Lu Yan, Liu Yao-Zhong, Liu Peng-Yuan, Dvornyk Volodymyr, Deng Hong-Wen
College of Life Sciences and Bioengineering, Beijing Jiaotong University, Beijing 100044, PR China.
Eur J Med Genet. 2011 Nov-Dec;54(6):e560-4. doi: 10.1016/j.ejmg.2011.07.002. Epub 2011 Jul 30.
A common purpose of microarray experiments is to study the variation in gene expression across the categories of an experimental factor such as tissue types and drug treatments. However, it is not uncommon that the studied experimental factor is a quantitative variable rather than categorical variable. Loss of information would occur by comparing gene-expression levels between groups that are factitiously defined according to the quantitative threshold values of an experimental factor. Additionally, lack of control for some sensitive clinical factors may bring serious false positive or negative findings. In the present study, we described a bootstrap-based regression method for analyzing gene-expression data from the non-categorical microarray experiments. To illustrate the utility of this method, we applied it to our recent gene-expression study of circulating monocytes in subjects with a wide range of variations in bone mineral density (BMD). This method allows a comprehensive discovery of gene expressions associated with osteoporosis-related traits while controlling other common confounding factors such as height, weight and age. Several genes identified in our study are involved in osteoblast and osteoclast functions and bone remodeling and/or menopause-associated estrogen-dependent pathways, which provide important clues to understand the etiology of osteoporosis.
SAS code is available from the authors upon request.
微阵列实验的一个常见目的是研究基因表达在诸如组织类型和药物治疗等实验因素类别之间的差异。然而，所研究的实验因素是定量变量而非分类变量的情况并不少见。通过比较根据实验因素的定量阈值人为定义的组之间的基因表达水平，会出现信息丢失。此外，对一些敏感临床因素缺乏控制可能会带来严重的假阳性或假阴性结果。在本研究中，我们描述了一种基于自助法的回归方法，用于分析来自非分类微阵列实验的基因表达数据。为了说明该方法的实用性，我们将其应用于我们最近对骨密度（BMD）存在广泛差异的受试者循环单核细胞的基因表达研究中。该方法能够在控制身高、体重和年龄等其他常见混杂因素的同时，全面发现与骨质疏松相关性状相关的基因表达。我们研究中鉴定出的几个基因参与成骨细胞和破骨细胞功能以及骨重塑和/或绝经相关的雌激素依赖途径，这为理解骨质疏松的病因提供了重要线索。
如有需要，作者可提供SAS代码。
