Project for the polygenic risk model for the schizophrenia risks prognosis considering the population characteristics of the Russian Federation

Understanding the genetic architecture of schizophrenia provides insight into the etiologic heterogeneity of the disease and helps to address a number of important issues related to the limitations of current genetic research. However, despite data based on large cohorts, assessing the risks of schizophrenia based on genetic data is currently difficult due to a number of factors. To a significant extent, this is due to ethnic diversity. This is especially relevant for the population of the Russian Federation, which is multiethnic in nature. As a result of significant migration and active interethnic mixing, the population of Russia is a complex ethnic conglomerate. At the same time, the genetic basis of mental illness in the multiethnic and multicultural population of the Russian Federation remains insufficiently studied. Objective: to propose a project for a model with high predictive values adapted to the Russian population based on the analysis of population genetic studies of schizophrenia. Results: The proposed project is aimed at integrating several cohorts of patients with schizophrenia and healthy volunteers into a single database of microarray genotyping, as well as the subsequent study of polygenic risk scores for schizophrenia in the Russian population. As a result of the project, a GWAS with a minimally sufficient cohort size will be performed in the Russian population for the first time, as well as a study of schizophrenia PRS, compiled on the basis of genome-wide association studies in European and East Asian cohorts and adapted to the multiethnic Russian cohort. A meta-predictor of schizophrenia risk based on polygenic scales will also be developed and validated, and a model for assessing the risk of schizophrenia adapted to the Russian population will be developed.

1. Lyubov EB, Yastrebov VS, Schevchenko LS, et al. The cost analysis of schizophrenia in Russia. Psihiatriya i psihofarmakoterapiya im. P.B. Gannushkina. 2013;15(01):7-19. (In Russ.).

2. National composition of the population of the Russian Federation, 2020 census. Federal State Statistical Service. [rosstat.gov.ru]. rosstat.gov; 2025 [cited 25 June 2025]. Available at: http://ssl.rosstat.gov.ru/storage/mediabank/Tom5_tab1_VPN-2020.xlsx

3. Rukavishnikov GV, Kasyanov ED, Zhilyaeva TV, Mazo GE. Schizophrenia and cardiometabolic disorders. Zhurnal nevrologii i psihiatrii im. S.S. Korsakova. 2021;121(6):132–138. (In Russ.). https://doi.org/10.17116/jnevro2021121061132

4. Schizophrenia, clinical guidelines, age category: adults, 2024. Rubricator of clinical guidelines of the Ministry of Health of the Russian Federation [cr.minzdrav.gov.ru]. cr.minzdrav.gov; 2025 [cited 25 June 2025]. Available at: https://cr.minzdrav.gov.ru/view-cr/451_3

5. Cheng MC, Chien WH, Huang YS, Fang TH, Chen CH. Translational Study of Copy Number Variations in Schizophrenia. Int J Mol Sci. 2021;23(1):457. https://doi.org/10.3390/ijms23010457

6. Correll CU, Solmi M, Croatto G, Schneider LK, Rohani-Montez SC, Fairley L, Smith N, Bitter I, Gorwood P, Taipale H, Tiihonen J. Mortality in people with schizophrenia: a systematic review and meta-analysis of relative risk and aggravating or attenuating factors. World Psychiatry. 2022;21(2):248-271. https://doi.org/10.1002/wps.20994

7. Dieset I, Andreassen OA, Haukvik UK. Somatic Comorbidity in Schizophrenia: Some Possible Biological Mechanisms Across the Life Span. Schizophr Bull. 2016;42(6):1316-1319. https://doi.org/10.1093/schbul/sbw028

8. Escott-Price V. Using polygenic risk score approaches to investigate the common-variant genetic architecture of schizophrenia. V.M. Bekterev review of psychiatry and medical psychology. 2019;(4-1):8-11. https://doi.org/10.31363/2313-7053-2019-4-1-8-11

9. Fedorenko OY, Golimbet VE, Ivanova SА, et al. Opening up new horizons for psychiatric genetics in the Russian Federation: moving toward a national consortium. Mol Psychiatry. 2019;24(8):1099-1111. https://doi.org/10.1038/s41380-019-0354-z

10. Gareeva AE. Genome-Wide Association Study: Analysis of Association of Polymorphic Loci in 4p15.2 and 20q13.31 Regions with Paranoid Schizophrenia. Russ J Genet. 2023;59:1058–1068. https://doi.org/10.1134/S1022795423100058

11. Hilker R, Helenius D, Fagerlund B, Skytthe A, Christensen K, Werge TM, Nordentoft M, Glenthøj B. Heritability of Schizophrenia and Schizophrenia Spectrum Based on the Nationwide Danish Twin Register. Biol Psychiatry. 2018;83(6):492-498. https://doi.org/10.1016/j.biopsych.2017.08.017

12. Howrigan DP, Rose SA, Samocha KE, et al. Exome sequencing in schizophrenia-affected parent-offspring trios reveals risk conferred by protein-coding de novo mutations. Nat Neurosci. 2020;23(2):185-193. https://doi.org/10.1038/s41593-019-0564-3

13. Iyegbe CO, O'Reilly PF. Genetic origins of schizophrenia find common ground. Nature. 2022;604(7906):433-435. https://doi.org/10.1038/d41586-022-00773-5

14. Jonas KG, Lencz T, Li K, Malhotra AK, Perlman G, Fochtmann LJ, Bromet EJ, Kotov R. Schizophrenia polygenic risk score and 20-year course of illness in psychotic disorders. Transl Psychiatry. 2019;9(1):300. https://doi.org/10.1038/s41398-019-0612-5

15. Kachuri L, Chatterjee N, Hirbo J, Schaid DJ, Martin I, Kullo IJ, Kenny EE, Pasaniuc B; Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium Methods Working Group; Witte JS, Ge T. Principles and methods for transferring polygenic risk scores across global populations. Nat Rev Genet. 2024;25(1):8-25. https://doi.org/10.1038/s41576-023-00637-2

16. Kozumplik O, Uzun S, Jakovljević M. Psychotic disorders and comorbidity: somatic illness vs. side effect. Psychiatr Danub. 2009;21(3):361-7.

17. Lam M, Chen CY, Li Z, et al. Comparative genetic architectures of schizophrenia in East Asian and European populations. Nat Genet. 2019;51(12):1670-1678. https://doi.org/10.1038/s41588-019-0512-x

18. Lambert SA, Wingfield B, Gibson JT, et al. The Polygenic Score Catalog: new functionality and tools to enable FAIR research. Preprint. medRxiv. 2024;2024.05.29.24307783. https://doi.org/10.1101/2024.05.29.24307783

19. Levchenko A, Kanapin A, Samsonova A, Fedorenko OY, Kornetova EG, Nurgaliev T, Mazo GE, Semke AV, Kibitov AO, Bokhan NA, Gainetdinov RR, Ivanova SA. A genome-wide association study identifies a gene network associated with paranoid schizophrenia and antipsychotics-induced tardive dyskinesia. Prog Neuropsychopharmacol Biol Psychiatry. 2021;105:110134. https://doi.org/10.1016/j.pnpbp.2020.110134

20. Liang Y, Pividori M, Manichaikul A, et al. Polygenic transcriptome risk scores (PTRS) can improve portability of polygenic risk scores across ancestries. Genome Biol. 2022;23(1):23. https://doi.org/10.1186/s13059-021-02591-w

21. Lin C, Zhang X, Jin H. The Societal Cost of Schizophrenia: An Updated Systematic Review of Cost-of-Illness Studies. Pharmacoeconomics. 2023;41(2):139-153. https://doi.org/10.1007/s40273-022-01217-8

22. Lowing PA, Mirsky AF, Pereira R. The inheritance of schizophrenia spectrum disorders: a reanalysis of the Danish adoptee study data. Am J Psychiatry. 1983;140(9):1167-71. https://doi.org/10.1176/ajp.140.9.1167

23. Massi MC, Franco NR, Manzoni A, et al. Learning high-order interactions for polygenic risk prediction. PLoS One. 2023;18(2):e0281618. https://doi.org/10.1371/journal.pone.0281618

24. Merikangas AK, Shelly M, Knighton A, Kotler N, Tanenbaum N, Almasy L. What genes are differentially expressed in individuals with schizophrenia? A systematic review. Mol Psychiatry. 2022;27(3):1373-1383. https://doi.org/10.1038/s41380-021-01420-7

25. Mostafavi H, Harpak A, Agarwal I, Conley D, Pritchard JK, Przeworski M. Variable prediction accuracy of polygenic scores within an ancestry group. Elife. 2020;9:e48376. https://doi.org/10.7554/eLife.48376

26. Oud MJ, Meyboom-de Jong B. Somatic diseases in patients with schizophrenia in general practice: their prevalence and health care. BMC Fam Pract. 2009;10:32. https://doi.org/10.1186/1471-2296-10-32

27. Patel AP, Wang M, Ruan Y, et al. A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease. Nat Med. 2023;29(7):1793-1803. https://doi.org/10.1038/s41591-023-02429-x

28. Ruan Y, Lin YF, Feng YA, et al. Improving polygenic prediction in ancestrally diverse populations. Nat Genet. 2022;54(5):573-580. https://doi.org/10.1038/s41588-022-01054-7

29. Sada-Fuente E, Aranda S, Papiol S, et al. Correction: Common genetic variants contribute to heritability of age at onset of schizophrenia. Transl Psychiatry. 2023;13(1):369. https://doi.org/10.1038/s41398-023-02651-8

30. Schizophrenia. WHO official site [who.int]. who; 2025 [Updated 10 January 2022; cited 25 June 2025]. Available at: https://www.who.int/news-room/fact-sheets/detail/schizophrenia

31. Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium. Genome-wide association study identifies five new schizophrenia loci. Nat Genet. 2011;43(10):969-76. https://doi.org/10.1038/ng.940

32. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511(7510):421-7. https://doi.org/10.1038/nature13595

33. Singh T, Poterba T, Curtis D, et al. Rare coding variants in ten genes confer substantial risk for schizophrenia. Nature. 2022;604(7906):509-516. https://doi.org/10.1038/s41586-022-04556-w

34. Taylor J, de Vries YA, van Loo HM, Kendler KS. Clinical characteristics indexing genetic differences in schizophrenia: a systematic review. Mol Psychiatry. 2023;28(2):883-890. https://doi.org/10.1038/s41380-022-01850-x

35. Tienari P. Interaction between genetic vulnerability and family environment: the Finnish adoptive family study of schizophrenia. Acta Psychiatr Scand. 1991;84(5):460-5. https://doi.org/10.1111/j.1600-0447.1991.tb03178.x

36. Trubetskoy V, Pardiñas AF, Qi T, et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature. 2022;604(7906):502-508. https://doi.org/10.1038/s41586-022-04434-5

37. Weissbrod O, Kanai M, Shi H, et al. Leveraging fine-mapping and multipopulation training data to improve cross-population polygenic risk scores. Nat Genet. 2022;54(4):450-458. https://doi.org/10.1038/s41588-022-01036-9

38. Wockner LF, Morris CP, Noble EP, et al. Brain-specific epigenetic markers of schizophrenia. Transl Psychiatry. 2015;5(11):e680. https://doi.org/10.1038/tp.2015.177

39. Zhang JP, Robinson D, Yu J, et al. Schizophrenia Polygenic Risk Score as a Predictor of Antipsychotic Efficacy in First-Episode Psychosis. Am J Psychiatry. 2019;176(1):21-28. https://doi.org/10.1176/appi.ajp.2018.17121363. Erratum in: Am J Psychiatry. 2019;176(3):252. https://doi.org/10.1176/appi.ajp.2019.1763correction

40. Zheutlin AB, Dennis J, Karlsson Linnér R, et al. Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients Across Four Health Care Systems. Am J Psychiatry. 2019;176(10):846-855. https://doi.org/10.1176/appi.ajp.2019.18091085