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Gi$$$$014pGenes and Immunity (1999) 1, 3–19
1999 Stockton Press All rights reserved 1466-4879/99 $15.00
Cytokine gene polymorphism in human disease:
J Bidwell1, L Keen1, G Gallagher2, R Kimberly3, T Huizinga4, MF McDermott5, J Oksenberg6,J McNicholl7, F Pociot8, C Hardt9 and S D’Alfonso101Department of Pathology and Microbiology, University of Bristol, Homoeopathic Hospital Site, Cotham, Bristol BS6 6JU, UK;2University of Glasgow Department of Surgery, Queen Elizabeth Building, Glasgow Royal Infirmary, Glasgow G31 2ER, Scotland;3Division of Clinical Immunology and Rheumatology, Tinsley Harrison Tower, Room 429, University of Alabama at Birmingham,1900 University Boulevard, Birmingham, AL 35294–0006, USA; 4Leiden University Medical Center, Department of Rheumatology,C4-R, P.O. Box 9600, 2300 RC Leiden, The Netherlands; 5Medical Unit, St. Bartholomew’s and the Royal London Hospital Schoolof Medicine and Dentistry, Whitechapel, London E1 1BB, UK; 6Department of Neurology, University of California San Francisco,513 Parnassus Ave., San Francisco, CA 94143–0435, USA; 7HIV Immunology and Diagnostics Branch, Division of AIDS, NationalCenter for Infectious Diseases, Centers for Disease Control, Mailstop A25, 1600 Clifton Road NE, Atlanta, GA 30333, USA; 8StenoDiabetes Center, Niels Steensensvej 2, DK-2820 Gentofte, Denmark; 9Institut fu¨r Humangenetik, Universita¨tsklinikum Essen,Hufelandstr. 55, 45122 Essen, Germany; 10Dipartimento Scienze Mediche, Via Solaroli 17, 28100 No¨vara, Italy The pathologies of many infectious, autoimmune and malignant diseases are influenced by the profiles of cytokineproduction in pro-inflammatory (TH1) and anti-inflammatory (TH2) T cells. Interindividual differences in cytokine profilesappear to be due, at least in part, to allelic polymorphism within regulatory regions of cytokine gene. Many studies haveexamined the relationship between cytokine gene polymorphism, cytokine gene expression in vitro, and the susceptibilityto and clinical severity of diseases. A review of the findings of these studies is presented. An on-line version featuringappropriate updates is accessible from the World Wide Web site, http://www.pam.bris.ac.uk/services/GAI/cytokine4.htm.
Keywords: cytokines; gene polymorphism; gene expression
Introduction: cytokines, the cytokine
ollary that the cytokine network is highly flexible, since network and the Th1–Th2 paradigm
there is considerable overlap and redundancy betweenthe function of individual cytokines.8–12 This feature con- Cytokines are humoral immunomodulatory proteins or tinues to complicate efforts to analyse both the function glycoproteins which control or modulate the activities of of individual cyokines and the influence of cytokine gene target cells, generally those within the haematopoietic polymorphism on gene expression and disease.
system. They act on target cells by binding to specific Cytokine production by the cells of the immune system cytokine receptor ligands, initiating signal transduction may occur through antigen-specific and non-antigen spe- and second messenger pathways within the target cell.1–5 cific stimuli. For example, monocytes when exposed to This can result in gene activation, leading to mitotic bacterial cell wall products, such as lipopolysaccharide, division, growth and differentiation, migration, or produce IL-12 and other cytokines which have multiple functions including influencing the expression of cyto- Cytokines are produced by a wide range of cell types kines by other cells. Antigen-specific responses are gener- ated by B and T cells through immunoglobulin and T cell (produced by cells of the monocyte lineage) or lympho- receptors respectively. B cell activation may result in the kines (produced by lymphocytes), though this is arguably production of IL-6 and other cytokines. T cells are central an over-simplistic classification: other classifications are players in linking non-antigen specific, B cell and T cell based on functional or structural groupings.6,7 Cytokines responses together. Two classes of T cells are recognized: act in a highly complex coordinated network in which ␣,␤ and ␥,␦ T cells, defined by their T cell receptor (TCR) they induce or repress their own synthesis as well as that chain usage. The majority of circulating ␣,␤ T cells carry of other cytokines and cytokine receptors. In addition, either CD4 or CD8 molecules, which bind to MHC class many cytokines appear to be pleiotropic, with the cor- II or MHC class I molecules, respectively. The ligand of ␥,␦ T cells is not clearly known, and these cells typicallycarry neither CD4 nor CD8 molecules, hence the name‘double negative’ T cells. Functionally, CD8+ T cells, are Correspondence: Dr JL Bidwell, University of Bristol Department of Path-ology and Microbiology, Homoeopathic Hospital Site, Cotham, Bristol typically cytotoxic T cells and can kill target cells presenting processed foreign peptide via HLA class I Received 9 June 1999; accepted 21 June 1999 molecules; some CD8+ T cells secrete cytokines such as Cytokine gene polymorphism in human disease
IFN␥. CD4+ T cells are typically helper T cells, although Table 1 List of human cytokine gene polymorphisms
rare subsets have cytoxic function. Several TH subsets ofCD4+ T cells have been identified. In the mouse these subsets are well defined and include Type 1 (TH1), whichpromote cell-mediated effector responses; and Type 2 CD4+ helper T cells (TH2), which promote B cell- mediated humoral responses. Cytokines produced by TH1 cells include interleukin-2 (IL-2), interferon gamma (IFN␥) and tumour necrosis factor beta (TNF␤), and constitute a pro-inflammatory cytokine profile; those pro- duced by TH2 cells include IL-4, IL-5, IL-6, and IL-10, ie, a predominantly anti-inflammatory cytokine profile. Both TH1 and TH2 cells produce IL-3 and granulocyte-macro- phage colony stimulating factor (GM-CSF).13–20 Recently a TH3 subset (characterized by TGF␤) has been defined.
In humans, the distinction between TH1, TH2 and TH3 is less well defined, and a subset of TH0 cells, which pro- duce some cytokines typical of TH1 and TH2 profiles can be identified. The clinical outcome of many infectious, autoimmune, or malignant diseases appears to be influ- enced by the overall balance of production (profiles) of pro-inflammatory and anti-inflammatory cytokines.21–31 Hence, much interest has focused upon the regulation of genes expressing these cytokines. In particular, a signifi- cant number of studies have addressed whether genetic polymorphism within these genes might influence the levels of expression, and therefore the overall immune response. A review of the findings of these studies is Cytokine gene polymorphism: influence
on protein structure, expression and
Cytokine gene polymorphism
Non-conservative mutation within the coding region of genes can result in loss, abrogation, or change of function in the expressed protein as a result of change in protein structure. Cytokine and cytokine receptor genes are gen- erally highly conserved in terms of exon sequences,32,33 although examples of amino acid sequence variation have been found for IL-4 receptor, LT␣ (TNF␤), TGF␤ and GM-CSF receptor ␤ in healthy individuals; and in the IL-2 receptor ␥ gene for persons with severe combined immunodeficiency (Tables 1 and 3). Although conserva- tive (silent) mutations do not affect amino acid sequence, they may influence protein expression in a variety of other ways: for example, they can alter mRNA splicing, mRNA stability, and levels of gene transcription. Poly- morphisms within the 5Ј- and 3Ј-regulatory sequences or introns of genes may have a significant effect on tran- scription, since they may alter the structure of transcrip- tion factor binding sites within gene promoters or the structure of enhancers and silencers within introns or at more remote regulatory sites. Finally, they may alter binding sites within the nuclear matrix for architectural geometry.34 Many of the reported polymorphisms within cytokine genes occur within known or putative regulat- The rationale for studying cytokine gene polymor- phisms in human disease can be broadly summarised Cytokine gene polymorphism in human disease
J Bidwell et al
Table 1 Continued
Table 2 In vitro expression studies
LT␣ (TNF␤) Intron 1, NcoI RFLP (Thr26Asn) Intron 1 (CA)n repeat, allele 2 Increased • To enhance the understanding of the aetiology and To identify potential markers of susceptibility, severity, • To identify potential markers for responders vs non- • To identify targets for therapeutic intervention.
studies attempt to determine a genetic basis for interindi- To identify novel strategies to prevent disease or to vidual differences in the immune response. This is achi- improve existing preventions such as vaccines.
eved by examining the relationship between individual The influence of cytokine gene polymorphisms on gene polymorphic alleles or haplotypes of cytokine genes and expression and disease has been addressed at two levels the expression of the transcript or cytokine in vitro. The of research: studies using in vitro gene expression, and main approaches used to date include measuring the lev- those involving in vivo disease association. Only a few els of cytokine or cytokine receptor mRNA, or of cytokine studies have thus far integrated both of these approaches.
or receptor protein, expressed as a result of in vitro stimu-lation of cells in culture with a mitogen; and isolation of In vitro gene expression studies
individual alleles of gene promoters by cloning adjacent Up-regulated and/or down-regulated expression and to a reporter gene in an expression vector, followed by production of cytokine mRNA and cytokines, or of their transfection of an appropriate cell line and measurement receptors, is a feature in most immune responses in of reporter protein expression. The majority of studies to human diseases. However, this response may differ sig- date have followed the first approach. It is becoming nificantly among individuals. In vitro gene expression increasingly apparent that the results of expression stud- Cytokine gene polymorphism in human disease
Table 3 In vivo disease association studies
Early-onset pauciarticular juvenile chronic Early-onset pauciatricular juvenile chronic frequency of allele5; decreasedfrequency of allele2) Inflammatory bowel disease and ulcerative Graft-versus-host disease in allogeneic bone Rheumatoid arthritis and Felty’s syndrome IL-10 −1082A, −819C, −592C haplotype IL-10 −1082A, −819T, −592A haplotype IL-10 −1082G, −819C, −592C haplotype Grave’s disease and Grave’s ophthalmopathy Insulin-dependent diabetes mellitus, Non- insulin-dependent diabetes mellitusnephropathy Cytokine gene polymorphism in human disease
J Bidwell et al
Table 3 Continued
Early-onset pauciarticular juvenile chronic Insulin-dependent diabetes mellitus (with Insulin-dependent diabetes mellitus (DR3- Low-grade squamous intraepithelial lesions IL-1␤ −511 G→A (AvaI), IL-1␣ −889, IL-1Ra Early-onset pauciarticular juvenile chronic Severe combined immunodeficiency disease* Early-onset pauciarticular juvenile chronic Systemic-onset juvenile chronic arthritis Rheumatoid arthritis, pauciarticular juvenile rheumatoid arthritis, systemic lupuserythematosus Cytokine gene polymorphism in human disease
Table 3 Continued
TNFa, TNFb, TNFc, TNFd TNFa1b5, a2b1, a2b3, a7b4, a6 b5 Campylobacter jejuni-related Guillain-Barre Early-onset pauciarticular juvenile chronic TNFa6, b5, c1, d3, e3 Graft-versus-host disease in allogeneic bone TNF receptor-associated periodic syndromes Early-onset pauciarticular juvenile chronic Cytokine gene polymorphism in human disease
J Bidwell et al
Table 3 Continued
Early-onset pauciarticular juvenile chronic Graft-versus-host disease in allogeneic bone Systemic lupus erythematosus and nephritis TNF␣ −308 and LT␣ (TNF␤) NcoI TNF␣ −308 and LT␣ (TNF␤) NcoI TNF␣ −308 and LT␣ (TNF␤) NcoI TNF␣ −308 and LT␣ (TNF␤) NcoI TNF␣ −308 and LT␣ (TNF␤) NcoI TNF␣ −308 and LT␣ (TNF␤) NcoI TNF␣ −308 and LT␣ (TNF␤) NcoI TNF␣ −308 and LT␣ (TNF␤) NcoI TNF␣ −308 and LT␣ (TNF␤) NcoI TNF␣ −308 and LT␣ (TNF␤) NcoI Cytokine gene polymorphism in human disease
Table 3 Continued
Hyperinsulinaemia in coronary artery disease Rheumatoid arthritis, pauciarticular juvenile rheumatoid arthritis, systemic lupuserythematosus, Sjo¨gren’s LT␣ (TNF␤) NcoI & EcoRI LT␣ (TNF␤) NcoI, TNFa, b, c *For other SCID-IL-2R␥ associations, information is available from the World Wide Web site: http://www.nhgri.nih.gov/DIR/LGT/SCID/IL2RGbase.html ies may be critically influenced by several factors such as ficulty in selecting from among the many candidate the cell lineage used in the assay and the therapeutic pre- possibilities, and the likely modest effect of any single conditioning or treatment of subjects prior to harvesting disease susceptibility gene. The difficulty in identifying cells for the assay. Therefore, the reader should refer to a perfectly matched control group creates an additional publications of individual studies in which apparent con- limitation, increasing the possibility that a potentially tradictions between results are evident. A review of the positive association is biologically irrelevant because of results of the principal studies is shown in Table 2.
population admixture. Furthermore, even when casesand controls are adequately matched, most study designs In vivo disease association studies
involve relatively small sample sizes which lack the stat- These studies attempt to identify immunogenetic mark- istical power to detect small or moderate gene effects.
ers for a given disease. Association is sought between Other approaches to identifying associations between specific cytokine gene polymorphisms and clinical out- complex traits and cytokine or cytokine receptor gene come by direct comparison of individual cytokine geno- polymorphism use a variety of family-based study types and the clinical features of the disease (eg, suscepti- designs. These include whole genome scanning using bility, duration and severity). The a priori involvement linkage analysis (LOD scores) and affected sib-pair (ASP) of dysregulation of a specific cytokine or receptor in the methods. With identification of specific chromosomal disease is usually, though not always, the rationale for regions, more precise localisation required the develop- selecting a cytokine or cytokine receptor gene for analy- ment of linkage disequilibrium mapping35 and trans- sis. Such data may be generated using population-based mission disequilibrium testing36,37 with the establishment or family studies in humans or using animal models, and of ancestral haplotypes among disease-associated chro- may be from analysis of secreted, cell surface or intra- cellular protein, or of cytokine mRNA. Using these and Allelic association methods based on increased trans- other clues, many studies have identified statistically sig- mission of marker alleles will need to be employed for nificant associations between cytokine alleles and disease.
the mapping of complex disease susceptibility genes.
However, in many of these studies the in vitro expression However, because the extent of association of single studies have not been attempted, or are the subject of marker alleles with disease is a function of the relative controversy, or by consensus have not indicated a con- frequency of the allele on disease-associated chromo- vincing functional rationale for the association.
somes vs non disease-predisposing chromosomes, the The genetic analysis of cytokines in human disease has most associated marker allele in a region will not neces- traditionally focused on case-control association studies, sarily be closest to the disease locus. Although this area in which the frequencies of marker alleles in groups of is controversial, the extended transmission/disequilbrium patients and healthy controls are compared, and the dif- ference is subjected to statistical analysis. The association While combined analysis of data from several studies is often expressed as the relative risk (or odds ratio) that can be pooled to increase confidence in the strength of an individual will develop the disorder if he or she car- observed associations, biases in reporting positive or ries the particular allele or marker, compared to an indi- weak associations as opposed to lack of reporting nega- vidual who does not carry the allele or marker. These tive associations also influences interpretation of pub- studies have met with only modest success in identifying disease-causing cytokine genes, in part because of the dif- One of the sometimes overlooked aspects of such dis- Cytokine gene polymorphism in human disease
J Bidwell et al
ease association studies is that the cytokine network is Related World Wide Web sites
highly complex, containing interactive cascades of geneactivation and suppression. One consequence of mutual Human cytokine gene nucleotide sequence alignments: TH1–TH2 antagonism may be the predominance of one http://www.pam.bris.ac.uk/services/cytokine2.htm or the other subset, which might directly influence the PubMed search engine, primed to search for cytokine clinical outcome of disease. Therefore, genetic polymor- phisms in cytokine genes and their receptors which regu- http://www.gla.ac.uk/Acad/FacMed/Surgery/ggtemp/ late expression should not in all cases be studied strictly in isolation. This is because individual associations maybe non-informative, whereas specific combinations of On-line Mendelian Inheritance in Man (OMIM) Web site: cytokine genotypes might predispose to disease suscepti- http://www3.ncbi.nlm.nih.gov/Omim/searchomim.html bility or outcome. Only a very few studies to date have attempted to analyse the combined contribution of morethan one cytokine gene polymorphism to disease.
In addition, other elements which can influence the A review of the results of the principal disease associ- expression of cytokine (and other?) genes should not be ation studies is shown in Table 3, both statistically sig- forgotten. For example, the rigour with which Fishman nificant (scored as ‘yes’) and statistically non-significant et al64 approached the measurement of IL-6 production in (scored as ‘no’). The statistical significance is recorded as their control subjects, demonstrates the importance of the interpreted by the originating authors: for details of the natural metabolic variation which occurs daily. This sup- statistical tests and corrections used, the reader should ported earlier studies, for example that of Petrovsky and refer to the papers cited. For certain combinations of Harrison,313 who showed that the LPs induction of IL-10 polymorphisms and diseases, contradictory results have and IFN-gamma varied throughout the day, observing been published. In these cases, the discordancy may be that the IFN-gamma/IL-10 ratio peaked early in the attributable to differences in ethnicity of populations, morning and concluding that both cortisol and melatonin patient and/or control cohort selection or size, disease could regulate diurnal immune variation. Although classification or status, or methods of statistical analysis.
much has been made of the requirement for caution Both in vitro expression studies and in vivo disease associ- when interpreting genetic data from the TNF cluster ation studies involving TNF␣ and LT␣ (TNF␤) polymor- without due consideration of the MHC and linkage dis- phisms are often complicated by their linkage disequilib- equilibrium, MHC effects on cytokines off chromosome rium (LD) with HLA genes and haplotypes within the 6 have not been so well documented. The evidence is major histocompatibility complex. This has created diffi- beginning to emerge, however. A study in 1997314 dem- culties in dissecting the independent role of TNF in onstrated that secreted levels of IFN-gamma varied expression and disease (see Table 2 and 3 for examples).
markedly with class-II alleles, in an MLR. DR1, DR2 andDR6 were associated with high IFN-gamma secretion On-line databases
while DR3, DR4 and DR7 were associated with lowerIFN-gamma production. Similar conclusions were drawn Tables 1, 2 and 3 and associated citations are reproduced for those DQ alleles in linkage disequilibrium with the in electronic form on the World Wide Web. They are DR alleles noted above. This pattern was reversed for searchable using the appropriate ‘find’ command of Web TNF secretion (ie, DR3 was high TNF and so on), mir- browsers. It is the intention of the authors to issue regular roring earlier work by Pociot et al115 who demonstrated updates of these tables as part of an ongoing feature of a DR-based hierarchy of TNF secretion which was of this Journal. Notification and details of the revisions to greater magnitude than the TNF-allele results for which the tables will be published as appropriate.
they are more usually remembered. Similar data are The Web site URL for Tables 1, 2 and 3 and associated available for other aspects of the immune system, for http://www.pam.bris.ac.uk/services/GAI/cytokine4.htm In this regard, DR3 has received the greatest attention.
T cell activation varies in DR3-positive individuals, per- Cytokine reviews database
haps because of diminished CD69 expression,316 as docytokines themselves317 particularly in regard to auto- In addition to these databases, we have issued a search- immune DR3 positive subjects.318 Apoptosis may differ able reference database containing 1000 cytokine review because these individuals have diminished expression of citations, from 1990 to the present. This database is pro- CD95 (FAS319) and indeed lower total lymphocyte counts have been described in aassociation with B8-DR3.320 Little insight to the mechanism of these various effects by the Endnote version 3 (filename CYTOREVIEWS.ENL) class-II on immune function was available until recently, Tagged MEDLARS format (.TAG) file (filename when it was demonstrated that different class-II mol- ecules varied in the efficiency with which they transduce The files contain both general and disease-specific reviews signals from CD4 across the cell membrane, and that this relating to cytokines and cytokine receptors. The Endnote variation is carried with the intracellular portion of the version may be searched using any criteria available class-II molecule.321 As if this were not confusing enough, within the Endnote application, eg, by author or the age of the donors themselves has been shown to affect keyword. The tagged MEDLARS version may be T cell activation322,323 through various mechanisms. In imported directly into other reference manager pro- conclusion, the genetic effect seen to be acting on cytokine grams. Both files may be downloaded directly from the production, and implicating them as disease-associated loci in their own right, are complicated by the MHC and age.
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