Diabetes & Metabolism Journal

Original Articles

Metabolic Risk/Epidemiology
Multiple Biomarkers Improved Prediction for the Risk of Type 2 Diabetes Mellitus in Singapore Chinese Men and Women: Yeli Wang, Woon-Puay Koh, Xueling Sim, Jian-Min Yuan, An Pan; Diabetes Metab J. 2020;44(2):295-306. Published online November 22, 2019; DOI: https://doi.org/10.4093/dmj.2019.0020

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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.

Methods

Plasma 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).

Results

The 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).

Conclusion

A composite score of blood biomarkers improved T2DM risk prediction among Chinese.

Citations

Citations to this article as recorded by

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; : 1. CrossRef
Remnant Cholesterol Is an Independent Predictor of Type 2 Diabetes: A Nationwide Population-Based Cohort Study
Ji Hye Huh, Eun Roh, Seong Jin Lee, Sung-Hee Ihm, Kyung-Do Han, Jun Goo Kang
Diabetes Care.2023; 46(2): 305. CrossRef
A FRAMEWORK FOR THE ANALYSIS OF COMORBID CONDITIONS USING INTELLIGENT EXTRACTION OF MULTIPLE FLUID BIOMARKERS
PRIYANKA JADHAV, VINOTHINI SELVARAJU, SARITH P SATHIAN, RAMAKRISHNAN SWAMINATHAN
Journal of Mechanics in Medicine and Biology.2023;[Epub] CrossRef
Strikes and Gutters: Biomarkers and anthropometric measures for predicting diagnosed diabetes mellitus in adults in low- and middle-income countries
Sally Sonia Simmons
Heliyon.2023; 9(9): e19494. CrossRef
Association of IL-16 rs11556218 T/G polymorphism with the risk of developing type 2 diabetes mellitus
Dalia Ghareeb Mohammad, Hamdy Omar, Taghrid B. El-Abaseri, Wafaa Omar, Shaymaa Abdelraheem
Journal of Diabetes & Metabolic Disorders.2021; 20(1): 649. CrossRef
Biomarker Score in Risk Prediction: Beyond Scientific Evidence and Statistical Performance
Heejung Bang
Diabetes & Metabolism Journal.2020; 44(2): 245. CrossRef

Epidemiology
Plasma Fetuin-A Levels and Risk of Type 2 Diabetes Mellitus in A Chinese Population: A Nested Case-Control Study: Yeli Wang, Woon-Puay Koh, Majken K. Jensen, Jian-Min Yuan, An Pan; Diabetes Metab J. 2019;43(4):474-486. Published online March 20, 2019; DOI: https://doi.org/10.4093/dmj.2018.0171

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71 Download
9 Web of Science
8 Crossref

Abstract PDF Supplementary Material PubReader

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.

Methods

A 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.

Results

Compared 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.

Conclusion

There is a positive association between plasma fetuin-A levels and risk of developing T2DM in this Chinese population.

Citations

Citations to this article as recorded by

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International Journal of Noncommunicable Diseases.2024; 9(1): 4. CrossRef
The predicted mechanisms and evidence of probiotics on type 2 diabetes mellitus (T2DM)
Ousman Bajinka, Kodzovi Sylvain Dovi, Lucette Simbilyabo, Ishmail Conteh, Yurong Tan
Archives of Physiology and Biochemistry.2023; : 1. CrossRef
Multiplexed measurements of salivary fetuin-A, insulin, and adiponectin as potential non-invasive biomarkers in childhood obesity
Vaithinathan Selvaraju, Jeganathan R. Babu, Thangiah Geetha
Cytokine.2022; 153: 155843. CrossRef
Recent Developments in Biomarkers for Diagnosis and Screening of Type 2 Diabetes Mellitus
Margarita Ortiz-Martínez, Mirna González-González, Alexandro J. Martagón, Victoria Hlavinka, Richard C. Willson, Marco Rito-Palomares
Current Diabetes Reports.2022; 22(3): 95. CrossRef
Serum Fetuin-A and Risk of Gestational Diabetes Mellitus: An Observational Study and Mendelian Randomization Analysis
Ping Wu, Yi Wang, Yi Ye, Xue Yang, Qi Lu, Jiaying Yuan, Li Zha, Yan Liu, Xingyue Song, Shijiao Yan, Ying Wen, Xiaorong Qi, Chun-Xia Yang, Yixin Wang, Gang Liu, Chuanzhu Lv, Xiong-Fei Pan, An Pan
The Journal of Clinical Endocrinology & Metabolism.2022; 107(9): e3841. CrossRef
Hepatokines as a Molecular Transducer of Exercise
Dae Yun Seo, Se Hwan Park, Jubert Marquez, Hyo-Bum Kwak, Tae Nyun Kim, Jun Hyun Bae, Jin-Ho Koh, Jin Han
Journal of Clinical Medicine.2021; 10(3): 385. CrossRef
Serum Fetuin-B Levels Are Elevated in Women with Metabolic Syndrome and Associated with Increased Oxidative Stress
Shiyao Xue, Hongdong Han, Shunli Rui, Mengliu Yang, Yizhou Huang, Bin Zhan, Shan Geng, Hua Liu, Chen Chen, Gangyi Yang, Ling Li, Colin Murdoch
Oxidative Medicine and Cellular Longevity.2021; 2021: 1. CrossRef
CD44, a Predominant Protein in Methylglyoxal-Induced Secretome of Muscle Cells, is Elevated in Diabetic Plasma
Shakuntala Bai, Arvindkumar H. Chaurasiya, Reema Banarjee, Prachi B. Walke, Faraz Rashid, Ambika G. Unnikrishnan, Mahesh J. Kulkarni
ACS Omega.2020; 5(39): 25016. CrossRef

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