- Metabolic Risk/Epidemiology
- Multiple Biomarkers Improved Prediction for the Risk of Type 2 Diabetes Mellitus in Singapore Chinese Men and Women
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Yeli Wang, Woon-Puay Koh, Xueling Sim, Jian-Min Yuan, An Pan
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Diabetes Metab J. 2020;44(2):295-306. Published online November 22, 2019
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DOI: https://doi.org/10.4093/dmj.2019.0020
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Abstract
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- Background
Multiple biomarkers have performed well in predicting type 2 diabetes mellitus (T2DM) risk in Western populations. However, evidence is scarce among Asian populations. MethodsPlasma triglyceride-to-high density lipoprotein (TG-to-HDL) ratio, alanine transaminase (ALT), high-sensitivity C-reactive protein (hs-CRP), ferritin, adiponectin, fetuin-A, and retinol-binding protein 4 were measured in 485 T2DM cases and 485 age-and-sex matched controls nested within the prospective Singapore Chinese Health Study cohort. Participants were free of T2DM at blood collection (1999 to 2004), and T2DM cases were identified at the subsequent follow-up interviews (2006 to 2010). A weighted biomarker score was created based on the strengths of associations between these biomarkers and T2DM risks. The predictive utility of the biomarker score was assessed by the area under receiver operating characteristics curve (AUC). ResultsThe biomarker score that comprised of four biomarkers (TG-to-HDL ratio, ALT, ferritin, and adiponectin) was positively associated with T2DM risk (P trend <0.001). Compared to the lowest quartile of the score, the odds ratio was 12.0 (95% confidence interval [CI], 5.43 to 26.6) for those in the highest quartile. Adding the biomarker score to a base model that included smoking, history of hypertension, body mass index, and levels of random glucose and insulin improved AUC significantly from 0.81 (95% CI, 0.78 to 0.83) to 0.83 (95% CI, 0.81 to 0.86; P=0.002). When substituting the random glucose levels with glycosylated hemoglobin in the base model, adding the biomarker score improved AUC from 0.85 (95% CI, 0.83 to 0.88) to 0.86 (95% CI, 0.84 to 0.89; P=0.032). ConclusionA composite score of blood biomarkers improved T2DM risk prediction among Chinese.
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Citations
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- The association between retinol-binding protein 4 and risk of type 2 diabetes: A systematic review and meta-analysis
Xiaomeng Tan, Han Zhang, Limin Liu, Zengli Yu, Xinxin Liu, Lingling Cui, Yao Chen, Huanhuan Zhang, Zhan Gao, Zijian Zhao International Journal of Environmental Health Research.2024; 34(2): 1053. CrossRef - Baseline glycated albumin level and risk of type 2 diabetes mellitus in Healthy individuals: a retrospective longitudinal observation in Korea
Kang-Su Shin, Min-Seung Park, Mi Yeon Lee, Eun Hye Cho, Hee-Yeon Woo, Hyosoon Park, Min-Jung Kwon Scandinavian Journal of Clinical and Laboratory Investigation.2024; 84(3): 168. CrossRef - Are Oxidative Stress Biomarkers Reliable Part of Multimarker Panel in Female Patients with Type 2 Diabetes Mellitus?
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- Epidemiology
- Plasma Fetuin-A Levels and Risk of Type 2 Diabetes Mellitus in A Chinese Population: A Nested Case-Control Study
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Yeli Wang, Woon-Puay Koh, Majken K. Jensen, Jian-Min Yuan, An Pan
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Diabetes Metab J. 2019;43(4):474-486. Published online March 20, 2019
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DOI: https://doi.org/10.4093/dmj.2018.0171
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- Background
Fetuin-A is a hepatokine that involved in the pathogenesis of insulin resistance. Previous epidemiological studies have found a positive association between blood fetuin-A and type 2 diabetes mellitus (T2DM) risk among Caucasians and African Americans. We aimed to investigate the prospective relationship between fetuin-A and T2DM in an Asian population for the first time. MethodsA nested case-control study was established within a prospective cohort of Chinese living in Singapore. At blood collection (1999 to 2004), all participants were free of diagnosed T2DM and aged 50 to 79 years. At subsequent follow-up (2006 to 2010), 558 people reported to have T2DM and were classified as incident cases, and 558 controls were randomly chosen from the participants who did not develop T2DM to match with cases on age, sex, dialect group, and date of blood collection. Plasma fetuin-A levels were measured retrospectively in cases and controls using samples collected at baseline. Conditional logistic regression models were used to compute the odds ratio (OR) and 95% confidence interval (CI). Restricted cubic spline analysis was used to examine a potential non-linear association between fetuin-A levels and T2DM risk. ResultsCompared with those in the lowest fetuin-A quintile, participants in the highest quintile had a two-fold increased risk of developing T2DM (OR, 2.06; 95% CI, 1.21 to 3.51). A non-linear association was observed (P nonlinearity=0.005), where the association between fetuin-A levels and T2DM risk plateaued at plasma concentrations around 830 µg/mL. ConclusionThere is a positive association between plasma fetuin-A levels and risk of developing T2DM in this Chinese population.
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