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. 2020 Feb 3:11:30.
doi: 10.3389/fimmu.2020.00030. eCollection 2020.

Identification of 67 Pleiotropic Genes Associated With Seven Autoimmune/Autoinflammatory Diseases Using Multivariate Statistical Analysis

Xiaocan Jia  1 , Nian Shi  2 , Yu Feng  1 , Yifan Li  1 , Jiebing Tan  1 , Fei Xu  1 , Wei Wang  3 , Changqing Sun  1 , Hongwen Deng  4 , Yongli Yang  1 , Xuezhong Shi  1
Affiliations

Identification of 67 Pleiotropic Genes Associated With Seven Autoimmune/Autoinflammatory Diseases Using Multivariate Statistical Analysis

Xiaocan Jia et al. Front Immunol. .

Abstract

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.

Keywords: GWAS; autoimmune/autoinflammatory diseases; metaCCA; pleiotropic gene; shared gene.

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Figures

Figure 1
Figure 1
Manhattan plot of –log10(metaCCA) values for univariate SNP-seven autoimmune/autoinflammatory diseases analysis. The red line marks the –log10(metaCCA) value of 5.92 corresponding to P < 1.21 × 10−6. If the –log10(metaCCA) value of a certain SNP was >5.92, this SNP was identified as a pleiotropic SNP for seven diseases.
Figure 2
Figure 2
Protein-protein interactions between 67 pleiotropic genes associated with seven autoimmune/autoinflammatory diseases.
See this image and copyright information in PMC

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