Research
Print page Print page
Switch language
The Capital Region of Denmark - a part of Copenhagen University Hospital
Published

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

Research output: Contribution to journalJournal articleResearchpeer-review

  1. Abnormal levels of adipokines in adolescent offspring of women with type 1 diabetes - Results from the EPICOM study

    Research output: Contribution to journalJournal articleResearchpeer-review

  2. Imbalance of plasma amino acids, metabolites and lipids in patients with lysinuric protein intolerance (LPI)

    Research output: Contribution to journalJournal articleResearchpeer-review

  3. Vagotomy and subsequent development of diabetes - A nested case-control study

    Research output: Contribution to journalJournal articleResearchpeer-review

  1. Impact of binge drinking on hepatic lipid metabolism: lipidome analysis of liver vein and peripheral blood during acute alcohol intoxication

    Research output: Contribution to journalConference abstract in journalResearchpeer-review

  2. Polyols and Branched Chained Amino Acids Are Associated with Present and Future Renal Impairment in Type 1 Diabetes

    Research output: Contribution to journalConference abstract in journalResearchpeer-review

  3. Targeted Clinical Metabolite Profiling Platform for the Stratification of Diabetic Patients

    Research output: Contribution to journalJournal articleResearchpeer-review

  4. Cell populations and molecular biomarkers in blood and urine characterise nephropathy in type 1 diabetes

    Research output: Contribution to journalConference abstract in journalResearchpeer-review

View graph of relations

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.

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.

Original languageEnglish
JournalMetabolism: Clinical and Experimental
Volume78
Pages (from-to)1-12
Number of pages12
ISSN0026-0495
DOIs
Publication statusPublished - 1 Jan 2018

    Research areas

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

ID: 52552438