Identification of atrial fibrillation-related genes through transcriptome data analysis and Mendelian randomization.

Atrial fibrillation (AF) is a common persistent arrhythmia characterized by rapid and chaotic atrial electrical activity, potentially leading to severe complications such as thromboembolism, heart failure, and stroke, significantly affecting patient quality of life and safety. As the global population ages, the prevalence of AF is on the rise, placing considerable strains on individuals and healthcare systems. This study utilizes bioinformatics and Mendelian Randomization (MR) to analyze transcriptome data and genome-wide association study (GWAS) summary statistics, aiming to identify biomarkers causally associated with AF and explore their potential pathogenic pathways. We obtained AF microarray datasets GSE41177 and GSE79768 from the Gene Expression Omnibus (GEO) database, merged them, and corrected for batch effects to pinpoint differentially expressed genes (DEGs). We gathered exposure data from expression quantitative trait loci (eQTL) and outcome data from AF GWAS through the IEU Open GWAS database. We employed inverse variance weighting (IVW), MR-Egger, weighted median, and weighted model approaches for MR analysis to assess exposure-outcome causality. IVW was the primary method, supplemented by other techniques. The robustness of our results was evaluated using Cochran's Q test, MR-Egger intercept, MR-PRESSO, and leave-one-out sensitivity analysis. A "Veen" diagram visualized the overlap of DEGs with significant eQTL genes from MR analysis, referred to as common genes (CGs). Additional analyses, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and immune cell infiltration studies, were conducted on these intersecting genes to reveal their roles in AF pathogenesis. The combined dataset revealed 355 differentially expressed genes (DEGs), with 228 showing significant upregulation and 127 downregulated. Mendelian randomization (MR) analysis identified that the autocrine motility factor receptor (AMFR) [IVW: OR = 0.977; 95% CI, 0.956-0.998; P = 0.030], leucine aminopeptidase 3 (LAP3) [IVW: OR = 0.967; 95% CI, 0.934-0.997; P = 0.048], Rab acceptor 1 (RABAC1) [IVW: OR = 0.928; 95% CI, 0.875-0.985; P = 0.015], and tryptase beta 2 (TPSB2) [IVW: OR = 0.971; 95% CI, 0.943-0.999; P = 0.049] are associated with a reduced risk of atrial fibrillation (AF). Conversely, GTPase-activating SH3 domain-binding protein 2 (G3BP2) [IVW: OR = 1.030; 95% CI, 1.004-1.056; P = 0.024], integrin subunit beta 2 (ITGB2) [IVW: OR = 1.050; 95% CI, 1.017-1.084; P = 0.003], glutaminyl-peptide cyclotransferase (QPCT) [IVW: OR = 1.080; 95% CI, 1.010-0.997; P = 1.154], and tripartite motif containing 22 (TRIM22) [IVW: OR = 1.048; 95% CI, 1.003-1.095; P = 0.035] are positively associated with AF risk. Sensitivity analyses indicated a lack of heterogeneity or horizontal pleiotropy (P > 0.05), and leave-one-out analysis did not reveal any single nucleotide polymorphisms (SNPs) impacting the MR results significantly. GO and KEGG analyses showed that CG is involved in processes such as protein polyubiquitination, neutrophil degranulation, specific and tertiary granule formation, protein-macromolecule adaptor activity, molecular adaptor activity, and the SREBP signaling pathway, all significantly enriched. The analysis of immune cell infiltration demonstrated associations of CG with various immune cells, including plasma cells, CD8T cells, resting memory CD4T cells, regulatory T cells (Tregs), gamma delta T cells, activated NK cells, activated mast cells, and neutrophils. By integrating bioinformatics and MR approaches, genes such as AMFR, G3BP2, ITGB2, LAP3, QPCT, RABAC1, TPSB2, and TRIM22 are identified as causally linked to AF, enhancing our understanding of its molecular foundations. This strategy may facilitate the development of more precise biomarkers and therapeutic targets for AF diagnosis and treatment.

Zhang Y ，Lian Q ，Nie Y ，Zhao W ... -  《Frontiers in Cardiovascular Medicine》

[Genetic Causation Analysis of Hyperandrogenemia Testing Indicators and Preeclampsia].

Some epidemiological studies have shown that pregnant women who develop preeclampsia (PE) have elevated levels of testosterone in their maternal plasma compared to women with normal blood pressure during pregnancy, revealing a potential association between hyperandrogenism in women and PE. To explore the causal relationship between hyperandrogenism and PE, this study selected total testosterone (TT), bioavailable testosterone (BIOT), and sex hormone binding globulin (SHBG) as exposure factors and PE and chronic hypertension with superimposed PE as disease outcomes. Two-sample Mendelian randomization (MR) analyses were used to genetically dissect the causal relationships between the three exposure factors (TT, BIOT, and SHBG) and the outcomes of PE and chronic hypertension with superimposed PE. Two independent genome-wide association study (GWAS) databases were used for the two-sample MR analysis. In the GWAS data of female participants from the UK Biobank cohort, single nucleotide polymorphisms (SNPs) associated with TT, BIOT, and SHBG were analyzed, involving 230454, 188507, and 188908 samples, respectively. GWAS data on PE and chronic hypertension with superimposed PE from the Finnish database were used to calculate SNP, involving 3556 PE cases and 114735 controls, as well as 38 cases of chronic hypertension with superimposed PE and 114735 controls. To meet the assumptions of instrumental relevance and independence in MR analysis, SNPs associated with exposure were identified at the genome-wide level (P<5.0×10-8), and those in linkage disequilibrium interference were excluded based on clustering thresholds of R 2<0.001 and an allele distance greater than 10000 kb. Known confounding factors, including previous PE, chronic kidney disease, chronic hypertension, diabetes, systemic lupus erythematosus, or antiphospholipid syndrome, were also identified and the relevant SNPs were removed. Finally, we extracted the outcome data based on the exposure-related SNPs in the outcome GWAS, integrating exposure and outcome data, and removing palindromic sequences. Five genetic causal analysis methods, including inverse variance-weighted method (IVW), MR-Egger regression, weighted median method, simple mode method, and weighted mode method, were used to infer causal relationships. In the IVW, it was assumed that the selected SNPs satisfied the three assumptions and provided the most ideal estimate of the effect. IVW was consequently used as the primary analysis method in this study. Considering the potential heterogeneity among the instrumental variables, random-effects IVW was used for MR analysis. The results were interpreted using odds ratios (OR) and the corresponding 95% confidence interval (CI) to explain the impact of exposure factors on PE and chronic hypertension with superimposed PE. If the CI did not include 1 and had a P value less than 0.05, the difference was considered statistically significant. Sensitivity analysis was conducted to assess heterogeneity and pleiotropy. Heterogeneity was examined using Cochran's Q test, and pleiotropy was assessed using MR-Egger intercept analysis. Additionally, leave-one-out analysis was conducted to examine whether individual SNPs were driving the causal associations. To further validate the findings, MR analyses were performed using the same methods and outcome variables, but with different exposure factors, including waist-to-hip ratio adjusted for BMI (WHRadjBMI) and 25-hydroxyvitamin D levels, with MR results for WHRadjBMI and PE serving as the positive controls and MR results for 25-hydroxyvitamin D levels and PE as the negative controls. According to the criteria for selecting genetic instrumental variables, 186, 127, and 262 SNPs were identified as genetic instrumental variables significantly associated with testosterone indicators TT, BIOT, and SHBG. MR analysis did not find a causal relationship between the TT, BIOT, and SHBG levels and the risk of developing PE and chronic hypertension with superimposed PE. The IVW method predicted that genetically predicted TT (OR [95% CI]=1.018 [0.897-1.156], P=0.78), BIOT (OR [95% CI]=1.11 [0.874-1.408], P=0.392), and SHBG (OR [95% CI]=0.855 [0.659-1.109], P=0.239) were not associated with PE. Similarly, genetically predicted TT (OR [95% CI]=1.222 [0.548-2.722], P=0.624), BIOT (OR [95% CI]=1.066 [0.242-4.695], P=0.933), and SHBG (OR [95% CI]=0.529 [0.119-2.343], P=0.402) were not significantly associated with chronic hypertension with superimposed PE. Additionally, MR analysis using the MR-Egger method, weighted median method, simple mode method, and weighted mode method yielded consistent results, indicating no significant causal relationship between elevated testosterone levels and PE or chronic hypertension with superimposed PE. Heterogeneity was observed for SHBG in the analysis with PE (Cochran's Q test, P=0.01), and pleiotropy was detected for BIOT in the analysis with PE (MR-Egger intercept analysis, P=0.014), suggesting that the instrumental variables did not affect PE through BIOT. Other instrumental variables did not show significant heterogeneity or pleiotropy. Leave-one-out analysis confirmed that the results of the MR analysis were not driven by individual instrumental variables. Consistent with previous MR studies, the results of the control MR analyses using WHRadjBMI and 25-hydroxyvitamin D levels supported the accuracy of the MR analysis approach and the methods used in this study. The MR analysis results suggest that current genetic evidence does not support a causal relationship between TT, BIOT, and SHBG levels and the development of PE and chronic hypertension with superimposed PE. This study suggests that elevated testosterone may be a risk factor for PE but not a direct cause.

Lin C ，Chen J ，Zhao X 《-》

Exploring the causality between ankylosing spondylitis and atrial fibrillation: A two-sample Mendelian randomization study.

Objective: To study whether ankylosing spondylitis (AS) has a causal effect on the risk of atrial fibrillation (AF) using two-sample Mendelian randomization (MR) analysis. Methods: Single nucleotide polymorphisms (SNPs) were selected as independent instrumental variables (IVs) from a GWAS study of AS. Summary data from a large-scale GWAS meta-analysis of AF was utilized as the outcome dataset. Inverse-variance weighted (IVW) model was used for the primary analysis. Multiple sensitivity and heterogeneity tests were conducted to confirm the robustness of the results. Results: In total, 18 SNPs were identified as IVs for MR analysis. Five MR methods consistently found that ankylosing spondylitis was not causally associated with atrial fibrillation (IVW: OR = 0.983 (0.894, 1.080), p = 0.718; MR-Egger: OR = 1.190 (0.973, 1.456), p = 0.109; Simple mode: OR = 0.888 (0.718, 1.098), p = 0.287; Weighted mode: OR = 0.989 (0.854, 1.147), p = 0.890; Weight median: OR = 0.963 (0.852, 1.088), p = 0.545). Leave-one-out analysis supported the stability of MR results. Both the MR-Egger intercept and MR-PRESSO method revealed the absence of horizontal pleiotropy. Conclusion: The two-sample MR analysis did not support a causal relationship between AS and the risk of AF.

Chen S ，Luo X ，Zhao J ，Liang Z ，Gu J ... -  《Frontiers in Genetics》

Relationship between cathepsins and cardiovascular diseases: a Mendelian randomized study.

Background: Cardiovascular diseases (CVDs) are the leading age-related disorders worldwide, with their prevalence increasing annually. Cathepsins are protein-degrading enzymes essential for processes such as intracellular protein breakdown, apoptosis, and immune responses. Recent studies suggest a potential link between cathepsins and CVDs, yet the exact causal relationship remains to be elucidated. To address this, we propose using Mendelian randomization (MR) to explore the causal relationships between cathepsins and CVDs. Methods: We obtained single nucleotide polymorphism (SNP) data for cathepsins from the INTERVAL study, a publicly accessible genome-wide association study (GWAS) dataset. Outcome SNP data were sourced from seven distinct GWAS datasets, ensuring a comprehensive analysis across multiple cardiovascular outcomes. For MR analysis, we primarily employed the inverse variance weighted (IVW) method, known for its efficiency when all SNPs are valid instruments. This was supplemented by the weighted median and MR-Egger methods to provide robustness against potential violations of MR assumptions, such as pleiotropy. The IVW method offers precision and efficiency, the weighted median method adds robustness against invalid instruments, and the MR-Egger method helps identify and correct for pleiotropic biases. Cochran's Q test was utilized to assess heterogeneity, and sensitivity analyses were conducted using MR-PRESSO and the leave-one-out approach. Results: The strength of the associations between exposure and outcome was measured using odds ratios (ORs), and results were presented with 95% confidence intervals (CIs). The cathepsin E increases the risk of myocardial infarction (MI) (OR = 1.053%, 95% CI: 1.007-1.101, p = 0.024) and ischemic stroke (IS) (OR = 1.06%, 95% CI: 1.019-1.103, p = 0.004). Conversely, cathepsin L2 decreases the risk of chronic heart failure (CHF) (OR = 0.922%, 95% CI: 0.859-0.99, p = 0.025) and atrial fibrillation (AF) (OR = 0.956%, 95% CI: 0.918-0.996, p = 0.033). Cathepsin O was associated with an increased risk of IS (OR = 1.054%, 95% CI: 1.008-1.102, p = 0.021) and AF (OR = 1.058%, 95% CI: 1.02-1.098, p = 0.002). Conclusion: Our MR analysis reveals that cathepsin E is a risk factor for MI and IS, cathepsin L2 offers protective effects against CHF and AF, and cathepsin O increases the risk for IS and AF.

Li Q ，Zhou Z ，Xu T ，Gao X ，Lou Y ，Chen Z ，Zhang M ，Fang Q ，Tan J ，Huang J ... -  《Frontiers in Pharmacology》

Causality of genetically determined metabolites on anxiety disorders: a two-sample Mendelian randomization study.

Xiao G ，He Q ，Liu L ，Zhang T ，Zhou M ，Li X ，Chen Y ，Chen Y ，Qin C ... -  《Journal of Translational Medicine》