Plasma lipidic fingerprint associated with type 2 diabetes in patients with coronary heart disease: CORDIOPREV study
Authors' conclusion
Our study showed the potential of comprehensive lipidomic analysis in identifying patients at risk of developing T2DM. In addition, the lipid species combined with clinical variables provided a new, highly sensitive model which can be used in clinical practice to identify patients at T2DM risk. Moreover, these results also indicate that we need to look closely at isomers to understand the role of this specific compound in T2DM development.
Study context
- Population
- Coronary heart disease (CHD) patients of the CORDIOPREV study without diabetes at the beginning of the intervention107 developed T2D
- Participants
- 462 patients
- Outcome
- T2D development (American Diabetes Association criteria)
- Follow-up
- Median 60 months
Methodological detailslipidomic analysis within the CORDIOPREV study, Training and Validation Set (60-40), Random Survival Forest, liquid chromatography (LC)-tandem mass spectrometry (MS) lipidomics
- Lipidomic analysis within the CORDIOPREV study
- Training and Validation Set (60-40)
- Random Survival Forest
- LC-tandem MS lipidomics
Main finding
As reported in the abstract
Lipid species annotated by LC-tandem MS
440
Lipid species with lowest prediction error identified by Random Survival Forest (RSF)
15
Lipidomic Risk (LR) HR per unit SD, Training Set
2.87
LR HR per unit SD, Validation Set
1.43
Observational data: associations, not effects.
Further findings
Insulin sensitivity and liver insulin resistance by LR score
- Higher LR score: lower insulin sensitivity
- P = 0.006
- Higher LR score: higher liver insulin resistance
- P = 0.005
Production model combining clinical variables and selected lipidic isomers (generalised lineal model)
- ROC AUC
- 81.3%
Original publication
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