Metabolic profiles in heart failure due to non-ischemic cardiomyopathy at rest and under exercise
Metabolic profiles in heart failure due to non-ischemic cardiomyopathy at rest and under exercise
复制标题
DOI：
10.1002/ehf2.12133
复制
发表时间：
2017-05-01
影响因子：
3.8
通讯作者：
Katus, Hugo A.
中科院分区：
文献类型：
--
作者：
Mueller-Hennessen, Matthias;Sigl, Johanna;Katus, Hugo A.
目的：鉴定心力衰竭（HF）患者的代谢特征，并评估其诊断潜力，以区分HF患者和健康对照组在基线和运动条件下。方法血浆样品收集自22名男性HF患者，非缺血性特发性心肌病和左心室收缩功能障碍和19名健康对照组之前（t0），在峰值（t1）和极限心肺运动试验后1小时（t2）。采用气相色谱-质谱联用（GC-MS）和液相色谱-质谱联用（LC-MS/MS）技术对252种代谢物进行了定量分析。HF的代谢特征表现为复合脂质和脂肪酸（特别是磷脂酰胆碱、胆固醇和鞘脂）水平降低。此外，观察到谷氨酰胺降低和谷氨酸盐血浆水平升高、嘌呤降解产物显著增加以及葡萄糖代谢受损的体征。根据纽约心脏协会功能分类，代谢差异显著增加，并且添加三种代谢物进一步改善了运动能力的预测（Q（2）= 0.24至0.35）。尽管大量代谢物随着运动发生显着变化（t1/t0时为30.2%），HF和对照组之间的显著变化数量在t（1）和t（2）时几乎不变（t（0）时为30.7和29.0% vs. 31.3%），预测组分离相似（Q（2）= t0为0.50，t1为0.52，t2为0.56，结论：我们的研究确定了非缺血性HF的代谢特征，其中复合脂质包括磷脂酰胆碱、胆固醇和鞘脂的显著变化。代谢变化在休息时已经很明显，在运动时基本上保持不变。
Aims Identification of metabolic signatures in heart failure (HF) patients and evaluation of their diagnostic potential to discriminate HF patients from healthy controls during baseline and exercise conditions.Methods Plasma samples were collected from 22 male HF patients with non-ischemic idiopathic cardiomyopathy and left ventricular systolic dysfunction and 19 healthy controls before (t0), at peak (t1) and 1h after (t2) symptom-limited cardiopulmonary exercise testing. Two hundred fifty-two metabolites were quantified by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography (LC)-MS/MS-based metabolite profiling.Results Plasma metabolite profiles clearly differed between HF patients and controls at t0 (P < 0.05). The metabolic signature of HF was characterized by decreased levels of complex lipids and fatty acids, notably phosphatidylcholines, cholesterol, and sphingolipids. Moreover, reduced glutamine and increased glutamate plasma levels, significantly increased purine degradation products, as well as signs of impaired glucose metabolism were observed. The metabolic differences increased strongly according to New York Heart Association functional class and the addition of three metabolites further improved prediction of exercise capacity (Q(2) = 0.24 to 0.35). Despite a high number of metabolites changing significantly with exercise (30.2% at t1/t0), the number of significant alterations between HF and controls was almost unchanged at t(1) and t(2) (30.7 and 29.0% vs. 31.3% at t(0)) with a similar predictive group separation (Q(2) = 0.50 for t0, 0.52 for t1, and 0.56 for t2, respectively).Conclusions Our study identified a metabolic signature of non-ischemic HF with prominent changes in complex lipids including phosphatidylcholines, cholesterol, and sphingolipids. The metabolic changes were already evident at rest and largely preserved under exercise.