Youjia Qiu

Background: Epidemiological studies have reported the association between ischemic stroke (IS) and intracerebral hemorrhage (ICH). However, their shared genetic basis remains incompletely characterized. This study quantifies the genetic overlap between them. Methods: We analyzed European-ancestry GWAS summary statistics for IS and ICH. Genetic correlation was estimated using linkage disequilibrium score regression (LDSC), with local correlation assessed by SUPER GeNetic covariance Analyzer (SUPERGNOVA). Partitioned heritability was evaluated across 96 functional categories. Shared loci were identified through cross-trait meta-analysis and evaluated by Bayesian colocalization. Transcriptome-wide association analysis (TWAS) was performed to identify shared gene-expression associations. Bidirectional MR with multiple pleiotropy-robust methods was used to explore causality. Tissue type-specific analysis was performed to investigate shared tissue enrichment. Results: LDSC showed a significant positive genetic correlation between IS and ICH (r_g = 0.57, p = 2.13 × 10⁻⁸). SUPERGNOVA identified significant local correlations at chromosomes 2q33 and 4q25. Partitioned heritability suggested shared genetic enrichment across five functional domains. Cross-trait analysis identified 25 candidate novel pleiotropic SNPs and strong colocalization at 1q22 (rs2736613 near PMF1). TWAS identified four overlapping genes between stroke subtypes, including FAM117B, ICA1L, NBEAL1, and WDR12, mainly located at 2q33. MR results suggested shared liability rather than direct causality. Tissue-specific analyses identified nominal enrichment signals, although none survived multiple-testing correction. Conclusions: Our findings support substantial shared genetic susceptibility between IS and ICH, likely reflecting pleiotropic mechanisms and shared vascular liability rather than a direct directional causal relationship. Further functional studies are needed to clarify the underlying biological mechanisms.

1. Post-traumatic stress disorder (PTSD) is a chronic psychiatric disorder that develops following exposure to traumatic events and represents a substantial global public health burden. According t...

Background: Evidence for reciprocal comorbidity of schizophrenia (SCZ) and suicide attempt (SA) has been discussed in recent years. However, little evidence is known regarding the shared genetic architecture between SCZ and SA. This study investigated the genetic correlation and causality between them. Methods: Leveraging the genome-wide association summary statistics from European ancestry, we qualified local and global genetic correlations between the two traits through Heritability Estimation from Summary Statistics ( ρ -HESS) and Linkage Disequilibrium Score Regression (LDSC). Cross-trait meta-analyses, cross-phenotype association, and colocalization analyses were utilized to identify and validate novel risk loci. Bidirectional Mendelian randomization (MR) was used to investigate causality. Tissue-level SNP heritability enrichment was assessed through Stratified LDSC and Multi-marker Analysis of GenoMic Annotation (MAGMA). Results: LDSC identified significant positive genetic correlation between SCZ and SA ( r _g = 0.48, p = 1.23 × 10 ^− 89 ), and ρ -HESS observed 13 distinct regions associated with both traits. Cross-trait meta-analysis identified 4,025 significant SNPs across the two phenotypes, corresponding to 79 independent loci after LD-based clumping and removing those in LD region. Then, variant functional annotation identified 44 SNPs as novel risk loci, and colocalization analysis identified five novel shared loci among these SNPs between SCZ and SA, including rs10456045 (PP.H4 97.98%), rs13195401 (PP.H4 93.65%), rs13198474 (PP.H4 95.91%), rs60135207 (PP.H4 89.89%), and rs3132450 (PP.H4 88.68%). In MR analysis, genetically predicted SCZ was positively associated with SA (OR 1.17, 95%CI 1.37 to 1.21, p = 7.39 × 10 ^− 22 ), with no reverse causality. Tissue-specific analysis showed that associated genes were predominantly enriched in brain tissues, particularly cortical, limbic, and basal ganglia-related regions. Conclusions: Our study suggests a shared genetic architecture between SCZ and SA, characterized by overlapping pleiotropic variants, tissue-specific expression, and functionally shared genes. These findings delineate previously underappreciated genetic overlaps between them and provide a framework for future mechanistic exploration and therapeutic target discovery. Clinical trial number: Not applicable.

Observational studies highlighted a strong association between gut microbiota (GM) and the onset of neuromyelitis optica spectrum disorder (NMOSD), however, the causality remains unclear. This study investigated the causal relationship between them through two-sample Mendelian randomization (MR) based on genome-wide association studies (GWAS). Two-step MR was used to investigate the potential role of inflammatory cytokines between the causal relationship. Several sensitive analysis were performed to validate the robustness of MR. The MR analysis revealed phylum Tenericutes ( P = .0357); class Mollicutes ( P = .0357); genus Eubacterium rectale group ( P = .0487); genus Barnesiella ( P = .03); genus Eubacterium xylanophilum group ( P = .037); and genus Ruminococcus torques group ( P = .0179) were positively associated with the risk of NMOSD, family Clostridiales vadin BB60 group ( P = .0244); genus Eggerthella ( P = .0214); and genus Intestinibacter ( P = .0308) were negatively correlated with NMOSD. Among 41 inflammatory cytokines, MR showed significant causal effects of Macrophage colony-stimulating factor 1 levels ( P = .00256), C-X-C motif chemokine 11 levels ( P = .0478), SIR2-like protein 2 levels ( P = .00338) and Tumor necrosis factor receptor superfamily member 9 levels ( P = .0234) on NMOSD. Sensitivity analyses confirmed the robustness of these findings. However, mediated MR analysis did not find evidence supporting inflammatory proteins as mediators in the GM-NMOSD pathway. The study presents evidence for a causal relationship between GM, inflammatory proteins, and NMOSD. Notably, inflammatory proteins do not mediate the pathway from GM to NMOSD, contributing to a deeper understanding of the interplay between GM and NMOSD.

Objective: Despite high cure rates, symptom persistence and auditory dysfunction occur sometimes after microvascular decompression (MVD) surgery for hemifacial spasm (HFS). This study evaluated whether combined intraoperative monitoring of the lateral spread response (LSR) and brainstem auditory evoked potentials (BAEP) can reduce the incidence of hearing impairment following MVD for HSF.Methods: A total of 244 HFS patients undergoing MVD were prospectively included and divided into an LSR monitoring group (121 cases) and a combined LRS + BAEP monitoring group (123 cases). Intraoperative recordings of abnormal muscle response (AMR) waves and BAEP were collected and correlated with postoperative HFS and hearing status.Results: HFS symptoms were similarly improved in the two groups, with no significant differences in the occurrence of AMR or the probability of AMR disappearance postoperatively. For both groups, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of AMR waves were also comparable. However, the incidence of postoperative hearing impairment was significantly lower in the LSR + BAEP group compared to the LSR group. Furthermore, receiver operating characteristic (ROC) analysis of BAEP's performance revealed an area under the ROC curve (AUC) of 0.991 (95% CI: 0.955–1.000), indicating a high diagnostic value of BAEP for predicting postoperative hearing decline.Conclusion: LSR monitoring is a reliable approach for assessing the effectiveness of MVD surgery for the facial nerve. The combination of LSR monitoring with BAEP does not affect diagnostic accuracy. More importantly, BAEP can sensitively reflect patients' hearing changes during surgery due to its high diagnostic value, guiding surgeons to adjust their intraoperative techniques and effectively reducing the incidence of postoperative hearing impairment.

Considering the potential links between breast cancer (BC), selective estrogen receptor modulators, and meningioma in previous epidemiology studies, this study aimed to investigate them through the Mendelian randomization approach. We extracted instrumental variables (IVs) of different subtypes of BC from the largest genome-wide association study. Gene targets of SERMs were obtained from the Drug–Gene Interaction Database. Mendelian randomization (MR) analysis applied inverse variance weighted approach to evaluate causality. A series of sensitivity analyses and reverse MR were used to evaluate the stability of the MR results. Genetically determined estrogen receptor (ER) positive BC, luminal A-like breast cancer (OR 1.17, 95% CI 1.04 to 1.32, p = 0.01), and luminal B-like breast cancer (OR 1.20, 95% CI 1.04 to 1.37, p = 0.009) were associated with an increased odds ratio of meningioma (OR 1.18, 95% CI 1.05 to 1.32, p = 0.005). Among SERM-targeted genes, CYP2D6 (OR 1.37, 95% CI 1.23 to 1.54, p = 4.15 × 10^{− 8}), NGR1 (OR 1.15, 95% CI 1.10 to 1.20, p = 2.59 × 10^{− 11}), and MAPT (OR 10.20, 95% CI 2.90 to 35.84, p = 0.0003) were associated with increased meningioma risk, while BRCA1 (OR 0.67, 95% CI 0.57 to 0.80, p = 4.88 × 10^{− 6}) showed negative causal association with meningioma risk. The outcome of the sensitivity analysis and reverse MR analysis corroborated the findings. These findings suggested a causal relationship between BC and meningioma, and identified potential target genes associated with meningioma, which was beneficial to early identification and prevention of meningioma risk.

Introduction: Bell’s palsy is a common acute peripheral neurological disorder causing unilateral facial paralysis. Its exact etiology remains unknown, but it is linked to inflammation, immune responses, infections, and ischemia. This study explores the potential causal relationship between Bell’s palsy and peripheral blood inflammatory proteins, metabolites, and immune cell characteristics. Methods: Genetic data for Bell’s palsy were obtained from the Finnish database (version R10) and IEU OpenGWAS. A two-sample Mendelian randomization (MR) approach was applied, analyzing 4907 plasma proteins, 731 immune cell traits, 91 inflammatory proteins, and 1400 metabolites. The Finnish dataset served as the discovery cohort, while the IEU OpenGWAS dataset acted as the validation cohort. Bioinformatics analyses included protein–protein interaction (PPI) networks, Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, colocalization, and Linkage Disequilibrium Score Regression (LDSC) to identify candidate proteins and explore potential therapeutic targets. Results: MR analysis identified 70 inflammatory proteins, 77 metabolites, and 26 immune cell traits as potentially causally associated with Bell’s palsy. After external validation, BLVRB, HMOX2, TNFRSF12A, DEFB128, ITM2A, VEGF-A, and DDX58 remained significantly associated (p < 0.05). PPI network analysis led to 31 candidate proteins, and six core proteins (JAK2, IL27RA, OSM, CCL19, SELL, VCAM-1) were identified. Conclusions: Our study identifies causal relationships between inflammatory proteins, metabolites, immune cells, and Bell’s palsy, highlighting that the JAK/STAT signaling pathway may be a potentially critical target for intervention in Bell’s palsy, and that its modulation may provide new directions and opportunities for therapeutic strategies and drug discovery for the disease.