Lokhov Petr G, Trifonova Oxana P, Maslov Dmitry L, Lichtenberg Steven, Balashova Elena E
Analytical Branch, Institute of Biomedical Chemistry, 10 Building 8, Pogodinskaya Street, 119121 Moscow, Russia.
Metabometrics, Inc., 651 N Broad Street, Suite 205 #1370, Middletown, DE 19709, USA.
Metabolites. 2021 Oct 20;11(11):715. doi: 10.3390/metabo11110715.
Today, the introduction of metabolomics, like other omics sciences, into clinical practice as a personal omics test that realizes the perfect analytical capabilities of this science has become an important subject. The assembled data show that the metabolome of biosamples is a collection of highly informative and accurate signatures of virtually all diseases that are widespread in the population. However, we have not seen the emergence of personalized metabolomics in clinical practice. This article analyzes the causes of this problem. The complexity of personal metabolic data analysis and its incompatibility with widely accepted data treatment in metabolomics are shown. As a result, the impossibility of translating metabolic signatures accumulated in databases into a personal test is revealed. Problem-solving strategies that may radically change the situation and realize the analytical capabilities of metabolomics in medical laboratory practice are discussed.
如今，将代谢组学与其他组学科学一样，作为一种能够实现该学科完美分析能力的个人组学检测引入临床实践已成为一个重要课题。汇总的数据表明，生物样本的代谢组是几乎所有在人群中广泛传播的疾病的高度信息丰富且准确的特征集合。然而，我们尚未看到个性化代谢组学在临床实践中出现。本文分析了这一问题的成因。展示了个人代谢数据分析的复杂性及其与代谢组学中广泛接受的数据处理方法的不兼容性。结果，揭示了将数据库中积累的代谢特征转化为个人检测的不可能性。讨论了可能从根本上改变这种状况并在医学实验室实践中实现代谢组学分析能力的解决策略。
