Lipidomic risk score independently and cost-effectively predicts risk of future type 2 diabetes: results from diverse cohorts.
Lipids Health Dis
; 15: 67, 2016 Apr 04.
Article
en En
| MEDLINE
| ID: mdl-27044508
ABSTRACT
BACKGROUND:
Detection of type 2 diabetes (T2D) is routinely based on the presence of dysglycemia. Although disturbed lipid metabolism is a hallmark of T2D, the potential of plasma lipidomics as a biomarker of future T2D is unknown. Our objective was to develop and validate a plasma lipidomic risk score (LRS) as a biomarker of future type 2 diabetes and to evaluate its cost-effectiveness for T2D screening.METHODS:
Plasma LRS, based on significantly associated lipid species from an array of 319 lipid species, was developed in a cohort of initially T2D-free individuals from the San Antonio Family Heart Study (SAFHS). The LRS derived from SAFHS as well as its recalibrated version were validated in an independent cohort from Australia--the AusDiab cohort. The participants were T2D-free at baseline and followed for 9197 person-years in the SAFHS cohort (n = 771) and 5930 person-years in the AusDiab cohort (n = 644). Statistically and clinically improved T2D prediction was evaluated with established statistical parameters in both cohorts. Modeling studies were conducted to determine whether the use of LRS would be cost-effective for T2D screening. The main outcome measures included accuracy and incremental value of the LRS over routinely used clinical predictors of T2D risk; validation of these results in an independent cohort and cost-effectiveness of including LRS in screening/intervention programs for T2D.RESULTS:
The LRS was based on plasma concentration of dihydroceramide 180, lysoalkylphosphatidylcholine 221 and triacyglycerol 160/180/181. The score predicted future T2D independently of prediabetes with an accuracy of 76%. Even in the subset of initially euglycemic individuals, the LRS improved T2D prediction. In the AusDiab cohort, the LRS continued to predict T2D significantly and independently. When combined with risk-stratification methods currently used in clinical practice, the LRS significantly improved the model fit (p < 0.001), information content (p < 0.001), discrimination (p < 0.001) and reclassification (p < 0.001) in both cohorts. Modeling studies demonstrated that LRS-based risk-stratification combined with metformin supplementation for high-risk individuals was the most cost-effective strategy for T2D prevention.CONCLUSIONS:
Considering the novelty, incremental value and cost-effectiveness of LRS it should be used for risk-stratification of future T2D.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Diabetes Mellitus Tipo 2
/
Lípidos
Tipo de estudio:
Etiology_studies
/
Health_economic_evaluation
/
Incidence_studies
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Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Lipids Health Dis
Asunto de la revista:
BIOQUIMICA
/
METABOLISMO
Año:
2016
Tipo del documento:
Article
País de afiliación:
Estados Unidos