Du Zhi-Yong, Shen Anna, Su Liang, Liang Jian-Qiu, Xu Ding-Li
Department of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Nan Fang Yi Ke Da Xue Xue Bao. 2012 Mar;32(3):415-9.
To investigate the feasibility of applying (1)H-NMR-based pattern recognition in the studies of serum metabonomics in chronic heart failure (HF).
(1)H-NMR technique was applied for examination of the serum samples from 9 patients with chronic heart failure and 6 healthy individuals. The data were analyzed for pattern recognition through principal component analysis (PCA) and Orthogonal Partial Least Square (OPLS) to determine the differences in serum metabolites between the two groups. The recognition ability of the two analysis methods were compared.
The serum (1)H-NMR spectra of heart failure patients and healthy individuals were significantly different. The PCA method failed to distinguish the patterns between the two groups, but OPLS clearly differentiated the two groups.
(1)H-NMR technique is effective in the study of serum metabolomics in chronic heart failure. The serum metabonomics of patients with chronic heart failure and the healthy individuals are significantly different. OPLS pattern recognition method is superior to PCA method in that the former can remove the influence of non-experimental factors and provide an improved characterization.
探讨基于氢核磁共振（¹H-NMR）的模式识别方法应用于慢性心力衰竭（HF）血清代谢组学研究的可行性。
采用¹H-NMR技术检测9例慢性心力衰竭患者和6例健康个体的血清样本。通过主成分分析（PCA）和正交偏最小二乘法（OPLS）对数据进行模式识别分析，以确定两组血清代谢物的差异。比较两种分析方法的识别能力。
心力衰竭患者与健康个体的血清¹H-NMR谱有显著差异。PCA方法未能区分两组之间的模式，但OPLS能清晰地区分两组。
¹H-NMR技术在慢性心力衰竭血清代谢组学研究中有效。慢性心力衰竭患者与健康个体的血清代谢组学存在显著差异。OPLS模式识别方法优于PCA方法，因为前者可以消除非实验因素的影响并提供更好的特征描述。
