Key Points
-
Human immune system composition and function are highly variable between healthy individuals, but they are relatively stable over time within a given individual.
-
Human immune systems vary as a consequence of heritable and non-heritable influences, but non-heritable influences explain most of the variation.
-
Understanding the specific factors that shape an individual's immune system is key for understanding immune competence and risk of immune-mediated and infectious diseases.
Abstract
The human immune system is highly variable between individuals but relatively stable over time within a given person. Recent conceptual and technological advances have enabled systems immunology analyses, which reveal the composition of immune cells and proteins in populations of healthy individuals. The range of variation and some specific influences that shape an individual's immune system is now becoming clearer. Human immune systems vary as a consequence of heritable and non-heritable influences, but symbiotic and pathogenic microbes and other non-heritable influences explain most of this variation. Understanding when and how such influences shape the human immune system is key for defining metrics of immunological health and understanding the risk of immune-mediated and infectious diseases.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Herrath, von, M. G. & Nepom, G. T. Lost in translation: barriers to implementing clinical immunotherapeutics for autoimmunity. J. Exp. Med. 202, 1159–1162 (2005).
Steinman, R. M. & Mellman, I. Immunotherapy: bewitched, bothered, and bewildered no more. Science 305, 197–200 (2004).
Davis, M. M. A. Prescription for human immunology. Immunity 29, 835–838 (2008).
Germain, R. N. & Schwartzberg, P. L. The human condition: an immunological perspective. Nat. Immunol. 12, 369–372 (2011).
Hayday, A. C. & Peakman, M. The habitual, diverse and surmountable obstacles to human immunology research. Nat. Immunol. 9, 575–580 (2008).
Hagan, T., Nakaya, H. I., Subramaniam, S. & Pulendran, B. Systems vaccinology: enabling rational vaccine design with systems biological approaches. Vaccine 33, 5294–5301 (2015).
Wrammert, J. et al. Rapid cloning of high-affinity human monoclonal antibodies against influenza virus. Nature 453, 667–671 (2008).
Han, A. et al. Dietary gluten triggers concomitant activation of CD4+ and CD8+ αβ T cells and γδ T cells in celiac disease. Proc. Natl Acad. Sci. USA 110, 13073–13078 (2013).
Ráki, M. et al. Tetramer visualization of gut-homing gluten-specific T cells in the peripheral blood of celiac disease patients. Proc. Natl Acad. Sci. USA 104, 2831–2836 (2007).
Brodin, P. Powerful populations respond to viruses and vaccines. Immunity 43, 1035–1037 (2015).
Brodin, P. et al. Variation in the human immune system is largely driven by non-heritable influences. Cell 160, 37–47 (2015). This systems immunology analysis of healthy human twins revealed that non-heritable influences mainly shape human immune systems and that the influence of heritable factors is limited in most cases. This influence is cumulative over the course of life, which leads to the divergence of the immune systems of monozygotic twin with time.
Querec, T. D. et al. Systems biology approach predicts immunogenicity of the yellow fever vaccine in humans. Nat. Immunol. 10, 116–125 (2008). A pioneering systems vaccinology study that revealed novel gene expression signatures, which indicated previously unappreciated pathways activated by vaccination.
Andres-Terre, M. et al. Integrated, multi-cohort analysis identifies conserved transcriptional signatures across multiple respiratory viruses. Immunity 43, 1199–1211 (2015).
Sobolev, O. et al. Adjuvanted influenza-H1N1 vaccination reveals lymphoid signatures of age-dependent early responses and of clinical adverse events. Nat. Immunol. 17, 204–213 (2016).
Tsang, J. S. et al. Global analyses of human immune variation reveal baseline predictors of postvaccination responses. Cell 157, 499–513 (2014).
Carr, E. J. et al. The cellular composition of the human immune system is shaped by age and cohabitation. Nat. Immunol. 17, 461–468 (2016). This study revealed a strong effect of co-habitation on immune system variation, emphasizing the importance of shared environmental factors.
Shen-Orr, S. S. et al. Defective signaling in the JAK-STAT pathway tracks with chronic inflammation and cardiovascular risk in aging humans. Cell Syst. 3, 374–384.e4 (2016).
Dowling, D. J. & Levy, O. Ontogeny of early life immunity. Trends Immunol. 35, 299–310 (2014).
Simon, A. K., Hollander, G. A. & McMichael, A. Evolution of the immune system in humans from infancy to old age. Proc. Biol. Sci. 282, 20143085 (2015).
Gibbons, D. L. et al. Neonates harbour highly active gammadelta T cells with selective impairments in preterm infants. Eur. J. Immunol. 39, 1794–1806 (2009).
Gibbons, D. et al. Interleukin-8 (CXCL8) production is a signatory T cell effector function of human newborn infants. Nat. Med. 20, 1206–1210 (2014).
Amenyogbe, N., Levy, O. & Kollmann, T. R. Systems vaccinology: a promise for the young and the poor. Phil. Trans. R. Soc. B, Biol. Sci. 370, 20140340 (2015).
Jiang, N. et al. Lineage structure of the human antibody repertoire in response to influenza vaccination. Sci. Transl. Med. 5, 171ra19 (2013).
Goronzy, J. J. & Weyand, C. M. Aging, autoimmunity and arthritis: T-cell senescence and contraction of T-cell repertoire diversity - catalysts of autoimmunity and chronic inflammation. Arthritis Res. Ther. 5, 225–234 (2003).
Qi, Q. et al. Diversity and clonal selection in the human T-cell repertoire. Proc. Natl Acad. Sci. USA 111, 13139–13144 (2014).
Michaud, M. et al. Proinflammatory cytokines, aging, and age-related diseases. J. Am. Med. Dir. Assoc. 14, 877–882 (2013).
Enroth, S., Johansson, Å., Enroth, S. B. & Gyllensten, U. Strong effects of genetic and lifestyle factors on biomarker variation and use of personalized cutoffs. Nat. Commun. 5, 4684 (2014).
Furman, D. et al. Apoptosis and other immune biomarkers predict influenza vaccine responsiveness. Mol. Syst. Biol. 9, 659–659 (2013).
Nakaya, H. I. et al. Systems analysis of immunity to influenza vaccination across multiple years and in diverse populations reveals shared molecular signatures. Immunity 43, 1186–1198 (2015).
Moltchanova, E. V., Schreier, N., Lammi, N. & Karvonen, M. Seasonal variation of diagnosis of Type 1 diabetes mellitus in children worldwide. Diabet. Med. 26, 673–678 (2009).
Iikuni, N. et al. What's in season for rheumatoid arthritis patients? Seasonal fluctuations in disease activity. Rheumatology 46, 846–848 (2007).
De Jong, S. et al. Seasonal changes in gene expression represent cell-type composition in whole blood. Hum. Mol. Genet. 23, 2721–2728 (2014).
Dopico, X. C. et al. Widespread seasonal gene expression reveals annual differences in human immunity and physiology. Nat. Commun. 6, 7000 (2015).
Straub, R. H. & Cutolo, M. Circadian rhythms in rheumatoid arthritis: implications for pathophysiology and therapeutic management. Arthritis Rheum. 56, 399–408 (2007).
Cutolo, M. & Straub, R. H. Circadian rhythms in arthritis: hormonal effects on the immune/inflammatory reaction. Autoimmun Rev. 7, 223–228 (2008).
Curtis, A. M., Bellet, M. M., Sassone-Corsi, P. & O'Neill, L. A. J. Circadian clock proteins and immunity. Immunity 40, 178–186 (2014).
Spitzer, M. H. & Nolan, G. P. Mass cytometry: single cells, many features. Cell 165, 780–791 (2016).
Lundberg, M., Eriksson, A., Tran, B., Assarsson, E. & Fredriksson, S. Homogeneous antibody-based proximity extension assays provide sensitive and specific detection of low-abundant proteins in human blood. Nucleic Acids Res. 39, e102 (2011).
Christiansson, L. et al. The use of multiplex platforms for absolute and relative protein quantification of clinical material. EuPA Open Proteom. 3, 37–47 (2014).
Roederer, M. et al. The genetic architecture of the human immune system: a bioresource for autoimmunity and disease pathogenesis. Cell 161, 387–403 (2015).
Banchereau, R. et al. Personalized immunomonitoring uncovers molecular networks that stratify lupus patients. Cell 165, 551–565 (2016).
Whitacre, C. C. Sex differences in autoimmune disease. Nat. Immunol. 2, 777–780 (2001).
Lee, W. et al. Are there gender differences in severity of ankylosing spondylitis? Results from the PSOAS cohort. Ann. Rheum. Dis. 66, 633–638 (2007).
Whitney, A. R. et al. Individuality and variation in gene expression patterns in human blood. Proc. Natl Acad. Sci. USA 100, 1896–1901 (2003).
Cutolo, M. et al. Sex hormones influence on the immune system: basic and clinical aspects in autoimmunity. Lupus 13, 635–638 (2004).
Furman, D. et al. Systems analysis of sex differences reveals an immunosuppressive role for testosterone in the response to influenza vaccination. Proc. Natl Acad. Sci. USA 111, 869–874 (2014).
Bhattacharya, S. et al. ImmPort: disseminating data to the public for the future of immunology. Immunol. Res. 58, 234–239 (2014).
Sørensen, T. I., Nielsen, G. G., Andersen, P. K. & Teasdale, T. W. Genetic and environmental influences on premature death in adult adoptees. N. Engl. J. Med. 318, 727–732 (1988).
Casanova, J.-L. & Abel, L. The human model: a genetic dissection of immunity to infection in natural conditions. Nat. Rev. Immunol. 4, 55–66 (2004).
Alcaïs, A. et al. Life-threatening infectious diseases of childhood: single-gene inborn errors of immunity? Ann. NY Acad. Sci. 1214, 18–33 (2010).
Kochi, Y. Genetics of autoimmune diseases: perspectives from genome-wide association studies. Int. Immunol. 28, 155–161 (2016).
Gregersen, P. K. & Olsson, L. M. Recent advances in the genetics of autoimmune disease. Annu. Rev. Immunol. 27, 363–391 (2009).
Pilia, G. et al. Heritability of Cardiovascular and Personality Traits in 6,148 Sardinians. PLoS Genet. 2, e132 (2006).
Nalls, M. A. et al. Multiple loci are associated with white blood cell phenotypes. PLoS Genet. 7, e1002113 (2011).
Garner, C. P. et al. Replication of celiac disease UK genome-wide association study results in a US population. Hum. Mol. Genet. 18, 4219–4225 (2009).
Orrù, V. et al. Genetic variants regulating immune cell levels in health and disease. Cell 155, 242–256 (2013).
Pascual, V., Farkas, L. & Banchereau, J. Systemic lupus erythematosus: all roads lead to type I interferons. Curr. Opin. Immunol. 18, 676–682 (2006).
Kariuki, S. N. & Niewold, T. B. Genetic regulation of serum cytokines in systemic lupus erythematosus. Translat. Res. 155, 109–117 (2010).
Baechler, E. C. et al. Interferon-inducible gene expression signature in peripheral blood cells of patients with severe lupus. Proc. Natl Acad. Sci. USA 100, 2610–2615 (2003).
Niewold, T. B., Hua, J., Lehman, T. J. A., Harley, J. B. & Crow, M. K. High serum IFN-α activity is a heritable risk factor for systemic lupus erythematosus. Genes Immun. 8, 492–502 (2007).
Matteini, A. M. et al. Novel gene variants predict serum levels of the cytokines IL-18 and IL-1ra in older adults. Cytokine 65, 10–16 (2014).
Ollier, W. E. R. Cytokine genes and disease susceptibility. Cytokine 28, 174–178 (2004).
De Jager, P. L. et al. ImmVar project: insights and design considerations for future studies of 'healthy' immune variation. Semin. Immunol. 27, 51–57 (2015).
Price, A. L. et al. Single-tissue and cross-tissue heritability of gene expression via identity-by-descent in related or unrelated individuals. PLoS Genet. 7, e1001317 (2011).
Gao, T., Brodin, P., Davis, M. M. & Jojic, V. Drug-induced mRNA signatures are enriched for the minority of genes that are highly heritable. Pac. Symp. Biocomput. 395–406 (2015).
Lee, M. N. et al. Common genetic variants modulate pathogen-sensing responses in human dendritic cells. Science 343, 1246980 (2014).
Ye, C. J. et al. Intersection of population variation and autoimmunity genetics in human T cell activation. Science 345, 1254665 (2014).
Grossman, Z. & Paul, W. E. Adaptive cellular interactions in the immune system: the tunable activation threshold and the significance of subthreshold responses. Proc. Natl Acad. Sci. USA 89, 10365–10369 (1992).
Brodin, P., Kärre, K. & Höglund, P. NK cell education: not an on-off switch but a tunable rheostat. Trends Immunol. 30, 143–149 (2009).
Fraga, M. F. et al. Epigenetic differences arise during the lifetime of monozygotic twins. Proc. Natl Acad. Sci. USA 102, 10604–10609 (2005).
Birney, E., Smith, G. D. & Greally, J. M. Epigenome-wide association studies and the interpretation of disease-omics. PLoS Genet. 12, e1006105 (2016).
Gensollen, T., Iyer, S. S., Kasper, D. L. & Blumberg, R. S. How colonization by microbiota in early life shapes the immune system. Science 352, 539–544 (2016).
Chung, H. et al. Gut immune maturation depends on colonization with a host-specific microbiota. Cell 149, 1578–1593 (2012).
Beura, L. K. et al. Normalizing the environment recapitulates adult human immune traits in laboratory mice. Nature 532, 512–516 (2016).
Reese, T. A. et al. Sequential infection with common pathogens promotes human-like immune gene expression and altered vaccine response. Cell Host Microbe 19, 713–719 (2016).
Strachan, D. P. Hay fever, hygiene, and household size. BMJ 299, 1259–1260 (1989). The original paper proposing the hygiene hypothesis.
Bach, J.-F. The effect of infections on susceptibility to autoimmune and allergic diseases. N. Engl. J. Med. 347, 911–920 (2002).
Braun-Fahrländer, C. et al. Environmental exposure to endotoxin and its relation to asthma in school-age children. N. Engl. J. Med. 347, 869–877 (2002).
Vatanen, T. et al. Variation in microbiome LPS immunogenicity contributes to autoimmunity in humans. Cell 165, 842–853 (2016).
Arrieta, M.-C. et al. Early infancy microbial and metabolic alterations affect risk of childhood asthma. Sci. Transl. Med. 7, 307ra152 (2015).
Dalal, S. R. & Chang, E. B. The microbial basis of inflammatory bowel diseases. J. Clin. Invest. 124, 4190–4196 (2014).
Jenq, R. R. et al. Regulation of intestinal inflammation by microbiota following allogeneic bone marrow transplantation. J. Exp. Med. 209, 903–911 (2012).
Oh, J. Z. et al. TLR5-mediated sensing of gut microbiota Is necessary for antibody responses to seasonal influenza vaccination. Immunity 41, 478–492 (2014).
Viaud, S. et al. The intestinal microbiota modulates the anticancer immune effects of cyclophosphamide. Science 342, 971–976 (2013).
Vétizou, M. et al. Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science 350, 1079–1084 (2015).
Sivan, A. et al. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science 350, 1084–1089 (2015).
Xu, G. J. et al. Viral immunology. Comprehensive serological profiling of human populations using a synthetic human virome. Science 348, aaa0698 (2015).
Sylwester, A. W. et al. Broadly targeted human cytomegalovirus-specific CD4+ and CD8+ T cells dominate the memory compartments of exposed subjects. J. Exp. Med. 202, 673–685 (2005).
Rölle, A. & Brodin, P. Immune adaptation to environmental influence: the case of NK cells and HCMV. Trends Immunol. 37, 233–243 (2016).
Furman, D. et al. Cytomegalovirus infection enhances the immune response to influenza. Sci Transl Med 7, 281ra43 (2015).
Virgin, H. W. The virome in mammalian physiology and disease. Cell 157, 142–150 (2014).
De Vlaminck, I. et al. Temporal response of the human virome to immunosuppression and antiviral therapy. Cell 155, 1178–1187 (2013).
Sopori, M. Effects of cigarette smoke on the immune system. Nat. Rev. Immunol. 2, 372–377 (2002).
Higuchi, T. et al. Current cigarette smoking is a reversible cause of elevated white blood cell count: cross-sectional and longitudinal studies. Prev. Med. Rep. 4, 417–422 (2016).
Ferson, M., Edwards, A., Lind, A., Milton, G. W. & Hersey, P. Low natural killer-cell activity and immunoglobulin levels associated with smoking in human subjects. Int. J. Cancer 23, 603–609 (1979).
Mathews, J. D., Whittingham, S., Hooper, B. M., Mackay, I. R. & Stenhouse, N. S. Association of autoantibodies with smoking, cardiovascular morbidity, and death in the Busselton population. Lancet 2, 754–758 (1973).
Padyukov, L. et al. A gene-environment interaction between smoking and shared epitope genes in HLA-DR provides a high risk of seropositive rheumatoid arthritis. Arthritis Rheum. 50, 3085–3092 (2004).
Chattopadhyay, P. K. & Roederer, M. A mine is a terrible thing to waste: high content, single cell technologies for comprehensive immune analysis. Am. J. Transplant. 15, 1155–1161 (2015).
Bandura, D. R. et al. Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Anal. Chem. 81, 6813–6822 (2009).
Frei, A. P. et al. Highly multiplexed simultaneous detection of RNAs and proteins in single cells. Nat. Methods 13, 269–275 (2016).
Newell, E. W., Sigal, N., Bendall, S. C., Nolan, G. P. & Davis, M. M. Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes. Immunity 36, 142–152 (2012).
Bodenmiller, B. et al. Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators. Nat. Biotechnol. 30, 858–867 (2012).
Bendall, S. C. et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332, 687–696 (2011).
Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).
Han, A., Glanville, J., Hansmann, L. & Davis, M. M. Linking T-cell receptor sequence to functional phenotype at the single-cell level. Nat. Biotechnol. 32, 684–692 (2014).
Stubbington, M. J. T. et al. T cell fate and clonality inference from single-cell transcriptomes. Nat. Methods 13, 329–332 (2016).
Pernemalm, M. & Lehtiö, J. Mass spectrometry-based plasma proteomics: state of the art and future outlook. Expert Rev. Proteom. 11, 431–448 (2014).
Acknowledgements
P.B. is supported by a starting grant from the European Research Council, the Swedish Research Council, the Swedish Society for Medical Research, and Karolinska Institutet. M.M.D. is supported by NIH grants U19 AI090019, U19 AI057229 and the Howard Hughes Medical Institute.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Related links
Glossary
- Rheumatoid arthritis
-
An immunological disorder that is characterized by symmetrical polyarthritis, often progressing to crippling deformation after years of synovitis. It is associated with systemic immune activation, with acute-phase reactants being present in the peripheral blood, as well as rheumatoid factor (immunoglobulins specific for IgG), which forms immune complexes that are deposited in many tissues.
- Cortisol
-
A steroid hormone produced by the adrenal glands and released in response to stress and has a generally suppressive function on the immune system.
- Systemic lupus erythematosus
-
(SLE). An autoimmune disease in which autoantibodies that are specific for DNA, RNA or proteins associated with nucleic acids form immune complexes that damage small blood vessels, especially in the kidney. Patients with SLE generally have abnormal B cell and T cell functions.
- Sjogren syndrome
-
A long-term autoimmune disease affecting mucous membranes and moisture-secreting glands of the eyes and mouth, resulting in decreased production of tears and saliva, but there are also systemic manifestations such as muscle and joint pain and fatigue.
- Ankylosing spondylitis
-
A long-term inflammatory disease, more common in men than women, affecting the joints of the spine causing vertebrae to fuse together.
- Hygiene hypothesis
-
A hypothesis stating that the lack of early childhood exposure to infectious and symbiotic microorganisms increases the susceptibility to allergic diseases later in life, by altering the normal development of the immune system.
- Graft–versus–host disease
-
(GVHD). An immune response mediated by donor T cells contained in a transplanted allograft and directed against the recipient. GVHD is not associated with solid-organ transplantation but can occur with bone marrow or haematopoietic stem cell transplants.
Rights and permissions
About this article
Cite this article
Brodin, P., Davis, M. Human immune system variation. Nat Rev Immunol 17, 21–29 (2017). https://doi.org/10.1038/nri.2016.125
Published:
Issue Date:
DOI: https://doi.org/10.1038/nri.2016.125