循环长链非编码RNA GAS5水平与2型糖尿病患病率相关

BBA clinical Pub Date : 2015-12-01 DOI:10.1016/j.bbacli.2015.09.001

Gay Carter , Branko Miladinovic , Achintya A. Patel , Lauren Deland , Stephen Mastorides , Niketa A. Patel

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引用次数: 135

摘要

背景:糖尿病(DM)是一种代谢疾病，以空腹血糖水平降低为特征。2型糖尿病是成人发病的糖尿病。长链非编码rna (lncRNAs)调节基因表达，多项研究已将lncRNAs与人类疾病联系起来。方法96例退伍军人血清标本保存于研究生物标本库。我们采用了两阶段策略来确定其水平与T2DM相关的lncRNA。最初，我们使用lncRNA阵列从糖尿病和非糖尿病个体中筛选了5个血清样本。接下来，使用定量PCR分析96份血清样本中GAS5 lncRNA的水平。受试者工作特征(ROC)分析以确定诊断糖尿病的最佳临界值。结果我们的研究结果表明，在美国退伍军人队列中，血清中GAS5水平降低与糖尿病有关。ROC分析显示最佳截断GAS5值小于或等于10。qPCR结果显示，具有绝对GAS5 <的个体;10 ng/μl的人患糖尿病的几率几乎高出12倍(确切优势比[OR] = 11.79 (95% CI: 3.97, 37.26)， p <0.001)。分析表明，ROC曲线下面积(AUC)为0.81，敏感性为85.1%，特异性为67.3%。阳性预测值为71.4%。结论lncrna GAS5水平与T2DM患病率相关。评估血清中GAS5和其他参数在识别糖尿病风险个体方面提供了更高的准确性。

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Circulating long noncoding RNA GAS5 levels are correlated to prevalence of type 2 diabetes mellitus

Background

Diabetes mellitus (DM), a metabolic disease, is characterized by impaired fasting glucose levels. Type 2 DM is adult onset diabetes. Long non-coding RNAs (lncRNAs) regulate gene expression and multiple studies have linked lncRNAs to human diseases.

Methods

Serum samples obtained from 96 participating veterans at JAH VA were deposited in the Research Biospecimen Repository. We used a two-stage strategy to identify an lncRNA whose levels correlated with T2DM. Initially we screened five serum samples from diabetic and non-diabetic individuals using lncRNA arrays. Next, GAS5 lncRNA levels were analyzed in 96 serum samples using quantitative PCR. Receiver operating characteristic (ROC) analysis was performed to determine the optimal cutoff GAS5 for diagnosis of DM.

Results

Our results demonstrate that decreased GAS5 levels in serum were associated with diabetes in a cohort of US military veterans. The ROC analysis revealed an optimal cutoff GAS5 value of less than or equal to 10. qPCR results indicated that individuals with absolute GAS5 < 10 ng/μl have almost twelve times higher odds of having diabetes (Exact Odds Ratio [OR] = 11.79 (95% CI: 3.97, 37.26), p < 0.001). Analysis indicated area under curve (AUC) of ROC of 0.81 with 85.1% sensitivity and 67.3% specificity in distinguishing non-diabetic from diabetic subjects. The positive predictive value is 71.4%.