Preview

Cardiovascular Therapy and Prevention

Advanced search

Role of biobanking in the development of personalized medicine in Russia and the world

https://doi.org/10.15829/1728-8800-2024-4214

EDN: PTPSGI

Abstract

To implement a modern personalized approach in practical healthcare, the latest biomedical technologies should be developed and genetic research should be performed. The analysis of a substantial quantity of data is essential for the investigation of the prevalence of genetic risk factors for various diseases, drug resistance genes, the development of genetic panels to determine the individual risk of pathologies, as well as the creation of genetic risk scores. The review demonstrates through the use of illustrative examples that contemporary biobanks have become a vital component in the field of genetics research, both in Russia and globally. These specialized institutions are capable of accumulating, storing, and utilizing a substantial quantity of biological samples and related data, which is essential for advancing genetic research. The data collected in biobanks and associated clinical information form the basis for large-scale genetic studies conducted in different countries. The efficacy of genetic advancements, such as the early diagnosis of diseases, is contingent upon the number of biobanks, the establishment of collaborative networks among them, and the capacity to leverage digital platforms uniting diverse databases. Biobanks and biobanking have emerged as the foundation for the advancement of personalized medicine.

About the Authors

M. S. Pokrovskaya
National Medical Research Center for Therapy and Preventive Medicine
Russian Federation

Moscow



A. L. Borisova
National Medical Research Center for Therapy and Preventive Medicine
Russian Federation

Moscow



A. V. Kiseleva
National Medical Research Center for Therapy and Preventive Medicine
Russian Federation

Moscow



A. I. Ershova
National Medical Research Center for Therapy and Preventive Medicine
Russian Federation

Moscow



A. N. Meshkov
National Medical Research Center for Therapy and Preventive Medicine
Russian Federation

Moscow



O. M. Drapkina
National Medical Research Center for Therapy and Preventive Medicine
Russian Federation

Moscow



References

1. Lazareva TE, Barbitoff YA, Changalidis AI, et al. Biobanking as a Tool for Genomic Research: From Allele Frequencies to Cross-Ancestry Association Studies. J Pers Med. 2022;12(12):2040. doi:10.3390/jpm12122040.

2. Choi SW, Mak TSH, O’Reilly PF. Tutorial: a guide to performing polygenic risk score analyses. Nat Protoc. 2020;15:2759-72. doi:10.1038/s41596-020-0353-1.

3. Zaichenoka M, Ershova AI, Kiseleva AV, et al. Search and replication of associations of genome variants with lipid levels in a Russian sample. Cardiovascular Therapy and Prevention. 2023;22(12):3871. (In Russ.) doi:10.15829/1728-8800-2023-3871.

4. Li R, Chen Y, Ritchie MD, Moore JH. Electronic health records and polygenic risk scores for predicting disease risk. Nat Rev Genet. 2020;21:493-502. doi:10.1038/s41576-020-0224-1.

5. Brandenburg JT, Chen WC, Boua PR, et al. Genetic association and transferability for urinary albumin-creatinine ratio as a marker of kidney disease in four Sub-Saharan African populations and non-continental individuals of African ancestry. Front Genet. 2024;15:1372042. doi:10.3389/fgene.2024.1372042.

6. Ouyang D, Huang C, Liu H, et al. Comprehensive analysis of genetic associations and single-cell expression profiles reveals potential links between migraine and multiple diseases: a phenome-wide association study. Front Neurol. 2024;15: 1301208. doi:10.3389/fneur.2024.1301208.

7. Zhao P, Ying Z, Yuan C, et al. Shared genetic architecture highlights the bidirectional association between major depressive disorder and fracture risk. Gen Psychiatr. 2024;37(3):e101418. doi:10.1136/gpsych-2023-101418.

8. Cao Z, Hou Y, Xu C. Leucocyte telomere length, brain volume Biobank and Hub: The BANGABANDHU Study. Int J Gen Med. 2024;17:2507-12. doi:10.2147/IJGM.S466706.

9. Ba H, Zhang L, Peng H, et al. Causal links between sedentary behavior, physical activity, and psychiatric disorders: a Mendelian randomization study. Ann Gen Psychiatry. 2024;23:9. doi:10.1186/s12991-024-00495-0.

10. Cao Y, Zhu G, Feng C, et al. Cardiovascular risk burden, dementia risk and brain structural imaging markers: a study from UK Biobank. Gen Psychiatry. 2024;37(1):e101209. doi:10.1136/gpsych2023-101209.

11. Shikov AE, Skitchenko RK, Predeus AV, Barbitoff YA. Phenomewide functional dissection of pleiotropic effects highlights key molecular pathways for human complex traits. Sci Rep. 2020;10:1037. doi:10.1038/s41598-020-58040-4.

12. De Vincentis A, Tavaglione F, Spagnuolo R, et al. Metabolic and genetic determinants for progression to severe liver disease in subjects with obesity from the UK Biobank. Int J Obes. 2022; 46:486-93. doi:10.1038/s41366-021-01015-w.

13. Zhernakova DV, Le TH, Kurilshikov A, et al. Individual variations in cardiovascular-disease-related protein levels are driven by genetics and gut microbiome. Nat Genet. 2018;50(12):1524-32. doi:10.1038/s41588-018-0224-7.

14. Magnusson PKE, Almqvist C, Rahman I, et al. The Swedish Twin Registry: Establishment of a Biobank and Other Recent Developments.

15. Twin Res Hum Genet. 2013;16(1):317-29. doi:10.1017/thg.2012.104. Mitsuhashi N, Toyo-Oka L, Katayama T, et al. TogoVar: A comprehensive Japanese genetic variation database. Hum Genome Var. 2022;9(1):44. doi:10.1038/s41439-022-00222-9.

16. Walters RG, Millwood IY, Lin K, et al. Genotyping and population characteristics of the China Kadoorie Biobank. Cell Genom. 2023;3(8):100361. doi:10.1016/j.xgen.2023.100361.

17. Moon S, Kim YJ, Han S, et al. The Korea Biobank Array: Design and Identification of Coding Variants Associated with Blood Biochemical Traits. Sci Rep. 2019;9(1):1382. doi:10.1038/s41598-018-37832-9.

18. Ranjan R, Hasan MK, Adhikary AB. Bangladeshi Atherosclerosis and risk of dementia: a prospective cohort study. Gen Psychiatr. 2023;36(4):e101120. doi:10.1136/gpsych-2023-101120.

19. Thompson R, Johnston L, Taruscio D, et al. RD-Connect: an integrated platform connecting databases, registries, biobanks and clinical bioinformatics for rare disease research. J Gen Intern Med. 2014;29(Suppl 3):780-7. doi:10.1007/s11606-014-2908-8.

20. Anisimov SV, Meshkov AN, Glotov AS, et al. National Association of Biobanks and Biobanking Specialists: New Community for Promoting Biobanking Ideas and Projects in Russia. Biopreserv Biobank. 2021;19(1):73-82. doi:10.1089/bio.2020.0049.

21. Pokrovskaya MS, Sivakova OV, Efimova IA, et al. Biobanking as a Necessary Tool for Research in the Field Of Personalized Medicine in the Scientific Medical Center. Pers Med. 2019;16(6): 501-9. doi:10.2217/pme-2019-0049.

22. Shalnova SA, Imaeva AE, Kutsenko VA, et al. Hyperuricemia and hypertension in working-age people: results of a population study. Cardiovascular Therapy and Prevention. 2023; 22(9S):3783. (In Russ.) doi:10.15829/1728-8800-2023-3783.

23. Shalnova SA, Drapkina OM, Kontsevaya AV, et al. A pilot project to study troponin I in a representative sample of the region from the ESSE-RF study: distribution among population and associations with risk factors. Cardiovascular Therapy and Prevention. 2021; 20(4):2940. (In Russ.) doi:10.15829/1728-38.8800-2021-2940.

24. Kontsevaya AV, Shalnova SA, Drapkina OM. ESSE-RF study: epidemiology and public health promotion. Cardiovascular Therapy and Prevention. 2021;20(5):2987. (In Russ.) doi:10.15829/1728-8800-2021-2987.

25. Meshkov AN, Ershova AI, Kiseleva AV, et al. The prevalence of heterozygous familial hypercholesterolemia in selected regions of the Russian federation: The FH-ESSE-RF study. J Pers Med. 2021;11(6):464. doi:10.3390/jpm11060464.

26. Blokhina AV, Ershova AI, Kiseleva AV, et al. Applicability of diagnostic criteria and high prevalence of familial dysbetalipo-proteinemia in Russia: A pilot study. Int J Mol Sci. 2023;24(17): 13159. doi:10.3390/ijms241713159.

27. Sotnikova EA, Kiseleva AV, Kutsenko VA, et al. Identification of Pathogenic Variant Burden and Selection of Optimal Diagnostic Method Is a Way to Improve Carrier Screening for Autosomal Recessive Diseases. J Pers Med. 2022;12(7):1132. doi:10.3390/jpm12071132.

28. Kiseleva AV, Klimushina MV, Sotnikova EA, et al. A data-driven approach to carrier screening for common recessive diseases. J Pers Med. 2020;10(3):140. doi:10.3390/jpm10030140.

29. Kiseleva A, Klimushina M, Sotnikova E, et al. Cystic Fibrosis Polymorphic Variants in a Russian Population. PGPM. 2020;13:679-86. doi:10.2147/PGPM.S278806.

30. Ramensky VE, Ershova AI, Zaicenoka M, et al. Targeted Sequencing of 242 Clinically Important Genes in the Russian Population from the Ivanovo Region. Front Genet. 2021; 12:709419. doi:10.3389/fgene.2021.709419.

31. Meshkov AN, Kiseleva AV, Ershova AI, et al. ANGPTL3, ANGPTL4, APOA5, APOB, APOC2, APOC3, LDLR, PCSK9, LPL gene variants and coronary artery disease risk. Russian Journal of Cardiology 2022;27(10):5232. (In Russ.) doi:10.15829/1560-4071-2022-5232.

32. Meshkov A, Ershova A, Kiseleva A, et al. The LDLR, APOB, and PCSK9 variants of index patients with familial hypercholesterolemia in Russia. Genes (Basel). 2021;12(1):66. doi:10.3390/genes12010066.

33. Meshkov AN, Myasnikov RP, Kiseleva AV, et al. Genetic landscape in Russian patients with familial left ventricular noncompaction. Front Cardiovasc Med. 2023;10. doi:10.3389/fcvm.2023.1205787.

34. Myasnikov RP, Kulikova OV, Meshkov AN, et al. A splice variant of the MYH7 gene is causative in a family with isolated left ventricular noncompaction cardiomyopathy. Genes (Basel). 2022; 13(10):1750. doi:10.3390/genes13101750.

35. Myasnikov R, Bukaeva A, Kulikova O, et al. A case of severe leftventricular noncompaction associated with splicing altering variant in the FHOD3 gene. Genes (Basel). 2022;13(2):309. doi:10.3390/genes13020309.

36. Myasnikov R, Brodehl A, Meshkov A, et al. The double mutation DSG2-p.S363X and TBX20-p.D278X is associated with left ventricular non-compaction cardiomyopathy: Case report. Int J Mol Sci. 2021;22:6775. doi:10.3390/ijms22136775.

37. Marakhonov AV, Brodehl A, Myasnikov RP, et al. Noncompaction cardiomyopathy is caused by a novel in‐frame desmin (DES) deletion mutation within the 1A coiled‐coil rod segment leading to a severe filament assembly defect. Hum Mutat. 2019;40(6):734-41. doi:10.1002/humu.23747.

38. Brodehl A, Meshkov A, Myasnikov R, et al. Hemiand homozygous loss-of-function mutations in DSG2 (desmoglein-2) cause recessive arrhythmogenic cardiomyopathy with an early onset. Int J Mol Sci. 2021;22(7):3786. doi:10.3390/ijms22073786.

39. Ershova AI, Ivanova AA, Kiseleva AV, et al. From biobanking to personalized prevention of obesity, diabetes and metabolic syndrome. Cardiovascular Therapy and Prevention. 2021;20(8): 3123. (In Russ.) doi:10.15829/1728-8800-2021-3123.

40. Kiseleva AV, Soplenkova AG, Kutsenko VA, et al. Validation of genetic risk scores for obesity on a sample of the population of Russian regions. Cardiovascular Therapy and Prevention. 2023;22(10):3755. (In Russ.) doi:10.15829/1728-8800-2023-3755.

41. Kiseleva AV, Soplenkova AG, Kutsenko VA, et al. Validation of genetic risk scores for type 2 diabetes on a Russian population sample from the biobank of the National Medical Research Center for Therapy and Preventive Medicine. Cardiovascular Therapy and Prevention. 2023;22(11):3746. (In Russ.) doi:10.15829/1728-8800-2023-3746.

42. Kolchina MA, Skripnikova IA, Meshkov AN, et al. Associations of bone mass and polygenic risk of osteoporosis with indicators of arterial wall condition. Osteoporosis and Bone Diseases. 2022;25(2):21-30. (In Russ.) doi:10.14341/osteo12951.

43. Limonova AS, Ershova AI, Kiseleva AV, et al. Validation of genetic risk scores for hypertension in the Central Russian population. Cardiovascular Therapy and Prevention. 2023;22(12):3801. (In Russ.) doi:10.15829/1728-8800-2023-3801.

44. Ershova AI, Meshkov AN, Kutsenko VA, et al. Validation of genetic risk scores for coronary artery disease, developed on European population samples, in Russian population. Cardiovascular Therapy and Prevention. 2023;22(12):3856. (In Russ.) doi:10.15829/1728-8800-2023-3856.

45. Kiseleva AV, Vasilyev DK, Soplenkova AG, et al. Association of plasma microRNA levels with different collateral circulation degree in chronic total occlusion patients with coronary artery disease: a pilot study. Cardiovascular Therapy and Prevention. 2024;23(7):4086. (In Russ.) doi:10.15829/1728-8800-2024-4086.

46. Balanovskaya EV, Balanovsky OP. Human population genetics. Hereditary diseases: a national guide. Edited by Academicians of RAMS Bochkov NP, Ginter EK and Puzyrev VP. Moscow: GEOTAR-Media, 2012:199-243. (In Russ.) ISBN 978-5-9704-2231-1.

47. Pylev VYu, Agdzhoyan AT, Gorin IO, et al. Population biobank as a basis for determining spatial variation of clinically relevan pharmacogenetic biomarkers of cardiovascular diseases. Cardiovascular Therapy and Prevention. 2022;21(11):3430. (In Russ.) doi:10.15829/1728-8800-2022-3430.

48. Mirzaev KB, Fedorinov DS, Ivashchenko DV, et al. ADME pharmacogenetics: future outlook for Russia. Pharmacogenomics. 2019;20(11):847-65. doi:10.2217/pgs-2019-0013.

49. Zhernakova DV, Brukhin V, Malov S, et al. Genome-wide sequence analyses of ethnic populations across Russia. Genomics. 2020; 112(1):442-58. doi:10.1016/j.ygeno.2019.03.007.

50. Nasykhova YA, Tonyan ZN, Mikhailova AA, et al. Pharmaco-genetics of Type 2 Diabetes–Progress and Prospects. Int J Mol Sci. 2020;21(18):6842. doi:10.3390/ijms21186842.

51. Glotov AS, Kazakov SV, Vashukova ES, et al. Targeted sequencing analysis of ACVR2A gene identifies novel risk variants associated with preeclampsia. J Matern Fetal Neonatal Med. 2019; 32(17):2790-6. doi:10.1080/14767058.2018.1449204.

52. Illarionov RA, Pachuliia OV, Vashukova ES, et al. Plasma miRNA Profile in High Risk of Preterm Birth during Early and Mid-Pregnancy. Genes. 2022;13(11):2018. doi:10.3390/genes13112018.

53. Tkachenko AA, Changalidis AI, Maksiutenko EM, et al. Replication of Known and Identification of Novel Associations in Biobank-Scale Datasets: A Survey Using UK Biobank and FinnGen. Genes. 2024;15(7):931. doi:10.3390/genes15070931.

54. Changalidis AI, Maksiutenko EM, Barbitoff YA, et al. Aggregation of Genome-Wide Association Data from FinnGen and UK Biobank Replicates Multiple Risk Loci for Pregnancy Complications. Genes. 2022;13(12):2255. doi:10.3390/genes13122255.

55. Shcherbak SG, Changalidi AI, Barbitoff YA, et al. Identification of Genetic Risk Factors of Severe COVID-19 Using Extensive Phenotypic Data: A Proof-of-Concept Study in a Cohort of Russian Patients. Genes. 2022;13(3):534. doi:10.3390/genes13030534.

56. Tabakov VYu. Management of biobanking for medical genetics research. Cardiovascular Therapy and Prevention. 2021; 20(8):3027. (In Russ.) doi:10.15829/1728-8800-2021-3027.

57. Kondrateva E, Demchenko A, Slesarenko Y, et al. Derivation of iPSC line (RCMGi002-A) from dermal fibroblasts of a cystic fibrosis female patient with homozygous F508del mutation. Stem Cell Res. 2021;53:102251. doi:10.1016/j.scr.2021.102251.

58. Kit OI, Timofeeva SV, Sitkovskaya AO, et al. The biobank of the National Medical Research Centre for Oncology as a resource for research in the field of personalized medicine: A review. Journal of Modern Oncology. 2022;24(1):6-11. (In Russ.) doi:10.26442/18151434.2022.1.201384.

59. Kosobokova EN, Kalinina NA, Baryshnikova MA, et al. Bioresource collections: algorithms for development and functioning; basic and applied significance. Cardiovascular Therapy and Prevention. 2023;22(11):3654. (In Russ.) doi:10.15829/1728-8800-2023-3654.

60. Kosobokova EN, Kalinina NA, Konoplina KM, et al. Human Metastatic Melanoma Cell Lines Panel for In Vitro and In Vivo Investigations. J Mol Pathol. 2024;5(1):11-27. doi:10.3390/jmp5010002.


Supplementary files

What is already known about the subject?

  • Medical genetic research aimed at identifying genetic conditioning or predisposition to diseases has become relevant recently due to the trend towards personalized medicine.
  • Establishment of biobanks and biobank networks in various fields of biomedicine are modern tools that increase the efficiency and quality of scientific research.

What might this study add?

  • The review summarizes the data of numerous publications on genetic research based on biosample collections and biobank databases. The role of Russian biobanks in the development of this area is described. It is due to biobanks that large-scale projects have been carried out, allowing to create genetic risk scores, diagnostic systems, to obtain data on associations of genetic variants with pathological conditions in order to implement personalized approaches to medicine.

Review

For citations:


Pokrovskaya M.S., Borisova A.L., Kiseleva A.V., Ershova A.I., Meshkov A.N., Drapkina O.M. Role of biobanking in the development of personalized medicine in Russia and the world. Cardiovascular Therapy and Prevention. 2024;23(11):4214. (In Russ.) https://doi.org/10.15829/1728-8800-2024-4214. EDN: PTPSGI

Views: 310


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1728-8800 (Print)
ISSN 2619-0125 (Online)