Exonhit, Inc., Gaithersburg, MD, USA.
Biomarkers. 2013 May;18(3):264-72. doi: 10.3109/1354750X.2013.773083. Epub 2013 Apr 5.
Microarray-based signatures for clinical application are often plagued by processing variability or batch effects that compromise the robustness of the test performance.
A splice variant array-based signature for early detection of Alzheimer's disease (AD) was developed using 315 AD or normal subjects processed in three disparate microarray batches.
A modified top scoring pair classifier using the signature, is robust to batch effects and outperforms other common classifiers, with sensitivity and specificity of 88.3% (95% CI:81.2%, 93.4%) and 88.9% (95% CI:65.3%, 98.6%), respectively, on an independent cohort.
This splice-variant array-based signature shows promise for clinical diagnostic use in AD.
基于微阵列的签名通常受到处理变异性或批次效应的困扰，这会影响测试性能的稳健性。
使用在三个不同的微阵列批次中处理的 315 个 AD 或正常受试者，开发了用于早期检测阿尔茨海默病 (AD) 的剪接变体阵列基签名。
使用该签名的经修改的最高得分对分类器对批次效应具有鲁棒性，并且优于其他常见分类器，在独立队列中，敏感性和特异性分别为 88.3%（95%CI：81.2%，93.4%）和 88.9%（95%CI：65.3%，98.6%）。
这种基于剪接变体的阵列基签名显示出在 AD 临床诊断中的应用前景。
