Serum retinal and retinoic acid predict the development of type 2 diabetes mellitus in korean subjects with impaired fasting glucose from the KCPS-II cohort

Youngmin Han, Yeunsoo Yang, Minjoo Kim, Sun Ha Jee, Hye Jin Yoo, Jong Ho Lee

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

We aimed to investigate whether retinal and retinoic acid (RA), which are newly discovered biomarkers from our previous research, reliably predict type 2 diabetes mellitus (T2DM) development in subjects with impaired fasting glucose (IFG). Among the Korean Cancer Prevention Study (KCPS)II cohort, subjects were selected and matched by age and sex (IFG-IFG group, n = 100 vs. IFG-DM group, n = 100) for study 1. For real-world validation of two biomarkers (study 2), other participants in the KCPS-II cohort who had IFG at baseline (n = 500) were selected. Targeted LC/MS was used to analyze the baseline serum samples; retinal and RA levels were quantified. In study 1, we revealed that both biomarkers were significantly decreased in the IFG-DM group (retinal, p = 0.017; RA, p < 0.001). The obese subjects in the IFG-DM group showed markedly lower retinal (p = 0.030) and RA (p = 0.003) levels than those in the IFG-IFG group. In study 2, the results for the two metabolites tended to be similar to those of study 1, but no significant difference was observed. Notably, the predictive ability for T2DM was enhanced when the metabolites were added to conventional risk factors for T2DM in both studies (study 1, AUC 0.682 → 0.775; study 2, AUC 0.734 → 0.786). The results suggest that retinal-and RA-related metabolic pathways are altered before the onset of T2DM.

Original languageEnglish
Article number510
JournalMetabolites
Volume11
Issue number8
DOIs
Publication statusPublished - 2021 Aug

Bibliographical note

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Molecular Biology

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