Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study.
Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study.
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DOI：
10.1136/bmjopen-2011-000191
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发表时间：
2011-08-27
期刊：
影响因子：
2.9
通讯作者：
Lin X
中科院分区：
文献类型：
--
作者：
Wu H;Yu Z;Qi Q;Li H;Sun Q;Lin X
2型糖尿病的发病率有哪些？评价多种生物标志物对中国人群2型糖尿病的鉴别能力。对3189例50-70岁中国人（男1419例，女1770例）血浆脂联素、纤溶酶原激活物抑制物-1、视黄醇结合蛋白4、C反应蛋白、白细胞介素6（IL-6）、肿瘤坏死因子α受体2和铁蛋白进行了测定。 基于这些生物标志物与2型糖尿病的关联强度，开发了加权生物标志物风险评分（BRS）。以受试者工作特征曲线下面积（AUC）作为判别指标。脂联素、纤溶酶原激活物抑制物-1、IL-6和铁蛋白与2型糖尿病患病率独立相关，并用于计算生物标志物风险评分（BRS）。校正混杂因素后，BRS每增加一点，2型糖尿病和空腹血糖受损的OR分别为1.28（95%CI 1.22 ~ 1.34）和1.16（1.12 ~ 1.20）。与BRS最低五分位数的参与者相比，最高五分位数的参与者患2型糖尿病的OR（95%CI）为6.67（4.21至10.55）。BRS和常规危险因素单独的曲线下面积分别为0.73和0.76，在结合BRS和常规危险因素后显著增加至0.81（p<0.001）。这些数据表明，结合多种生物标志物和传统的风险因素可能会大大提高识别2型糖尿病患者的能力。需要更多的前瞻性数据来证实这一观察结果。2型糖尿病的发展可以通过改变生活方式来延缓甚至预防。2型糖尿病的发病率有哪些？本研究评价了多种生物标志物在中国人群中对2型糖尿病的区分能力。检测了3189名中国人血浆脂联素、纤溶酶原激活物抑制物-1、视黄醇结合蛋白4、C反应蛋白、白细胞介素6、肿瘤坏死因子-α受体2和铁蛋白。基于这些生物标志物与2型糖尿病的关联强度，开发了加权生物标志物风险评分（BRS）。调整混杂因素后，BRS每增加一点，2型糖尿病的OR为1.28（95%CI 1.22 - 1.34）。BRS和常规危险因素单独的曲线下面积分别为0.73和0.76，在结合BRS和常规危险因素后显著增加至0.81（p<0.001）。这些发现表明，结合多种生物标志物和传统的风险因素可能会大大提高识别2型糖尿病患者的能力。这是第一项同时评估多种生物标志物与传统危险因素在中国北方和南方大规模人群样本中对2型糖尿病的区分能力的研究。局限性包括研究的横截面性质，不允许确定BRS预测糖尿病发病率的程度;空腹血糖仅测量一次。口服葡萄糖耐量试验既费时又费力，没有在如此大的人群中进行。
Identifying individuals with high risk of type 2 diabetes is important. To evaluate discriminatory ability of multiple biomarkers for type 2 diabetes in a Chinese population. Plasma adiponectin, plasminogen activator inhibitor-1, retinol-binding protein 4, resistin, C-reactive protein, interleukin 6 (IL-6), tumour necrosis factor α receptor 2 and ferritin were measured in a population-based sample of 3189 Chinese (1419 men and 1770 women) aged 50–70 years. A weighted biomarkers risk score (BRS) was developed based on the strength of associations of these biomarkers with type 2 diabetes. The discriminatory ability was tested by the area under receiver operating characteristics curve (AUC). Adiponectin, plasminogen activator inhibitor-1, IL-6 and ferritin were independently associated with the prevalence of type 2 diabetes, and they were used to calculate the biomarkers risk score (BRS). After adjustment for the confounding factors, the ORs for type 2 diabetes and impaired fasting glucose with each point increment of BRS were 1.28 (95% CI 1.22 to 1.34) and 1.16 (1.12 to 1.20), respectively. Compared with those in the lowest quintile of the BRS, the participants in the highest quintile have an OR (95% CI) of 6.67 (4.21 to 10.55) for type 2 diabetes. The area under the curve for the BRS and conventional risk factors alone was 0.73 and 0.76, respectively, and substantially increased to 0.81 after combining both BRS and conventional risk factors (p<0.001). These data suggest that combining multiple biomarkers and conventional risk factors might substantially enhance the ability to identify individuals with type 2 diabetes. More prospective data are warranted to confirm this observation. Development of type 2 diabetes could be delayed or even prevented by lifestyle modification. Identifying individuals with high risk of type 2 diabetes is important. This study evaluated the discriminatory ability of multiple biomarkers for type 2 diabetes in a Chinese population. Plasma adiponectin, plasminogen activator inhibitor-1, retinol-binding protein 4, resistin, C reactive protein, interleukin 6, tumour necrosis factor-α receptor 2 and ferritin were measured in a population-based sample of 3189 Chinese. A weighted biomarkers risk score (BRS) was developed based on the strength of associations of these biomarkers with type 2 diabetes. After adjustment for the confounding factors, the OR for type 2 diabetes with each point increment of BRS was 1.28 (95% CI 1.22 to 1.34). The area under the curve for the BRS and conventional risk factors alone was 0.73 and 0.76, respectively, and substantially increased to 0.81 after combining both BRS and conventional risk factors (p<0.001). These finding suggested that combining multiple biomarkers and conventional risk factors might substantially enhance the ability to identify individuals with type 2 diabetes. This is the first study simultaneously assessing the discriminatory ability of multiple biomarkers together with conventional risk factors for type 2 diabetes in a large population-based sample from the north and south of China. Limitations including, the cross-sectional nature of the study, did not allow determination of the extent to which diabetes incidence would be predicted by the BRS; fasting glucose was measured only once. The oral glucose tolerance test, which was time-consuming and labour intensive, was not performed in such a large population.
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