Ku Kam-Ching, Zhong Junda, Song Erfei, Fong Carol Ho-Yi, Lam Karen Siu-Ling, Xu Aimin, Lee Chi-Ho, Cheung Chloe Yu-Yan
Department of Medicine, University of Hong Kong, Hong Kong 999077, China.
State Key Laboratory of Pharmaceutical Biotechnology, University of Hong Kong, Hong Kong 999077, China.
World J Diabetes. 2025 Apr 15;16(4):102867. doi: 10.4239/wjd.v16.i4.102867.
Despite being the gold standard, the use of glycated hemoglobin (HbA1c) and fasting plasma glucose (FPG) for diagnosing dysglycemia is imperfect. In particular, a low level of agreement between HbA1c and FPG in detecting prediabetes and diabetes has led to difficulties in clinical interpretation. Glycated albumin (GA) and 1,5-anhydroglucitol (1,5-AG) may potentially serve as biomarkers for the detection and prediction of diabetes, as well as glycemic monitoring.
To explore the diagnostic performance of GA and 1,5-AG for screening dysglycemia; assess whether they can be used for glycemic monitoring in Chinese morbidly-obese patients; and examine their predictive ability for incident diabetes in a Chinese community-based cohort.
GA and 1,5-AG concentrations were measured in 462 morbidly-obese patients from the Obese Chinese Cohort (OCC). A sub-group of diabetes subjects ( = 24) was prospectively followed-up after bariatric surgery. Differences between baseline and post-surgery biomarker values were converted to percentage change from baseline to assess the response to glycemic control. Predictive ability of the biomarkers was assessed in 132 incident diabetes cases and 132 matched non-diabetes controls in the community-based Cardiovascular Risk Factor Prevalence Study (CRISPS). A prediction model was developed and compared with clinical models based on conventional risk factors.
GA exhibited an excellent diagnostic value with an area under the receiver operating characteristic curve (AUC) of 0.919 (95%CI: 0.884-0.955) for identifying diabetes and a high agreement in the classification of diabetes with both FPG and HbA1c in the OCC. GA demonstrated the fastest response to glycemic control. In CRISPS, the 'B3A' prediction model, which consisted of body mass index (BMI) and 3 biomarkers (HbA1c, GA and 1,5-AG), achieved a comparable predictive value [AUC (95%CI): 0.793 (0.744-0.843)] to that of a clinical model comprising BMI, HbA1c, FPG and 2-hour glucose (2hG) [AUC (95%CI): 0.783 (0.733-0.834); DeLong value = 0.736]. The 'B3A' was significantly superior to a clinical model including BMI, HbA1c, FPG and triglycerides [AUC (95%CI): 0.729 (0.673-0.784); DeLong value = 0.027].
GA and 1,5-AG have the potential to act as robust biomarkers for the screening and risk prediction of diabetes. FPG and 2hG may be replaced by GA and 1,5-AG in future diabetes predictions.
尽管糖化血红蛋白（HbA1c）和空腹血糖（FPG）是诊断血糖异常的金标准，但它们的应用并不完美。特别是，HbA1c和FPG在检测糖尿病前期和糖尿病时一致性较低，导致临床解读困难。糖化白蛋白（GA）和1,5-脱水葡萄糖醇（1,5-AG）可能作为检测和预测糖尿病以及血糖监测的生物标志物。
探讨GA和1,5-AG用于筛查血糖异常的诊断性能；评估它们是否可用于中国病态肥胖患者的血糖监测；并在中国社区队列中检验它们对新发糖尿病的预测能力。
在462名来自中国肥胖队列（OCC）的病态肥胖患者中测量GA和1,5-AG浓度。对24名糖尿病患者亚组在减重手术后进行前瞻性随访。将基线和手术后生物标志物值的差异转换为相对于基线的百分比变化，以评估血糖控制的反应。在基于社区的心血管危险因素患病率研究（CRISPS）中，对132例新发糖尿病病例和132例匹配的非糖尿病对照评估生物标志物的预测能力。开发了一个预测模型，并与基于传统危险因素的临床模型进行比较。
GA在识别糖尿病方面表现出优异的诊断价值，受试者工作特征曲线（AUC）下面积为0.919（95%CI：0.884 - 0.955），并且在OCC中与FPG和HbA1c对糖尿病的分类有高度一致性。GA对血糖控制的反应最快。在CRISPS中，由体重指数（BMI）和3种生物标志物（HbA1c、GA和1,5-AG）组成的“B3A”预测模型与包含BMI、HbA1c、FPG和餐后2小时血糖（2hG）的临床模型具有相当的预测价值[AUC（95%CI）：0.793（0.744 - 0.843）] [AUC（95%CI）：0.783（0.733 - 0.834）；DeLong检验值 = 0.736]。“B3A”模型显著优于包含BMI、HbA1c、FPG和甘油三酯的临床模型[AUC（95%CI）：0.729（0.673 - 0.784）；DeLong检验值 = 0.027]。
GA和1,5-AG有潜力作为糖尿病筛查和风险预测的可靠生物标志物。在未来糖尿病预测中，FPG和2hG可能会被GA和1,5-AG取代。
