The metabolic wiring of patient cells is altered drastically in many diseases, including cancer. Understanding the nature of such changes may pave the way for new therapeutic opportunities as well as the development of personalized treatment strategies for patients. In this paper, we propose an algorithm called Metabolitics, which allows systems-level analysis of changes in the biochemical network of cells in disease states. It enables the study of a disease at both reaction- and pathway-level granularities for a detailed and summarized view of disease etiology. Metabolitics employs flux variability analysis with a dynamically built objective function based on biofluid metabolomics measurements in a personalized manner. Moreover, Metabolitics builds supervised classification models to discriminate between patients and healthy subjects based on the computed metabolic network changes. The use of Metabolitics is demonstrated for three distinct diseases, namely, breast cancer, Crohn's disease, and colorectal cancer. Our results show that the constructed supervised learning models successfully differentiate patients from healthy individuals by an average f1-score of 88 percent. Besides, in addition to the confirmation of previously reported breast cancer-associated pathways, we discovered that Biotin Metabolism along with Arginine and Proline Metabolism is subject to a significant increase in flux capacity, which have not been reported before.

中文翻译：

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疾病的个性化代谢分析

在包括癌症在内的许多疾病中，患者细胞的代谢线路发生了巨大变化。了解此类变化的性质可能为新的治疗机会以及为患者制定个性化治疗策略铺平道路。在本文中，我们提出了一种称为代谢学的算法，该算法允许对疾病状态下细胞生化网络的变化进行系统级分析。它能够在反应和通路级别的粒度上研究疾病，以获得疾病病因的详细和总结视图。代谢学以个性化的方式使用基于生物流体代谢组学测量的动态构建目标函数的通量变异性分析。而且，代谢学建立监督分类模型，根据计算出的代谢网络变化来区分患者和健康受试者。代谢学的用途已被证明可用于三种不同的疾病，即乳腺癌、克罗恩病和结肠直肠癌。我们的结果表明，构建的监督学习模型通过 88% 的平均 f1 分数成功地将患者与健康个体区分开来。此外，除了证实先前报道的乳腺癌相关途径外，我们发现生物素代谢以及精氨酸和脯氨酸代谢受到通量容量的显着增加，这是以前未报道过的。克罗恩病和结直肠癌。我们的结果表明，构建的监督学习模型通过 88% 的平均 f1 分数成功地将患者与健康个体区分开来。此外，除了证实先前报道的乳腺癌相关途径外，我们发现生物素代谢以及精氨酸和脯氨酸代谢受到通量容量的显着增加，这是以前未报道过的。克罗恩病和结直肠癌。我们的结果表明，构建的监督学习模型通过 88% 的平均 f1 分数成功地将患者与健康个体区分开来。此外，除了证实先前报道的乳腺癌相关途径外，我们发现生物素代谢以及精氨酸和脯氨酸代谢受到通量容量的显着增加，这是以前未报道过的。