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Identification of free fatty acids profiling of type 2 diabetes mellitus and exploring possible biomarkers by GC–MS coupled with chemometrics

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Free fatty acids (FFAs), which are considered to be closely related with type 2 diabetes mellitus (T2DM), are not only the main energy source as nutrients, but also signaling molecules in insulin secretion. In this study, gas chromatography–mass spectrometry (GC–MS) coupled with two chemometric resolution methods, heuristic evolving latent projections (HELP) and selective ion analysis (SIA), was successfully applied to investigate plasma FFAs profiling of T2DM. Totally, twenty-three FFAs were identified and quantified. The results showed that HELP and SIA methods could be used to effectively handle overlapping peaks of GC–MS data and hence improve the qualitative and quantitative accuracy. Furthermore, a newly proposed competitive adaptive reweighted sampling (CARS) method coupled with partial least squares linear discriminant analysis (PLS-LDA) was introduced to seek the potential biomarkers. Finally, three fatty acids, oleic acid (OLA C18:1n-9), α-linolenic acid (ALA C18:3n-3), and eicosapentaenoic acid (EPA C20:5n-3), were identified as the potential biomarkers of T2DM for their powerful discriminant ability of T2DM patients from healthy controls. The study indicated that GC–MS combining with chemometric methods was a useful strategy to analyze metabolites and further screen the potential biomarkers of T2DM.

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This work is financially supported by the National Nature Foundation Committee of People’s Republic of China (Grant No. 20875104), the International cooperation project of ministry of science and technology of China (Grant No. 2007DFA40680), and 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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Correspondence to Yizeng Liang or Lunzhao Yi.

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Tan, B., Liang, Y., Yi, L. et al. Identification of free fatty acids profiling of type 2 diabetes mellitus and exploring possible biomarkers by GC–MS coupled with chemometrics. Metabolomics 6, 219–228 (2010). https://doi.org/10.1007/s11306-009-0189-8

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  • Free fatty acids (FFAs)
  • Type 2 diabetes mellitus (T2DM)
  • Heuristic evolving latent projections (HELP)
  • Selective ion analysis (SIA)
  • Competitive adaptive reweighted sampling (CARS)
  • Biomarkers