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Engineering >> 2019, Volume 5, Issue 5 doi: 10.1016/j.eng.2019.03.011

Traditional Chinese Medicine-Based Subtyping of Early-Stage Type 2 Diabetes Using Plasma Metabolomics Combined with Ultra-Weak Photon Emission

a Leiden University–European Center for Chinese Medicine and Natural Compounds, Institute of Biology, Leiden University, Leiden,
2333 BE, the Netherlands
b Analytical BioSciences, Leiden Academic Center for Drug Research (LACDR), Leiden University, Leiden, 2333 CC, the Netherlands
c Changchun University of Chinese Medicine, Changchun 130117, China
d Sino-Dutch Center for Preventive and Personalized Medicine, Tiel, 4002 AG, the Netherlands
e Meluna Research, Geldermalsen, 4191 LC, the Netherlands
f SU Biomedicine, Leiden, 2300 AM, the Netherlands
g Shenzhen Huakai Traditional Chinese Medicine and Natural Medicine Research Center, Shenzhen 518114 ,China

Received: 2018-07-05 Revised: 2018-09-30 Accepted: 2019-03-05 Available online: 2019-06-19

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Abstract

The prevalence of type 2 diabetes mellitus (T2DM) is increasing rapidly worldwide. Because of the limited success of generic interventions, the focus of the disease study has shifted toward personalized strategies, particularly in the early stages of the disease. Traditional Chinese medicine (TCM) is based on a systems view combined with personalized strategies and has improved our knowledge of personalized diagnostics. From a systems biology perspective, the understanding of personalized diagnostics can be improved to yield a biochemical basis for such strategies; for example, metabolomics can be used in combination with other systembased diagnostic methods such as ultra-weak photon emission (UPE). In this study, we investigated the feasibility of using plasma metabolomics obtained from 44 pre-diabetic subjects to stratify the following TCM-based subtypes: Qi-Yin deficiency, Qi-Yin deficiency with dampness, and Qi-Yin deficiency with stagnation. We studied the relationship between plasma metabolomics and UPE with respect to TCM-based subtyping in order to obtain biochemical information for further interpreting disease subtypes. Principal component analysis of plasma metabolites revealed differences among the TCM-based pre-T2DM subtypes. Relatively high levels of lipids (e.g., cholesterol esters and triglycerides) were important discriminators of two of the three subtypes and may be associated with a higher risk of cardiovascular disease. Plasma metabolomics data indicate that the lipid profile is an essential component captured by UPE with respect to stratifying subtypes of T2DM. The results suggest that metabolic differences exist among different TCM-based subtypes of pre-T2DM, and profiling plasma metabolites can be used to discriminate among these subtypes. Plasma metabolomics thus provides biochemical insights into system-based UPE measurements.

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