aterosklerozАтеросклерозAteroscleroz2078-256X2949-3633НИИТПМ-филиал ИЦиГ СО РАН10.52727/2078-256X-2024-20-2-154-161ateroskleroz-1054Research ArticleДИСКУССИИDISCUSSIONSСовременные подходы к оценке индивидуального риска развития ИБС: состояние, проблемы, перспективыModern approaches to the assessment of individual risk of CHD development: status, problems, prospectshttps://orcid.org/0000-0002-7165-4496МаксимовВ. Н.MaksimovV. N.

Владимир Николаевич Максимов, д-р мед. наук, проф., зав. лабораторией

лаборатория молекулярно-генетических исследований терапевтических заболеваний

630089; ул. Бориса Богаткова, 175/1; 630091; Красный пр., 52; 630090; пр. Академика Лаврентьева, 10; Новосибирск 

Vladimir N. Maximov, doctor of medical sciences, professor, head. laboratory

laboratory of molecular genetic research of therapeutic diseases

630089; 175/1, Boris Bogatkov str.; 630091; 52, Krasny av.; 630090; 10, Academician Lavrentiev av.; Novosibirsk

medik11@mail.ruhttps://orcid.org/0000-0002-2472-181XМиннихС. В.MinnikhS. V.

Софья Владимировна Минних, младший научный сотрудник

лаборатория молекулярно-генетических исследований терапевтических заболеваний

630089; ул. Бориса Богаткова, 175/1; 630091; Красный пр., 52; Новосибирск

Sofya V. Minnikh, junior researcher

laboratory of molecular genetic studies of therapeutic diseases

630089; 175/1, Boris Bogatkov str.; 630091; 52, Krasny av.; Novosibirsk

maxisofiav@yandex.ruhttps://orcid.org/0000-0002-9460-6294ИвановаА. А.IvanovaA. A.

Анастасия Андреевна Иванова, д-р мед. наук, старший научный сотрудник

лаборатория молекулярно-генетических исследований терапевтических заболеваний

630089; ул. Бориса Богаткова, 175/1; Новосибирск

Anastasiya A. Ivanova, Doctor of Medical Sciences, Senior researcher

laboratory of molecular genetic studies of therapeutic diseases

630089; 175/1, Boris Bogatkov str.; Novosibirsk

ivanova_a_a@mail.ruНаучно-исследовательский институт терапии и профилактической медицины – филиал Федерального государственного бюджетного научного учреждения «Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук»; Федеральное государственное бюджетное образовательное учреждение высшего образования «Новосибирский государственный медицинский университет» Министерства здравоохранения Российской Федерации; Федеральное государственное бюджетное научное учреждение «Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук»Research Institute of Internal and Preventive Medicine – Branch of the Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences; Novosibirsk State Medical University of Ministry of Health of Russian Federation; Federal Research Center Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of SciencesНаучно-исследовательский институт терапии и профилактической медицины – филиал Федерального государственного бюджетного научного учреждения «Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук»; Федеральное государственное бюджетное образовательное учреждение высшего образования «Новосибирский государственный медицинский университет» Министерства здравоохранения Российской ФедерацииResearch Institute of Internal and Preventive Medicine – Branch of the Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences; Novosibirsk State Medical University of Ministry of Health of Russian FederationНаучно-исследовательский институт терапии и профилактической медицины – филиал Федерального государственного бюджетного научного учреждения «Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук»Research Institute of Internal and Preventive Medicine – Branch of the Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences202404072024202154161Copyright © Максимов В.Н., Минних С.В., Иванова А.А., 20242024Максимов В.Н., Минних С.В., Иванова А.А.Maksimov V.N., Minnikh S.V., Ivanova A.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://ateroskleroz.elpub.ru/jour/article/view/1054

   Сердечно-сосудистые заболевания являются основной причиной ненасильственных смертей в мире. Критерии формирования групп повышенного риска необходимы для первичной профилактики развития заболеваний. Это послужило толчком для проведения исследований по разработке рискометров. В обзоре представлено описание современных проблем оценки индивидуального риска ИБС. Основные подходы к созданию рискометров не претерпели существенных изменений на протяжении нескольких десятилетий. Увеличение размера групп исследования и количества молекулярно-генетических маркеров, несомненно, дает определенные результаты. Однако для того чтобы перейти от популяционного уровня к индивидуальному, необходимо учитывать гораздо больше факторов при оценке. То есть необходимо научиться анализировать сложнейший набор данных одного человека (геном, транскриптом, метилом, протеом, а может быть, и микробиом) не только с глубоким пониманием механизмов его функционирования (от зачатия до смерти), но и возможных нарушений, исходя из имеющихся признаков. А для этого необходимо опираться не только и не столько на статистические данные, сколько на максимально похожие наборы индивидуальных данных (в первую очередь, родственников). Представляется, что оценивать сходство должна система искусственного интеллекта, обученная на колоссальном массиве индивидуальных данных.

   Cardiovascular diseases are the leading cause of non-violent deaths in the world. Criteria for the formation of high-risk groups are necessary for primary prevention of disease development. This was the reason for research on the development of riskmeters. A brief description of the history of the creation of CHD riskmeters. The review provides a description of the current challenges in assessing individual risk for CHD. The main approaches to the creation of riskmeters have not changed significantly for several decades. The increase in the size of study groups and the number of molecular genetic markers undoubtedly give certain results. However, in order to move from the population level to the individual level, it is necessary to take into account many more factors in the assessment. That is, it is necessary to learn how to analyze the most complex set of data of one person (genome, transcriptome, proteome, and maybe even microbiome) not only with a deep understanding of the mechanisms of its functioning (from conception to death), but also possible disorders, based on the available features. And for this purpose it is necessary to rely not only and not so much on statistical data, but on maximally similar sets of individual data (first of all, relatives). It seems that similarity should be evaluated by an artificial intelligence system trained on a colossal array of individual data.

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The authors declare that there are no conflicts of interest present.