Journal of affective disorders · 2025
Unveiling the genetic pleiotropy between anxiety disorders and autoimmune diseases: insights from large-scale genome-wide cross-trait analysis.
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Lin Haitao, Xiao Yao, Liu Yingqiao, Lin Xiaoyang, Liu Xiqiang
Аннотация
BACKGROUND: This study investigates the shared genetic architecture between anxiety disorders (ADs) and ten autoimmune diseases: rheumatoid arthritis (RA), Crohn's disease (CD), ulcerative colitis (UC), psoriasis (PsO), mixed connective tissue disease (MCTD), graves' disease (GD), ankylosing spondylitis (AS), Sjögren's syndrome (SS), multiple sclerosis (MS), and systemic lupus erythematosus (SLE). It aims to identify shared risk loci, key immune traits, and genetic mechanisms contributing to the pathophysiology of these conditions.
METHODS: Utilizing GWAS summary data from IEU Open GWAS and Finngen R11, we identified significant genetic correlations between ADs and autoimmune diseases. Cross-trait pleiotropy analysis identified shared loci and genes, followed by functional annotation and tissue-specific analyses. Heritability enrichment analysis highlighted critical immune cell types and tissues, while immuno-localization analysis explored disease associations.
RESULTS: 34 pleiotropic loci were identified between ADs and six autoimmune diseases at genome-wide significance (P < 5 × 10-8), of which 4 loci (rs12624433, rs72745322, rs12967143, rs2759663) passed the causal colocalization test (PPH.4 > 0.8). Further gene-level analysis identified 83 pleiotropic genes (P < 0.05/18488 = 2.704 × 10-6), including PUS10, RBM4, RBM4B, and RBM5. Tissue enrichment analysis highlighted pleiotropic mechanisms in the pituitary, whole blood, and brain cerebellum. Immuno-localization analysis suggested that CD14- CD16+ monocytes play a vital role in shared genetic mechanisms between ADs and CD.
CONCLUSIONS: Our study uncovers positive genetic correlations between ADs and six autoimmune diseases-RA, CD, UC, PsO, MCTD, and SS, uncovering pleiotropic loci and genes associated with inflammation, adaptive immunity, and the PID CD40 pathway, with CD14- CD16+ monocytes potentially serving a key role in shared genetic mechanisms between ADs and CD.
METHODS: Utilizing GWAS summary data from IEU Open GWAS and Finngen R11, we identified significant genetic correlations between ADs and autoimmune diseases. Cross-trait pleiotropy analysis identified shared loci and genes, followed by functional annotation and tissue-specific analyses. Heritability enrichment analysis highlighted critical immune cell types and tissues, while immuno-localization analysis explored disease associations.
RESULTS: 34 pleiotropic loci were identified between ADs and six autoimmune diseases at genome-wide significance (P < 5 × 10-8), of which 4 loci (rs12624433, rs72745322, rs12967143, rs2759663) passed the causal colocalization test (PPH.4 > 0.8). Further gene-level analysis identified 83 pleiotropic genes (P < 0.05/18488 = 2.704 × 10-6), including PUS10, RBM4, RBM4B, and RBM5. Tissue enrichment analysis highlighted pleiotropic mechanisms in the pituitary, whole blood, and brain cerebellum. Immuno-localization analysis suggested that CD14- CD16+ monocytes play a vital role in shared genetic mechanisms between ADs and CD.
CONCLUSIONS: Our study uncovers positive genetic correlations between ADs and six autoimmune diseases-RA, CD, UC, PsO, MCTD, and SS, uncovering pleiotropic loci and genes associated with inflammation, adaptive immunity, and the PID CD40 pathway, with CD14- CD16+ monocytes potentially serving a key role in shared genetic mechanisms between ADs and CD.