Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China.
Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China; Hebei Key Laboratory of Environment and Human Health, Hebei Province, Shijiazhuang 050017, China.
J Environ Sci (China). 2025 Apr;150:116-133. doi: 10.1016/j.jes.2024.03.022. Epub 2024 Mar 21.
Although per- and polyfluoroalkyl substances (PFAS) have been frequently linked to cardiovascular and renal disease separately, evidence remains scarce regarding their systematic effect. Therefore, we recruited 546 newly diagnosed acute coronary syndrome (ACS) patients and detected seven myocardial enzymes and six kidney function biomarkers. Twelve PFAS were also assessed with ultra-high-performance liquid chromatography-tandem mass spectrometry. Generalized linear model and restricted cubic spline model were applied to single pollutant analysis. Quantile g-computation was used for mixture analysis. Network model was utilized to identify central and bridge nodes of pollutants and phenotypes. In the present study, perfluorohexane sulfonic acid was positively associated with uric acid (UA) (β= 0.04, 95% confidence interval (CI): 0.01, 0.07), and perfluorobutanoic acid was negatively associated with estimated glomerular filtration rate (β= -0.04, 95% CI: -0.07, -0.01) but positively associated with UA (β= 0.03, 95% CI: 0.01, 0.06). In mixture analysis, each quantile increase in the PFAS mixture was significantly associated with UA (β= 0.08, 95% CI: 0.04, 0.11). Network analysis revealed that perfluorooctanoate, UA, and myoglobin were denoted as bridge nodes, and the first principal component of lactate dehydrogenase and creatine kinase- myocardial band was identified as the node with the highest strength and expected influence. This study investigates the systematic impact of PFAS exposure through cardiorenal interaction network, which highlights that PFAS may serve as an upstream approach in UA-modulated cardiorenal network to affect cardiorenal system comprehensively.
虽然全氟和多氟烷基物质（PFAS）经常分别与心血管和肾脏疾病相关联，但关于它们的系统影响的证据仍然很少。因此，我们招募了 546 名新诊断的急性冠状动脉综合征（ACS）患者，并检测了七种心肌酶和六种肾功能生物标志物。还使用超高效液相色谱-串联质谱法检测了 12 种 PFAS。应用广义线性模型和限制立方样条模型进行单污染物分析。定量 g 计算用于混合物分析。网络模型用于识别污染物和表型的中心和桥接节点。在本研究中，全氟己烷磺酸与尿酸（UA）呈正相关（β=0.04，95%置信区间（CI）：0.01，0.07），而全氟丁烷磺酸与估算肾小球滤过率（β= -0.04，95%CI：-0.07，-0.01）呈负相关，但与 UA 呈正相关（β=0.03，95%CI：0.01，0.06）。在混合物分析中，PFAS 混合物的每个分位数增加均与 UA 显著相关（β=0.08，95%CI：0.04，0.11）。网络分析表明，全氟辛烷磺酸、UA 和肌红蛋白被标记为桥接节点，而乳酸脱氢酶和肌酸激酶-MB 的第一主成分被确定为具有最高强度和预期影响的节点。本研究通过心脏-肾脏相互作用网络研究了 PFAS 暴露的系统影响，该网络突出表明，PFAS 可能作为 UA 调节的心脏-肾脏网络中的上游方法，全面影响心脏-肾脏系统。
