Early Prediction of Developing Type 2 Diabetes by Plasma Acylcarnitines: A Population-Based Study

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Abstract
OBJECTIVE: Acylcarnitines were suggested as early biomarkers even prior to insulin resistance in animal studies, but their roles in predicting type 2 diabetes were unknown. Therefore, we aimed to determine whether acylcarnitines could independently predict type 2 diabetes by using a targeted metabolic profiling approach. RESEARCH DESIGN AND METHODS: A population-based prospective study was conducted among 2,103 community-living Chinese individuals aged 50–70 years from Beijing and Shanghai with a mean follow-up duration of 6 years. Fasting glucose, glycohemoglobin, and insulin were determined at baseline and in a follow-up survey. Baseline plasma acylcarnitines were profiled by liquid chromatography–tandem mass spectrometry. RESULTS: Over the 6-year period, 507 participants developed diabetes. A panel of acylcanitines, especially with long chain, was significantly associated with increased risk of type 2 diabetes. The relative risks of type 2 diabetes per SD increase of the predictive model score were 2.48 (95% CI 2.20–2.78) for the conventional and 9.41 (95% CI 7.62–11.62) for the full model including acylcarnitines, respectively. Moreover, adding selected acylcarnitines substantially improved predictive ability for incident diabetes, as area under the receiver operator characteristic curve improved to 0.89 in the full model compared with 0.73 in the conventional model. Similar associations were obtained when the predictive models were established separately among Beijing or Shanghai residents. CONCLUSIONS: A panel of acylcarnitines, mainly involving mitochondrial lipid dysregulation, significantly improved predictive ability for type 2 diabetes beyond conventional risk factors. These findings need to be replicated in other populations, and the underlying mechanisms should be elucidated.
Funding Information
  • Ministry of Science and Technology of China (2012CB524900, 2014CB910500)
  • National Natural Science Foundation of China (30930081, 31470808, 81321062, 81561128018)
  • Chinese Academy of Sciences (KJZD-EW-L14, KSCX2-EW-R-10)
  • Novo Nordisk A/S

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