Gut microbiota have been linked to immune thrombocytopenia (ITP) and Henoch–Schönlein purpura (HSP) in recent studies, but a cause-and-effect relationship is unclear. We used Mendelian randomization (MR) to assess causal relationships between gut microbiota and HSP/ITP using summary statistics from the GWAS dataset of the international MiBioGen and FinnGen consortium. The IVW method was used as the main evaluation indicator. MR analysis of 196 intestinal flora and HSP/ITP/sTP phenotypes showed that 12 flora were potentially causally associated with ITP, 6 with HSP, and 9 with sTP. The genes predicted that genus Coprococcus3 (p = 0.0264, OR = 2.05, 95% CI 1.09–3.88)and genus Gordonibacter (p = 0.0073, OR = 1.38; 95% CI 1.09–1.75) were linked to a higher likelihood of developing ITP. Additionally, family Actinomycetaceae (p = 0.02, OR = 0.51, 95% CI 0.28–0.90) and order Actinomycetales (p = 0.0199, OR = 0.50, 95% CI 0.28–0.90) linked to reduced HSP risk. Genus Ruminococcaceae UCG013 (p = 0.0426, OR = 0.44, 95% CI 0.20–0.97) negatively correlated with sTP risk. Our MR analyses offer evidence of a possible cause-and-effect connection between certain gut microbiota species and the likelihood of HSP/ITP.

Introduction: The role of Tumor Necrosis Factor (TNF)-Related Apoptosis-Inducing Ligand (TRAIL) has been highlighted in autoimmune and metabolic disorders. However, there is still an inadequate explanation of its causal relationship with primary immune thrombocytopenia (ITP). This study employed Mendelian Randomization (MR) to identify the potential causal associations among TRAIL, plasma metabolites, and ITP. Method: This study was conducted focusing on analyzing data from a Genome-Wide Association Study (GWAS) comprising inflammatory proteins, plasma metabolites, and the FinnGen consortium. The Inverse Variance Weighted (IVW) method was adopted to derive the causal estimates primarily. Sensitivity analyses included Cochran’s Q test for heterogeneity, MR-Egger regression for horizontal pleiotropy, leave-one-out analysis, and validation via Bayesian Weighted MR (BWMR). In addition, the identification and quantification of potential mediating metabolites were realized through a two-step MR approach. Results: Genetically predicted higher TRAIL levels were associated with a reduced risk of ITP (IVW odds ratio [OR] = 0.78, 95% confidence interval [CI]: 0.65–0.92, P = 0.0042), which was confirmed by BWMR (OR = 0.77, 95% CI: 0.65–0.92, P = 0.0043). Reverse MR analysis revealed no significant causal effect of ITP on TRAIL. Among the 48 plasma metabolites causally associated with TRAIL, only 12,13-dihydroxyoctadecenoic acid (12,13-DiHOME) exhibited a significant association with ITP in BWMR (OR = 0.75, 95% CI: 0.58–0.97, P = 0.0316). Mediation analysis suggested that 12,13-DiHOME might partially mediate the effect of TRAIL on ITP, with an exploratory estimated mediation proportion of 7.55%. Discussion: Mediation analysis revealed that 12,13-DiHOME mediated 7.55% of the TRAIL-related ITP risk reduction. These findings provide preliminary evidence supporting a potential mediating role of 12,13-DiHOME in the protective effect of TRAIL against ITP, suggesting the existence of an immunometabolic pathway linking TRAIL to ITP pathogenesis. Conclusion: This MR study provides genetic evidence of the potentially protective causal effect of TRAIL against ITP, which may be mediated partially by 12,13-DiHOME. Our findings may highlight a novel immunometabolic pathway in ITP pathogenesis, meriting further investigation

Background/Objectives: Epidemiological studies link autoimmune diseases (AIDs) to follicular lymphoma (FL) risk, but their shared genetic architecture and causal mechanisms remain unclear. Methods: A two-sample Mendelian randomization (MR) analysis was employed to assess causal relationships between 15 AIDs and FL. Pleiotropic loci were identified through the Pleiotropy Analysis under Composite Null (PLACO). Bayesian colocalization analysis, functional mapping, and Multi-marker Analysis of GenoMic Annotation were applied to fine-map shared genetic variants and identify their target genes. Summary data-based MR was used with multitissue expression quantitative trait locus data to infer causal effects of gene expression. HyPrColoc analysis was applied to decipher shared genetic regulation of immune cell phenotypes. Results: MR revealed that rheumatoid arthritis increased FL risk (OR_IVW = 1.55, nominal p = 7.16 × 10⁻⁵, FDR-corrected p = 1.07 × 10⁻³), whereas composite autoimmune disease reduced FL risk (OR_IVW = 0.70, nominal p = 4.61 × 10⁻⁵, FDR-corrected p = 6.92 × 10⁻⁴). Hypothyroidism showed only a nominally suggestive protective trend (OR_IVW = 0.88, nominal p = 0.015), which did not survive Benjamini–Hochberg multiple-testing correction (FDR-corrected p = 0.075). Fifty-five pleiotropic loci shared between FL and AIDs were identified, among which key loci such as 1p36.32, 6p21.32, 17p13.1, and 11q23.3 exhibited strong colocalization evidence. Core pleiotropic genes (e.g., TNFRSF14, MMEL1, CXCR5, and RNASET2) were prioritized, which implicated pathways related to MHC class II antigen presentation, interferon signaling, and T cell activation. HyPrColoc analysis demonstrated that these loci colocalized with the expression of immune receptors, including BAFF-R on B cells and HVEM (TNFRSF14) on naïve CD8⁺ T cells. Conclusions: Our study identifies divergent causal effects of selected AIDs on FL risk and demonstrates localized pleiotropy at key loci, providing novel insights into shared immunogenetic mechanisms.