Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm 171 77, Sweden.
Food and Nutrition Sciences, Department of Life Sciences, Chalmers University of Technology, Gothenburg 412 96, Sweden.
Environ Sci Technol. 2024 Jan 16;58(2):1036-1047. doi: 10.1021/acs.est.3c06388. Epub 2024 Jan 4.
Cardiovascular disease (CVD) development may be linked to persistent organic pollutants (POPs), including organochlorine compounds (OCs) and perfluoroalkyl and polyfluoroalkyl substances (PFAS). To explore underlying mechanisms, we investigated metabolites, proteins, and genes linking POPs with CVD risk. We used data from a nested case-control study on myocardial infarction (MI) and stroke from the Swedish Mammography Cohort - Clinical ( = 657 subjects). OCs, PFAS, and multiomics (9511 liquid chromatography-mass spectrometry (LC-MS) metabolite features; 248 proteins; 8110 gene variants) were measured in baseline plasma. POP-related omics features were selected using random forest followed by Spearman correlation adjusted for confounders. From these, CVD-related omics features were selected using conditional logistic regression. Finally, 29 (for OCs) and 12 (for PFAS) unique features associated with POPs and CVD. One omics subpattern, driven by lipids and inflammatory proteins, associated with MI (OR = 2.03; 95% CI = 1.47; 2.79), OCs, age, and BMI, and correlated negatively with PFAS. Another subpattern, driven by carnitines, associated with stroke (OR = 1.55; 95% CI = 1.16; 2.09), OCs, and age, but not with PFAS. This may imply that OCs and PFAS associate with different omics patterns with opposite effects on CVD risk, but more research is needed to disentangle potential modifications by other factors.
心血管疾病 (CVD) 的发生可能与持久性有机污染物 (POPs) 有关,包括有机氯化合物 (OCs) 和全氟烷基及多氟烷基物质 (PFAS)。为了探索潜在的机制,我们研究了将 POPs 与 CVD 风险联系起来的代谢物、蛋白质和基因。我们使用了来自瑞典乳腺摄影队列 - 临床队列(= 657 名受试者)的心肌梗死 (MI) 和中风的巢式病例对照研究的数据。在基线血浆中测量了 OCs、PFAS 和多组学(9511 个液相色谱-质谱 (LC-MS) 代谢物特征;248 种蛋白质;8110 种基因变体)。使用随机森林选择与 POP 相关的组学特征,然后使用 Spearman 相关性调整混杂因素。从这些特征中,使用条件逻辑回归选择与 CVD 相关的组学特征。最后,确定了 29 个(OCs)和 12 个(PFAS)与 POP 和 CVD 相关的独特特征。一个由脂质和炎症蛋白驱动的组学亚模式与 MI 相关(OR = 2.03;95% CI = 1.47;2.79),与 OCs、年龄和 BMI 相关,与 PFAS 呈负相关。另一个由肉碱驱动的亚模式与中风相关(OR = 1.55;95% CI = 1.16;2.09),与 OCs 和年龄相关,但与 PFAS 无关。这可能意味着 OCs 和 PFAS 与不同的组学模式相关,对 CVD 风险的影响相反,但需要进一步研究来理清其他因素的潜在影响。