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Metabolic alterations of impaired fasting glucose by GC/MS based plasma metabolic profiling combined with chemometrics

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Abstract

In this paper, a new strategy for processing GC/MS based metabolic profiling data via multivariate methods was proposed, which is applied to a small pilot study of impaired fasting glucose. The data obtained from plasma samples of impaired fasting glucose patients and healthy controls were first treated by principal component analysis and partial least squares-discriminant analysis to explore the differences and discriminators of the two groups. Subsequently, correlation analyses were employed to examine the relationships between blood glucose and the discriminators or their linear combination, thus may be considered as potential biomarkers of impaired fasting glucose. The results showed that the metabolic patterns of the two groups were different. Furthermore, eleven metabolites were screened as discriminators. Levels of nine of the eleven discriminators, say lactate, 2-ketoisocaproic acid, alanine, α-hydroxyisobutyric acid, urea, phosphoric acid, α-glycerophosphoric acid, palmitic acid and stearic acid, were found to be significantly higher in impaired fasting glucose patients, while 1-monopalmitin and 1-monostearin showed the opposite trend. Correlation analysis indicated that 2-ketoisocaproic acid, stearic acid were positively, while 1-monopalmitin and 1-monostearin were negatively correlated with blood glucose. Moreover, blood glucose correlated well with the linear combination of the eleven discriminators by canonical correlation analysis. The results have demonstrated that 2-ketoisocaproic acid, stearic acid and the linear combination of the eleven discriminators may be considered as the potential biomarkers of impaired fasting glucose and the proposed method may be useful in a larger study for exploring the metabolic alterations and biomarker candidates of diseases.

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Abbreviations

BMI:

Body mass index

DBP:

Diastolic blood pressure

FBS:

Fasting blood sugar

HDL:

High density lipoprotein

LDL:

Low density lipoprotein

PCA:

Principal component analysis

PLS-DA:

Partial least squares-discriminant analysis

SBP:

Systolic blood pressure

TC:

Total cholesterol

TG:

Total triglyceride

WHR:

Waist-hip ratio

References

  • Alberti, K. G., & Zimmet, P. Z. (1998). Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus. Provisional report of a WHO Consultation. Diabetic Medicine, 15, 539–553.

    Article  CAS  PubMed  Google Scholar 

  • Barker, M., & Rayens, W. (2003). Partial least squares for discrimination. Journal of Chemometrics, 17, 166–173.

    Article  CAS  Google Scholar 

  • Bock, G., Chittilapilly, E., Basu, R., Toffolo, G., Cobelli, C., Chandramouli, V., et al. (2007). Contribution of hepatic and extrahepatic insulin resistance to the pathogenesis of impaired fasting glucose. Diabetes, 56, 1703–1711.

    Article  CAS  PubMed  Google Scholar 

  • Breiman, L. (2001). Random forest. Machine Learning, 45, 5–32.

    Article  Google Scholar 

  • Bruce, S. J., Jonsson, P., Antti, H., Cloarec, O., Trygg, J., Marklund, S. L., et al. (2008). Evaluation of a protocol for metabolic profiling studies on human blood plasma by combined ultra-performance liquid chromatography/mass spectrometry: From extraction to data analysis. Analytical Biochemistry, 72, 237–249.

    Article  Google Scholar 

  • Chan, E. C. Y., Koh, P. K., Mal, M., Cheah, P. Y., Eu, K. W., Backshall, A., et al. (2009). Metabolic profiling of human colorectal cancer using high-resolution magic spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy and gas chromatography mass spectrometry (GC/MS). Journal of Proteome Research, 8, 352–361.

    Article  CAS  PubMed  Google Scholar 

  • De Jong, S. (1993). SIMPLS: An alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 18, 251–263.

    Article  Google Scholar 

  • Dumas, M. E., Barton, R. H., Toye, A., Cloarec, O., Blancher, C., Rothwell, A., et al. (2006). Metabolic profiling reveals a contribution gut microbiota to fatty liver phenotype in insulin-resistance mice. Proceedings of the National Academy of Sciences USA, 103, 12511–12516.

    Article  CAS  Google Scholar 

  • Genuth, S. (2003). Lowering the criterion for impaired fasting glucose is in order. Diabetes Care, 26, 3331–3332.

    Article  PubMed  Google Scholar 

  • Gong, F., Liang, Y. Z., Cui, H., Chau, F. T., & Chan, B. T. (2001). Determination of volatile components in peptic power by gas chromatograpy-mass spectrometry and chemometric resolution. Journal of Chromatography. A, 909, 237–247.

    Article  CAS  PubMed  Google Scholar 

  • Harris, M. I., Flegal, K. M., Cowie, C. C., Eberhardt, M. S., Goldstein, D. E., Little, R. R., et al. (1998). Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults. The Third National Health and Nutrition Examination Survey. Diabetes Care, 21, 518–524.

    Article  CAS  PubMed  Google Scholar 

  • King, H., Aubert, R. E., & Herman, W. H. (1998). Global burden of diabetes, 1995–2005: Prevalence, numerical estimates, and projections. Diabetes Care, 21, 1414–1431.

    Article  CAS  PubMed  Google Scholar 

  • Kvalheim, O. M., & Liang, Y. Z. (1992). Heuristic evolving latent projections: Resolving two-way multicomponent data. 1, selectivity, latent-projective graph, datascope, local rank, and unique resolution. Analytical Chemistry, 64, 936–946.

    Article  CAS  Google Scholar 

  • Liang, Y. Z., Kvalheim, O. M., Keller, H. R., Massart, D. L., Kiechle, P., & Erni, F. (1992). Heuristic evolving latent projections: Resolving two-way multicomponent data. 2, detection and resolution of minor constituents. Analytical Chemistry, 64, 946–953.

    Article  CAS  Google Scholar 

  • Mal, M., Koh, P. K., Cheah, P. Y., & Chan, E. C. Y. (2009). Development and validation of a gas chromatography/mass spectrometry method for the metabolic profiling of human colon tissue. Rapid Communications in Mass Spectrometry, 23, 487–494.

    Article  CAS  PubMed  Google Scholar 

  • McGarry, J. D. (2002). Banting lecture 2001: Dysregulation of fatty acid metabolism in the etiology of type 2 diabetes mellitus. Diabetes, 51, 7–18.

    Article  CAS  PubMed  Google Scholar 

  • Meyer, C., Stumvoll, M., Nadkarni, V., Dostou, J., Mitrakou, A., & Gerich, J. (1998). Abnormal renal and hepatic glucose metabolism in type 2 diabetes mellitus. Journal of Clinical Investigation, 102, 619–624.

    Article  CAS  PubMed  Google Scholar 

  • Nathan, D. M., Davidson, M. B., DeFronzo, R. A., Heine, R. J., Henry, R. R., Pratley, R., et al. (2007). Impaired fasting glucose and impaired glucose tolerance. Diabetes Care, 30, 753–759.

    Article  CAS  PubMed  Google Scholar 

  • Pasikanti, K. K., Ho, P. C., & Chan, E. C. Y. (2008). Gas chromatography/mass spectrometry in metabolic profiling of biological fluids. Journal of Chromatography B, 871, 202–211.

    Article  CAS  Google Scholar 

  • Pongsuwan, W., Fukusaki, E., Bamba, T., Yonetani, T., Yamahara, T., & Kobayashi, A. (2007). Prediction of Japanese green tea ranking by gas chromatography/mass spectrometry-based hydrophilic metabolite fingerprinting. Journal of Agriculture and Food Chemistry, 55, 231–236.

    Article  CAS  Google Scholar 

  • Rao, C. R. (1958). Some statistical methods for comparison of growth curves. Biometrics, 14, 1–17.

    Article  Google Scholar 

  • Rudell, D. R., Mattheis, J. P., & Curry, E. A. (2008). Prestorage ultraviolet-white light irradiation alters apple peel metabolome. Journal of Agriculture and Food Chemistry, 56, 1138–1147.

    Article  CAS  Google Scholar 

  • Shepherd, T., Dobson, G., Verrall, S. R., Conner, S., Griffiths, D. W., McNicol, J. W., et al. (2007). Potato metabolomics by GC-MS: What are the limiting factors. Metabolomics, 3, 475–488.

    Article  CAS  Google Scholar 

  • Snehalatha, C., Ramachandran, A., Sivasankari, S., Satyavani, K., & Vijay, V. (2003). Insulin secretion and action show differences in impaired fasting glucose and in impaired glucose tolerance in Asian Indians. Diabetes/Metabolism Research and Reviews, 19, 329–332.

    Article  CAS  PubMed  Google Scholar 

  • Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society B, 36, 111–147.

    Google Scholar 

  • Wade, J. B., Dougherty, L. M., Hart, R. P., Rafii, A., & Price, D. D. (1992). A canonical correlation analysis of the influence of neuroticism and extroversion on chronic pain, suffering, and pain behavior. Pain, 51, 67–73.

    Article  CAS  PubMed  Google Scholar 

  • Wang, C., Kong, H. W., Guan, Y. F., Yang, J., Gu, J. R., Yang, S. L., et al. (2005). Plasma phospholipid metabolic profiling and biomarkers of type 2 diabetes mellitus based on high-performance liquid chromatography/electrospray mass spectrometry and multivariate statistical analysis. Analytical Chemistry, 7, 4108–4116.

    Article  Google Scholar 

  • Webb, G. C., Akbar, M. S., Zhao, C. J., & Steiner, D. F. (2000). Expression profiling of pancreatic β-cells: glucose regulation of secretory and metabolic pathway genes. Proceedings of the National Academy of Sciences USA, 97, 5773–5778.

    Article  CAS  Google Scholar 

  • Winder, C. L., Dunn, W. B., Schuler, S., Broadhurst, D., Jarvis, R., Stephens, G. M., et al. (2008). Global metabolic profiling of Escherichia coli cultures: An evaluation of methods for quenching and extraction of intracellular metabolites. Analytical Chemistry, 80, 2939–2948.

    Article  CAS  PubMed  Google Scholar 

  • Wold, S., Esbensen, K., & Geladi, P. (1987). Principal component analysis. Chemometrics and Intelligent Laboratory Systems, 2, 37–52.

    Article  CAS  Google Scholar 

  • Wold, S., Sjostrom, M., & Eriksson, L. (2001). PLS-regression: A basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems, 58, 109–130.

    Article  CAS  Google Scholar 

  • Xu, Q. S., & Liang, Y. Z. (2001). Monte Carlo cross validation. Chemometrics and Intelligent Laboratory Systems, 56, 1–11.

    Article  CAS  Google Scholar 

  • Zeng, M. M., Che, Z. H., Liang, Y. Z., Wang, B., Chen, X., Li, H. D., et al. (2009). GC-MS based plasma metabolic profiling of type 2 diabetes mellitus. Chromatographia, 69, 941–948.

    Article  CAS  Google Scholar 

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Acknowledgment

This work was supported financially by International Traditional Chinese Medicine Program for Cooperation in Science and Technology (No. 2006DFA41090 and 2007DFA40680), National Key Basic Research Program (No. 2006CB503901) founded by the Ministry of Science and Technology of the People’s Republic of China.

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Authors and Affiliations

  1. College of Chemistry and Chemical Engineering, Central South University, 410083, Changsha, China

    Maomao Zeng, Yizeng Liang, Bing Wang, Xian Chen, Dongsheng Cao, Hongdong Li & Mei Wang

  2. Diabetes Center & Metabolic Syndrome Research Center, Institute of Metabolism and Endocrinology, Central South University, 410011, Changsha, China

    Yang Xiao & Zhiguang Zhou

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  1. Maomao Zeng
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  2. Yang Xiao
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  3. Yizeng Liang
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  4. Bing Wang
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  5. Xian Chen
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  6. Dongsheng Cao
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  7. Hongdong Li
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  8. Mei Wang
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  9. Zhiguang Zhou
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Correspondence to Yizeng Liang or Zhiguang Zhou.

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Zeng, M., Xiao, Y., Liang, Y. et al. Metabolic alterations of impaired fasting glucose by GC/MS based plasma metabolic profiling combined with chemometrics. Metabolomics 6, 303–311 (2010). https://doi.org/10.1007/s11306-009-0193-z

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  • DOI: https://doi.org/10.1007/s11306-009-0193-z

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