Journal of the Korean Magnetic Resonance Society (한국자기공명학회논문지)

Korean Magnetic Resonance Society (한국자기공명학회)
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1H NMR metabolomics study for diabetic neuropathy and diabetes

  • Hyun, Ja-Shil (College of Pharmacy and Gachon Institute of Pharmaceutical Sciences, Gachon University) ;
  • Yang, Jiwon (Department of Neurology, Gil Medical Center, Gachon University College of Medicine) ;
  • Kim, Hyun-Hwi (College of Pharmacy and Gachon Institute of Pharmaceutical Sciences, Gachon University) ;
  • Lee, Yeong-Bae (Department of Neurology, Gil Medical Center, Gachon University College of Medicine) ;
  • Park, Sung Jean (College of Pharmacy and Gachon Institute of Pharmaceutical Sciences, Gachon University)
  • Received : 2018.12.02
  • Accepted : 2018.12.18
  • Published : 2018.12.20
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Abstract

Diabetes is known to be one of common causes for several types of peripheral nerve damage. Diabetic neuropathy (DN) is a significant complication lowering the quality of life that can be frequently found in diabetes patients. In this study, the metabolomic characteristic of DN and Diabetes was investigated with NMR spectroscopy. The sera samples were collected from DN patients, Diabetes patients, and healthy volunteers. Based on the pair-wise comparison, three metabolites were found to be noticeable: glucose, obviously, was upregulated both in DN patients (DNP) and Diabetes. Citrate is also increased in both diseases. However, the dietary nutrient and biosynthesized metabolite from glucose, ascorbate, was elevated only in DNP, compared to healthy control. The multivariate model of OPLS-DA clearly showed the group separation between healthy control-DNP and healthy control-Diabetes. The most significant metabolites that contributed the group separation included glucose, citrate, ascorbate, and lactate. Lactate did not show the statistical significance of change in t-test while it tends to down-regulated both in DNP and Diabetes. We also conducted the ROC curve analysis to make a multivariate model for discrimination of healthy control and diseases with the identified three metabolites. As a result, the discrimination model between healthy control and DNP (or Diabetes) was successful while the model between DNP and Diabetes was not satisfactory for discrimination. In addition, multiple combinations of lactate and citrate in the OPLS-DA model of healthy control and diabetes group (DNP + Diabetes patients) gave good ROC value of 0.952, which imply these two metabolites could be used for diagnosis of Diabetes without glucose information.

Keywords

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Fig 1. OPLS-DA model for two group comparison. The OPLS-DA models of two group comparison are shown in A (healthy control- Diabetic neuropathy) and B (healthy control-diabetes). The 95 % confidence ellipse of the group is depicted. The circle in the score plot represents the healthy control sample and the square represents the diabetic neuropathy (A) and diabetes (B), respectively. The values of R2Y, Q2 and p-value of CV-ANOVA were 0.983, 0.745 and 0.025 (A) and 0.984, 0.843 and 0.002 (B). The Mahalanobis p-values for two group comparison were 3.0583e-10 and 1.3211e-14 respectively (A and B).

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Fig 2. Box and Whisker plots of metabolites with significant difference. Box and whisker plots of four metabolites are illustrated (HC, healthy control; DNP, Diabetic neuropathic patient; D, Diabetic patient). Lactate is not statistically significant but affecting group separation. The groups of which the comparison was identified as significant are linked with lines. The horizontal line in the middle portion of the box is median value. The bottom and top boundaries of boxes represent lower and upper quartile. The open circles represent outliers.

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Fig 3. The S-plot from OPLS-DA model between two groups of healthy control-diabetic neuropathy group (A) and healthy control-diabetes group (B). The S-plot between two groups of healthy control-diabetic neuropathy group (A) and healthy control-diabetes group (B) from OPLS-DA are shown and metabolites that were highly contributed to the group separation are depicted on the plots. The important metabolites (p < 0.05, FDR <0.05) with the strongest association to disease are depicted on the S-plot. Lactate was also depicted because it contributed group separation, although it was not significant in univariate analysis.

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Fig 4. The ROC curve analysis for two composite metabolites (lactate and citrate). The AUC values were obtained from OPLS-DA models of healthy control – diabetic group (diabetic neuropathy + diabetes) with combination of metabolites. All NMR signals of glucose were not included in the metabolite list to remove the effect of glucose signal on the discrimination. The combination of two metabolites in the group comparison of healthy control – diabetic group (diabetic neuropathy + diabetes) provided the AUC value, 0.952.

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Fig 5. Three representative 1H NMR spectra from the serum samples of healthy control (A), diabetic neuropathy (B) and diabetic group (C). 1H CPMG spectra were processed using Mnova 10.0.20 Statistically significant metabolites (ascorbate, glucose, and citrate) were labeled on the spectrum. Lactate was also labeled because it contributed group separation. The enlarged spectra for ascorbate, citrate, glucose and lactate are depicted in the figure. The black line in the enlarged figure represent the spectra of healthy control group, the red line represents the spectra of diabetic neuropathy group and the blue line represent the spectra of diabetic group.

Table 1. Demographic and clinical characteristics of the patients

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Table 2. Statistical analysis of the non-parametric Kruskal-Wallis test

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