Zuyderduyn Scott D
BMC Genomics. 2009 Feb 18;10:82. doi: 10.1186/1471-2164-10-82.
In the work of Chari et al. entitled "Effect of active smoking on the human bronchial epithelium transcriptome" the authors use SAGE to identify candidate gene expression changes in bronchial brushings from never, former, and current smokers. These gene expression changes are categorized into those that are reversible or irreversible upon smoking cessation. A subset of these identified genes is validated on an independent cohort using RT-PCR. The authors conclude that their results support the notion of gene expression changes in the lungs of smokers which persist even after an individual has quit.
This correspondence raises questions about the validity of the approach used by the authors to analyze their data. The majority of the reported results suffer deficiencies due to the methods used. The most fundamental of these are explained in detail: biases introduced during data processing, lack of correction for multiple testing, and an incorrect use of clustering for gene discovery. A randomly generated "null" dataset is used to show the consequences of these shortcomings.
Most of Chari et al.'s findings are consistent with what would be expected by chance alone. Although there is clear evidence of reversible changes in gene expression, the majority of those identified appear to be false positives. However, contrary to the authors' claims, no irreversible changes were identified. There is a broad consensus that genetic change due to smoking persists once an individual has quit smoking; unfortunately, this study lacks sufficient scientific rigour to support or refute this hypothesis or identify any specific candidate genes. The pitfalls of large-scale analysis, as exemplified here, may not be unique to Chari et al.
在查里等人题为《主动吸烟对人支气管上皮转录组的影响》的研究中，作者使用基因表达序列分析（SAGE）来识别从不吸烟者、曾经吸烟者和当前吸烟者支气管刷检样本中候选基因的表达变化。这些基因表达变化被分类为戒烟后可逆或不可逆的变化。其中一部分已识别基因在一个独立队列中通过逆转录聚合酶链反应（RT-PCR）进行了验证。作者得出结论，他们的结果支持吸烟者肺部基因表达变化的观点，即使个体戒烟后这些变化仍然存在。
这封通信对作者用于分析其数据的方法的有效性提出了质疑。所报告的大多数结果由于所使用的方法而存在缺陷。其中最基本的缺陷将详细解释：数据处理过程中引入的偏差、对多重检验缺乏校正以及在基因发现中对聚类的错误使用。使用一个随机生成的“空”数据集来展示这些缺点的后果。
查里等人的大多数发现与仅由偶然因素所预期的结果一致。虽然有明确证据表明基因表达存在可逆变化，但所识别的大多数变化似乎是假阳性。然而，与作者的主张相反，未识别到不可逆变化。人们普遍认为，吸烟导致的基因变化在个体戒烟后仍然存在；不幸的是，这项研究缺乏足够的科学严谨性来支持或反驳这一假设，也无法识别任何特定的候选基因。如此处所示的大规模分析的陷阱可能并非查里等人所独有。
