Giresi Paul G, Stevenson Eric J, Theilhaber Joachim, Koncarevic Alan, Parkington Jascha, Fielding Roger A, Kandarian Susan C
Department of Health Sciences, Boston University, Boston, Massachusetts, USA.
Physiol Genomics. 2005 Apr 14;21(2):253-63. doi: 10.1152/physiolgenomics.00249.2004. Epub 2005 Feb 1.
Investigating the molecular mechanisms underlying sarcopenia in humans with the use of microarrays has been complicated by low sample size and the variability inherent in human gene expression profiles. We have conducted a study using Affymetrix GeneChips to identify a molecular signature of aged skeletal muscle. The molecular signature was defined as the set of expressed genes that best distinguished the vastus lateralis muscle of young (n = 10) and older (n = 12) male subjects, when a k-nearest neighbor supervised classification method was used in conjunction with a signal-to-noise ratio gene selection method and a holdout cross-validation procedure. The age-specific expression signature was comprised of 45 genes; 27 were upregulated and 18 were downregulated. This signature also correctly classified 75% of the muscle samples from young and older subjects published by an independent laboratory, based on their expression profiles. The signature revealed increased expression of several genes involved in mediating cellular responses to inflammation and apoptosis, including complement component C1QA, Galectin-1, C/EBP-beta, and FOXO3A, among others. The increased expressions of genes that regulate pre-mRNA splicing, localization, and modification of RNA comprise markers of the aging signature. Downregulated genes in the signature were the glutamine transporter SLC38A1, a TRAF-6 inhibitory zinc finger protein, and membrane-bound transcription factor protease S2P, among others. The sarcopenia signature developed here will be useful as a molecular model to judge the effectiveness of exercise and other therapeutic treatments aimed at ameliorating the effects of muscle loss associated with aging.
利用微阵列研究人类肌肉减少症背后的分子机制,因样本量小和人类基因表达谱固有的变异性而变得复杂。我们进行了一项研究,使用Affymetrix基因芯片来识别衰老骨骼肌的分子特征。当使用k近邻监督分类方法结合信噪比基因选择方法和留出交叉验证程序时,分子特征被定义为最能区分年轻男性(n = 10)和老年男性(n = 12)股外侧肌的一组表达基因。年龄特异性表达特征由45个基因组成;27个上调,18个下调。基于其表达谱,该特征还正确分类了独立实验室发表的75%的年轻和老年受试者的肌肉样本。该特征揭示了几种参与介导细胞对炎症和凋亡反应的基因表达增加,包括补体成分C1QA、半乳糖凝集素-1、C/EBP-β和FOXO3A等。调节前体mRNA剪接、RNA定位和修饰的基因表达增加构成了衰老特征的标志物。该特征中下调的基因包括谷氨酰胺转运体SLC38A1、一种TRAF-6抑制性锌指蛋白和膜结合转录因子蛋白酶S2P等。这里开发的肌肉减少症特征将作为一种分子模型,用于判断旨在改善与衰老相关的肌肉流失影响的运动和其他治疗方法的有效性。