Application of ¹H-NMR-based pattern recognition in serum metabolomics of patients with chronic heart failure.
- Author:
Zhi-Yong DU
1
;
Anna SHEN
;
Liang SU
;
Jian-Qiu LIANG
;
Ding-Li XU
Author Information
- Publication Type:Journal Article
- MeSH: Aged; Chronic Disease; Female; Heart Failure; blood; metabolism; Humans; Least-Squares Analysis; Magnetic Resonance Spectroscopy; methods; Male; Metabolome; Metabolomics; methods; Middle Aged; Natriuretic Peptide, Brain; blood; Pattern Recognition, Automated; Principal Component Analysis; Uric Acid; blood
- From: Journal of Southern Medical University 2012;32(3):415-419
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo investigate the feasibility of applying (1)H-NMR-based pattern recognition in the studies of serum metabonomics in chronic heart failure (HF).
METHODS(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.
RESULTSThe 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.
CONCLUSIONS(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.
