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Evidence-Based Complementary and Alternative Medicine
Volume 2013, Article ID 517018, 9 pages
Research Article

Metabolic Profiles Distinguish Non-Dampness-Phlegm and Dampness-Phlegm Patterns among Korean Patients with Acute Cerebral Infarction

1Medical Research Division, Korea Institute of Oriental Medicine, 1672 Yuseongdae-ro, Yuseong-gu, Daejeon 305-811, Republic of Korea
2Department of Biochemistry and Molecular Biology, Michigan State University, 603 Wilson Road, East Lansing, MI 48824, USA
3Department of Chemistry, Michigan State University, 578 South Shaw Lane, East Lansing, MI 48824, USA

Received 6 November 2012; Accepted 18 February 2013

Academic Editor: MinKyun Na

Copyright © 2013 Min Ho Cha et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Traditional Korean Medicine classifies stroke into four subtype patterns according to symptomatic pattern identification: Qi deficiency (QD), Yin deficiency (YD), Dampness-phlegm (DP), and Fire and Heat (FH). This study investigated the difference in metabolic profiles of plasma comparing subjects displaying non-DP and DP patterns. A total of 141 patients with cerebral infarction enrolled in this study were distributed as non-DP ( ) and DP ( ). Anthropometric parameters and symptom/sign index were measured. Metabolic profiling was performed using ultrahigh-performance liquid chromatography-mass spectrometry. The Ratio of subjects with slippery pulse was higher in DP pattern, but fine pulse was lower than that in non-DP pattern. As a result of metabolomics analysis, twenty-one metabolites displayed different levels between non-DP and DP patterns. Two were identified as lysophosphatidylcholines (LPCs), LPC(18:2), and LPC(20:3) having an unsaturated acyl chain and showed lower levels in DP pattern than in non-DP pattern ( , 0.034, resp.). However, the saturated LPCs, LPC(18:0) and LPC(16:0), exhibited slight but statistically insignificant elevation in DP pattern. Our results demonstrated that plasma LPCs with polyunsaturated fatty acid groups were associated with DP pattern and suggest that variation of plasma lipid profiles may serve as potential biomarker for diagnosis of DP pattern.