Department of Cardiovascular Surgery, Lihuili Hospital Affiliated to Ningbo University, Ningbo, 315041, Zhejiang, China.
Institute of Pharmaceutics, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Eur J Med Res. 2024 Aug 31;29(1):446. doi: 10.1186/s40001-024-02014-z.
Aortic stenosis (AS) is a prevalent and serious valvular heart disease with a complex etiology involving genetic predispositions, lipid dysregulation, and inflammation. The specific roles of lipid and protein biomarkers in AS development are not fully elucidated. This study aimed to elucidate the causal relationships between lipidome, inflammatory proteins, and AS using Mendelian randomization (MR), identifying potential therapeutic targets.
Utilizing data from large-scale genome-wide association studies (GWAS) and genome-wide protein quantitative trait loci (pQTL) studies, we conducted MR analyses on 179 plasma lipidome and 91 inflammatory proteins to assess their causal associations with AS. Our approach included Inverse Variance Weighting (IVW), Wald ratio, and robust adjusted profile score (RAPS) analyses to refine these associations. MR-Egger regression was used to address directional horizontal pleiotropy.
Our MR analysis showed that genetically predicted 50 lipids were associated with AS, including 38 as risk factors [(9 Sterol ester, 18 Phosphatidylcholine, 4 Phosphatidylethanolamine, 1 Phosphatidylinositol and 6 Triacylglycerol)] and 12 as protective. Sterol ester (27:1/17:1) emerged as the most significant risk factor with an odds ratio (OR) of 3.11. Additionally, two inflammatory proteins, fibroblast growth factor 19 (FGF19) (OR = 0.830, P = 0.015), and interleukin 6 (IL-6) (OR = 0.729, P = 1.79E-04) were significantly associated with reduced AS risk. However, a two-step MR analysis showed no significant mediated correlations between these proteins and the lipid-AS pathway.
This study reveals complex lipid and protein interactions in AS, identifying potential molecular targets for therapy. These results go beyond traditional lipid profiling and significantly advance our genetic and molecular understanding of AS, highlighting potential pathways for intervention and prevention.
主动脉瓣狭窄(AS)是一种普遍且严重的瓣膜性心脏病,其病因复杂,涉及遗传易感性、脂质失调和炎症等因素。脂质和蛋白质生物标志物在 AS 发展中的具体作用尚未完全阐明。本研究旨在通过孟德尔随机化(MR)阐明脂质组、炎症蛋白与 AS 之间的因果关系,确定潜在的治疗靶点。
利用大规模全基因组关联研究(GWAS)和全基因组蛋白质定量性状基因座(pQTL)研究的数据,我们对 179 种血浆脂质组和 91 种炎症蛋白进行了 MR 分析,以评估它们与 AS 的因果关系。我们的方法包括逆方差加权(IVW)、Wald 比和稳健调整的轮廓得分(RAPS)分析,以细化这些关联。MR-Egger 回归用于解决方向性水平偏倚。
我们的 MR 分析表明,遗传预测的 50 种脂质与 AS 相关,其中 38 种为风险因素(9 种甾醇酯、18 种磷脂酰胆碱、4 种磷脂酰乙醇胺、1 种磷脂酰肌醇和 6 种三酰基甘油),12 种为保护因素。甾醇酯(27:1/17:1)是最显著的风险因素,其比值比(OR)为 3.11。此外,两种炎症蛋白,成纤维细胞生长因子 19(FGF19)(OR=0.830,P=0.015)和白细胞介素 6(IL-6)(OR=0.729,P=1.79E-04)与 AS 风险降低显著相关。然而,两步 MR 分析表明,这些蛋白质与脂质-AS 途径之间没有显著的介导相关性。
本研究揭示了 AS 中复杂的脂质和蛋白质相互作用,确定了潜在的治疗靶点。这些结果超越了传统的脂质谱分析,极大地提高了我们对 AS 的遗传和分子认识,突出了潜在的干预和预防途径。