Diagnosis of Schizophrenia Based on the Data of Various Modalities: Biomarkers and Machine Learning Techniques (Review).

Autor:	Sharaev MG; Senior Researcher; Skolkovo Institute of Science and Technology (Skoltech), Territory of Skolkovo Innovation Center, Bldg 1, 30 Bolshoy Boulevard, Moscow, 121205, Russia; Department Senior Researcher; N.A. Alekseyev Psychiatric Clinical Hospital No.1, 2 Zagorodnoye Shosse, Moscow, 117152, Russia., Malashenkova IK; Head of the Laboratory of Molecular Immunology and Virology; National Research Center 'Kurchatov Institute', 1 Akademika Kurchatova Square, Moscow, 123182, Russia; Senior Researcher, Laboratory of Clinical Immunology; Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical Biological Agency of Russia, 1A Malaya Pirogovskaya St., Moscow, 119435, Russia., Maslennikova AV; Researcher, Laboratory of Human Higher Nervous Activity; Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, 5A Butlerova St., Moscow, 117485, Russia., Zakharova NV; Head of the Laboratory for Fundamental Research Methods, Research Clinical Center of Neuropsychiatry; N.A. Alekseyev Psychiatric Clinical Hospital No.1, 2 Zagorodnoye Shosse, Moscow, 117152, Russia., Bernstein AV; Professor, Professor of the Center of Applied Artificial Intelligence; Skolkovo Institute of Science and Technology (Skoltech), Territory of Skolkovo Innovation Center, Bldg 1, 30 Bolshoy Boulevard, Moscow, 121205, Russia., Burnaev EV; Associate Professor, Professor of the Center of Applied Artificial Intelligence; Skolkovo Institute of Science and Technology (Skoltech), Territory of Skolkovo Innovation Center, Bldg 1, 30 Bolshoy Boulevard, Moscow, 121205, Russia., Mamedova GS; Junior Researcher, Laboratory for Fundamental Research Methods, Research Clinical Center of Neuropsychiatry; N.A. Alekseyev Psychiatric Clinical Hospital No.1, 2 Zagorodnoye Shosse, Moscow, 117152, Russia., Krynskiy SA; Researcher, Laboratory of Molecular Immunology and Virology; National Research Center 'Kurchatov Institute', 1 Akademika Kurchatova Square, Moscow, 123182, Russia., Ogurtsov DP; Researcher, Laboratory of Molecular Immunology and Virology; National Research Center 'Kurchatov Institute', 1 Akademika Kurchatova Square, Moscow, 123182, Russia., Kondrateva EA; PhD Student; Skolkovo Institute of Science and Technology (Skoltech), Territory of Skolkovo Innovation Center, Bldg 1, 30 Bolshoy Boulevard, Moscow, 121205, Russia., Druzhinina PV; PhD Student; Skolkovo Institute of Science and Technology (Skoltech), Territory of Skolkovo Innovation Center, Bldg 1, 30 Bolshoy Boulevard, Moscow, 121205, Russia., Zubrikhina MO; PhD Student; Skolkovo Institute of Science and Technology (Skoltech), Territory of Skolkovo Innovation Center, Bldg 1, 30 Bolshoy Boulevard, Moscow, 121205, Russia., Arkhipov AY; Researcher, Laboratory of Human Higher Nervous Activity; Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, 5A Butlerova St., Moscow, 117485, Russia., Strelets VB; Chief Researcher, Laboratory of Human Higher Nervous Activity; Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, 5A Butlerova St., Moscow, 117485, Russia., Ushakov VL; Associate Professor, Chief Researcher, Institute for Advanced Brain Research; Lomonosov Moscow State University, 27/1 Lomonosov Avenue, Moscow, 119192, Russia; Head of the Department; N.A. Alekseyev Psychiatric Clinical Hospital No.1, 2 Zagorodnoye Shosse, Moscow, 117152, Russia; Senior Researcher; National Research Nuclear University MEPhI, 31 Kashirskoye Shosse, Moscow, 115409, Russia.
Jazyk:	angličtina
Zdroj:	Sovremennye tekhnologii v meditsine [Sovrem Tekhnologii Med] 2022; Vol. 14 (5), pp. 53-75. Date of Electronic Publication: 2022 Sep 29.
DOI:	10.17691/stm2022.14.5.06
Abstrakt:	Schizophrenia is a socially significant mental disorder resulting frequently in severe forms of disability. Diagnosis, choice of treatment tactics, and rehabilitation in clinical psychiatry are mainly based on the assessment of behavioral patterns, socio-demographic data, and other investigations such as clinical observations and neuropsychological testing including examination of patients by the psychiatrist, self-reports, and questionnaires. In many respects, these data are subjective and therefore a large number of works have appeared in recent years devoted to the search for objective characteristics (indices, biomarkers) of the processes going on in the human body and reflected in the behavioral and psychoneurological patterns of patients. Such biomarkers are based on the results of instrumental and laboratory studies (neuroimaging, electro-physiological, biochemical, immunological, genetic, and others) and are successfully being used in neurosciences for understanding the mechanisms of the emergence and development of nervous system pathologies. Presently, with the advent of new effective neuroimaging, laboratory, and other methods of investigation and also with the development of modern methods of data analysis, machine learning, and artificial intelligence, a great number of scientific and clinical studies is being conducted devoted to the search for the markers which have diagnostic and prognostic value and may be used in clinical practice to objectivize the processes of establishing and clarifying the diagnosis, choosing and optimizing treatment and rehabilitation tactics, predicting the course and outcome of the disease. This review presents the analysis of the works which describe the correlates between the diagnosis of schizophrenia, established by health professionals, various manifestations of the psychiatric disorder (its subtype, variant of the course, severity degree, observed symptoms, etc.), and objectively measured characteristics/quantitative indicators (anatomical, functional, immunological, genetic, and others) obtained during instrumental and laboratory examinations of patients. A considerable part of these works has been devoted to correlates/biomarkers of schizophrenia based on the data of structural and functional (at rest and under cognitive load) MRI, EEG, tractography, and immunological data. The found correlates/biomarkers reflect anatomic disorders in the specific brain regions, impairment of functional activity of brain regions and their interconnections, specific microstructure of the brain white matter and the levels of connectivity between the tracts of various structures, alterations of electrical activity in various parts of the brain in different EEG spectral ranges, as well as changes in the innate and adaptive links of immunity. Current methods of data analysis and machine learning to search for schizophrenia biomarkers using the data of diverse modalities and their application during building and interpretation of predictive diagnostic models of schizophrenia have been considered in the present review. Competing Interests: The authors have no conflicts of interest to declare.
Databáze:	MEDLINE
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