vavilovВавиловский журнал генетики и селекцииVavilov Journal of Genetics and Breeding2500-3259Institute of Cytology and Genetics of Siberian Branch of the RAS10.18699/vjgb-25-105vavilov-4882Research ArticleСИСТЕМНАЯ КОМПЬЮТЕРНАЯ БИОЛОГИЯSYSTEMS COMPUTATIONAL BIOLOGYКомпьютерная реконструкция генной сети цитокиновой регуляции генов и белков, ассоциированных с РАСIn silico reconstruction of the gene network for cytokine regulation of ASD-associatedЛевановаН. М.LevanovaN. M.

Новосибирск

Novosibirsk

levanova@bionet.nsc.ruhttps://orcid.org/0000-0002-8352-5368ВергуновЕ. Г.VergunovE. G.

Новосибирск

Novosibirsk

https://orcid.org/0000-0002-3514-2901СавостьяновА. Н.SavostyanovA. N.

Новосибирск

Novosibirsk

https://orcid.org/0009-0001-9245-8988ЯцыкИ. В.YatsykI. V.

Новосибирск

Novosibirsk

https://orcid.org/0000-0002-1859-4631ИванисенкоВ. А.IvanisenkoV. A.

Новосибирск

Novosibirsk

Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наукРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of SciencesRussian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук; Научно-исследовательский институт нейронаук и медицины; Новосибирский национальный исследовательский государственный университетРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Scientific Research Institute of Neurosciences and Medicine; Novosibirsk State UniversitRussian Federation20251212202529710001008Copyright © Леванова Н.М., Вергунов Е.Г., Савостьянов А.Н., Яцык И.В., Иванисенко В.А., 20252025Леванова Н.М., Вергунов Е.Г., Савостьянов А.Н., Яцык И.В., Иванисенко В.А.Levanova N.M., Vergunov E.G., Savostyanov A.N., Yatsyk I.V., Ivanisenko V.A.This work is licensed under a Creative Commons Attribution 4.0 License.https://vavilov.elpub.ru/jour/article/view/4882

   Многочисленные исследования подтверждают связь нарушений цитокиновой регуляции с развитием расстройств аутистического спектра (РАС) на уровне генов, белков и их межмолекулярных взаимодействий. В работе эти данные были систематизированы с применением биоинформатического анализа и методов машинного обучения.

   Главным инструментом в исследовании являлась когнитивная система AND-System, разработанная в Институте цитологии и генетики СО РАН и задействующая методы искусственного интеллекта для автоматического извлечения информации из биомедицинских баз данных и текстов научных публикаций.

   С использованием AND-System была реконструирована ассоциативная генная сеть цитокиновой регуляции генов и белков, ассоциированных с РАС. В результате анализа удалось идентифицировать 110 цитокинов, которые, согласно воссозданной сети, регулируют активность, деградацию и транспорт 58 белков, вовлеченных в развитие РАС, а также экспрессию 91 гена, ассоциированного с этими расстройствами. Анализ перепредставленности биологических процессов Gene Ontology выявил статистически значимые ассоциации этих генов с процессами, связанными с развитием и работой центральной нервной системы. Анализ топологических характеристик сети и оценка функциональной значимости элементов сети через их ассоциацию с биологическими процессами Gene Ontology, связанными с РАС, позволили выделить 21 цитокин, оказывающий наибольшее влияние на элементы сети. Среди них наибольший приоритет имели восемь цитокинов (IL-4, TGF-β1, BMP4, VEGFA, BMP2, IL-10, IFN-γ, TNF-α), которые занимали высокое положение по результатам всех использованных методик приоритизации. Кроме того, из 21 приоритетного цитокина выделяются восемь цитокинов (TNF-α, IL- 6, IL-4, VEGFA, IL-2, IL-1β, IFN-γ, IL-17), которые являются мишенями препаратов, применяемых в качестве иммуносупрессантов и противоопухолевых средств. Установленная роль этих цитокинов в патогенезе РАС создает предпосылки для потенциального перепрофилирования препаратов, направленных на их ингибирование, для терапии расстройств аутистического спектра.

   Accumulated evidence links dysregulated cytokine signaling to the pathogenesis of autism spectrum disorder (ASD), implicating genes, proteins, and their intermolecular networks. This paper systematizes these findings using bioinformatics analysis and machine learning methods.

   The primary tool employed in the study was the AND-System cognitive platform, developed at the Institute of Cytology and Genetics, which utilizes artificial intelligence techniques for automated knowledge extraction from biomedical databases and scientific publications.

   Using AND-System, we reconstructed a gene network of cytokine-mediated regulation of autism spectrum disorder (ASD)-associated genes and proteins. The analysis identified 110 cytokines that regulate the activity, degradation, and transport of 58 proteins involved in ASD pathogenesis, as well as the expression of 91 ASD-associated genes. Gene Ontology (GO) enrichment analysis revealed statistically significant associations of these genes with biological processes related to the development and function of the central nervous system. Furthermore, topological network analysis and functional significance assessment based on association with ASD-related GO biological processes allowed us to identify 21 cytokines exerting the strongest influence on the regulatory network. Among these, eight cytokines (IL-4, TGF-β1, BMP4, VEGFA, BMP2, IL-10, IFN-γ, TNF-α) had the highest priority, ranking at the top across all employed metrics. Notably, eight of the 21 prioritized cytokines (TNF-α, IL-6, IL-4, VEGFA, IL-2, IL-1β, IFN-γ, IL-17) are known targets of drugs currently used as immunosuppressants and antitumor agents. The pivotal role of these cytokines in ASD pathogenesis provides a rationale for potentially repurposing such inhibitory drugs for the treatment of autism spectrum disorders.

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