Текст олборлолт ба сүлжээний анализаар илрүүлсэн аутизмын хүрээний эмгэгтэй холбоотой генүүд
DOI:
https://doi.org/10.22353/mjeas.v7i1.9322Keywords:
аутизм, аутизмын хүрээний эмгэг, текст олборлолт, сүлжээний анализ, CTNNB1, DLG4, STAT3Abstract
Аутизмын хүрээний эмгэг (АХЭ) нь генетикийн болон хүрээлэн буй орчны олон хүчин зүйлийн нөлөөгөөр мэдрэлийн хөгжлийн хоцрогдол үүсгэдэг нарийн төвөгтэй эмгэг юм. АХЭ-ийн шалтгаан нь одоо ч нарийн тодорхой болоогүй бөгөөд судлаачид энэ төрлийн эмгэгийг илүү сайн ойлгох, эрсдэлт хүчин зүйлсийг үнэлэх, урьдчилан сэргийлэх чиглэлд ихээхэн анхаарал хандуулж байна. Судалгаагаар АХЭ-ийн 50 орчим хувь нь генетик шалтгаантай байх магадлалтай болохыг харуулж байна. Олон тооны уураг кодлогч генд тэр дундаа мэдрэлийн эсийн хөгжил, мэдрэлийн эсийн сигнал дамжуулалт зэрэгт чухал үүрэгтэй генүүдийн мутаци нь АХЭ-тэй холбоотой болох нь тогтоогдоод байна. Бид уг судалгааны ажлаар текст олборлолтын аргаар аутизмтай холбоотой генүүдийн шинжлэх ухааны өгүүллийн хураангуйд дурдагдсан байдлаар нь тодорхойлон, уураг-уургийн харилцан үйлчлэлийн сүлжээ байгуулж, АХЭ-ийн голлох шалтгаан байж болох эмчилгээний бай болох боломжитой уургуудыг тодорхойлов. Үр дүнд нь олон тооны уургуудтай харилцан үйлчилдэг, сүлжээний хувьд зангилаа цэгүүд болж байгаа катенин бета-1 (CTNNB1), синапсын дараах нягтралын 95 (PSD-95 буюу DLG4), сигнал дамжуулагч ба транскрипцийн идэвхжүүлэгч 3 (STAT3) зэрэг уургууд АХЭ үүсэхэд чухал нөлөөтэй байж болохыг тодорхойлов. Мөн бидний байгуулсан сүлжээнд олон тооны цитокинууд байгаа нь дархлааны нөлөөтэй АХЭ-ийн хувилбар байж болохыг харуулж байна. Цаашлаад ДНХ-ийн метилжилт, гистоны модификаци зэрэг процессоор эпигенетикийн түвшинд нөлөөлсөн АХЭ-ийн шалтгаан байж болох нь харагдаж байна. Энэ судалгааны үр дүнд цаашдын судалгаа, эмчилгээний бай болохуйц уургуудыг илрүүлэв.
Downloads
References
Rice C. Prevalence of autism spectrum disorders– Autism and Developmental Disabilities Monitoring Network, United States, 2006; 2009. National Center on Birth Defects and Developmental Disabilities (Centers for Disease Control and Prevention), Autism and Developmental Disabilities Monitoring Network. Available from: https://stacks.cdc.gov/view/cdc/5465.
Kanner L. Autistic disturbances of affective contact. Nervous child. 1943;2(3):217-50.
Asperger H. Die „Autistischen psychopathen” im kindesalter. Archiv f¨ur psychiatrie und nervenkrankheiten. 1944;117(1):76-136.
Baxter AJ, Brugha TS, Erskine HE, Scheurer RW, Vos T, Scott JG. The epidemiology and global burden of autism spectrum disorders. Psychol Med. 2015;45(3):601-13.
Chaste P, Leboyer M. Autism risk factors: genes, environment, and gene-environment interactions. Dialogues in Clinical Neuroscience. 2012;14(3):281-92.
Kim JY, Son MJ, Son CY, Radua J, Eisenhut M, Gressier F, et al. Environmental risk factors and biomarkers for autism spectrum disorder: an umbrella review of the evidence. The Lancet Psychiatry. 2019;6(7):590-600.
Lord C, Brugha TS, Charman T, Cusack J, Dumas G, Frazier T, et al. Autism spectrum disorder. Nat Rev Dis Primers. 2020;6(1):5.
Bromley R, Mawer G, Clayton-Smith J, Baker G, Liverpool GM, et al. Autism spectrum disorders following in utero exposure to antiepileptic drugs. Neurology. 2008;71(23):1923.
DeStefano F, Thompson WW. MMR vaccine and autism: an update of the scientific evidence. Expert review of vaccines. 2004;3(1):19-22.
Promotion BoH, Prevention D, ISR C. Immunization safety review: vaccines andautism. Immunization Safety Review. 2004.
Taylor B. Vaccines and the changing epidemiology of autism. Child: care, health and development. 2006;32(5):511-9.
Ronald A, Hoekstra RA. Autism spectrum disorders and autistic traits: A decade of new twin studies. American J of Med Genetics Pt B. 2011;156(3):255-74.
Sandin S, Lichtenstein P, Kuja-Halkola R, Larsson H, Hultman CM, Reichenberg A. The Familial Risk of Autism. JAMA. 2014;311(17):1770-7.
Miles JH. Autism spectrum disorders—A genetics review. Genetics in Medicine. 2011;13(4):278-94.
Becker KG, Barnes KC, Bright TJ, Wang SA. The Genetic Association Database. Nature Genetics. 2004;36(5):431-2.
Abrahams BS, Arking DE, Campbell DB, Mefford HC, Morrow EM, Weiss LA, et al. SFARI Gene 2.0: a community-driven knowledgebase for the autism spectrum disorders (ASDs). Molecular Autism. 2013;4(1):36.
Li X, Zou H, Brown WT. Genes associated with autism spectrum disorder. Brain Research Bulletin. 2012;88(6):543-52.
Qiu S, Qiu Y, Li Y, Cong X. Genetics of autism spectrum disorder: an umbrella review of systematic reviews and meta-analyses. Transl Psychiatry. 2022;12(1):249.
Gauthier J, Siddiqui TJ, Huashan P, Yokomaku D, Hamdan FF, Champagne N, et al. Truncating mutations in NRXN2 and NRXN1 in autism spectrum disorders and schizophrenia. HumGenet. 2011;130(4):563-73.
Sanders SJ, Murtha MT, Gupta AR, Murdoch JD, Raubeson MJ, Willsey AJ, et al. Denovo mutations revealed by whole-exome
sequencing are strongly associated with autism. Nature. 2012;485(7397):237-41. Available from:https://doi.org/10.1038/nature10945.
O’Roak BJ, Deriziotis P, Lee C, Vives L, Schwartz JJ, Girirajan S, et al. Exome sequencing in sporadic autism spectrum
disorders identifies severe de novo mutations. Nat Genet. 2011;43(6):585-9. Available from: https://doi.org/10.1038/ng.835.
O’Roak BJ, Vives L, Girirajan S, Karakoc E, Krumm N, Coe BP, et al. Sporadic autism exomes reveal a highly interconnected protein
network of de novo mutations. Nature. 2012;485(7397):246-50. Available from: https://doi.org/10.1038/nature10989.
Kim SS. Recent trends in autism spectrum disorder research using text mining of PubMed:importance of early detection. Clin Exp
Pediatr. 2021;64(7):339-40. Available from: https://doi.org/10.3345/cep.2020.01564.
Jurca G, Addam O, Aksac A, Gao S, Ozyer ¨ T, Demetrick D, et al. Integrating text mining, data mining, and network analysis
for identifying genetic breast cancer trends. BMC Res Notes. 2016;9:236. Available from:https://doi.org/10.1186/s13104-016-2023-5.
Jiang L, Cheng J, Chen Y. A review of text mining in healthcare. Journal of Healthcare Engineering. 2018;2018:1-10.
Rogers J, Hotez PJ, Bottazzi ME. The role of text mining in personalized medicine. Nature Reviews Genetics. 2019;20(12):757-69.
Beller E, Clark J, Tsafnat G, Thomas J, Marshall I, Wallace B, et al. Systematic reviews and text mining: The case for automation. Journal of Biomedical Informatics. 2020;108:103500.
Bian J, Wu Y, Shen F, Liu Y, Xu H. Text mining for clinical decision support: Opportunities and challenges. Artificial Intelligence in Medicine. 2017;75:68-81.
Liu Y, Liu H, Shen F, Wu Y, Wu SJ, Xu H. Mining adverse drug reactions from clinical narratives: A review. Journal of Biomedical Informatics. 2015;57:68-78.
Povey S, Lovering R, Bruford E, Wright M, Lush M, Wain H. The HUGO Gene Nomenclature Committee (HGNC). Human
Genetics. 2001;109(6):678.
Mering CV. STRING: a database of predicted functional associations between proteins. Nucleic Acids Research. 2003;31(1):258-61. Available from: https://doi.org/10.1093/nar/gkg034.
Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, et al. The STRING database in 2021: customizable protein–protein
networks, and functional characterization of useruploaded gene/measurement sets. Nucleic Acids Research. 2021;49(D1):D605-12. Available from:https://doi.org/10.1093/nar/gkaa1074.
van Rossum G, the Python development team. Python Tutorial. Python Software Foundation; 2016.
Cock PJA, Antao T, Chang JT, Chapman BA, Cox CJ, Dalke A, et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics. 2009;25(11):1422-3. Available from:
https://doi.org/10.1093/bioinformatics/btp163.
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: A Software Environment for Integrated Models of
Biomolecular Interaction Networks. Genome Res. 2003;13(11):2498-504. Available from:https://doi.org/10.1101/gr.1239303.
Xu C, Cao H, Zhang F, Cheadle C. Comprehensive literature data-mining analysis reveals a broad genetic network functionally
associated with autism spectrum disorder. International Journal of Molecular Medicine. 2018;42(5):2353-62.
Wei CH, Allot A, Lai PT, Leaman R, Tian S, Luo L, et al. PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge. Nucleic Acids Research. 2024;52(W1):W540-6.
Consortium GO. The Gene Ontology (GO) database and informatics resource. Nucleic Acids Research. 2004;32:D258-61.
Schriml LM, Munro JB, Schor M, Olley D, McCracken C, Felix V, et al. The human disease ontology 2022 update. Nucleic Acids Research. 2022;50(D1):D1255-61.
Fatemi SH, Eschenlauer A, Aman J, Folsom TD, Chekouo T. Quantitative proteomics of dorsolateral prefrontal cortex reveals an
early pattern of synaptic dysmaturation in children with idiopathic autism. Cerebral Cortex. 2024;34(13):161-71. Available from:
https://doi.org/10.1093/cercor/bhae044.
Levy AM, Gomez-Puertas P, T¨umer Z. Neurodevelopmental Disorders Associated with PSD-95 and Its Interaction Partners.
IJMS. 2022;23(8):4390. Available from: https://doi.org/10.3390/ijms23084390.
Ji Y, Xia Q, Zhang H, Huo H, Cao X, Wang W, et al. Whole Exome Sequencing Identified two Novel Truncation Mutations
in the CTNNB1 Gene Associated with Neurodevelopmental Disorder, Language Dysfunction, and Microcephaly in Chinese
Children. Child Neurology Open. 2023;10:2329048X231184184. Available from: https://doi.org/10.1177/2329048X231184184.
Dong F, Jiang J, McSweeney C, Zou D, Liu L, Mao Y. Deletion of CTNNB1 in inhibitory circuitry contributes to autismassociated behavioral defects. Human Molecular Genetics. 2016;25:2738-51. Available from: https://doi.org/10.1093/hmg/ddw131.
Waye MMY, Cheng HY. Genetics and epigenetics of autism: A Review. Psychiatry and Clinical Neurosciences. 2018;72:228-44. Available from:https://doi.org/10.1111/pcn.12606.
Masi A, DeMayo MM, Glozier N, Guastella AJ. An Overview of Autism Spectrum Disorder, Heterogeneity and Treatment Options.
Neurosci Bull. 2017;33:183-93. Available from: https://doi.org/10.1007/s12264-017-0100-y.
Li J, You Y, Yue W, Yu H, Lu T, Wu Z, et al. Chromatin remodeling gene EZH2 involved in the genetic etiology of autism
in Chinese Han population. Neuroscience Letters. 2016;610:182-6. Available from:https://doi.org/10.1016/j.neulet.2015.10.074.
Tseng CEJ, McDougle CJ, Hooker JM, Z¨urcher NR. Epigenetics of Autism Spectrum Disorder: Histone Deacetylases. Biological
Psychiatry. 2022;91:922-33. Available from: https://doi.org/10.1016/j.biopsych.2021.11.021.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Mongolian Journal of Engineering and Applied Sciences

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.