy number are still unknown. This study enrolled a sample of 544 coke oven workers and 238 non-exposed controls so as to assess the effect of exposure of coke oven emissions (COEs) and polymorphisms in cell-cycle genes on the mtDNA copy number. We found that the mtDNA copy number in the exposed group (0.60 ± 0.29) was significantly lower than that in the control group (1.03 ± 0.31) (t =18.931, P &lt; 0.001). The analysis of covariance showed that both the rs1801270 (CA+CC) and the rs1059234 (CT+CC) in p21 gene were associated with lower mtDNA copy number in the exposed group (P = 0.001). Generalized linear models indicated COEs-exposure (β = −0.432, P &lt; 0.001) and rs1059234 (CT+CC) in p21 gene (β = −0.060, P = 0.024) were the factors in mtDNA copy number reduction. In conclusion, this study suggests that the decrease of the mtDNA copy number is associated with COEs-exposure and the rs1059234 (CT+CC) in the p21 gene.