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Guiping Wan

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Open access Jan 2026

Shared Genetic Architecture and Pleiotropic Loci Linking Endometriosis and Inflammatory Bowel Disease: An Integrative GWAS, Colocalization, and Mendelian Randomization Study

Background Endometriosis (EMS) and inflammatory bowel disease (IBD) are both chronic inflammatory disorders with overlapping clinical features, suggesting a potentially shared etiology. Although epidemiological studies have reported an association between the two conditions, the genetic basis of this relationship remains poorly understood. This study is aimed at characterizing the shared genetic architecture of EMS and IBD, identify pleiotropic loci implicated in both conditions, and explore the potential causal relationships and underlying biological mechanisms. Methods We analyzed large‐scale GWAS summary statistics to investigate the genetic relationship between EMS and IBD. Linkage‐disequilibrium score regression (LDSC) was used to estimate genetic correlation. The PLACO method was applied to identify pleiotropic loci, which were further evaluated by Bayesian colocalization. Functional implications were assessed using MAGMA gene‐set analysis, tissue enrichment analysis, and functional annotation. Bidirectional two‐sample Mendelian randomization (MR) was performed to examine causal inference, accompanied by leave‐one‐out sensitivity analyses and statistical power calculations. Results A statistically significant but modest positive genetic correlation was observed between EMS and IBD (rg = 0.0957, p = 0.0042). Twenty‐four genomic loci showed evidence of pleiotropic effects, and six of these carried strong evidence of a shared causal variant (posterior probability: PP.H4 > 0.7), including loci at 2p23.3 (ADCY3/DNAJC27), 4q12, 5q23.3, 7p15.2, 11q13.1 (CCDC88B), and 1q22. Functional analyses consistently implicated eight pleiotropic genes across multiple platforms: ADCY3, CCDC88B, GREB1, NOD2, RSPO3, SYNE1, THADA, and TRAIP. Pathway enrichment highlighted “positive regulation of gene expression” as a key shared mechanism (p < 0.05). Tissue‐specific analyses revealed strong signals in whole blood, spleen, and colon, consistent with the immunoinflammatory etiology of both diseases. Bidirectional MR did not support a causal relationship in either direction (IBD on EMS: OR = 1.007, 95% CI: 0.986–1.028, p = 0.543; EMS on IBD: OR = 1.054, 95% CI: 0.991–1.122, p = 0.092). Leave‐one‐out analyses confirmed that no single variant drove these estimates, and power analysis indicated adequate power to detect moderate causal effects. Conclusions The findings provide evidence for a shared, albeit modest, and genetic basis between EMS and IBD that is likely mediated through immune regulation, hormonal signaling, and tissue repair. The absence of significant causal effects in MR suggests that the observed comorbidity reflects common genetic susceptibility rather than a direct causal link. These results offer new insight into the mechanisms underlying the co‐occurrence of the two conditions and may inform future investigation of shared therapeutic targets.

Xinyue Cui, Jian-Hong Wang, Jingjing Chen et al. · 0 citations
Jul 2026

Integrated multi-omics analysis identifies key microglial subpopulations and therapeutic targets in Parkinson's disease.

BACKGROUND Parkinson's disease (PD) is a rapidly growing global health concern, with aging populations driving increasing prevalence. While neuronal degeneration is a hallmark, emerging evidence implicates chronic neuroinflammation as a key contributor to disease progression. Despite its recognized importance, the cellular sources, functional heterogeneity, and actionable mechanisms of inflammation in the human substantia nigra remain poorly understood, limiting the development of precise diagnostic biomarkers and therapeutic interventions. METHODS We integrated single-nucleus RNA sequencing (snRNA-seq) from postmortem substantia nigra with bulk transcriptomic datasets (GSE133101, GSE7621) across multiple cohorts. Using Harmony-based batch correction, cell-type annotation, microglia-specific re-clustering (resolution = 0.1), pseudotime trajectory inference, weighted gene co-expression network analysis (WGCNA), and machine learning, we mapped the neuroinflammatory landscape of PD at single-cell resolution. Diagnostic performance was assessed via receiver operating characteristic (ROC) curve analysis (AUC >0.7), and druggable targets were prioritized through molecular docking and 100-ns molecular dynamics (MD) simulations. RESULTS Microglia emerged as the principal immune driver of PD-associated inflammation. Six transcriptionally distinct microglial subpopulations were identified, with Micro1 enriched for antigen presentation, complement activation, and early pseudotime states. An 8-gene microglia-preferential signature (HSPA6, SERPINH1, CHORDC1, P4HA1, HSPH1, IER5, SLC38A2, and FKBP4), associated with ER stress, protein folding, and immune activation, achieved robust diagnostic performance (AUC >0.9) across cohorts. Gene set enrichment analysis revealed convergence on proteostasis and innate immune pathways, and pan-cellular activation patterns indicated a systemic, non-cell-autonomous inflammatory environment. MD simulations confirmed the structural stability of the FKBP4-SAR260301 complex, highlighting its therapeutic potential. CONCLUSIONS By indicating microglial functional heterogeneity and defining a validated, biologically grounded diagnostic signature, this study advances the mechanistic understanding of PD neuroinflammation. This study transforms neuroinflammation from a correlative hallmark to a mechanistically actionable axis, providing an urgently needed roadmap for inflammation-informed precision medicine in PD.

Lei Yang, Lu Wang, Jiaxing Guo et al. · 0 citations