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- 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
- 5,531 View
- 101 Download
- 7 Web of Science
- 7 Crossref
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Abstract
PDF
Supplementary Material
PubReader 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.
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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
- The association between retinol-binding protein 4 and risk of type 2 diabetes: A systematic review and meta-analysis
- Metabolic Risk/Epidemiology
- Association between Higher Blood Pressure and Risk of Diabetes Mellitus in Middle-Aged and Elderly Chinese Adults
- Xue Yang, Jian Chen, An Pan, Jason H.Y. Wu, Fei Zhao, Yue Xie, Yi Wang, Yi Ye, Xiong-Fei Pan, Chun-Xia Yang
- Diabetes Metab J. 2020;44(3):436-445. Published online November 14, 2019
- DOI: https://doi.org/10.4093/dmj.2019.0081
- 4,838 View
- 83 Download
- 11 Web of Science
- 10 Crossref
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Abstract
PDFPubReader
Background To examine the prospective association between higher blood pressure (BP) and risk of type 2 diabetes mellitus (T2DM) in middle-aged and elderly Chinese adults.
Methods A total of 9,642 middle-aged and elderly Chinese adults (≥45 years old; 47.30% men) without diabetes from the China Health and Retirement Longitudinal Study were included for analyses. Participants were categorized into three groups: normal BP, prehypertension, and hypertension, according to the 2010 Chinese Guidelines for the Management of Hypertension. The incidence of T2DM was determined by self-reported physician diagnosis during two follow-up surveys conducted in 2013 to 2014 and 2015 to 2016.
Results During the 4-year follow-up, 429 participants (4.45%) developed T2DM, including 3.51% of the men and 5.29% of the women. The incidence rates of T2DM were 2.57%, 3.75%, and 6.71% in the normal BP, prehypertension, and hypertension groups, respectively. After adjustment for age, sex, education level, residence, smoking status, alcohol consumption, body mass index, waist circumference, and dyslipidemia, both prehypertension (odds ratio [OR], 1.32; 95% confidence interval [CI], 0.98 to 1.77) and hypertension (OR, 2.02; 95% CI, 1.54 to 2.64) were associated with increased risk of T2DM, compared to those with a normal BP. The ORs associated with T2DM were 1.08 (95% CI, 1.03 to 1.13) for an increase of 10 mm Hg in systolic BP and 1.06 (95% CI, 1.01 to 1.10) for an increase of 5 mm Hg in diastolic BP.
Conclusion Higher BP is a risk factor for T2DM in middle-aged and elderly Chines. It may be a potential target for diabetes prevention.
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Citations
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Haotian Wang, Yuan Li, Weijie Cao, Jie Zhang, Mingyang Cao, Xiaoni Meng, Di Liu, Youxin Wang
Diabetology & Metabolic Syndrome.2023;[Epub] CrossRef - Externalizing traits: Shared causalities for COVID-19 and Alzheimer's dementia using Mendelian randomization analysis
Haotian Wang, Mingyang Cao, Yingjun Xi, Weijie Cao, Xiaoyu Zhang, Xiaoni Meng, Deqiang Zheng, Lijuan Wu, Wei Wang, Di Liu, Youxin Wang, Shibu Yooseph
PNAS Nexus.2023;[Epub] CrossRef - Causal Paradigm Between Common Comorbidities of Cardiovascular and Metabolism-Related Diseases in Elderly: Evidence from Cross-Sectional and Mendelian Randomization Studies
Junwang Gu, Qi Wang, Xuanhui Wu, Han Zhang, Chunmei Wu, Wei Qiu
Diabetes, Metabolic Syndrome and Obesity.2023; Volume 16: 2953. CrossRef - Hypertension, Arterial Stiffness, and Diabetes: a Prospective Cohort Study
Xue Tian, Yingting Zuo, Shuohua Chen, Yijun Zhang, Xiaoli Zhang, Qin Xu, Shouling Wu, Anxin Wang
Hypertension.2022; 79(7): 1487. CrossRef - Integrated analysis of probability of type 2 diabetes mellitus with polymorphisms and methylation of SLC30A8 gene: a nested case-control study
Fulan Hu, Yanyan Zhang, Pei Qin, Yang Zhao, Dechen Liu, Qionggui Zhou, Gang Tian, Quanman Li, Chunmei Guo, Xiaoyan Wu, Ranran Qie, Shengbing Huang, Minghui Han, Yang Li, Dongsheng Hu, Ming Zhang
Journal of Human Genetics.2022; 67(11): 651. CrossRef - Understanding Frailty: Probabilistic Causality between Components and Their Relationship with Death through a Bayesian Network and Evidence Propagation
Ricardo Ramírez-Aldana, Juan Carlos Gomez-Verjan, Carmen García-Peña, Luis Miguel Gutiérrez-Robledo, Lorena Parra-Rodríguez
Electronics.2022; 11(19): 3001. CrossRef - Novel lipid indicators and the risk of type 2 diabetes mellitus among Chinese hypertensive patients: findings from the Guangzhou Heart Study
Hai Deng, Peng Hu, Huoxing Li, Huanning Zhou, Xiuyi Wu, Maohua Yuan, Xueru Duan, Miaochan Lao, Chuchu Wu, Murui Zheng, Xiang Qian Lao, Wenjing Zhao, Xudong Liu
Cardiovascular Diabetology.2022;[Epub] CrossRef - Trends and Comparisons of Blood Pressure and Fasting Plasma Glucose in Patients with Hypertension, Diabetes, and Comorbidity: 4-Year Follow-Up Data
Luxinyi Xu, Xiaotong Wen, Ying Yang, Dan Cui
Risk Management and Healthcare Policy.2022; Volume 15: 2221. CrossRef - Policyholder cluster divergence based differential premium in diabetes insurance
Benjiang Ma, Qing Tang, Yifang Qin, Muhammad Farhan Bashir
Managerial and Decision Economics.2021; 42(7): 1793. CrossRef - Association of hypertension and incident diabetes in Chinese adults: a retrospective cohort study using propensity-score matching
Yang Wu, Haofei Hu, Jinlin Cai, Runtian Chen, Xin Zuo, Heng Cheng, Dewen Yan
BMC Endocrine Disorders.2021;[Epub] CrossRef
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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
- 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
- 4,589 View
- 71 Download
- 9 Web of Science
- 8 Crossref
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Abstract
PDFSupplementary MaterialPubReader
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.
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Cytokine.2022; 153: 155843. CrossRef - Recent Developments in Biomarkers for Diagnosis and Screening of Type 2 Diabetes Mellitus
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Current Diabetes Reports.2022; 22(3): 95. CrossRef - Serum Fetuin-A and Risk of Gestational Diabetes Mellitus: An Observational Study and Mendelian Randomization Analysis
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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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