Identification of 67 pleiotropic genes for seven autoimmune diseases using multivariate statistical analysis

Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility locus discovery, this univariate approach has limitation in detecting complex genotype-phenotype correlations. It is essential to identify shared genetic risk factors acting through common biological mechanisms of autoimmune diseases with a multivariate analysis. In this study, the GWAS summary statistics including 41,274 single nucleotide polymorphisms (SNPs) located in 11,516 gene regions was analyzed to identify shared variants of seven autoimmune diseases using 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 function of the identified genes. After metaCCA analysis, 4,962 SNPs (P