Thirty-one novel biomarkers as predictors for clinically incident diabetes.
Thirty-one novel biomarkers as predictors for clinically incident diabetes.
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DOI：
10.1371/journal.pone.0010100
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发表时间：
2010-04-09
期刊：
影响因子：
3.7
通讯作者：
Blankenberg S
中科院分区：
文献类型：
--
作者：
Salomaa V;Havulinna A;Saarela O;Zeller T;Jousilahti P;Jula A;Muenzel T;Aromaa A;Evans A;Kuulasmaa K;Blankenberg S
糖尿病的流行率在所有工业化国家都在增加，预防糖尿病已成为公共卫生的优先事项。然而，糖尿病风险的预测因素还没有得到充分的了解。我们评估了31种新的生物标志物是否有助于预测糖尿病发病风险。生物标志物主要在FINRISK 97队列中进行评价（n = 7，827;随访期间有417例临床新发糖尿病病例）。 这些发现在健康2000队列中得到了重复（n = 4，977;随访期间有179例临床糖尿病病例）。 我们使用考克斯比例风险模型计算糖尿病的相对风险，在调整了经典的风险因素后，分别为每个生物标志物。接下来，我们使用受试者工作特征曲线和C-统计、综合区分改善（IDI）和净重新分类改善（NRI）评估了单个生物标志物的区分能力。最后，我们在FINRISK 97队列中推导出生物标志物评分，并在Health 2000队列中对其进行了验证。由脂联素、载脂蛋白B、C-反应蛋白和铁蛋白组成的评分几乎使验证队列中糖尿病的相对风险增加了一倍（HR每增加一个标准差1.88，p = 2.8 e-5）。 它还改善了模型的区分度（IDI = 0.0149，p<0.0001）和糖尿病风险的重新分类（NRI = 11.8%，p = 0.006）。 按性别划分的分析表明，男女之间的最佳得分不同。在男性中，四种生物标志物的评分结果最好：脂联素、载脂蛋白B、铁蛋白和白细胞介素1受体拮抗剂，其NRI为25.4%（p<0.0001）。在女性中，最好的评分包括脂联素、载脂蛋白B、C反应蛋白和胰岛素。NRI为13.6%（p = 0.041）。 我们发现了新的生物标志物，这些生物标志物与临床糖尿病发病风险相关，超过了经典的风险因素。这为糖尿病的发病机制提供了新的见解，并可能有助于靶向预防和治疗。
The prevalence of diabetes is increasing in all industrialized countries and its prevention has become a public health priority. However, the predictors of diabetes risk are insufficiently understood. We evaluated, whether 31 novel biomarkers could help to predict the risk of incident diabetes. The biomarkers were evaluated primarily in the FINRISK97 cohort (n = 7,827; 417 cases of clinically incident diabetes during the follow-up). The findings were replicated in the Health 2000 cohort (n = 4,977; 179 cases of clinically incident diabetes during the follow-up). We used Cox proportional hazards models to calculate the relative risk of diabetes, after adjusting for the classic risk factors, separately for each biomarker. Next, we assessed the discriminatory ability of single biomarkers using receiver operating characteristic curves and C-statistics, integrated discrimination improvement (IDI) and net reclassification improvement (NRI). Finally, we derived a biomarker score in the FINRISK97 cohort and validated it in the Health 2000 cohort. A score consisting of adiponectin, apolipoprotein B, C-reactive protein and ferritin almost doubled the relative risk of diabetes in the validation cohort (HR per one standard deviation increase 1.88, p = 2.8 e-5). It also improved discrimination of the model (IDI = 0.0149, p<0.0001) and reclassification of diabetes risk (NRI = 11.8%, p = 0.006). Gender-specific analyses suggested that the best score differed between men and women. Among men, the best results were obtained with the score of four biomarkers: adiponectin, apolipoprotein B, ferritin and interleukin-1 receptor antagonist, which gave an NRI of 25.4% (p<0.0001). Among women, the best score included adiponectin, apolipoprotein B, C-reactive protein and insulin. It gave an NRI of 13.6% (p = 0.041). We identified novel biomarkers that were associated with the risk of clinically incident diabetes over and above the classic risk factors. This gives new insights into the pathogenesis of diabetes and may help with targeting prevention and treatment.
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影响因子：
158.5
作者：
Knowler, WC;Barrett-Connor, E;Nathan, DM
通讯作者：
Nathan, DM
预测糖尿病：临床，生物学和遗传方法：来自胰岛素抵抗综合征（DESIR）的流行病学研究的数据。
影响因子：
16.2
作者：
Balkau, Beverley;Lange, Celine;Fezeu, Leopold;Tichet, Jean;De Lauzon-Guillain, Blandine;Cernichow, Sebastien;Fumeron, Frederic;Froguel, Philippe;Vaxillaire, Martine;Cauchi, Stephane;Ducimetiere, Pierre;Eschwege, Eveline
通讯作者：
Eschwege, Eveline
影响因子：
16.2
作者：
Kolberg JA;Jørgensen T;Gerwien RW;Hamren S;McKenna MP;Moler E;Rowe MW;Urdea MS;Xu XM;Hansen T;Pedersen O;Borch-Johnsen K
通讯作者：
Borch-Johnsen K
影响因子：
16.2
作者：
Herder C;Brunner EJ;Rathmann W;Strassburger K;Tabák AG;Schloot NC;Witte DR
通讯作者：
Witte DR
影响因子：
105.7
作者：
Huxley, R;Barzi, F;Woodward, M
通讯作者：
Woodward, M