Unknown

Dataset Information

0

Identification of metabolic markers predictive of prediabetes in a Korean population.


ABSTRACT: Prediabetes (PD) is a high-risk state of developing type 2 diabetes, and cardiovascular and metabolic diseases. Metabolomics-based biomarker studies can provide advanced opportunities for prediction of PD over the conventional methods. Here, we aimed to identify metabolic markers and verify their abilities to predict PD, as compared to the performance of the traditional clinical risk factor (CRF) and previously reported metabolites in other population-based studies. Targeted metabolites quantification was performed in 1723 participants in the Korea Association REsource (KARE) cohort, from which 500 normal individuals were followed up for 6 years. We selected 12 significant metabolic markers, including five amino acids, four glycerophospholipids, two sphingolipids, and one acylcarnitine, at baseline, resulting in a predicted incidence of PD with an area under the curve (AUC) of 0.71 during follow-up. The performance of these metabolic markers compared to that of fasting glucose was significantly higher in obese patients (body mass index: BMI ≥ 25 kg/m2, 0.79 vs. 0.58, P < 0.001). The combination with metabolic markers, CRF, and fasting glucose yielded the best prediction performance (AUC = 0.86). Our results revealed that metabolic markers were not only associated with the risk of PD, but also improved the prediction performance in combination with conventional approaches.

SUBMITTER: Lee HS 

PROVIDER: S-EPMC7738529 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

Identification of metabolic markers predictive of prediabetes in a Korean population.

Lee Heun-Sik HS   Park Tae-Joon TJ   Kim Jeong-Min JM   Yun Jun Ho JH   Yu Ho-Yeong HY   Kim Yeon-Jung YJ   Kim Bong-Jo BJ  

Scientific reports 20201215 1


Prediabetes (PD) is a high-risk state of developing type 2 diabetes, and cardiovascular and metabolic diseases. Metabolomics-based biomarker studies can provide advanced opportunities for prediction of PD over the conventional methods. Here, we aimed to identify metabolic markers and verify their abilities to predict PD, as compared to the performance of the traditional clinical risk factor (CRF) and previously reported metabolites in other population-based studies. Targeted metabolites quantifi  ...[more]

Similar Datasets

| S-EPMC8766640 | biostudies-literature
| S-EPMC5082612 | biostudies-literature
| S-EPMC11196549 | biostudies-literature
2015-10-23 | GSE74303 | GEO
| S-EPMC11266026 | biostudies-literature
2015-10-23 | E-GEOD-74303 | biostudies-arrayexpress
2016-07-01 | GSE74203 | GEO
| S-EPMC10743615 | biostudies-literature
| S-EPMC4612998 | biostudies-literature
2016-07-01 | E-GEOD-74203 | biostudies-arrayexpress