We read with great interest the article by Kurt and colleagues. The authors, using microarray in clinical samples, found altered expression of lncRNAs in peripheral blood mononuclear cells (PBMCs) of patients with Alzheimer’s disease (AD). The findings from this study may open a door to the understanding of AD pathogenesis targeted by lncRNAs. In our opinion, it is necessary to further clarify the data analysis strategy of this study. According to the authors’ description, they seem to use unadjusted p values and fold change of expression values when defining significantly differentially expressed lncRNAs in PBMCs of subjects with probable AD and healthy control groups. However, due to the characteristics of lncRNA and high false positives caused by multiple comparisons, t-test is not suitable for high-level microarray analysis. It seems that a specialized high-level microarray analysis method is essential to reach a reliable result. Accurate analysis results will provide a convincing basis for subsequent experiments.

我们怀着极大的兴趣阅读了 Kurt 及其同事的文章。作者在临床样本中使用微阵列，发现阿尔茨海默病 (AD) 患者外周血单个核细胞 (PBMC) 中 lncRNA 的表达发生了改变。这项研究的结果可能为了解 lncRNA 靶向的 AD 发病机制打开了大门。我们认为，有必要进一步明确本研究的数据分析策略。根据作者的描述，在定义可能患有 AD 的受试者和健康对照组的 PBMC 中显着差异表达的 lncRNA 时，他们似乎使用了未经调整的p值和表达值的倍数变化。然而，由于 lncRNA 的特性和多重比较造成的高假阳性，t-test 不适用于高级微阵列分析。似乎需要一种专门的高级微阵列分析方法才能获得可靠的结果。准确的分析结果将为后续实验提供令人信服的依据。