Recent progress in both conceptual and technological approaches to human immunology have rejuvenated a field that has long been in the shadow of the inbred mouse model. This is a healthy development both for the clinical relevance of immunology and for the fact that it is a way to gain access to the wealth of phenomenology in the many human diseases that involve the immune system. This is where we are likely to discover new immunological mechanisms and principals, especially those involving genetic heterogeneity or environmental influences that are difficult to model effectively in inbred mice. We also suggest that there are likely to be novel immunological mechanisms in long-lived, less fecund mammals such as human beings since they must remain healthy far longer than short-lived rodents in order for the species to survive.


Article metrics loading...

Loading full text...

Full text loading...


Literature Cited

  1. Steinman RM, Mellman I. 1.  2004. Immunotherapy: bewitched, bothered, and bewildered no more. Science 305:5681197–200 [Google Scholar]
  2. Herrath von MG, Nepom GT. 2.  2005. Lost in translation: barriers to implementing clinical immunotherapeutics for autoimmunity. J. Exp. Med. 202:91159–62 [Google Scholar]
  3. Davis MM. 3.  2008. A prescription for human immunology. Immunity 29:6835–38 [Google Scholar]
  4. Quintana-Murci L, Alcaïs A, Abel L, Casanova J-L. 4.  2007. Immunology in natura: clinical, epidemiological and evolutionary genetics of infectious diseases. Nat. Immunol. 8:111165–71 [Google Scholar]
  5. Davis MM, Tato CM, Furman D. 5.  2017. Systems immunology: just getting started. Nat. Immunol. 18:7725–32 [Google Scholar]
  6. Wrammert J, Smith K, Miller J, Langley WA, Kokko K. 6.  et al. 2008. Rapid cloning of high-affinity human monoclonal antibodies against influenza virus. Nature 453:7195667–71 [Google Scholar]
  7. Ráki M, Fallang L-E, Brottveit M, Bergseng E, Quarsten H. 7.  et al. 2007. Tetramer visualization of gut-homing gluten-specific T cells in the peripheral blood of celiac disease patients. PNAS 104:82831–36 [Google Scholar]
  8. Brodin P, Davis MM. 8.  2017. Human immune system variation. Nat. Rev. Immunol. 17:121–29 [Google Scholar]
  9. Fredolini C, Byström S, Pin E, Edfors F, Tamburro D. 9.  et al. 2016. Immunocapture strategies in translational proteomics. Expert Rev. Proteom. 13:183–98 [Google Scholar]
  10. Lundberg M, Eriksson A, Tran B, Assarsson E, Fredriksson S. 10.  2011. Homogeneous antibody-based proximity extension assays provide sensitive and specific detection of low-abundant proteins in human blood. Nucleic Acids Res 39:15e102 [Google Scholar]
  11. Gold L, Ayers D, Bertino J, Bock C, Bock A. 11.  et al. 2010. Aptamer-based multiplexed proteomic technology for biomarker discovery. PLOS ONE 5:12e15004 [Google Scholar]
  12. Xu GJ, Kula T, Xu Q, Li MZ, Vernon SD. 12.  et al. 2015. Comprehensive serological profiling of human populations using a synthetic human virome. Science 348:6239aaa0698 [Google Scholar]
  13. Lipkin WI. 13.  2015. A vision for investigating the microbiology of health and disease. J. Infect. Dis. 212:Suppl. 126–30 [Google Scholar]
  14. Mohn KG-I, Brokstad KA, Pathirana RD, Bredholt G, Jul-Larsen Å. 14.  et al. 2016. Live attenuated influenza vaccine in children induces B-cell responses in tonsils. J. Infect. Dis. 214:5722–31 [Google Scholar]
  15. Mestas J, Hughes CCW. 15.  2004. Of mice and not men: differences between mouse and human immunology. J. Immunol. 172:52731–38 [Google Scholar]
  16. Han A, Glanville J, Hansmann L, Davis MM. 16.  2014. Linking T-cell receptor sequence to functional phenotype at the single-cell level. Nat. Biotechnol. 32:7684–92. Corrigendum. 2015. Nat. Biotechnol. 33:210 [Google Scholar]
  17. Carlson CS, Emerson RO, Sherwood AM, Desmarais C, Chung M-W. 17.  et al. 2013. Using synthetic templates to design an unbiased multiplex PCR assay. Nat. Commun. 4:ncomms3680 [Google Scholar]
  18. Stubbington MJT, Lönnberg T, Proserpio V, Clare S, Speak AO. 18.  et al. 2016. T cell fate and clonality inference from single-cell transcriptomes. Nat. Methods 13:4329–32 [Google Scholar]
  19. Glanville J, Huang H, Nau A, Hatton O, Wagar LE. 19.  et al. 2017. Identifying specificity groups in the T cell receptor repertoire. Nature 547:766194–98 [Google Scholar]
  20. Dash P, Fiore-Gartland AJ, Hertz T, Wang GC, Sharma S. 20.  et al. 2017. Quantifiable predictive features define epitope-specific T cell receptor repertoires. Nature 547:766189–93 [Google Scholar]
  21. Davis MM, Bjorkman PJ. 21.  1988. T-cell antigen receptor genes and T-cell recognition. Nature 334:6181395–402 [Google Scholar]
  22. Rudolph MG, Wilson IA. 22.  2002. The specificity of TCR/pMHC interaction. Curr. Opin. Immunol. 14:152–65 [Google Scholar]
  23. Lindestam Arlehamn CS, McKinney DM, Carpenter C, Paul S, Rozot V. 23.  et al. 2016. A quantitative analysis of complexity of human pathogen-specific CD4 T cell responses in healthy M. tuberculosis infected South Africans. PLOS Pathog 12:7e1005760 [Google Scholar]
  24. Chen DS, Mellman I. 24.  2017. Elements of cancer immunity and the cancer-immune set point. Nature 541:7637321–30 [Google Scholar]
  25. Birnbaum ME, Mendoza JL, Sethi DK, Dong S, Glanville J. 25.  et al. 2014. Deconstructing the peptide-MHC specificity of T cell recognition. Cell 157:51073–87 [Google Scholar]
  26. Gee MH, Han A, Lofgren SM, Beausang JF, Mendoza JL. 26.  et al. 2017. Antigen identification for orphan T cell receptors expressed on tumor-infiltrating lymphocytes. Cell 172:549–63 [Google Scholar]
  27. Andres-Terre M, McGuire HM, Pouliot Y, Bongen E, Sweeney TE. 27.  et al. 2015. Integrated, multi-cohort analysis identifies conserved transcriptional signatures across multiple respiratory viruses. Immunity 43:61199–211 [Google Scholar]
  28. Sweeney TE, Braviak L, Tato CM, Khatri P. 28.  2016. Genome-wide expression for diagnosis of pulmonary tuberculosis: a multicohort analysis. Lancet Respir. Med. 4:3213–24 [Google Scholar]
  29. Khatri P, Roedder S, Kimura N, De Vusser K, Morgan AA. 29.  et al. 2013. A common rejection module (CRM) for acute rejection across multiple organs identifies novel therapeutics for organ transplantation. J. Exp. Med. 210:112205–21 [Google Scholar]
  30. Sweeney TE, Shidham A, Wong HR, Khatri P. 30.  2015. A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set. Sci. Transl. Med. 7:287287ra71 [Google Scholar]
  31. Sparks R, Lau WW, Tsang JS. 31.  2016. Expanding the immunology toolbox: embracing public-data reuse and crowdsourcing. Immunity 45:61191–204 [Google Scholar]
  32. Bhattacharya S, Andorf S, Gomes L, Dunn P, Schaefer H. 32.  et al. 2014. ImmPort: disseminating data to the public for the future of immunology. Immunol. Res. 58:2–3234–39 [Google Scholar]
  33. Brusic V, Gottardo R, Kleinstein SH, Davis MM, HIPC. 33. Steer. Comm. 2014. Computational resources for high-dimensional immune analysis from the Human Immunology Project Consortium. Nat. Biotechnol. 32:2146–48 [Google Scholar]
  34. Carpenter DJ, Granot T, Matsuoka N, Senda T, Kumar BV. 34.  et al. 2018. Human immunology studies using organ donors: impact of clinical variations on immune parameters in tissues and circulation. Am. J. Transplant. 18:74–88 [Google Scholar]
  35. McCune JM, Namikawa R, Kaneshima H, Shultz LD, Lieberman M, Weissman IL. 35.  1988. The SCID-hu mouse: murine model for the analysis of human hematolymphoid differentiation and function. Science 241:48731632–39 [Google Scholar]
  36. Legrand N, Ploss A, Balling R, Becker PD, Borsotti C. 36.  et al. 2009. Humanized mice for modeling human infectious disease: challenges, progress, and outlook. Cell Host Microbe 6:15–9 [Google Scholar]
  37. Rongvaux A, Willinger T, Martinek J, Strowig T, Gearty SV. 37.  et al. 2014. Development and function of human innate immune cells in a humanized mouse model. Nat. Biotechnol. 32:4364–72 [Google Scholar]
  38. Yu H, Borsotti C, Schickel J-N, Zhu S, Strowig T. 38.  et al. 2017. A novel humanized mouse model with significant improvement of class-switched, antigen-specific antibody production. Blood 129:8959–69 [Google Scholar]
  39. Philip VM, Sokoloff G, Ackert-Bicknell CL, Striz M, Branstetter L. 39.  et al. 2011. Genetic analysis in the Collaborative Cross breeding population. Genome Res 21:81223–38 [Google Scholar]
  40. Civelek M, Lusis AJ. 40.  2014. Systems genetics approaches to understand complex traits. Nat. Rev. Genet. 15:134–48 [Google Scholar]
  41. Beura LK, Hamilton SE, Bi K, Schenkel JM, Odumade OA. 41.  et al. 2016. Normalizing the environment recapitulates adult human immune traits in laboratory mice. Nature 532:7600512–16 [Google Scholar]
  42. Carr EJ, Dooley J, Garcia-Perez JE, Lagou V, Lee JC. 42.  et al. 2016. The cellular composition of the human immune system is shaped by age and cohabitation. Nat. Immunol. 17:4461–68 [Google Scholar]
  43. Tsang JS, Schwartzberg PL, Kotliarov Y, Biancotto A, Xie Z. 43.  et al. 2014. Global analyses of human immune variation reveal baseline predictors of postvaccination responses. Cell 157:2499–513 [Google Scholar]
  44. Shen-Orr SS, Furman D, Kidd BA, Hadad F, Lovelace P. 44.  et al. 2016. Defective signaling in the JAK-STAT pathway tracks with chronic inflammation and cardiovascular risk in aging humans. Cell Syst 3:4374–84 [Google Scholar]
  45. Querec TD, Akondy RS, Lee EK, Cao W, Nakaya HI. 45.  et al. 2009. Systems biology approach predicts immunogenicity of the yellow fever vaccine in humans. Nat. Immunol. 10:1116–25 [Google Scholar]
  46. Nakaya HI, Wrammert J, Lee EK, Racioppi L, Marie-Kunze S. 46.  et al. 2011. Systems biology of vaccination for seasonal influenza in humans. Nat. Immunol. 12:8786–95 [Google Scholar]
  47. Furman D, Jojic V, Kidd B, Shen-Orr S, Price J. 47.  et al. 2013. Apoptosis and other immune biomarkers predict influenza vaccine responsiveness. Mol. Syst. Biol. 9:1659–59 [Google Scholar]
  48. Sobolev O, Binda E, O'Farrell S, Lorenc A, Pradines J. 48.  et al. 2016. Adjuvanted influenza-H1N1 vaccination reveals lymphoid signatures of age-dependent early responses and of clinical adverse events. Nat. Immunol. 17:2204–13 [Google Scholar]
  49. Nakaya HI, Hagan T, Duraisingham SS, Lee EK, Kwissa M. 49.  et al. 2015. Systems analysis of immunity to influenza vaccination across multiple years and in diverse populations reveals shared molecular signatures. Immunity 43:61186–98 [Google Scholar]
  50. Oh JZ, Ravindran R, Chassaing B, Carvalho FA, Maddur MS. 50.  et al. 2014. TLR5-mediated sensing of gut microbiota is necessary for antibody responses to seasonal influenza vaccination. Immunity 41:3478–92 [Google Scholar]
  51. Ravindran R, Khan N, Nakaya HI, Li S, Loebbermann J. 51.  et al. 2014. Vaccine activation of the nutrient sensor GCN2 in dendritic cells enhances antigen presentation. Science 343:6168313–17 [Google Scholar]
  52. Kaczorowski KJ, Shekhar K, Nkulikiyimfura D, Dekker CL, Maecker H. 52.  et al. 2017. Continuous immunotypes describe human immune variation and predict diverse responses. PNAS 17:201705065 [Google Scholar]
  53. Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E. 53.  et al. 2016. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536:7616285–91 [Google Scholar]
  54. Cetani F, Barbesino G, Borsari S, Pardi E, Cianferotti L. 54.  et al. 2001. A novel mutation of the autoimmune regulator gene in an Italian kindred with autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy, acting in a dominant fashion and strongly cosegregating with hypothyroid autoimmune thyroiditis. J. Clin. Endocrinol. Metab. 86:104747–52 [Google Scholar]
  55. Oftedal BE, Hellesen A, Erichsen MM, Bratland E, Vardi A. 55.  et al. 2015. Dominant mutations in the autoimmune regulator AIRE are associated with common organ-specific autoimmune diseases. Immunity 42:61185–96 [Google Scholar]
  56. Kuehn HS, Ouyang W, Lo B, Deenick EK, Niemela JE. 56.  et al. 2014. Immune dysregulation in human subjects with heterozygous germline mutations in CTLA4. . Science 345:62041623–27 [Google Scholar]
  57. Brodin P, Jojic V, Gao T, Bhattacharya S, Angel CJL. 57.  et al. 2015. Variation in the human immune system is largely driven by non-heritable influences. Cell 160:1–237–47 [Google Scholar]
  58. Roederer M, Quaye L, Mangino M, Beddall MH, Mahnke Y. 58.  et al. 2015. The genetic architecture of the human immune system: a bioresource for autoimmunity and disease pathogenesis. Cell 161:2387–403 [Google Scholar]
  59. Orrù V, Steri M, Sole G, Sidore C, Virdis F. 59.  et al. 2013. Genetic variants regulating immune cell levels in health and disease. Cell 155:1242–56 [Google Scholar]
  60. Mangino M, Roederer M, Beddall MH, Nestle FO, Spector TD. 60.  2017. Innate and adaptive immune traits are differentially affected by genetic and environmental factors. Nat. Commun. 8:13850 [Google Scholar]
  61. Evans DM, Frazer IH, Martin NG. 61.  1999. Genetic and environmental causes of variation in basal levels of blood cells. Twin Res 2:4250–57 [Google Scholar]
  62. Höhler T, Reuss E, Evers N, Dietrich E, Rittner C. 62.  et al. 2002. Differential genetic determination of immune responsiveness to hepatitis B surface antigen and to hepatitis A virus: a vaccination study in twins. Lancet 360:9338991–95 [Google Scholar]
  63. Yan K, Cai W, Cao F, Sun H, Chen S. 63.  et al. 2013. Genetic effects have a dominant role on poor responses to infant vaccination to hepatitis B virus. J. Hum. Genet. 58:5293–97 [Google Scholar]
  64. Sylwester AW, Mitchell BL, Edgar JB, Taormina C, Pelte C. 64.  et al. 2005. Broadly targeted human cytomegalovirus-specific CD4+ and CD8+ T cells dominate the memory compartments of exposed subjects. J. Exp. Med. 202:5673–85 [Google Scholar]
  65. Sansoni P, Vescovini R, Fagnoni FF, Akbar A, Arens R. 65.  et al. 2014. New advances in CMV and immunosenescence. Exp. Gerontol. 55:54–62 [Google Scholar]
  66. Furman D, Jojic V, Sharma S, Shen-Orr SS, Angel CJL. 66.  et al. 2015. Cytomegalovirus infection enhances the immune response to influenza. Sci. Transl. Med. 7:281281ra43 [Google Scholar]
  67. Hansen SG, Sacha JB, Hughes CM, Ford JC, Burwitz BJ. 67.  et al. 2013. Cytomegalovirus vectors violate CD8+ T cell epitope recognition paradigms. Science 340:61351237874 [Google Scholar]
  68. Strachan DP. 68.  1989. Hay fever, hygiene, and household size. BMJ 299:67101259–60 [Google Scholar]
  69. Arnold IC, Dehzad N, Reuter S, Martin H, Becher B. 69.  et al. 2011. Helicobacter pylori infection prevents allergic asthma in mouse models through the induction of regulatory T cells. J. Clin. Investig. 121:83088–93 [Google Scholar]
  70. Russell SL, Gold MJ, Willing BP, Thorson L, McNagny KM, Finlay BB. 70.  2013. Perinatal antibiotic treatment affects murine microbiota, immune responses and allergic asthma. Gut Microbes 4:2158–64 [Google Scholar]
  71. Arrieta M-C, Stiemsma LT, Dimitriu PA, Thorson L, Russell S. 71.  et al. 2015. Early infancy microbial and metabolic alterations affect risk of childhood asthma. Sci. Transl. Med. 7:307307ra152 [Google Scholar]
  72. Barreiro LB, Quintana-Murci L. 72.  2010. From evolutionary genetics to human immunology: how selection shapes host defence genes. Nat. Rev. Genet. 11:117–30 [Google Scholar]
  73. Laayouni H, Oosting M, Luisi P, Ioana M, Alonso S. 73.  et al. 2014. Convergent evolution in European and Roma populations reveals pressure exerted by plague on Toll-like receptors. PNAS 111:72668–73 [Google Scholar]
  74. Abi-Rached L, Jobin MJ, Kulkarni S, McWhinnie A, Dalva K. 74.  et al. 2011. The shaping of modern human immune systems by multiregional admixture with archaic humans. Science 334:605289–94 [Google Scholar]
  75. Deschamps M, Laval G, Fagny M, Itan Y, Abel L. 75.  et al. 2016. Genomic signatures of selective pressures and introgression from archaic hominins at human innate immunity genes. Am. J. Hum. Genet 98:15–21 [Google Scholar]
  76. Burnet FM. 76.  1959. The Clonal Selection Theory of Acquired Immunity Nashville, TN: Vanderbilt Univ. Press [Google Scholar]
  77. Nossal GJ. 77.  1983. Cellular mechanisms of immunologic tolerance. Annu. Rev. Immunol. 1:33–62 [Google Scholar]
  78. Kappler JW, Roehm N, Marrack P. 78.  1987. T cell tolerance by clonal elimination in the thymus. Cell 49:2273–80 [Google Scholar]
  79. Frankel WN, Rudy C, Coffin JM, Huber BT. 79.  1991. Linkage of Mls genes to endogenous mammary tumour viruses of inbred mice. Nature 349:6309526–28 [Google Scholar]
  80. Woodland DL, Happ MP, Gollob KJ, Palmer E. 80.  1991. An endogenous retrovirus mediating deletion of αβ T cells?. Nature 349:6309529–30 [Google Scholar]
  81. Dyson PJ, Knight AM, Fairchild S, Simpson E, Tomonari K. 81.  1991. Genes encoding ligands for deletion of Vβ11 T cells cosegregate with mammary tumour virus genomes. Nature 349:6309531–32 [Google Scholar]
  82. Marrack P, Kushnir E, Kappler J. 82.  1991. A maternally inherited superantigen encoded by a mammary tumour virus. Nature 349:6309524–26 [Google Scholar]
  83. Herman A, Kappler JW, Marrack P, Pullen AM. 83.  1991. Superantigens: mechanism of T-cell stimulation and role in immune responses. Annu. Rev. Immunol. 9:745–72 [Google Scholar]
  84. von Boehmer H. 84.  1990. Developmental biology of T cells in T cell–receptor transgenic mice. Annu. Rev. Immunol. 8:531–56 [Google Scholar]
  85. Altman JD, Moss PA, Goulder PJ, Barouch DH, McHeyzer-Williams MG. 85.  et al. 1996. Phenotypic analysis of antigen-specific T lymphocytes. Science 274:528494–96 [Google Scholar]
  86. Toebes M, Coccoris M, Bins A, Rodenko B, Gomez R. 86.  et al. 2006. Design and use of conditional MHC class I ligands. Nat. Med. 12:2246–51 [Google Scholar]
  87. Moon JJ, Chu HH, Pepper M, McSorley SJ, Jameson SC. 87.  et al. 2007. Naive CD4+ T cell frequency varies for different epitopes and predicts repertoire diversity and response magnitude. Immunity 27:2203–13 [Google Scholar]
  88. Yu W, Jiang N, Ebert PJR, Kidd BA, Müller S. 88.  et al. 2015. Clonal deletion prunes but does not eliminate self-specific αβ CD8+ T lymphocytes. Immunity 42:5929–41 [Google Scholar]
  89. Legoux FP, Lim J-B, Cauley AW, Dikiy S, Ertelt J. 89.  et al. 2015. CD4+ T cell tolerance to tissue-restricted self antigens is mediated by antigen-specific regulatory T cells rather than deletion. Immunity 43:5896–908 [Google Scholar]
  90. Su LF, Kidd BA, Han A, Kotzin JJ, Davis MM. 90.  2013. Virus-specific CD4+ memory-phenotype T cells are abundant in unexposed adults. Immunity 38:2373–83 [Google Scholar]
  91. Akue AD, Lee J-Y, Jameson SC. 91.  2012. Derivation and maintenance of virtual memory CD8 T cells. J. Immunol. 188:62516–23 [Google Scholar]
  92. Selin LK, Varga SM, Wong IC, Welsh RM. 92.  1998. Protective heterologous antiviral immunity and enhanced immunopathogenesis mediated by memory T cell populations. J. Exp. Med. 188:91705–15 [Google Scholar]
  93. Mason D. 93.  1998. A very high level of crossreactivity is an essential feature of the T-cell receptor. Immunol. Today 19:9395–404 [Google Scholar]
  94. Ebert PJR, Jiang S, Xie J, Li Q-J, Davis MM. 94.  2009. An endogenous positively selecting peptide enhances mature T cell responses and becomes an autoantigen in the absence of microRNA miR-181a. Nat. Immunol. 10:111162–69 [Google Scholar]
  95. Lo W-L, Felix NJ, Walters JJ, Rohrs H, Gross ML, Allen PM. 95.  2009. An endogenous peptide positively selects and augments the activation and survival of peripheral CD4+ T cells. Nat. Immunol. 10:111155–61 [Google Scholar]
  96. Kuhn TS. 96.  1970. The Structure of Scientific Revolutions Chicago: Univ. Chicago Press [Google Scholar]

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error