Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, United States of America.
PLoS Comput Biol. 2010 Feb 26;6(2):e1000692. doi: 10.1371/journal.pcbi.1000692.
Human disease is heterogeneous, with similar disease phenotypes resulting from distinct combinations of genetic and environmental factors. Small-molecule profiling can address disease heterogeneity by evaluating the underlying biologic state of individuals through non-invasive interrogation of plasma metabolite levels. We analyzed metabolite profiles from an oral glucose tolerance test (OGTT) in 50 individuals, 25 with normal (NGT) and 25 with impaired glucose tolerance (IGT). Our focus was to elucidate underlying biologic processes. Although we initially found little overlap between changed metabolites and preconceived definitions of metabolic pathways, the use of unbiased network approaches identified significant concerted changes. Specifically, we derived a metabolic network with edges drawn between reactant and product nodes in individual reactions and between all substrates of individual enzymes and transporters. We searched for "active modules"--regions of the metabolic network enriched for changes in metabolite levels. Active modules identified relationships among changed metabolites and highlighted the importance of specific solute carriers in metabolite profiles. Furthermore, hierarchical clustering and principal component analysis demonstrated that changed metabolites in OGTT naturally grouped according to the activities of the System A and L amino acid transporters, the osmolyte carrier SLC6A12, and the mitochondrial aspartate-glutamate transporter SLC25A13. Comparison between NGT and IGT groups supported blunted glucose- and/or insulin-stimulated activities in the IGT group. Using unbiased pathway models, we offer evidence supporting the important role of solute carriers in the physiologic response to glucose challenge and conclude that carrier activities are reflected in individual metabolite profiles of perturbation experiments. Given the involvement of transporters in human disease, metabolite profiling may contribute to improved disease classification via the interrogation of specific transporter activities.
人类疾病具有异质性，相似的疾病表型可能由不同的遗传和环境因素组合导致。小分子分析可以通过非侵入性地检测个体血浆代谢物水平，来评估其潜在的生物学状态，从而解决疾病的异质性问题。我们分析了 50 名个体的口服葡萄糖耐量试验（OGTT）中的代谢物谱，其中 25 名个体的葡萄糖耐量正常（NGT），25 名个体的葡萄糖耐量受损（IGT）。我们的重点是阐明潜在的生物学过程。尽管我们最初发现，在发生变化的代谢物和预先设定的代谢途径定义之间几乎没有重叠，但使用无偏网络方法可以识别出显著的协同变化。具体来说，我们构建了一个代谢网络，其中每条边连接的是个体反应中的反应物和产物节点，以及每个酶和转运体的所有底物。我们搜索了“活性模块”——代谢物水平变化丰富的代谢网络区域。活性模块确定了变化代谢物之间的关系，并突出了特定溶质载体在代谢物谱中的重要性。此外，层次聚类和主成分分析表明，OGTT 中的变化代谢物根据氨基酸转运体系统 A 和 L、渗透物载体 SLC6A12 和线粒体天冬氨酸-谷氨酸转运体 SLC25A13 的活性自然分组。NGT 和 IGT 组之间的比较支持 IGT 组中葡萄糖和/或胰岛素刺激活性减弱。使用无偏路径模型，我们提供了证据支持溶质载体在对葡萄糖挑战的生理反应中的重要作用，并得出结论，载体活性反映在扰动实验的个体代谢物谱中。鉴于转运体在人类疾病中的参与，代谢物分析可能通过检测特定转运体的活性来促进疾病分类的改善。
