Plasma metabolomics was used to ide

血浆代谢组学被用于识别缺血性HF和HF-CKD患者的代谢变化和潜在的生物标志物。共有32例HF患者，15例HF-CKD患者和47名健康对照组参加。基于UPLC / HRMS的血浆代谢谱分析鉴定出78种代谢产物。PLS-DA模型能够区分HF和健康对照，以及HF和HF-CKD。六个生物标记物（LysoPC [18：2]，胆碱，缬氨酸，吲哚，3-吲哚丙烯酸和对甲酚硫酸盐）与HF连接，而四个生物标记物（LysoPC [18：3]，γ-己内酯，酮戊酸_1，和酮戊酸_2）与HF-CKD连接。脂质代谢和氨基酸代谢主要受到干扰。

血浆代谢组学用于识别缺血性HF和HF-CKD患者的代谢变化和潜在的生物标志物。共有32名高频患者、15名HF-CKD患者和47名健康对症患者登记。基于 UPLC/HRMS 的血浆代谢分析鉴定为 78 种代谢产物。PLS-DA 模型能够区分 HF 和健康控制，以及 HF 和 HF-CKD。六个生物标志物（LysoPC [18：2]， 胆碱、胆碱、丁二烯、三叶草酸和硫酸钠）与HF有关，而四种生物标志物（LysoPC [18：3]、γ-卡普拉酮、酮谷素acid_1和酮谷素acid_2）与HF-CKD有关。脂质代谢和氨基酸代谢主要受干扰。

Plasma metabolomics was used to identify metabolic changes and potential biomarkers in patients with ischemic HF and HF-CKD. A total of 32 patients with HF, 15 with HF-CKD, and 47 healthy controls were enrolled. UPLC/HRMS-based plasma metabolic profiling identified 78 metabolites. PLS-DA models were able to discriminate between HF and healthy controls, as well as between HF and HF-CKD. Six biomarkers (LysoPC [18:2], choline, valine, indole, 3-indoleacrylic acid, and p-cresyl sulfate) were linked to HF, while four biomarkers (LysoPC [18:3], γ-caprolactone, ketovaleric acid_1, and ketovaleric acid_2) were linked to HF-CKD. Lipid metabolism and amino acid metabolism were mainly disturbed.<br>