Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea.
Nakdonggang National Institute of Biological Resources, Sangju, Gyeongsangbuk-do, Republic of Korea.
J Nutr. 2023 Sep;153(9):2552-2560. doi: 10.1016/j.tjnut.2023.07.014. Epub 2023 Aug 3.
Dyslipidemia is important because of its association with various metabolic complications. Numerous studies have sought to obtain scientific evidence for managing dyslipidemia patients.
This study aims to identify differences in the nutritional traits of dyslipidemia subjects based on metabolite patterns.
Dyslipidemia (n = 73) and control (n = 80) subjects were included. Dyslipidemia was defined as triglycerides ≥200 mg/dL, total cholesterol ≥240 mg/dL, low density lipoprotein cholesterol ≥160 mg/dL, high-density lipoprotein cholesterol <40 mg/dL (men) or 50 mg/dL (women), or lipid-lowering medicine use. Nontargeted metabolomics based on ultra-high performance liquid chromatography-mass spectrometry identified plasma metabolites, and K-means clustering was used to reconstitute groups based on the similarity of metabolomic patterns across all subjects. Then, with eXtreme Gradient Boosting, metabolites significantly contributing to the new grouping were selected. Statistical analysis was conducted to analyze traits demonstrating appreciable differences between the groups.
Dyslipidemia subjects were divided into 2 groups based on whether they were (n = 24) or were not (n = 56) in a similar metabolic state as the controls by K-means clustering. The considerable contribution of 4 metabolites (3-hydroxybutyrylcarnitine, 2-octenal, 1,3,5-heptatriene, and 5β-cholanic acid) to this new subset of dyslipidemia was confirmed by eXtreme Gradient Boosting. Furthermore, fiber intake was significantly higher in dyslipidemia subjects whose metabolic state was similar to that of the control than in the dissimilar group (P = 0.002). Moreover, significant correlations were observed between the 4 metabolites and fiber intake. Regression analysis determined that the ideal cutoff for fiber intake was 17.28 g/d.
Dyslipidemia patients who consume 17.28 g/d or more of dietary fiber may maintain similar metabolic patterns to healthy individuals, with substantial effects on the changes in the concentrations of 4 metabolites. Our findings could be applied to developing dietary guidelines for dyslipidemia patients.
血脂异常很重要,因为它与各种代谢并发症有关。许多研究都试图为血脂异常患者的管理提供科学证据。
本研究旨在根据代谢物模式确定血脂异常患者营养特征的差异。
纳入血脂异常(n=73)和对照组(n=80)患者。血脂异常定义为甘油三酯≥200mg/dL,总胆固醇≥240mg/dL,低密度脂蛋白胆固醇≥160mg/dL,高密度脂蛋白胆固醇<40mg/dL(男性)或<50mg/dL(女性),或使用降脂药物。基于超高效液相色谱-质谱的非靶向代谢组学鉴定了血浆代谢物,使用 K-均值聚类根据所有受试者代谢模式的相似性重新构建组。然后,使用极端梯度增强选择对新分组有显著贡献的代谢物。进行统计分析以分析显示组间差异明显的特征。
通过 K-均值聚类,根据血脂异常患者的代谢状态与对照组是否相似(n=24)或不相似(n=56)将其分为 2 组。极端梯度增强证实了 4 种代谢物(3-羟基丁酸酰肉碱、2-辛烯醛、1,3,5-庚三烯和 5β-胆酸)对这一新的血脂异常亚组的重要贡献。此外,与代谢状态与对照组不相似的组相比,代谢状态与对照组相似的血脂异常患者的膳食纤维摄入量显著更高(P=0.002)。此外,还观察到 4 种代谢物与膳食纤维摄入量之间存在显著相关性。回归分析确定膳食纤维摄入量的理想临界值为 17.28g/d。
摄入 17.28g/d 或更多膳食纤维的血脂异常患者可能保持与健康个体相似的代谢模式,对 4 种代谢物浓度的变化有显著影响。我们的研究结果可用于制定血脂异常患者的饮食指南。