Background Perturbed lipid metabolic pathways may play important roles in the development of cardiovascular disease (CVD). However, existing epidemiological studies have focused more on discovering individual lipid metabolites for CVD risk prediction rather than assessing metabolic pathways. Methods This study included a subcohort of 787 participants and all 230 incident CVD cases from the PREDIMED trial. Applying a network-based analytical method, we identified lipid subnetworks and clusters from a global network of 200 lipid metabolites and linked these subnetworks/clusters to CVD risk. Results Lipid metabolites with more double bonds clustered within one subnetwork, whereas lipid metabolites with fewer double bonds clustered within other subnetworks. We identified 10 lipid clusters that were divergently associated with CVD risk. The hazard ratios [HRs, 95% confidence interval (CI)] of CVD per a 1-standard deviation (SD) increment in cluster score were 1.39 (1.17-1.66) for the hydroxylated phosphatidylcholine (HPC) cluster and 1.24 (1.11-1.37) for a cluster that included diglycerides and a monoglyceride with stearic acyl chain. Every 1-SD increase in the score of cluster that included highly unsaturated phospholipids and cholesterol esters was associated with an HR for CVD of 0.81 (95% CI, 0.67-0.98). Despite a suggestion that MedDiet modified the association between a subnetwork that included most lipids with a high degree of unsaturation and CVD, changes in lipid subnetworks/clusters during the first-year follow-up were not significantly different between intervention groups. Conclusions The degree of unsaturation was a major determinant of the architecture of lipid metabolic network. Lipid clusters that strongly predicted CVD risk, such as the HPC cluster, warrant further functional investigations.

中文翻译：

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在PREDIMED试验中，脂质代谢网络，地中海饮食和心血管疾病。

背景扰动的脂质代谢途径可能在心血管疾病（CVD）的发展中起重要作用。然而，现有的流行病学研究更多地集中于发现用于CVD风险预测的单个脂质代谢物，而不是评估代谢途径。方法该研究包括了787名参与者的亚队列，以及PREDIMED试验中的所有230例CVD病例。应用基于网络的分析方法，我们从200个脂质代谢物的全球网络中识别出了脂质子网络和簇，并将这些子网络/簇与CVD风险相关联。结果具有更多双键的脂质代谢物聚集在一个子网络中，而具有较少双键的脂质代谢物聚集在其他子网络中。我们确定了10个与CVD风险不同相关的脂质簇。簇状分数每增加1个标准差（SD），CVD的危险比[HRs，95％置信区间（CI）]对于羟基化磷脂酰胆碱（HPC）簇为1.39（1.17-1.66），而对于1.24（1.11-1.37） ）的簇，其中包括甘油二酯和带有硬脂酸酰基链的甘油单酯。包括高度不饱和磷脂和胆固醇酯在内的簇的分数每增加1-SD，其CVD HR值为0.81（95％CI，0.67-0.98）。尽管有人提出MedDiet修改了包括高度不饱和度最高的大多数脂质的子网络与CVD之间的关联，但干预组在第一年随访期间，脂质子网络/簇的变化没有显着差异。结论不饱和度是脂质代谢网络结构的主要决定因素。强烈预测CVD风险的脂质簇（例如HPC簇）需要进行进一步的功能研究。