What is the immunome?

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Abstract

Advances in Immunology have led to the understanding that the immune system is not only involved in the pathogenesis of various diseases but also plays a key role in maintaining homeostasis and tissue repair. It mediates interactions between the organism and dietary as well as environmental antigens, supports pregnancy, and enables coexistence with the microbiota, highlighting its role as an integrative system of the body.

This review examines the term immunome in both narrow and broad senses, describes key achievements of the Human Immunome Project, and discusses the advantages of this approach for studying the immune system. Initially, the term immunome referred to the repertoire of rearranged antibody genes, as well as T- and B-cell antigen receptors (TCR and BCR). The AIRR-seq technology has been developed for the collection and analysis of adaptive immune receptor repertoires. Knowledge of TCR and BCR repertoires can be applied to the development of modern vaccines against highly dangerous pathogens, rapid vaccine design in response to emerging pathogens, and the creation of personalized vaccines for elderly individuals and specific patient groups. An example of successful application of immunome research in the narrow sense is the development of a Russian drug for the treatment of ankylosing spondylitis. With substantial advances in immunology and biotechnology, the concept of the immunome has expanded. In its broader definition, the immunome includes not only immunocompetent cells, their receptors, and the molecules they produce, but also nonimmune cells and molecules involved in regulating immune responses, as well as the microenvironment in which immune reactions occur. Studies identifying changes in immune cell phenotypes, receptors, transcripts, cytokines, and their associations with disease activity or subtype provide valuable insights. However, their fragmented nature complicates the identification of the pathogenic role of individual factors.

Comprehensive analysis of the immunome facilitates the understanding of immunopathogenesis, the discovery of biomarkers for various diseases, patient stratification, and personalized therapy selection. The extreme complexity of the immunome and its internal interactions necessitates the use of advanced mathematical modeling, bioinformatics, computational tools, and rapidly developing artificial intelligence technologies.

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About the authors

Anna P. Toptygina

G.N. Gabrichevsky Research Institute for Epidemiology and Microbiology; Lomonosov Moscow State University

Author for correspondence.
Email: toptyginaanna@rambler.ru
ORCID iD: 0000-0002-9981-4762
SPIN-code: 8523-5018

MD, Dr. Sci. (Medicine)

Russian Federation, Moscow; Moscow

References

  1. Genomes Project Consortium; Abecasis GR, Auton A, Brooks LD, et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491(7422):56–65. doi: 10.1038/nature11632
  2. Lander ES, Linton LM, Birren B, et al; International human genome sequencing consortium. Initial sequencing and analysis of the human genome. Nature. 2001;409(6822):860–921. doi: 10.1038/35057062 EDN: LYYXST
  3. Wasinger VC, Cordwell SJ, Cerpa-Poljak A, et al. Progress with gene-product mapping of the Mollicutes: Mycoplasma genitalium. Electrophoresis. 1995;16(7):1090–1094. doi: 10.1002/elps.11501601185
  4. NIH HMP Working Group; Peterson J, Garges S, Giovanni M, et al. The NIH human microbiome project. Genome Res. 2009;19(12):2317–2323. doi: 10.1101/gr.096651.109
  5. The human microbiome project consortium. Structure, function and diversity of the healthy human microbiome. Nature. 2012;486(7402):207–214. doi: 10.1038/nature11234
  6. Tweeddale H, Notley-McRobb L, Ferenci T. Effect of slow growth on metabolism of Escherichia coli, as revealed by global metabolite pool (“metabolome”) analysis. J Bacteriol. 1998;180(19):5109–5116. doi: 10.1128/JB.180.19.5109-5116.1998
  7. Toptygina AP. Tissue-resident immune cells in homeostasis and tissue repair. Medical Immunology (Russia). 2025;27(3):475–484. doi: 10.15789/1563-0625-TRI-3156 EDN: CEMPZQ
  8. Toptygina AP. Role of non-canonical T cells in homeostasis and pathology. Medical Immunology (Russia). 2024;26(3):449–464. doi: 10.15789/1563-0625-RON-2918 EDN: NESGKV
  9. Pederson T. The immunome. Mol Immunol. 1999;36(15–16):1127–1128. doi: 10.1016/S0161-5890(99)00125-X
  10. Medzhitov R. The spectrum of inflammatory responses. Science. 2021;374(6571):1070–1075. doi: 10.1126/science.abi5200 EDN: CRGYAE
  11. De Groot AS, Moise L, McMurry JA, Martin W. Epitope-based immunome-derived vaccines: a strategy for improved design and safety. Clinical Applications of Immunomics. 2008;2:39–69. doi: 10.1007/978-0-387-79208-8_3
  12. Briney B, Inderbitzin A, Joyce C, Burton DR. Commonality despite exceptional diversity in the baseline human antibody repertoire. Nature. 2019;566(7744):393–397. doi: 10.1038/s41586-019-0879-y
  13. Soto C, Bombardi RG, Branchizio A, et al. High frequency of shared clonotypes in human B cell receptor repertoires. Nature. 2019;566(7744):398–402. doi: 10.1038/s41586-019-0934-8
  14. Wooden SL, Koff WC. The human vaccines project: towards a comprehensive understanding of the human immune response to immunization. Hum Vaccin Immunother. 2018;14(9):2214–2216. doi: 10.1080/21645515.2018.1476813 EDN: XAVAPX
  15. Biancotto A, McCoy JP. Studying the human immunome: the complexity of comprehensive leukocyte immunophenotyping. Curr Top Microbiol Immunol. 2014;377:23–60. doi: 10.1007/82_2013_336
  16. Yosef N, Regev A. Writ large: genomic dissection of the effect of cellular environment on immune response. Science. 2016;354(6308):64–68. doi: 10.1126/science.aaf5453
  17. Landhuis E. Single-cell approaches to immune profiling. Nature. 2018;557(7706):595–597. doi: 10.1038/d41586-018-05214-w
  18. Arnaout RA, Prak ETL, Schwab N, Rubelt F; Adaptive immune receptor repertoire community. The future of blood testing is the immunome. Front Immunol. 2021;12:626793. doi: 10.3389/fimmu.2021.626793 EDN: DAOHGM
  19. Crowe JE Jr. Influenza virus-specific human antibody repertoire studies. J Immunol. 2019;202(2):368–373. doi: 10.4049/jimmunol.1801459
  20. Bashford-Rogers RJM, Smith KGC, Thomas DC. Antibody repertoire analysis in polygenic autoimmune diseases. Immunology. 2018;155(1):3–17. doi: 10.1111/imm.12927 EDN: SETCIX
  21. Tabibian-Keissar H, Hazanov L, Schiby G, et al. Aging affects B-cell antigen receptor repertoire diversity in primary and secondary lymphoid tissues. Eur J Immunol. 2016;46(2):480–492. doi: 10.1002/eji.201545586
  22. Bian X, Wasserfall C, Wallstrom G, et al. Tracking the antibody immunome in type 1 diabetes using protein arrays. J Proteome Res. 2017;16(1):195–203. doi: 10.1021/acs.jproteome.6b00354
  23. Conrad C, Gilliet M. Psoriasis: from Pathogenesis to targeted therapies. Clin Rev Allergy Immunol. 2018;54(1):102–113. doi: 10.1007/s12016-018-8668-1 EDN: SUFPZD
  24. Sennikova SV, Toptygina AP, Kolobov AA, Simbirtsev AS. Treatment-dependent changes in cytokine profile of capillary and venous blood in patients with psoriasis. Medical Immunology (Russia). 2023;25(6):1395–1406. doi: 10.15789/1563-0625-CIT-2592 EDN: JINYRQ
  25. Gawel DR, Serra-Musach J, Lilja S, et al. A validated single-cell-based strategy to identify diagnostic and therapeutic targets in complex diseases. Genome Med. 2019;11(1):47. doi: 10.1186/s13073-019-0657-3 EDN: KFEATN
  26. Tsokos GC. Autoimmunity and organ damage in systemic lupus erythematosus. Nat Immunol. 2020;21(6):605–614. doi: 10.1038/s41590-020-0677-6 EDN: ZSWGZE
  27. Orange DE, Yao V, Sawicka K, et al. RNA identification of PRIME cells predicting rheumatoid arthritis flares. N Engl J Med. 2020;383(3):218–228. doi: 10.1056/NEJMoa2004114 EDN: WLNOYX
  28. Seyed Tabib NS, Madgwick M, Sudhakar P, et al. Big data in IBD: big progress for clinical practice. Gut. 2020;69(8):1520–1532. doi: 10.1136/gutjnl-2019-320065
  29. Kosoy R, Kim-Schulze S, Rahman A, et al. Deep analysis of the peripheral immune system in IBD reveals new insight in disease subtyping and response to monotherapy or combination therapy. Cell Mol Gastroenterol Hepatol. 2021;12(2):599–632. doi: 10.1016/j.jcmgh.2021.03.012 EDN: WOPVRI
  30. Argmann C, Tokuyama M, Ungaro RC, et al. Molecular characterization of limited ulcerative colitis reveals novel biology and predictors of disease extension. Gastroenterology. 2021;161(6):1953–1968.e15. doi: 10.1053/j.gastro.2021.08.053 EDN: PPRVWV
  31. Toptygina AP, Semikina EL, Tsvetkova VS, et al. Dependence of cytokine concentration in coproextracts in children with inflammatory bowel diseases on disease activity. Cytokines and inflammation. 2023;20(2):40–48. doi: 10.17816/CI627073 EDN: EPMIHE
  32. Falloon KA, Fiocchi C. Current therapy in inflammatory bowel disease: why and how we need to change? EMJ Innov. 2022;6(1):40–49. doi: 10.33590/emjinnov/21-00134 EDN: CIDKNQ
  33. Alsoud D, Verstockt B, Fiocchi C, Vermeire S. Breaking the therapeutic ceiling in drug development in ulcerative colitis. Lancet Gastroenterol Hepatol. 2021;6(7):589–595. doi: 10.1016/S2468-1253(21)00065-0 EDN: LHWSBG
  34. Vermeulen R, Schymanski EL, Barabási AL, Miller GW. The exposome and health: where chemistry meets biology. Science. 2020;367(6476):392–396. doi: 10.1126/science.aay3164 EDN: AFGVDX
  35. Kirchgesner J, Lemaitre M, Carrat F, et al. Risk of serious and opportunistic infections associated with treatment of inflammatory bowel diseases. Gastroenterology. 2018;155(2):337–346.e10. doi: 10.1053/j.gastro.2018.04.012
  36. Fiocchi C, Iliopoulos D. Inflammatory bowel disease therapy: beyond the immunome. Front Immunol. 2022;13:864762. doi: 10.3389/fimmu.2022.864762 EDN: TCPZHA
  37. Revilla L, Mayorgas A, Corraliza AM, et al. Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis. PLoS One. 2021;16(2):e0246367. doi: 10.1371/journal.pone.0246367 EDN: BPYZCB
  38. Toptygina A, Grebennikov D, Bocharov G. Prediction of specific antibody- and cell-mediated responses using baseline immune status parameters of individuals received measles-mumps-rubella vaccine. Viruses. 2023;15(2):524. doi: 10.3390/v15020524 EDN: MAMGQB
  39. Yang X, Garner LI, Zvyagin IV, et al. Autoimmunity-associated T cell receptors recognize HLA-B*27-bound peptides. Nature. 2022;612(7941):771–777. doi: 10.1038/s41586-022-05501-7 EDN: PNTVAM
  40. Britanova OV, Lupyr KR, Staroverov DB, et al. Targeted depletion of TRBV9+ T cells as immunotherapy in a patient with ankylosing spondylitis. Nat Med. 2023;29(11):2731–2736. doi: 10.1038/s41591-023-02613-z EDN: HOBFJZ

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