Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, United States.
Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, United States.
Elife. 2023 Mar 29;12:e80560. doi: 10.7554/eLife.80560.
Causality between plasma triglyceride (TG) levels and atherosclerotic cardiovascular disease (ASCVD) risk remains controversial despite more than four decades of study and two recent landmark trials, STRENGTH, and REDUCE-IT. Further unclear is the association between TG levels and non-atherosclerotic diseases across organ systems.
Here, we conducted a phenome-wide, two-sample Mendelian randomization (MR) analysis using inverse-variance weighted (IVW) regression to systematically infer the causal effects of plasma TG levels on 2600 disease traits in the European ancestry population of UK Biobank. For replication, we externally tested 221 nominally significant associations (p<0.05) in an independent cohort from FinnGen. To account for potential horizontal pleiotropy and the influence of invalid instrumental variables, we performed sensitivity analyses using MR-Egger regression, weighted median estimator, and MR-PRESSO. Finally, we used multivariable MR (MVMR) controlling for correlated lipid fractions to distinguish the independent effect of plasma TG levels.
Our results identified seven disease traits reaching Bonferroni-corrected significance in both the discovery (p<1.92 × 10) and replication analyses (p<2.26 × 10), suggesting a causal relationship between plasma TG levels and ASCVDs, including coronary artery disease (OR 1.33, 95% CI 1.24-1.43, p=2.47 × 10). We also identified 12 disease traits that were Bonferroni-significant in the discovery or replication analysis and at least nominally significant in the other analysis (p<0.05), identifying plasma TG levels as a novel potential risk factor for nine non-ASCVD diseases, including uterine leiomyoma (OR 1.19, 95% CI 1.10-1.29, p=1.17 × 10).
Taking a phenome-wide, two-sample MR approach, we identified causal associations between plasma TG levels and 19 disease traits across organ systems. Our findings suggest unrealized drug repurposing opportunities or adverse effects related to approved and emerging TG-lowering agents, as well as mechanistic insights for future studies.
RD is supported by the National Institute of General Medical Sciences of the National Institutes of Health (NIH) (R35-GM124836) and the National Heart, Lung, and Blood Institute of the NIH (R01-HL139865 and R01-HL155915).
尽管已有四十多年的研究和最近的两项里程碑式试验 STRENGTH 和 REDUCE-IT，但血浆甘油三酯（TG）水平与动脉粥样硬化性心血管疾病（ASCVD）风险之间的因果关系仍存在争议。此外，TG 水平与器官系统中各种非动脉粥样硬化性疾病之间的关联尚不清楚。
在这里，我们使用逆方差加权（IVW）回归进行了全表型、两样本孟德尔随机化（MR）分析，以系统推断欧洲血统 UK Biobank 人群中血浆 TG 水平对 2600 种疾病特征的因果影响。为了复制，我们在来自 FinnGen 的独立队列中外部测试了 221 个名义上显著的关联（p<0.05）。为了解决潜在的水平多效性和无效工具变量的影响，我们使用 MR-Egger 回归、加权中位数估计和 MR-PRESSO 进行了敏感性分析。最后，我们使用多变量 MR（MVMR）控制相关脂质分数来区分血浆 TG 水平的独立影响。
我们的结果在发现（p<1.92×10）和复制分析（p<2.26×10）中都确定了七种达到 Bonferroni 校正显著的疾病特征，表明血浆 TG 水平与 ASCVD 之间存在因果关系，包括冠心病（OR 1.33，95%CI 1.24-1.43，p=2.47×10）。我们还确定了 12 种疾病特征，在发现或复制分析中达到 Bonferroni 显著水平，在另一项分析中至少达到名义显著水平（p<0.05），表明血浆 TG 水平是 9 种非 ASCVD 疾病的新的潜在风险因素，包括子宫平滑肌瘤（OR 1.19，95%CI 1.10-1.29，p=1.17×10）。
采用全表型、两样本 MR 方法，我们确定了血浆 TG 水平与器官系统中 19 种疾病特征之间的因果关系。我们的发现表明，与已批准和新兴的 TG 降低药物相关的药物重新定位机会或不良反应，以及未来研究的机制见解。
RD 得到美国国立卫生研究院（NIH）国立普通医学科学研究所（NIGMS）（R35-GM124836）和 NIH 国家心脏、肺和血液研究所（R01-HL139865 和 R01-HL155915）的支持。
