Metabolome of cerebrovascular disease. Research methods and prospects for clinical applicationThe review is devoted to the prospects of applying metabolomic approaches to the diagnosis and prediction of the course of cerebrovascular disease. The main methods of research are defined, it is shown that metabolome studies can be useful for the development of new methods of clinical forecasting in patients with cerebrovascular disease.Evaluation of the metabolome allows to determine the phenotypes of the organism. Metabolites can be identified and classified using a number of different technologies, including nuclear magnetic resonance spectroscopy and mass spectrometry. At the same time, they must be combined with various forms of liquid chromatography, gas chromatography or capillary electrophoresis to facilitate the separation of compounds. Each method is typically capable of simultaneously identifying or characterizing 50-5,000 different metabolites or «features» of metabolites, depending on the instrument or protocol used. Today, it is impossible to analyze the entire spectrum of metabolites with one analytical method, so their combinations are used.There is evidence that multiple serum metabolites are associated with the severity of small vessel disease, including Fazekas class, cognitive decline, and dementia.According to the authors, further research is needed to determine whether these associations are robust causal relationships and whether they can be used to predict the rate of progression and severity of onset of lacunar stroke and dementia, both in clinical practice and in basic science.The authors conclude that the main methods of studying the metabolome are nuclear magnetic resonance spectroscopy and mass spectrometry, which will allow the development of new methods of predicting cerebrovascular diseases, and numerous serum metabolites are associated with the severity of small vessel disease.