DataSheet1_Evaluating Causal Relationship Between Metabolites and Six Cardiovascular Diseases Based on GWAS Summary Statistics.docx

Cardiovascular diseases (CVDs) remain the main cause of morbidity and mortality worldwide. The pathological mechanism and underlying biological processes of these diseases with metabolites remain unclear. In this study, we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the causal effect of metabolites on these diseases by making full use of the latest GWAS summary statistics for 486 metabolites and six major CVDs. Extensive sensitivity analyses were implemented to validate our MR results. We also conducted linkage disequilibrium score regression (LDSC) and colocalization analysis to investigate whether MR findings were driven by genetic similarity or hybridization between LD and disease-associated gene loci. We identified a total of 310 suggestive associations across all metabolites and CVDs, and finally obtained four significant associations, including bradykinin, des-arg(9) (odds ratio [OR] = 1.160, 95% confidence intervals [CIs]: 1.080–1.246, false discovery rate [FDR] = 0.022) on ischemic stroke, N-acetylglycine (OR = 0.946, 95%CIs: 0.920–0.973, FDR = 0.023), X-09026 (OR = 0.845, 95%CIs: 0.779–0.916, FDR = 0.021) and X-14473 (OR = 0.938, 95%CIs = 0.907–0.971, FDR = 0.040) on hypertension. Sensitivity analyses showed that these causal associations were robust, the LDSC and colocalization analyses demonstrated that the identified associations were unlikely confused by LD. Moreover, we identified 15 important metabolic pathways might be involved in the pathogenesis of CVDs. Overall, our work identifies several metabolites that have a causal relationship with CVDs, and improves our understanding of the pathogenesis and treatment strategies for these diseases.

心血管疾病 (Cardiovascular Diseases, CVDs) 仍是全球范围内发病率与死亡率的首要诱因。目前此类疾病与代谢物相关的病理机制及潜在生物学过程仍未阐明。本研究充分利用针对486种代谢物及6种主要心血管疾病的最新全基因组关联研究 (Genome-Wide Association Study, GWAS) 汇总统计数据，开展两样本孟德尔随机化 (Mendelian Randomization, MR) 分析，以评估代谢物对这类疾病的因果效应。本研究实施了多维度敏感性分析以验证孟德尔随机化分析结果的可靠性；同时通过连锁不平衡得分回归 (Linkage Disequilibrium Score Regression, LDSC) 与共定位分析，探究孟德尔随机化结果是否由遗传相似性，或是连锁不平衡 (Linkage Disequilibrium, LD) 与疾病相关基因位点间的混杂效应所驱动。本研究在所有代谢物与心血管疾病的组合中，共识别出310条提示性关联，最终得到4项具有统计学意义的关联：缓激肽 (bradykinin)、去精氨酸(9) (des-arg(9)) 与缺血性脑卒中相关（比值比[OR]=1.160，95%置信区间[CI]：1.080~1.246，错误发现率[FDR]=0.022）；N-乙酰甘氨酸 (N-acetylglycine，OR=0.946，95%CI：0.920~0.973，FDR=0.023)、X-09026 (OR=0.845，95%CI：0.779~0.916，FDR=0.021) 及X-14473 (OR=0.938，95%CI：0.907~0.971，FDR=0.040) 与高血压相关。敏感性分析结果显示，上述因果关联具有良好的稳健性；连锁不平衡得分回归与共定位分析表明，本研究识别的关联不太可能受连锁不平衡因素的混杂干扰。此外，本研究还识别出15条可能参与心血管疾病发病机制的重要代谢通路。综上，本研究明确了数种与心血管疾病存在因果关联的代谢物，加深了学界对这类疾病病理机制与治疗策略的认知。