Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men

Tommi Suvitaival (Corresponding Author), Isabel Bondia-Pons, Laxman Yetukuri, Päivi Pöhö, John J. Nolan, Tuulia Hyötyläinen, Johanna Kuusisto, Matej Orešič

Research output: Contribution to journalArticleScientificpeer-review

24 Citations (Scopus)

Abstract

Background: There is a need for early markers to track and predict the development of type 2 diabetes mellitus (T2DM) from the state of normal glucose tolerance through prediabetes. In this study we tested whether the plasma molecular lipidome has biomarker potential to predicting the onset of T2DM. Methods: We applied global lipidomic profiling on plasma samples from well-phenotyped men (107 cases, 216 controls) participating in the longitudinal METSIM study at baseline and at five-year follow-up. To validate the lipid markers, an additional study with a representative sample of adult male population (n = 631) was also conducted. A total of 277 plasma lipids were analyzed using the lipidomics platform based on ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry. Lipids with the highest predictive power for the development of T2DM were computationally selected, validated and compared to standard risk models without lipids. Results: A persistent lipid signature with higher levels of triacylglycerols and diacyl-phospholipids as well as lower levels of alkylacyl phosphatidylcholines was observed in progressors to T2DM. Lysophosphatidylcholine acyl C18:2 (LysoPC(18:2)), phosphatidylcholines PC(32:1), PC(34:2e) and PC(36:1), and triacylglycerol TG(17:1/18:1/18:2) were selected to the full model that included metabolic risk factors and FINDRISC variables. When further adjusting for BMI and age, these lipids had respective odds ratios of 0.32, 2.4, 0.50, 2.2 and 0.31 (all p < 0.05) for progression to T2DM. The independently-validated predictive power improved in all pairwise comparisons between the lipid model and the respective standard risk model without the lipids (integrated discrimination improvement IDI > 0; p < 0.05). Notably, the lipid models remained predictive of the development of T2DM in the fasting plasma glucose-matched subset of the validation study. Conclusion: This study indicates that a lipid signature characteristic of T2DM is present years before the diagnosis and improves prediction of progression to T2DM. Molecular lipid biomarkers were shown to have predictive power also in a high-risk group, where standard risk factors are not helpful at distinguishing progressors from non-progressors.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalMetabolism: clinical and experimental
Volume78
DOIs
Publication statusPublished - 1 Jan 2018
MoE publication typeA1 Journal article-refereed

Fingerprint

Type 2 Diabetes Mellitus
Lipids
Phosphatidylcholines
Triglycerides
Biomarkers
Prediabetic State
Glucose
Lysophosphatidylcholines
Validation Studies
Liquid Chromatography
Longitudinal Studies
Fasting
Mass Spectrometry
Phospholipids
Odds Ratio
Population

Keywords

  • Lipidomics
  • Mass-spectrometry
  • METSIM study
  • Plasma profiling
  • Type 2 diabetes mellitus

Cite this

Suvitaival, T., Bondia-Pons, I., Yetukuri, L., Pöhö, P., Nolan, J. J., Hyötyläinen, T., ... Orešič, M. (2018). Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men. Metabolism: clinical and experimental, 78, 1-12. https://doi.org/10.1016/j.metabol.2017.08.014
Suvitaival, Tommi ; Bondia-Pons, Isabel ; Yetukuri, Laxman ; Pöhö, Päivi ; Nolan, John J. ; Hyötyläinen, Tuulia ; Kuusisto, Johanna ; Orešič, Matej. / Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men. In: Metabolism: clinical and experimental. 2018 ; Vol. 78. pp. 1-12.
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Suvitaival, T, Bondia-Pons, I, Yetukuri, L, Pöhö, P, Nolan, JJ, Hyötyläinen, T, Kuusisto, J & Orešič, M 2018, 'Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men', Metabolism: clinical and experimental, vol. 78, pp. 1-12. https://doi.org/10.1016/j.metabol.2017.08.014

Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men. / Suvitaival, Tommi (Corresponding Author); Bondia-Pons, Isabel; Yetukuri, Laxman; Pöhö, Päivi; Nolan, John J.; Hyötyläinen, Tuulia; Kuusisto, Johanna; Orešič, Matej.

In: Metabolism: clinical and experimental, Vol. 78, 01.01.2018, p. 1-12.

Research output: Contribution to journalArticleScientificpeer-review

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T1 - Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men

AU - Suvitaival, Tommi

AU - Bondia-Pons, Isabel

AU - Yetukuri, Laxman

AU - Pöhö, Päivi

AU - Nolan, John J.

AU - Hyötyläinen, Tuulia

AU - Kuusisto, Johanna

AU - Orešič, Matej

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Background: There is a need for early markers to track and predict the development of type 2 diabetes mellitus (T2DM) from the state of normal glucose tolerance through prediabetes. In this study we tested whether the plasma molecular lipidome has biomarker potential to predicting the onset of T2DM. Methods: We applied global lipidomic profiling on plasma samples from well-phenotyped men (107 cases, 216 controls) participating in the longitudinal METSIM study at baseline and at five-year follow-up. To validate the lipid markers, an additional study with a representative sample of adult male population (n = 631) was also conducted. A total of 277 plasma lipids were analyzed using the lipidomics platform based on ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry. Lipids with the highest predictive power for the development of T2DM were computationally selected, validated and compared to standard risk models without lipids. Results: A persistent lipid signature with higher levels of triacylglycerols and diacyl-phospholipids as well as lower levels of alkylacyl phosphatidylcholines was observed in progressors to T2DM. Lysophosphatidylcholine acyl C18:2 (LysoPC(18:2)), phosphatidylcholines PC(32:1), PC(34:2e) and PC(36:1), and triacylglycerol TG(17:1/18:1/18:2) were selected to the full model that included metabolic risk factors and FINDRISC variables. When further adjusting for BMI and age, these lipids had respective odds ratios of 0.32, 2.4, 0.50, 2.2 and 0.31 (all p < 0.05) for progression to T2DM. The independently-validated predictive power improved in all pairwise comparisons between the lipid model and the respective standard risk model without the lipids (integrated discrimination improvement IDI > 0; p < 0.05). Notably, the lipid models remained predictive of the development of T2DM in the fasting plasma glucose-matched subset of the validation study. Conclusion: This study indicates that a lipid signature characteristic of T2DM is present years before the diagnosis and improves prediction of progression to T2DM. Molecular lipid biomarkers were shown to have predictive power also in a high-risk group, where standard risk factors are not helpful at distinguishing progressors from non-progressors.

AB - Background: There is a need for early markers to track and predict the development of type 2 diabetes mellitus (T2DM) from the state of normal glucose tolerance through prediabetes. In this study we tested whether the plasma molecular lipidome has biomarker potential to predicting the onset of T2DM. Methods: We applied global lipidomic profiling on plasma samples from well-phenotyped men (107 cases, 216 controls) participating in the longitudinal METSIM study at baseline and at five-year follow-up. To validate the lipid markers, an additional study with a representative sample of adult male population (n = 631) was also conducted. A total of 277 plasma lipids were analyzed using the lipidomics platform based on ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry. Lipids with the highest predictive power for the development of T2DM were computationally selected, validated and compared to standard risk models without lipids. Results: A persistent lipid signature with higher levels of triacylglycerols and diacyl-phospholipids as well as lower levels of alkylacyl phosphatidylcholines was observed in progressors to T2DM. Lysophosphatidylcholine acyl C18:2 (LysoPC(18:2)), phosphatidylcholines PC(32:1), PC(34:2e) and PC(36:1), and triacylglycerol TG(17:1/18:1/18:2) were selected to the full model that included metabolic risk factors and FINDRISC variables. When further adjusting for BMI and age, these lipids had respective odds ratios of 0.32, 2.4, 0.50, 2.2 and 0.31 (all p < 0.05) for progression to T2DM. The independently-validated predictive power improved in all pairwise comparisons between the lipid model and the respective standard risk model without the lipids (integrated discrimination improvement IDI > 0; p < 0.05). Notably, the lipid models remained predictive of the development of T2DM in the fasting plasma glucose-matched subset of the validation study. Conclusion: This study indicates that a lipid signature characteristic of T2DM is present years before the diagnosis and improves prediction of progression to T2DM. Molecular lipid biomarkers were shown to have predictive power also in a high-risk group, where standard risk factors are not helpful at distinguishing progressors from non-progressors.

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KW - Mass-spectrometry

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KW - Plasma profiling

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Suvitaival T, Bondia-Pons I, Yetukuri L, Pöhö P, Nolan JJ, Hyötyläinen T et al. Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men. Metabolism: clinical and experimental. 2018 Jan 1;78:1-12. https://doi.org/10.1016/j.metabol.2017.08.014