DOI: 10.6084/m9.figshare.30999532
title: <b>Identification of Shared Immunological Mechanisms in Ulcerative Colitis and Primary Sclerosing Cholangitis: Insights from Mendelian Randomization and In Silico Analysis</b>

description: Supplementary Figure 1:Mendelian randomization study flowchart.<br>Supplementary Figure 2:The funnel plot (left), scatter plot (middle), and leave-one-out plot (right) of five UC-PSC signatures on UC.<br>Supplementary Figure 3:The funnel plot (left), scatter plot (middle), and leave-one-out plot (right) of five UC-PSC signatures on PSC.<br>Supplementary Figure 4:The funnel plot (left), scatter plot (middle), and leave-one-out plot (right) of five UC-PSC signatures on UC-PSC.<br>Supplementary Figure 5:Heatmap of immune cell infiltration levels in normal and UC intestines of GSE38713 (A) and GSE87473 cohorts (B). The box plots depict the differential infiltration levels of immune cells between normal and UC intestines in cohorts GSE38713 (C) and GSE87473 (D). *:p＜0.05; **:p＜0.01; ***:p＜0.001.<br>Supplementary Figure 6:Single-cell sequencing of PSC. (A) PCs selection using JackStraw function. (B) UMAP plot showing the cells of the single cell atlas. All the NK cells were isolated and reclustered into 7 distinct clusters (0-6). (C) The gene expression levels of different NK cell subtypes' gene signatures between the different clusters. (D) UMAP plot showing the NK cell types. (E) Heatmap of top differentially expressed genes across NK cell types. (F) The gene expression levels of SELL and CD74 in each NK cells.<br>Supplementary Figure 7:WGCNA analysis investigating the potential functions of CD74 in NK cells in patients with PSC. WGCNA clusters all NK cells (A) and genes (B). (C) Determination of power value in the WGCNA analysis. (D) Heatmap of the correlation between module eigengenes CD74 expression. (E) The correlation between the module membership (MM) and gene significance (GS) of red module. (F) Gene enrichment analysis of the red module.<br>Supplementary Table 1:The taxonomic classification and corresponding GWAS Catalog database identifiers of immune cell signatures used in MR analysis.<br>Supplementary Table 2:The IVs associated with all immune cell signatures used in MR analysis.<br>Supplementary Table 3:The results of the MR analysis showing the effect of immune cell signatures on UC, with P-values less than 0.05 obtained through IVW method while mitigating pleiotropy effects.<br>Supplementary Table 4:Egger test results of all the immune cell signatures on UC.<br>Supplementary Table 5:Cochran’s Q-test results of all the immune cell signatures on UC.<br>Supplementary Table 6:The results of the MR analysis showing the effect of immune cell signatures on PSC, with P-values less than 0.05 obtained through IVW method while mitigating pleiotropy effects.<br>Supplementary Table 7:Egger test results of all the immune cell signatures on PSC.<br>Supplementary Table 8:Cochran’s Q-test results of all the immune cell signatures on PSC.<br>Supplementary Table 9:Egger test results of five UC-PSC signatures on UC-PSC.<br>Supplementary Table 10:Cochran’s Q-test results of five UC-PSC signatures on UC-PSC.<br>Supplementary Table 11:The expression differences of TLRs, various cytokines, CD80, and CD86, which are associated with the functionality of myeloid DCs between myeloid DCs with high and low surface expression levels of SELL.