Serum metabolomics reveals many novel metabolic markers of heart failure, including pseudouridine and 2-oxoglutarate
Serum metabolomics reveals many novel metabolic markers of heart failure, including pseudouridine and 2-oxoglutarate
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DOI：
10.1007/s11306-007-0063-5
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发表时间：
2007-12-01
期刊：
影响因子：
3.6
通讯作者：
Neyses, Ludwig
中科院分区：
文献类型：
--
作者：
Dunn, Warwick B.;Broadhurst, David I.;Neyses, Ludwig
人们对鉴定可改善心力衰竭诊断的新型生物标志物产生了浓厚的兴趣。通过气相色谱-飞行时间质谱分析 52 名收缩性心力衰竭患者（EF < 40% 加上衰竭体征和症状）和 57 名对照者的血清样本，原始数据减少至 272 个统计上稳健的代谢物峰。 38 个峰显示病例和对照之间存在显着差异 (p < 5x10(-5))。两种这样的代谢物是假尿苷，一种存在于 t- 和 rRNA 中的修饰核苷酸，也是细胞更新的标志物，以及三羧酸循环中间体 2-酮戊二酸。此外，另外 3 种新化合物也是患者和对照组之间的极好区分器：2-羟基、2-甲基丙酸、赤藓糖醇和 2,4,6-三羟基嘧啶。尽管肾脏疾病可能与心力衰竭有关，并且与肾脏疾病相关的代谢物和其他标志物也升高（例如尿素、肌酐和尿酸），但在患者组内，这些代谢物与我们的心力衰竭生物标志物之间没有相关性，表明这些确实是心力衰竭的生物标志物，而不是肾脏疾病本身。这些发现证明了数据驱动的代谢组学方法在识别此类疾病标志物方面的力量。
There is intense interest in the identification of novel biomarkers which improve the diagnosis of heart failure. Serum samples from 52 patients with systolic heart failure (EF < 40% plus signs and symptoms of failure) and 57 controls were analyzed by gas chromatography-time of flight-mass spectrometry and the raw data reduced to 272 statistically robust metabolite peaks. 38 peaks showed a significant difference between case and control (p < 5x10(-5)). Two such metabolites were pseudouridine, a modified nucleotide present in t-and rRNA and a marker of cell turnover, as well as the tricarboxylic acid cycle intermediate 2-oxoglutarate. Furthermore, 3 further new compounds were also excellent discriminators between patients and controls: 2-hydroxy, 2-methylpropanoic acid, erythritol and 2,4,6-trihydroxypyrimidine. Although renal disease may be associated with heart failure, and metabolites associated with renal disease and other markers were also elevated (e. g. urea, creatinine and uric acid), there was no correlation within the patient group between these metabolites and our heart failure biomarkers, indicating that these were indeed biomarkers of heart failure and not renal disease per se. These findings demonstrate the power of data-driven metabolomics approaches to identify such markers of disease.