International data repositories of population-based immunological and genetic research

Introduction. Due to the active development of multiomics technologies, more and more information about human genetic and immunological research is becoming available. Data repositories are used to systematize and store such information, which facilitates the search and use of information for carrying out scientific research and solving applied problems in the area of medicine.

Objective. To analyze the global experience of using repositories of human genetic and immunological data to define their functional features and role in the development of population immunology and genetics.

Discussion. Functional features of genetic and immunological data repositories were analyzed. The data on the repositories included in the study was obtained from open sources. The selection process for repositories included three stages: selection of scientific publications, deduplication, and filtering based on selection criteria. The main criteria for the subsequent evaluation of human genetic and immunological data repositories were as follows: data volume, data accessibility, and data formats. The search for information about repositories and biobanks in the Russian Federation was conducted using online search queries on the Internet. The study analyzed 15 largest genetic and immunological data repositories, of which 37.5% are affiliated with the UK and 43.75% are affiliated with the USA. The task of creating and maintaining large repositories is solved, as a rule, by forming international and inter-institutional consortia. The availability of genetic data repositories is ensured by a combination of technological, organizational, and legal mechanisms. The most common sources of repository funding are state budgets, funds from private foundations and charitable organizations, and investments from pharmaceutical companies. The main risks associated with the operation of a repository can be divided into four groups: ethical, legal, biological, and technological risks related to data privacy. In the Russian Federation, genetic research is one of the most rapidly developing scientific directions. As a result, the challenges of secure storage, ethical use, and legal protection of data are acquiring particular importance. The presented review discusses possible directions for further development of national genetic and immunological data repositories, as well as the possibilities of additional regulation of genetic data handling at the legislative level.

Conclusions. The conducted review has identified possible risks associated with repository functioning and proposed various approaches to minimizing these risks and optimizing the development of data repositories. One of the most promising areas is the development of AI-based integration modules for processing and annotating data presented in standardized protocols.

1. Kochetova OV, Avzaletdinova DS, Korytina GF, Morugova TV, Boboedova OV. The Role of the Genes of Immune Response in the Development of Type 2 Diabetes. Medicine. 2022;4:1–9 (In Russ.). https://doi.org/10.29234/2308-9113-2022-10-4-1-9

2. Troshina EA, Yukina MYu, Nuralieva NF. The role of HLA genes: from autoimmune diseases to COVID-19. Problems of Endocrinology. 2020;66(4):9–15 (In Russ.). https://doi.org/10.14341/probl12470

3. Deutsch AJ, Udler MS. Phenotypic and genetic diversity in diabetes across populations. The Journal of Clinical Endocrinology and Metabolism.2025;dgaf234. https://doi.org/10.1210/clinem/dgaf234

4. Fairley S, Lowy-Gallego E, Perry E, Flicek P. The International Genome Sample Resource (IGSR) collection of open human genomic variation resources. Nucleic Acids Research. 2020;48(D1):D941–7. https://doi.org/10.1093/nar/gkz836

5. Gonzalez-Galarza FF, McCabe A, Melo Dos Santos EJ, Ghattaoraya G, Jones AR, Middleton D. Allele Frequency Net Database. Methods in Molecular Biology. 2024;2809:19–36. https://doi.org/10.1007/978-1-0716-3874-3_2

6. Sollis E, Mosaku A, Abid A, Buniello A, Cerezo M, Gil L, et al. The NHGRI-EBI GWAS Catalog: knowledge-base and deposition resource. Nucleic Acids Research. 2023;51(D1):D977–85. https://doi.org/10.1093/nar/gkac1010

7. Chen S, Francioli LC, Goodrich JK, Collins RL, Kanai M, Wang Q, et al. Author Correction: A genomic mutational constraint map using variation in 76,156 human genomes. Nature. 2024;625(7993):92–100. https://doi.org/10.1038/s41586-023-06045-0

8. Clough E, Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, et al. NCBI GEO: archive for gene expression and epigenomics data sets: 23-year update. Nucleic Acids Research. 2024;52(D1):D138–44. https://doi.org/10.1093/nar/gkad965

9. van den Akker EB, Trompet S, Wolf JJHB, Beekman M, Suchiman HED, Deelen J, et al. Metabolic Age Based on the BBMRI-NL 1H-NMR Metabolomics Repository as Biomarker of Age-related Disease. Circulation: Genomic and Precision Medicine. 2020;13(5):541–7. https://doi.org/10.1161/CIRCGEN.119.002610

10. Viñas-Giménez L, Padilla N, Batlle-Masó L, Casals F, Riviere JG, Martínez-Gallo M, et al. FHLdb: A Comprehensive Database on the Molecular Basis of Familial Hemophagocytic Lymphohistiocytosis. Frontiers in Immunology. 2020;31(11):107. https://doi.org/10.3389/fimmu.2020.00107

11. Marquez S, Babrak L, Greiff V, Hoehn KB, Lees WD, Prak ETL, et al. AIRR Community. Adaptive Immune Receptor Repertoire (AIRR) Community Guide to Repertoire Analysis. Methods in Molecular Biology. 2022;2453:297–316. https://doi.org/10.1007/978-1-0716-2115-8_17

12. Fernández-Orth D, Rueda M, Singh B, Moldes M, Jene A, Ferri M, et al. A quality control portal for sequencing data deposited at the European genome-phenome archive. Briefings in Bioinformatics. 2022;23(3):bbac136. https://doi.org/10.1093/bib/bbac136

13. Vita R, Mahajan S, Overton JA, Dhanda SK, Martini Sh, Cantrell JR, et al. The Immune Epitope Database (IEDB): 2018 update. Nucleic Acids Research. 2019;47(D1):D339–43. https://doi.org/10.1093/nar/gky1006

14. Rasmussen SA, Hamosh A, Amberger J, Arnold C, Bocchini C, O’Neill MJF, et al. What’s in a name? Issues to consider when naming Mendelian disorders. Genetics in Medicine. 2020;22(10):1573–5. https://doi.org/10.1038/s41436-020-0851-0

15. Thakur M, Brooksbank C, Finn RD, Firth HV, Foreman J, Freeberg M, et al. EMBL’s European Bioinformatics Institute (EMBL-EBI) in 2024. Nucleic Acids Research. 2024;gkae1089. https://doi.org/10.1093/nar/gkae1089

16. Wong KM, Langlais K, Tobias GS, Fletcher-Hoppe C, Krasnewich D, Leeds HS, et al. The dbGaP data browser: a new tool for browsing dbGaP controlled-access genomic data. Nucleic Acids Research. 2017;45(D1):D819–26. https://doi.org/10.1093/nar/gkw1139

17. Karimov VKh, Kazantsev DA. Potential threats of using genetic technologies and legal ways to resolve them. Security Issues. 2022;1:48–63 (In Russ.). https://doi.org/10.25136/2409-7543.2022.1.36744

18. Brandt DYC, Del Brutto OH, Nielsen R. Signatures of natural selection may indicate a genetic basis for the beneficial effects of oily fish intake in indigenous people from coastal Ecuador. G3 (Bethesda). 2025;15(4):jkaf014. https://doi.org/10.1093/g3journal/jkaf014

19. Arnaiz-Villena A, Lledo T, Silvera-Redondo C, Juarez I, Vaquero-Yuste Ch, Martin-Villa JM, et al. The Origin of Amerindians: A Case Study of Secluded Colombian Chimila, Wiwa, and Wayúu Ethnic Groups and Their Trans-Pacific Gene Flow. Genes (Basel). 2025;16(3):286. https://doi.org/10.3390/genes16030286

20. Barbitoff YA, Khmelkova DN, Pomerantseva EA, Slepchenkov AV, Zubashenko NA, Mironova IV, et al. Expanding the Russian allele frequency reference via cross-laboratory data integration: insights from 7452 exome samples. National Science Review. 2024;11(10):nwae326. https://doi.org/10.1093/nsr/nwae326

21. Poterba T, Vittal C, King D, Goldstein D, Goldstein JI, Schultz P, et al. The scalable variant call representation: enabling genetic analysis beyond one million genomes. Bioinformatics. 2024;41(1):btae746. https://doi.org/10.1093/bioinformatics/btae746

22. Patsakis M, Provatas K, Baltoumas FA, Chantzi N, Mouratidis I, Pavlopoulos GA, et al. MAFin: motif detection in multiple alignment files. Bioinformatics. 2025;41(4):btaf125. https://doi.org/10.1093/bioinformatics/btaf125

23. Przhilenskiy VI. Legal and ethical regulation of genetic research. RUDN Journal of Law. 2021;25(1):214–31 (In Russ.). https://doi.org/10.22363/2313-2337-2021-25-1-214-231

24. Akhtyamova EV, Alsynbayeva EM, Masalimova AA. Problems of legal regulation of the protection of genetic information obtained by preimplantation and prenatal genetic diagnostics in the Russian Federation. The Rule of Law: Theory and Practice. 2022;3(69):20–6 (In Russ.). https://doi.org/10.33184/pravgos-2022.3.3

25. Khusainova RI, Minniakhmetov IR, Yalaev BI, Akhtyamova EV, Alsynbaeva EM. Legal problems in the protection of human rights in the russian federation in the use of molecular genetic technologies in medicine. Genes & Cells. 2021;3:97–103 (In Russ.). https://doi.org/10.23868/202110014

26. Rassolov IM, Chubukova SG. Protection of Genetic Data in Genetic Testing and Gene-Therapy Treatment: IT Law Aspects. Actual Problems of Russian Law. 2020;15(5):65–72 (In Russ.). https://doi.org/10.17803/1994-1471.2020.114.5.065-072

27. Trikoz EN, Mustafina-Bredikhina DM, Gulyaeva EE. Legal regulation of gene editing procedure: USA and EU experience. RUDN Journal of Law. 2021;25(1):67–86 (In Russ.). https://doi.org/10.22363/2313-2337-2021-25-1-67-86

28. Novoselova LA, Kolzdorf MA. Genetic Information as Intellectual Property. Perm University Herald. Juridical Sciences. 2020;48:290–321 (In Russ.). https://doi.org/10.17072/1995-4190-2020-48-290-321