Геномная нестабильность как фактор формирования индивидуальных особенностей проявления заболевания: вызов для современной персонализированной медицины

В последнее время все больше внимания уделяется геномным нарушениям, поражающим не все клетки организма, а только их определенную пропорцию (соматический мозаицизм и нестабильность генома). Тем не менее, во многих областях современной медицинской геномики роль данных форм геномной вариабельности до настоящего времени оценена в недостаточной степени. В частности, остается малоизученным эффект геномной нестабильности (прогрессирующего увеличения числа клеток с неспецифическими мутациями), которая является механизмом широкого спектра заболеваний, на индивидуальные особенности проявления и течения болезни. В рамках основной парадигмы персонализированной геномики необходимо рассматривать две основных компоненты соматического мутагенеза, приводящего к нестабильности генома и/или хромосом: индивидуальный геномный профиль (набор геномных изменений во всех клетках организма), который способствует возникновению геномной нестабильности, и последствия геномной нестабильности в клиническом контексте, которые являются результатом случайных мутационных процессов и, следовательно, формируют патологию, обладающую исключительной индивидуальностью (уникальностью) не только для организма, но и для соответствующей клеточной популяции. В настоящей работе рассматриваются причины и возможные последствия геномной нестабильности, ее способность формировать индивидуальные особенности проявления и течения болезни, а также технологические сложности, ассоциированные с диагностикой и определением влияния данной формы геномной патологии на клинико-фенотипические особенности пациента.

1. Claussnitzer M, Cho JH, Collins R, et al. A brief history of human disease genetics. Nature. 2020;577(7789):179‒189. https://doi.org/10.1038/s41586-019-1879-7

2. Boix CA, James BT, Park YP, et al. Regulatory genomic circuitry of human disease loci by integrative epigenomics. Nature. 2021;590(7845):300‒307. https://doi.org/10.1038/s41586-020-03145-z

3. Iourov IYu, Vorsanova SG, Yurov YuB. Somatic genome variations in health and disease. Curr Genomics. 2010; 11(6):387‒396. https://doi.org/10.2174/138920210793176065

4. Iourov IYu, Vorsanova SG, Yurov YuB, Kutsev SI. Ontogenetic and pathogenetic views on somatic chromosomal mosaicism. Genes (Basel). 2019;10(5):379. https://doi.org/10.3390/genes10050379

5. Tinker RJ, Bastarache L, Ezell K, et al. Undiagnosed diseases network. The contribution of mosaicism to genetic diseases and de novo pathogenic variants. Am J Med Genet A. 2023;191(10):2482‒2492. https://doi.org/10.1002/ajmg.a.63309

6. Militaru MS, Babliuc IM, Bloaje-Florică VL, et al. The impact of chromosomal mosaicisms on prenatal diagnosis and genetic counseling: a narrative review. J Pers Med. 2024;14(7):774. https://doi.org/10.3390/jpm14070774

7. Iourov IYu, Vorsanova SG, Yurov YuB. Somatic cell genomics of brain disorders: a new opportunity to clarify genetic-environmental interactions. Cytogenet Genome Res. 2013;139(3):181‒188. https://doi.org/10.1159/000347053

8. Bennett RJ, Forche A, Berman J. Rapid mechanisms for generating genome diversity: whole ploidy shifts, aneuploidy, and loss of heterozygosity. Cold Spring Harb Perspect Med. 2014;4(10):a019604. https://doi.org/10.1101/cshperspect.a019604

9. Heng J, Heng HH. Genome chaos, information creation, and cancer emergence: searching for new frameworks on the 50th Anniversary of the “War on Cancer”. Genes (Basel). 2021;13(1):101. https://doi.org/10.3390/genes13010101

10. Юров И. Ю., Ворсанова С. Г., Куринная О. С. и др. Причины и последствия геномной нестабильности при психических и нейродегенеративных заболеваниях. Молекулярная биология. 2021;55(1):42‒53. https://doi.org/10.31857/S0026898421010158, https://elibrary.ru/cmauxh

11. Kirsch-Volders M, Fenech M. Aneuploidy, inflammation and diseases. Mutat Res. 2022;824:111777. https://doi.org/10.1016/j.mrfmmm.2022.111777

12. Iourov IYu, Vorsanova SG, Kurinnaia OS, et al. Somatic mosaicism in the diseased brain. Mol Cytogenet. 2022;15(1):45. https://doi.org/10.1186/s13039-022-00624-y

13. Goehring L, Huang TT, Smith DJ. Transcription-replication conflicts as a source of genome instability. Annu Rev Genet. 2023;57:157‒179. https://doi.org/10.1146/annurev-genet-080320-031523

14. Veschetti L, Treccani M, De Tomi E, Malerba G. Genomic instability evolutionary footprints on human health: driving forces or side effects? Int J Mol Sci. 2023;24(14):11437. https://doi.org/10.3390/ijms241411437

15. Mazzagatti A, Engel JL, Ly P. Boveri and beyond: chromothripsis and genomic instability from mitotic errors. Mol Cell. 2024;84(1):55‒69. https://doi.org/10.1016/j.molcel.2023.11.002

16. Iourov IYu, Vorsanova SG, Pankratova ED, et al. Unstable genomes in the human brain: what does it mean for personalized psychiatry and neurology. Pers Psychiat Neurol. 2025;5(4):16‒25. https://doi.org/10.52667/2712-9179-2025-5-4-16-25

17. Thorpe J, Osei-Owusu IA, Avigdor BE, et al. Mosaicism in human health and disease. Annu Rev Genet. 2020;54:487‒510. https://doi.org/10.1146/annurev-genet-041720-093403

18. Ray S, Chakrabarty S, Chaudhuri AR. Impact of genome instability on human health. Front Mol Biosci. 2023;10:1243968. https://doi.org/10.3389/fmolb.2023.1243968

19. Юров И. Ю., Ворсанова С. Г., Юров Ю. Б. Геномные и хромосомные болезни центральной нервной системы: молекулярные и цитогенетические аспекты. М.: Медпрактика; 2014. 384 c.

20. Potter H, Chial HJ, Caneus J, et al. Chromosome instability and mosaic aneuploidy in neurodegenerative and neurodevelopmental disorders. Front Genet. 2019;10:1092. https://doi.org/10.3389/fgene.2019.0109

21. Юров И. Ю., Ворсанова С. Г., Куринная О. С. и др. Геномная и хромосомная нестабильность у детей с нарушением развития центральной нервной системы (ЦНС). Медицинская генетика. 2025;24(9):150‒152. https://doi.org/10.25557/2073-7998.2025.09.150-152, https://elibrary.ru/rzvgha

22. Schmitz EG, Griffith M, Griffith OL, Cooper MA. Identifying genetic errors of immunity due to mosaicism. J Exp Med. 2025;222(5):e20241045. https://doi.org/10.1084/jem.20241045

23. Vijayraghavan S, Saini N. Genome instability and somatic mutagenesis in autoimmune diseases. Cancers (Basel). 2026;18(3):513. https://doi.org/10.3390/cancers18030513

24. Тиганов А. С., Юров Ю. Б., Ворсанова С. Г., Юров И. Ю. Нестабильность генома головного мозга: этиология, патогенез и новые биологические маркеры психических болезней. Вестник Российской академии медицинских наук. 2012;67(9):45‒53. https://doi.org/10.15690/vramn.v67i9.406, https://elibrary.ru/nrjjmq

25. Yurov YuB, Vorsanova SG, Iourov IYu. Chromosome instability in the neurodegenerating brain. Front Genet. 2019;10:892. https://doi.org/10.3389/fgene.2019.00892

26. Puzuka A, Alksere B, Gailite L, Erenpreiss J. Idiopathic infertility as a feature of genome instability. Life (Basel). 2021;11(7):628. https://doi.org/10.3390/life11070628

27. Vijg J, Dong X. Pathogenic mechanisms of somatic mu-tation and genome mosaicism in aging. Cell. 2020;182(1):12‒23. https://doi.org/10.1016/j.cell.2020.06.024

28. Iourov IYu, Yurov YuB, Vorsanova SG, Kutsev SI. Chromosome instability, aging and brain diseases. Cells. 2021; 10(5):1256. https://doi.org/10.3390/cells10051256

29. Wu Z, Qu J, Liu GH. Roles of chromatin and genome instability in cellular senescence and their relevance to ageing and related diseases. Nat Rev Mol Cell Biol. 2024;25(12):979‒1000. https://doi.org/10.1038/s41580-024-00775-3

30. Gabriel GC, Yagi H, Tan T, et al. Mitotic block and epigenetic repression underlie neurodevelopmental defects and neurobehavioral deficits in congenital heart disease. Nat Commun. 2025;16(1):469. https://doi.org/10.1038/s41467-024-55741-6

31. Yurov YuB, Vorsanova SG, Iourov IYu. GIN’n’CIN hypothesis of brain aging: deciphering the role of somatic genetic instabilities and neural aneuploidy during ontogeny. Mol Cytogenet. 2009;2:23. https://doi.org/10.1186/1755-8166-2-23

32. Waldvogel SM, Posey JE, Goodell MA. Human embryonic genetic mosaicism and its effects on development and disease. Nat Rev Genet. 2024;25(10):698‒714. https://doi.org/10.1038/s41576-024-00715-z

33. Iourov IYu, Vorsanova SG, Yurov YuB, et al. The cytogenomic “theory of everything”: chromohelkosis may underlie chromosomal instability and mosaicism in disease and aging. Int J Mol Sci. 2020;21(21):8328. https://doi.org/10.3390/ijms21218328

34. Vihinen M. Individual genetic heterogeneity. Genes (Basel). 2022;13(9):1626. https://doi.org/10.3390/genes13091626

35. Iourov IYu, Vorsanova SG, Yurov YuB. The variome concept: focus on CNVariome. Mol Cytogenet. 2019;12:52. https://doi.org/10.1186/s13039-019-0467-8

36. Zhang FL, Feng YQ, Wang JY, et al. Single cell epigenomic and transcriptomic analysis uncovers potential transcription factors regulating mitotic/meiotic switch. Cell Death Dis. 2023;14(2):134. https://doi.org/10.1038/s41419-023-05671-w

37. Islam A, Shaukat Z, Hussain R, et al. Aneuploidy is linked to neurological phenotypes through oxidative stress. J Mol Neurosci. 2024;74(2):50. https://doi.org/10.1007/s12031-024-02227-1

38. Poetsch MS, Strano A, Guan K. Human induced pluripotent stem cells: from cell origin, genomic stability, and epigenetic memory to translational medicine. Stem Cells. 2022;40(6):546‒555. https://doi.org/10.1093/stmcls/sxac020

39. Vorsanova SG, Yurov YuB, Iourov IYu. Neurogenomic pathway of autism spectrum disorders: linking germline and somatic mutations to genetic-environmental interactions. Current Bioinformatics. 2017;12(1):19‒26. https://doi.org/10.2174/1574893611666160606164849

40. Chen C, Wang J, Pan D, et al. Applications of multi-om-ics analysis in human diseases. MedComm (2020). 2023;4(4):e315. https://doi.org/10.1002/mco2.315

41. Hassan M, Awan FM, Naz A, et al. Innovations in genomics and big data analytics for personalized medicine and health care: a review. Int J Mol Sci. 2022;23(9):4645. https://doi.org/10.3390/ijms23094645

42. Molla G, Bitew M. Revolutionizing personalized medicine: synergy with multi-omics data generation, main hur dles, and future perspectives. Biomedicines. 2024;12(12):2750. https://doi.org/10.3390/biomedicines12122750

43. Zhan C, Tang T, Wu E, et al. From multi-omics approaches to personalized medicine in myocardial infarction. Front Cardiovasc Med. 2023;10:1250340. https://doi.org/10.3389/fcvm.2023.1250340

44. Arga KY, Sinha R. Recent Developments in cancer systems biology: lessons learned and future directions. J Pers Med. 2021;11(4):271. https://doi.org/10.3390/jpm11040271

45. Fawaz A, Ferraresi A, Isidoro C. Systems biology in cancer diagnosis integrating omics technologies and artificial intelligence to support physician decision making. J Pers Med. 2023;13(11):1590. https://doi.org/10.3390/jpm13111590

46. Alfonso-González L, Fernández FJ, Vega MC. Systems immunology: when systems biology meets immunology. Front Immunol. 2025;16:1630488. https://doi.org/10.3389/fim-mu.2025.1630488

47. Ilan Y. Next-Generation Personalized Medicine: Implementation of variability patterns for overcoming drug resistance in chronic diseases. J Pers Med. 2022;12(8):1303. https://doi.org/10.3390/jpm12081303

48. Bhattacharyya S, Ehsan SF, Karacosta LG. Phenotypic maps for precision medicine: a promising systems biology tool for assessing therapy response and resistance at a personalized level. Front Netw Physiol. 2023;3:1256104. https://doi.org/10.3389/fnetp.2023.1256104

49. Lamb JR, Jennings LL, Gudmundsdottir V, et al. It’s in our blood: a glimpse of personalized medicine. Trends Mol Med. 2021;27(1):20‒30. https://doi.org/10.1016/j.molmed.2020.09.003

50. Iourov IYu, Vorsanova SG, Yurov YuB. Pathway-based classification of genetic diseases. Mol Cytogenet. 2019;12:4. https://doi.org/10.1186/s13039-019-0418-4

51. Vallée A. Multi-scale digital twins for personalized medicine. Front Digit Health. 2026;8:1753906. https://doi.org/10.3389/fdgth.2026.1753906

52. Tiwari P, Pandey R, Chadha S. Integrative multi-omics approaches for personalized medicine and health. Current Bioinformatics. 2026;21(2):109‒121. https://doi.org/10.2174/0115748936360644250127095005

53. Dubois F, Sidiropoulos N, Weischenfeldt J, Beroukhim R. Structural variations in cancer and the 3D genome. Nat Rev Cancer. 2022;22(9):533‒546. https://doi.org/10.1038/s41568-022-00488-9

54. Sreenivasan VKA, Yumiceba V, Spielmann M. Structural variants in the 3D genome as drivers of disease. Nat Rev Genet. 2025;26(11):742‒760. https://doi.org/10.1038/s41576-025-00862-x

55. Vorsanova SG, Yurov YuB, Iourov IYu. Dynamic nature of somatic chromosomal mosaicism, genetic-environmental interactions and therapeutic opportunities in disease and aging. Mol Cytogenet. 2020;13:16. https://doi.org/10.1186/s13039-020-00488-0

56. Smirnov P, Przybilla MJ, Simovic-Lorenz M, et al. Multi-omic and single-cell profiling of chromothriptic medulloblastoma reveals genomic and transcriptomic consequences of genome instability. Nat Commun. 2024;15(1):10183. https://doi.org/10.1038/s41467-024-54547-w

57. Chabanon RM, Danlos FX, Ouali K, Postel-Vinay S. Genome instability and crosstalk with the immune response. Genome Med. 2025;17(1):139. https://doi.org/10.1186/s13073-025-01509-6

58. Pikor L, Thu K, Vucic E, Lam W. The detection and implication of genome instability in cancer. Cancer Metastasis Rev. 2013;32(3‒4):341‒352. https://doi.org/10.1007/s10555-013-9429-5

59. Cohen AS, Wilson SL, Trinh J, Ye XC. Detecting somatic mosaicism: considerations and clinical implications. Clin Genet. 2015;87(6):554‒562. https://doi.org/10.1111/cge.12502

60. Ворсанова С. Г., Юров И. Ю., Куринная О. С. и др. Геномные аномалии у детей с умственной отсталостью и аутизмом: использование технологии сравнительной геномной гибридизации на хромосомах in situ (HRCGH) и молекулярного кариотипирования на ДНК-микроматрицах (array CGH). Журнал неврологии и психиатрии им. С.С. Корсакова. 2013;113(8):46‒49. https://elibrary.ru/rbmclv

61. Boßelmann CM, Leu C, Lal D. Technological and computational approaches to detect somatic mosaicism in epilepsy. Neurobiol Dis. 2023;184:106208. https://doi.org/10.1016/j.nbd.2023.106208

62. Poot M. Methods of detection and mechanisms of origin of complex structural genome variations. Methods Mol Biol. 2024;2825:39‒65. https://doi.org/10.1007/978-1-0716-3946-7_2

63. Zhang D, Lin SY, Lee M. Exploring genomic instability of cancers: applications in diagnosis and treatment. Front Cell Dev Biol. 2025;13:1528281. https://doi.org/10.3389/fcell.2025.1528281

64. Iourov IYu, Vorsanova SG, Yurov YuB. A paradoxical role for somatic chromosomal mosaicism and chromosome instability in cancer: theoretical and technological aspects. Methods Mol Biol. 2024;2825:67‒78. https://doi.org/10.1007/978-1-0716-3946-7_3

65. Lim J, Chin V, Fairfax K, et al. Transitioning single-cell genomics into the clinic. Nat Rev Genet. 2023;24(8):573‒584. https://doi.org/10.1038/s41576-023-00613-w

66. Le J, Dian Y, Zhao D, et al. Single-cell multi-omics in cancer immunotherapy: from tumor heterogeneity to personalized precision treatment. Mol Cancer. 2025;24(1):221. https://doi.org/10.1186/s12943-025-02426-3

67. Shapiro JA. How chaotic is genome chaos? Cancers (Basel). 2021;13(6):1358. https://doi.org/10.3390/cancers13061358

68. Heng J, Heng HH. Genome chaos: creating new genomic information essential for cancer macroevolution. Semin Cancer Biol. 2022;81:160‒175. https://doi.org/10.1016/j.semcan-cer.2020.11.003

69. Pellestor F. Chromoanagenesis and beyond: catastrophic events shaping the genome. Methods Mol Biol. 2025;2968:65‒73. https://doi.org/10.1007/978-1-0716-4750-9_4

70. Ye JC, Horne S, Zhang JZ, et al. Therapy induced genome chaos: a novel mechanism of rapid cancer drug resistance. Front Cell Dev Biol. 2021;9:676344. https://doi.org/10.3389/fcell.2021.676344

71. Baslan T, Morris JP 4th, Zhao Z, et al. Ordered and deterministic cancer genome evolution after p53 loss. Nature. 2022;608(7924):795‒802. https://doi.org/10.1038/s41586-022-05082-5

72. Fountzilas E, Tsimberidou AM, Vo HH, Kurzrock R. Clinical trial design in the era of precision medicine. Genome Med. 2022;14(1):101. https://doi.org/10.1186/s13073-022-01102-1

73. Rehm HL, Alaimo JT, Aradhya S, et al. Medical genome initiative steering committee. The landscape of reported VUS in multi-gene panel and genomic testing: time for a change. Genet Med. 2023;25(12):100947. https://doi.org/10.1016/j.gim.2023.100947

74. Brlek P, Bulić L, Bračić M, et al. Implementing whole genome sequencing (WGS) in clinical practice: advantages, challenges, and future perspectives. Cells. 2024;13(6):504. https://doi.org/10.3390/cells13060504

75. Sadee W, Wang D, Hartmann K, Toland AE. Pharmacogenomics: driving personalized medicine. Pharmacol Rev. 2023;75(4):789‒814. https://doi.org/10.1124/pharmrev.122. 000810