Shi Ying, Liu Hairun, Chen Yi
Department of Cardiology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Department of Cognitive and Sleep, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Medicine (Baltimore). 2025 Feb 28;104(9):e41651. doi: 10.1097/MD.0000000000041651.
Hypertension continues to pose a huge burden to global public health. Abnormal metabolism not only serves as a risk factor for hypertension but also acts as a driving force in its aggravation. However, there remains a lack of large-scale causal demonstration based on extensive samples. Our study aims to investigate the causal relationship between metabolism and primary hypertension (PH) using Mendelian randomization analysis. We used genome-wide association studies instrumental variables for Mendelian randomization association analysis integrating the diagnosis results of PH in 3 populations from East Asia, the Middle East, and Africa with serum metabolites and metabolite ratios. This allowed us to identify predictive metabolites and metabolic pathways for diagnosing or treating PH. Inverse-variance weighting was the main model for establishing causal associations. In addition horizontal pleiotropy test, linkage disequilibrium test, and sensitivity analysis were employed to test the explanatory power of instrumental variables. A total of 10,922 cases of PH and 8299 cases of metabolomics detection cohorts were included in the study. In East Asian, Middle Eastern, and African populations, we found 36, 57, and 40 known metabolites respectively strongly associated with PH (P < .05). Cross-section and meta-analysis of these strongly correlated metabolites across the 3 ethnic groups revealed 7 common metabolites. Notably, elevated isoleucine (odds ratio = 0.74, 95% confidence interval: 0.56-0.96) was demonstrated as a potential protective factor against PH across 3 ethnic groups. The metabolites associated with PH have certain polymorphisms in different populations. Isoleucine may be a promising biomarker for PH diagnosis or treatment, but more clinical validation is needed.
高血压继续给全球公共卫生带来巨大负担。代谢异常不仅是高血压的一个危险因素,也是其病情加重的驱动力。然而,目前仍缺乏基于大量样本的大规模因果论证。我们的研究旨在使用孟德尔随机化分析来探究代谢与原发性高血压(PH)之间的因果关系。我们使用全基因组关联研究的工具变量进行孟德尔随机化关联分析,将来自东亚、中东和非洲3个群体的PH诊断结果与血清代谢物及代谢物比值相结合。这使我们能够识别用于诊断或治疗PH的预测性代谢物和代谢途径。逆方差加权是建立因果关联的主要模型。此外,还采用了水平多效性检验、连锁不平衡检验和敏感性分析来检验工具变量的解释力。该研究共纳入了10922例PH病例和8299例代谢组学检测队列。在东亚、中东和非洲人群中,我们分别发现了36种、57种和40种与PH密切相关的已知代谢物(P < 0.05)。对这3个种族群体中这些高度相关代谢物的横断面和荟萃分析揭示了7种常见代谢物。值得注意的是,异亮氨酸升高(优势比 = 0.74,95%置信区间:0.56 - 0.96)被证明是3个种族群体中预防PH的潜在保护因素。与PH相关的代谢物在不同人群中具有一定的多态性。异亮氨酸可能是用于PH诊断或治疗的一个有前景的生物标志物,但还需要更多临床验证。