Panum Institutet and Center for Healthy Ageing, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
J Appl Physiol (1985). 2010 Jun;108(6):1487-96. doi: 10.1152/japplphysiol.01295.2009. Epub 2010 Feb 4.
A low maximal oxygen consumption (VO2max) is a strong risk factor for premature mortality. Supervised endurance exercise training increases VO2max with a very wide range of effectiveness in humans. Discovering the DNA variants that contribute to this heterogeneity typically requires substantial sample sizes. In the present study, we first use RNA expression profiling to produce a molecular classifier that predicts VO2max training response. We then hypothesized that the classifier genes would harbor DNA variants that contributed to the heterogeneous VO2max response. Two independent preintervention RNA expression data sets were generated (n=41 gene chips) from subjects that underwent supervised endurance training: one identified and the second blindly validated an RNA expression signature that predicted change in VO2max ("predictor" genes). The HERITAGE Family Study (n=473) was used for genotyping. We discovered a 29-RNA signature that predicted VO2max training response on a continuous scale; these genes contained approximately 6 new single-nucleotide polymorphisms associated with gains in VO2max in the HERITAGE Family Study. Three of four novel candidate genes from the HERITAGE Family Study were confirmed as RNA predictor genes (i.e., "reciprocal" RNA validation of a quantitative trait locus genotype), enhancing the performance of the 29-RNA-based predictor. Notably, RNA abundance for the predictor genes was unchanged by exercise training, supporting the idea that expression was preset by genetic variation. Regression analysis yielded a model where 11 single-nucleotide polymorphisms explained 23% of the variance in gains in VO2max, corresponding to approximately 50% of the estimated genetic variance for VO2max. In conclusion, combining RNA profiling with single-gene DNA marker association analysis yields a strongly validated molecular predictor with meaningful explanatory power. VO2max responses to endurance training can be predicted by measuring a approximately 30-gene RNA expression signature in muscle prior to training. The general approach taken could accelerate the discovery of genetic biomarkers, sufficiently discrete for diagnostic purposes, for a range of physiological and pharmacological phenotypes in humans.
低最大摄氧量（VO2max）是导致过早死亡的一个强有力的危险因素。有监督的耐力运动训练可以使人类的 VO2max 得到极大的提高，其效果范围非常广泛。发现导致这种异质性的 DNA 变体通常需要大量的样本量。在本研究中，我们首先使用 RNA 表达谱分析来产生一个分子分类器，该分类器可以预测 VO2max 训练反应。然后，我们假设分类器基因中会存在导致 VO2max 反应异质性的 DNA 变体。从接受有监督的耐力训练的受试者中生成了两个独立的预干预 RNA 表达数据集（n=41 个基因芯片）：一个确定了，第二个则盲法验证了一个可以预测 VO2max 变化的 RNA 表达特征（“预测”基因）。HERITAGE 家族研究（n=473）用于基因分型。我们发现了一个 29-RNA 特征，可以对 VO2max 训练反应进行连续尺度的预测；这些基因包含大约 6 个与 HERITAGE 家族研究中 VO2max 增加相关的新单核苷酸多态性。HERITAGE 家族研究中 4 个新候选基因中的 3 个被证实为 RNA 预测基因（即，定量特征基因座基因型的“相互”RNA 验证），从而提高了基于 29-RNA 的预测器的性能。值得注意的是，预测基因的 RNA 丰度不受运动训练的影响，这支持了表达是由遗传变异预先设定的观点。回归分析得出的模型表明，11 个单核苷酸多态性解释了 VO2max 增加的 23%的方差，这相当于 VO2max 遗传方差的约 50%。总之，将 RNA 谱分析与单基因 DNA 标记关联分析相结合，可以产生具有很强验证性和有意义解释能力的分子预测器。在训练前测量肌肉中大约 30 个基因的 RNA 表达特征，可以预测对耐力训练的 VO2max 反应。这种总体方法可以加速发现用于人类一系列生理和药理学表型的遗传生物标志物，这些标志物足够离散，可用于诊断目的。
