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Rheumatic diseases: Environment and genetics
Joint Bone Spine 76 (2009) 602–607
Clinical-state-of-the-art
Rheumatic diseases: Environment and genetics Philippe Dieudé ∗ LREPR-EA3886, Evry-Génopole, université d’Evry-Val-d’Essonne, Evry, France Accepted 28 September 2009 Available online 17 November 2009
Abstract Rheumatology deals with many different entities among which dys/autoimmune diseases occupy a position of preponderance. This review focuses on the concept of complex genetic disease, which is illustrated by three different chronic inflammatory joint diseases: rheumatoid arthritis, systemic lupus erythematosus, and systemic sclerosis. Genetic studies have established that a common genetic background is shared by many autoimmune disorders. Interestingly, although common genetic factors are shared by diseases that produce different phenotypes, risk variants can exert a strong influence on the phenotype of a given disease. Genetics cannot fully explain the determinism of complex genetic diseases. Future genetic studies must incorporate data on exposure to potential environmental factors. The next step in unravelling complex genetic diseases will involve investigations not only of gene–gene and gene–environment interactions, but also of epigenetics, defined as transmissible and reversible changes in gene expression that are not related to changes in the DNA sequence. The past decade has witnessed an impressive accumulation of data on the determinism of complex diseases, and the next will probably bring further insights into the pathophysiology of dys/autoimmune diseases. © 2009 Société franc¸aise de rhumatologie. Published by Elsevier Masson SAS. All rights reserved. Keywords: Genetics; Environment; Epigenetic process; Complex genetic disease
1. Introduction
2. Complex genetic diseases
Rheumatology deals with many different entities among which dys/autoimmune diseases occupy a position of preponderance, as shown by the rapid rise in the number of biotherapies intended for use in rheumatology. Over the past decade, advances in genetics and epidemiology have led to the identification not only of numerous susceptibility genes, but also of several environmental factors, thus shedding new light on the pathophysiology of dys/autoimmune diseases. Here, we review current data on environmental and genetic factors identified over the past decade. An exhaustive review of the diseases managed by rheumatologists would be a formidable challenge, and we will instead focus on the concept of complex genetic disease and on genetic/environmental susceptibility factors. To this end, we will discuss three chronic inflammatory joint diseases: rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and systemic sclerosis (SS).
Most of the conditions managed by rheumatologists are complex or multifactorial diseases: they are related, not to a functional mutation found in a small minority of the general population, but to interactions between multiple genetic and environmental factors. Taken alone, each genetic factor makes only a modest contribution to the overall genetic risk of developing a given complex disease. Thus, the challenge resides in identifying the various susceptibility factors and in determining the susceptibility allele combinations that are associated with the highest relative risk of developing the disease. Over the past decade, new knowledge on the human genome sequence [1] and genetic diversity of populations [2] has considerably benefited our understanding of complex genetic diseases. The early casecontrol linkage studies based on the candidate gene approach in medium-sized samples have been superseded by genome-wide association (GWA) studies in several thousand individuals. Crucial to this progress was the establishment of consortiums such as the Wellcome Trust Case-Control Consortium (WTCCC) that focus on investigating complex diseases [3] and the development of DNA microarrays (or gene chips), a technological breakthrough that allows single-run testing of thousands of polymorphisms distributed over the genome. Although GWA studies
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are undoubtedly useful for identifying new genetic susceptibility factors, it should be borne in mind that the large number of polymorphisms/genes of interest identified by these studies must then be validated by independent replication studies. 3. Evaluating the weight of the genetic component of a complex disease Several steps are involved in the investigation of a complex disease. First, enough evidence must be accumulated to suggest a role for genetic factors in the disease. Familial aggregation constitutes indirect support for an influence of genetic factors. However, familial aggregation may reflect exposure of the family members to the same environmental factors. Therefore, studies must be undertaken to establish that genetic factors are responsible, in part at least, for the clustering within families. 3.1. Family studies Family studies seek to suggest the existence of an inherited component in the development of a specific disease by showing that cases cluster within families. An increased rate of the disease among first-degree relatives of affected individuals (parents, siblings, and children) compared to the general population is taken as evidence of an inherited component. A useful measure is the relative risk λR (R for relatives), or recurrence risk, defined as the ratio of the rate of disease in first-degree relatives of a patient over the rate in the general population. The recurrence risk can be evaluated for several categories of relatives, usually within sibships (λS , where “S” indicates “sibling”). The recurrence risk reflects the impact of both genetic factors and environmental factors. 3.2. Twin studies Twin studies provide valuable information on the genetic component of multifactorial diseases. They consist in comparing the concordance rate (proportion of twin pairs in which both twins are affected) between monozygotic pairs and same-sex dizygotic pairs. Monozygotic twins have identical genomes, and dizygotic twins share the same environmental factors to a greater extent than do non-twin siblings. Thus, the concordance rate difference between monozygotic and dizygotic twins reflects the impact of genetic factors: a larger difference indicates a greater role for genetics in the development of the disease. In complex diseases, the concordance rate between monozygotic twins is always less than 100%, reflecting the involvement of environmental factors.
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to 10% for same-sex dizygotic twins [8–10]. On average, the concordance rate is three to four times higher in monozygotic twins than in same-sex dizygotic twins, confirming the role for a genetic component in the susceptibility to RA. The main genetic susceptibility factors for RA known to date were identified using both candidate gene studies and GWA studies [11]. The association of genes in the HLA region with RA was first suspected in 1976 by Stastny [12]. In the late 1980s, after the HLA-DRB1 locus was sequenced, the shared epitope hypothesis was developed to explain the association between the Class II major histocompatibility complex (MHC) region and susceptibility to RA [13]. According to the shared epitope hypothesis, HLA-DR molecules are directly involved in the pathophysiology of RA. The association between HLA-DR and RA is ascribed to susceptibility alleles that encode a homologous amino acid sequence in the third hypervariable region of the first domain of the HLA-DR beta chain [13]. This sequence, which consists of the amino acids at position 70 to 74 (70 QRRAA74 or 70 KRRAA74 or 70 RRRAA74 ), is encoded by the DR4 (DRB1*0401, 0404, and 0405), DR1 (DRB1*0101 and 0102), and DR10 (DRB1*1010) alleles and is associated with RA [13]. The exact role for the shared epitope has not yet been determined [14,15]. Although HLA-DRB1 is the main genetic component in RA, the HLA locus contributes only about 30% of the overall familial risk, indicating a role for non-HLA genetic factors in the susceptibility to RA [4,16,17]. Among non-HLA susceptibility factors, a functional polymorphism (R620W) of PTPN22, the gene for tyrosine phosphatase nonreceptor 22, has been identified as conferring susceptibility to RA [18–20]. This functional variant may be involved in the mechanisms that regulate T- and B-cell activation [21,22]. The association between PTPN22 and RA has been replicated in many populations; however, an interesting point is that the risk variant was not found among Asians [23]. The gene encoding peptidyl arginine deiminase 4 (PADI4), an enzyme involved in citrullination, has been shown to confer susceptibility to RA in Asians [24,25]. Many studies in Caucasian Europeans found no association with PADI4. However, a recent metaanalysis combining data from six European populations showed that a unique PADI4 variant (PADI4 94) was associated with RA [26]. The numerous GWA studies conducted by consortiums such as the WTCCC, North American Rheumatoid Arthritis Consortium (NARAC), and Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) have confirmed that PTPN22, PADI4, and CTLA4 confer susceptibility to RA [27]. The current surge in GWA and candidate-gene studies is translating into the identification each month of new susceptibility factors such as STAT4, IRF5, TNFAIP3, TRAF1-C5, CD40 and, very recently, REL [11,28].
4. Rheumatoid arthritis 4.2. Environmental factors 4.1. Genetic susceptibility factors The prevalence of RA among first-degree relatives of patients ranges from 2 to 12%, instead of 0.2 to 1% in the general population [4]. In RA, λS is estimated at 3 to 15 [5–7]. Concordance rates range from 12 to 30% for monozygotic twins and from 5
The main studies of environmental factors associated with RA focused on diet, smoking, and hormones [29]. Only a few environmental factors were identified. The main environmental factor is smoking. Although a role for smoking was reported over 15 years ago [30], recent studies have established that it is
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confined to RA with production of anticitrullinated peptide antibodies (ACPA) [31,32]. The RA risk correlates with smoking duration and intensity [33]. A prospective study in a vast population of women (Nurse’s Health Study) showed that smoking duration and intensity correlated linearly with the risk of RA [34]. A smoking history of more than 40 pack-years was associated with a two-fold risk increase compared to nonsmokers, and the risk increase was still present 20 years after smoking cessation [34]. Several studies found evidence of a gene–environment interaction between smoking and HLA-DRB1*SE, illustrating the mechanisms involved in complex genetic diseases. In a casecontrol study of patients with RA onset within the last year (EIRA cohort), smokers without HLADRB1*SE alleles (SE negative) were 1.5 times more likely to develop ACPA-positive RA compared to nonsmokers who were SE negative [35]. The risk of ACPA-positive RA in individuals having two SE copies was increased 21-fold compared to SE-negative nonsmokers [35]. Subsequently, this interaction was demonstrated in numerous independent cohorts [36]. Alcohol consumption may protect against the development of RA. Although the underlying pathogenic mechanisms remain obscure, results from a Swedish cohort (EIRA) and a Danish cohort (CACORA) establish that drinking more than 80 mg of alcohol per day (about five drinks) decreases the risk of RA by 40 to 50% compared to nondrinkers. Again, the protective effect against ACPA-positive RA was substantially stronger among SE-positive patients, suggesting an interaction between alcohol use and HLADRB1*SE [37]. Many other environmental factors such as vitamin D intake, oral contraception, and a high intake of red meat have been suspected to affect the risk of RA, although discrepancies across study results preclude definitive conclusions [36]. A recent study confirmed earlier evidence that breastfeeding for longer than 12 months protects against RA [38]. 5. Systemic lupus erythematosus 5.1. Genetic factors Evidence supporting a strong role for genetic factors in susceptibility to SLE include λS values ranging from 20 to 29 and a concordance rate of 24 to 57% among monozygotic twins compared to 2 to 5% among dizygotic twins [39,40]. Again, the HLA locus was the first susceptibility factor to be identified [41]. However, the association between the HLA locus and SLE involves the immunological abnormalities rather than the clinical phenotype of the disease [42,43]. Over the past decade, our understanding of the genetic background of SLE has made considerable progress, as highlighted recently by a literature review [44]. To date, two GWA studies have been conducted. They identified a large number of susceptibility factors, including IRF5, STAT4, BLK, ITGAM, and MCH [45]. IRF5 encodes Interferon Regulatory Factor 5 (IRF5), a transcription factor crucial to the interferon type 1 pathway. Transcriptome studies, most notably those done on peripheral blood mononuclear cells, have shown that an interferon signature is present not only in SLE, but also in many other
autoimmune diseases, underlying the major pathophysiological role for the interferon type 1 pathway [46,47]. Several functional IRF5 variants have been identified as risk factors for SLE [48,49]. The susceptibility alleles of these polymorphisms have functional effects consisting in either IRF5 mRNA stabilization or increased IRF5 mRNA expression [49–52]. STAT4 encodes Signal Transducer and Activator of Transcription 4 (STAT4), a transcription factor involved in transducing signals from interleukins (IL) 23 and 12 and from interferons type 1. Although initially a single nonfunctional variant was identified as an SLE susceptibility factor, evidence obtained later on suggested that several STAT4 haplotypes might be associated with an increased risk of developing SLE [45,53,54]. Candidate gene case-control studies identified other genes such as PTPN22, PDCD1, BANK1, FCGR2A, TNFSF4, C4 [44]. The female predominance of SLE has generated interest in the sex chromosomes X and Y as genetic susceptibility factors for RA. A very interesting study showed that men with SLE had a far higher prevalence of Klinefelter syndrome (47, XXY) compared to the general population, suggesting an effect of the X chromosome [55]. 5.2. Environmental factors Most of the studies of environmental risk factors for SLE focused on the role for hormones, because of the far higher prevalence of the disease among females than males. In a recent population-based case-control study, breastfeeding was found to protect against SLE, the risk of SLE being correlated with both the number of breast-fed babies and total breastfeeding duration [56]. Although several hormonal factors seem to affect the risk of SLE, there is no convincing proof that hormone replacement therapy or oral contraception play a role [57]. Alcohol use has been suggested as a protective factor [58]. Chemical exposures have been investigated in many studies. Using lipstick more than three times a week was associated with an increased risk of SLE in one study, the suggested explanation being absorption of 2-octyanoid acid and phtalane through the oral mucosa [59]. No gene–environment interaction studies have been reported to date. 6. Systemic sclerosis 6.1. Genetic factors A study of familial clustering of SS in three North American cohorts showed a significant increase in the prevalence of SS compared to the general population (2.6% vs. 0.026%, respectively), with a λR value in first-degree relatives of about 13 [60]. In twin studies, concordance for antinuclear antibodies was significantly greater among monozygotic twins than among same-sex dizygotic twins but concordance for the disease phenotype was similarly low in both groups [61]. Thus, the genetic component may have a stronger influence on the dysimmunity phenotype than on the SS phenotype. The genetic factors involved in SS have been reviewed in detail elsewhere [62], and we will therefore focus on the main recently identified susceptibility factors that support a stronger
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role for the genetic component in the dysimmunity phenotype. Given the shared genetic background in several autoimmune diseases (as discussed below) and the clinical symptom overlap between SLE and SS, recent genetic studies of SS used the candidate gene approach to test various factors associated with susceptibility to SLE. The results showed that susceptibility to SS was conferred by PTPN22, IRF5, STAT4 and, based on more recent data, BANK1 [63–67]. BANK1 encodes the B-cell-specific scaffold protein and LYN tyrosine kinase substrate involved in phosphorylating the inositol 1,4,5-trisphosphate receptors. Two functional BANK1 polymorphisms, previously identified as risk factors for SLE, were found to be associated with diffuse cutaneous SS [67]. No GWA studies of SS have been reported to date. However, two European groups and one North American group have just completed a first genome-wide scan whose results will probably be presented at upcoming international meetings.
Table 1 Main shared genetic factors in autoimmune diseases.
6.2. Environmental factors
8.1. Usefulness of establishing a population of patients exhibiting individual clustering of multiple autoimmune diseases
A high prevalence of SS has been found in specific locations, supporting a role for environmental factors. Most of the environmental factors identified to date are inhaled chemicals, most notably silica. Scleroderma related to the inhalation of silica dust is known as Erasmus syndrome [68]. Many studies have confirmed the role for silica in SS [69,70]. A metaanalysis established that exposure to solvents (including vinyl chloride) increases the risk of SS [71]. Many other chemicals can probably affect the risk of SS. For instance, the increased prevalence of the disease near airports suggests a role for kerosene combustion products [72]. 7. The shared genetic background concept The clustering of autoimmune disorders within families and/or individuals supports a role for shared genetic factors. However, studies designed to investigate this possibility are scarce, and most of them focused on common autoimmune diseases such as RA or type 1 diabetes. The results usually showed familial clustering of some groups of autoimmune diseases, supporting a role for common genetic factors. Overall, findings from genetic studies are consistent with a shared genetic background in dysimmunity/autoimmunity. For instance, many genes including PTPN22, STAT4, and IRF5 are involved in the genetic susceptibility to RA, SLE, and SS (Table 1). Interestingly, although these genetic factors are shared by diseases that differ phenotypically, risk variants can exert a major influence on the phenotype of a given disease. In other words, although these variants are not specific of the disease to which they confer susceptibility, they are highly specific of a disease subgroup [19,20,63,64,67]. One hypothesis is that a common genetic background confers susceptibility to autoimmunity and that environmental factors play the main role in the development of a specific autoimmune phenotype. Thus, smoking superimposed on the common genetic background would lead to ACPA-positive RA and exposure to solvents or silica to the SS phenotype.
Disease
T-cell differentiation
Cell activation and signaling
Innate immunity and signaling
Autoimmune thyroiditis
None
NALP1
Rheumatoid arthritis
STAT4
CTLA4 PTPN22 CTLA4 PTPN22
Systemic lupus erythematosus
STAT4
Systemic sclerosis
STAT4
CTLA4 PTPN22 BANK1 PTPN22 BANK1
IRF5 TNFAIP3 TRAF1-C5 IRF5 TNFAIP3 IRF5
8. Perspectives
In a population that exhibits a single autoimmune phenotype, the contribution of each factor is modest. A population of patients with multiple autoimmune diseases would be expected to contain a larger “dose” of susceptibility factors. To date, a single genetic linkage study in such a population has been published [73]. The results led to the identification of NALP1, the gene for NACTH leucine-rich-repeat protein 1, as probably conferring susceptibility not only to vitiligo but also to various autoimmune disorders such as RA, SLE, autoimmune thyroiditis, and Biermer’s anemia [73]. A few publications suggest that studying patients who have at least two autoimmune diseases may increase the likelihood of detecting genetic factors that confer susceptibility to autoimmunity [74–76]. These association studies underline the usefulness of populations characterized by individual clustering of multiple autoimmune diseases for investigating genes associated with susceptibility to autoimmunity. 8.2. Usefulness of collecting information on environmental factors Genetic studies cannot fully explain the occurrence of complex diseases. In future genetic studies, data on environmental exposures must be collected. The next step in the genetic evaluation of complex diseases will focus on gene–gene and gene–environment interactions. The genetic studies conducted to date have chiefly investigated simple genetic variants (insertion-deletion, single-nucleotide polymorphisms). However, variability in the number of gene copies is emerging as a major source of human genome polymorphism that will have to be taken into account in future studies [77]. 8.3. Epigenetics The term “epigenetics” refers to transmissible and reversible changes in gene expression that are not caused by changes in
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the underlying DNA sequence. These changes are related to modifications affecting either the DNA molecule (e.g., cytosine methylation) or the proteins linked to DNA (e.g., histones). These modifications may occur spontaneously, in response to an environmental factor or to the presence of a specific allele, even when this allele is not found in the descendants. Thus, epigenetics is to genetics what reading (interpreting) is to writing. Epigenetics is one of the fundamental sources of biological diversity and is generating growing interest among researchers working on the determinism of dysimmune/autoimmune complex diseases [78,79].
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dance for the presence of antinuclear antibodies. Arthritis Rheum 2003;48: 1956–63. Allanore Y, Wipff J, Kahan A, et al. Genetic basis for systemic sclerosis. Joint Bone Spine 2007;74:577–83. Dieude P, Guedj M, Wipff J, et al. Association between the IRF5 rs2004640 functional polymorphism and systemic sclerosis: a new perspective for pulmonary fibrosis. Arthritis Rheum 2009;60:225–33. Dieude P, Guedj M, Wipff J, et al. The PTPN22 620W allele confers susceptibility to systemic sclerosis: findings of a large case-control study of European Caucasians and a meta-analysis. Arthritis Rheum 2008;58:2183–8. Dieude P, Guedj M, Wipff J, et al. STAT4 is a genetic risk factor for systemic sclerosis having additive effects with IRF5 on disease susceptibility and related pulmonary fibrosis. Arthritis Rheum 2009;60:2472–9. Rueda B, Broen J, Simeon C, et al. The STAT4 gene influences the genetic predisposition to systemic sclerosis phenotype. Hum Mol Genet 2009;18:2071–7. Dieude P, Wipff J, Guedj M, et al. BANK1 is a genetic risk factor for diffuse cutaneous systemic sclerosis having additive effects with IRF5 and STAT4. Arthritis Rheum 2009;60:2472–9. Devulder B, Plouvier B, Martin JC, et al. The association: sclerodermasilicosis or Erasmus’ syndrome (author’s translation). Nouv Presse Med 1977;6:2877–9. Rodnan GP, Benedek TG, Medsger Jr TA, et al. The association of progressive systemic sclerosis (scleroderma) with coal miners’ pneumoconiosis and other forms of silicosis. Ann Intern Med 1967;66:323–34. Haustein UF, Anderegg U. Silica induced scleroderma – clinical and experimental aspects. J Rheumatol 1998;25:1917–26. Aryal BK, Khuder SA, Schaub EA. Meta-analysis of systemic sclerosis and exposure to solvents. Am J Ind Med 2001;40:271–4. Silman AJ, Howard Y, Hicklin AJ, et al. Geographical clustering of scleroderma in south and west London. Br J Rheumatol 1990;29:93–6. Jin Y, Mailloux CM, Gowan K, et al. NALP1 in vitiligo-associated multiple autoimmune disease. N Engl J Med 2007;356:1216–25. Vaidya B, Pearce SH, Charlton S, et al. An association between the CTLA4 exon 1 polymorphism and early rheumatoid arthritis with autoimmune endocrinopathies. Rheumatology (Oxford) 2002;41:180–3. Ikegami H, Awata T, Kawasaki E, et al. The association of CTLA4 polymorphism with type 1 diabetes is concentrated in patients complicated with autoimmune thyroid disease: a multicenter collaborative study in Japan. J Clin Endocrinol Metab 2006;91:1087–92. Wu H, Cantor RM, Graham DS, et al. Association analysis of the R620W polymorphism of protein tyrosine phosphatase PTPN22 in systemic lupus erythematosus families: increased T allele frequency in systemic lupus erythematosus patients with autoimmune thyroid disease. Arthritis Rheum 2005;52:2396–402. Jakobsson M, Scholz SW, Scheet P, et al. Genotype, haplotype and copy-number variation in worldwide human populations. Nature 2008;451:998–1003. Strietholt S, Maurer B, Peters MA, et al. Epigenetic modifications in rheumatoid arthritis. Arthritis Res Ther 2008;10:219. Pan Y, Sawalha AH. Epigenetic regulation and the pathogenesis of systemic lupus erythematosus. Transl Res 2009;153:4–10.
Clinical-state-of-the-art
Rheumatic diseases: Environment and genetics Philippe Dieudé ∗ LREPR-EA3886, Evry-Génopole, université d’Evry-Val-d’Essonne, Evry, France Accepted 28 September 2009 Available online 17 November 2009
Abstract Rheumatology deals with many different entities among which dys/autoimmune diseases occupy a position of preponderance. This review focuses on the concept of complex genetic disease, which is illustrated by three different chronic inflammatory joint diseases: rheumatoid arthritis, systemic lupus erythematosus, and systemic sclerosis. Genetic studies have established that a common genetic background is shared by many autoimmune disorders. Interestingly, although common genetic factors are shared by diseases that produce different phenotypes, risk variants can exert a strong influence on the phenotype of a given disease. Genetics cannot fully explain the determinism of complex genetic diseases. Future genetic studies must incorporate data on exposure to potential environmental factors. The next step in unravelling complex genetic diseases will involve investigations not only of gene–gene and gene–environment interactions, but also of epigenetics, defined as transmissible and reversible changes in gene expression that are not related to changes in the DNA sequence. The past decade has witnessed an impressive accumulation of data on the determinism of complex diseases, and the next will probably bring further insights into the pathophysiology of dys/autoimmune diseases. © 2009 Société franc¸aise de rhumatologie. Published by Elsevier Masson SAS. All rights reserved. Keywords: Genetics; Environment; Epigenetic process; Complex genetic disease
1. Introduction
2. Complex genetic diseases
Rheumatology deals with many different entities among which dys/autoimmune diseases occupy a position of preponderance, as shown by the rapid rise in the number of biotherapies intended for use in rheumatology. Over the past decade, advances in genetics and epidemiology have led to the identification not only of numerous susceptibility genes, but also of several environmental factors, thus shedding new light on the pathophysiology of dys/autoimmune diseases. Here, we review current data on environmental and genetic factors identified over the past decade. An exhaustive review of the diseases managed by rheumatologists would be a formidable challenge, and we will instead focus on the concept of complex genetic disease and on genetic/environmental susceptibility factors. To this end, we will discuss three chronic inflammatory joint diseases: rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and systemic sclerosis (SS).
Most of the conditions managed by rheumatologists are complex or multifactorial diseases: they are related, not to a functional mutation found in a small minority of the general population, but to interactions between multiple genetic and environmental factors. Taken alone, each genetic factor makes only a modest contribution to the overall genetic risk of developing a given complex disease. Thus, the challenge resides in identifying the various susceptibility factors and in determining the susceptibility allele combinations that are associated with the highest relative risk of developing the disease. Over the past decade, new knowledge on the human genome sequence [1] and genetic diversity of populations [2] has considerably benefited our understanding of complex genetic diseases. The early casecontrol linkage studies based on the candidate gene approach in medium-sized samples have been superseded by genome-wide association (GWA) studies in several thousand individuals. Crucial to this progress was the establishment of consortiums such as the Wellcome Trust Case-Control Consortium (WTCCC) that focus on investigating complex diseases [3] and the development of DNA microarrays (or gene chips), a technological breakthrough that allows single-run testing of thousands of polymorphisms distributed over the genome. Although GWA studies
∗ Service de rhumatologie, hôpital Bichat Claude-Bernard, 46, rue HenriHuchard, 75018 Paris, France. Tel.: +33 01 40 25 74 01; fax: +33 142 290 688. E-mail address: [email protected].
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are undoubtedly useful for identifying new genetic susceptibility factors, it should be borne in mind that the large number of polymorphisms/genes of interest identified by these studies must then be validated by independent replication studies. 3. Evaluating the weight of the genetic component of a complex disease Several steps are involved in the investigation of a complex disease. First, enough evidence must be accumulated to suggest a role for genetic factors in the disease. Familial aggregation constitutes indirect support for an influence of genetic factors. However, familial aggregation may reflect exposure of the family members to the same environmental factors. Therefore, studies must be undertaken to establish that genetic factors are responsible, in part at least, for the clustering within families. 3.1. Family studies Family studies seek to suggest the existence of an inherited component in the development of a specific disease by showing that cases cluster within families. An increased rate of the disease among first-degree relatives of affected individuals (parents, siblings, and children) compared to the general population is taken as evidence of an inherited component. A useful measure is the relative risk λR (R for relatives), or recurrence risk, defined as the ratio of the rate of disease in first-degree relatives of a patient over the rate in the general population. The recurrence risk can be evaluated for several categories of relatives, usually within sibships (λS , where “S” indicates “sibling”). The recurrence risk reflects the impact of both genetic factors and environmental factors. 3.2. Twin studies Twin studies provide valuable information on the genetic component of multifactorial diseases. They consist in comparing the concordance rate (proportion of twin pairs in which both twins are affected) between monozygotic pairs and same-sex dizygotic pairs. Monozygotic twins have identical genomes, and dizygotic twins share the same environmental factors to a greater extent than do non-twin siblings. Thus, the concordance rate difference between monozygotic and dizygotic twins reflects the impact of genetic factors: a larger difference indicates a greater role for genetics in the development of the disease. In complex diseases, the concordance rate between monozygotic twins is always less than 100%, reflecting the involvement of environmental factors.
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to 10% for same-sex dizygotic twins [8–10]. On average, the concordance rate is three to four times higher in monozygotic twins than in same-sex dizygotic twins, confirming the role for a genetic component in the susceptibility to RA. The main genetic susceptibility factors for RA known to date were identified using both candidate gene studies and GWA studies [11]. The association of genes in the HLA region with RA was first suspected in 1976 by Stastny [12]. In the late 1980s, after the HLA-DRB1 locus was sequenced, the shared epitope hypothesis was developed to explain the association between the Class II major histocompatibility complex (MHC) region and susceptibility to RA [13]. According to the shared epitope hypothesis, HLA-DR molecules are directly involved in the pathophysiology of RA. The association between HLA-DR and RA is ascribed to susceptibility alleles that encode a homologous amino acid sequence in the third hypervariable region of the first domain of the HLA-DR beta chain [13]. This sequence, which consists of the amino acids at position 70 to 74 (70 QRRAA74 or 70 KRRAA74 or 70 RRRAA74 ), is encoded by the DR4 (DRB1*0401, 0404, and 0405), DR1 (DRB1*0101 and 0102), and DR10 (DRB1*1010) alleles and is associated with RA [13]. The exact role for the shared epitope has not yet been determined [14,15]. Although HLA-DRB1 is the main genetic component in RA, the HLA locus contributes only about 30% of the overall familial risk, indicating a role for non-HLA genetic factors in the susceptibility to RA [4,16,17]. Among non-HLA susceptibility factors, a functional polymorphism (R620W) of PTPN22, the gene for tyrosine phosphatase nonreceptor 22, has been identified as conferring susceptibility to RA [18–20]. This functional variant may be involved in the mechanisms that regulate T- and B-cell activation [21,22]. The association between PTPN22 and RA has been replicated in many populations; however, an interesting point is that the risk variant was not found among Asians [23]. The gene encoding peptidyl arginine deiminase 4 (PADI4), an enzyme involved in citrullination, has been shown to confer susceptibility to RA in Asians [24,25]. Many studies in Caucasian Europeans found no association with PADI4. However, a recent metaanalysis combining data from six European populations showed that a unique PADI4 variant (PADI4 94) was associated with RA [26]. The numerous GWA studies conducted by consortiums such as the WTCCC, North American Rheumatoid Arthritis Consortium (NARAC), and Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) have confirmed that PTPN22, PADI4, and CTLA4 confer susceptibility to RA [27]. The current surge in GWA and candidate-gene studies is translating into the identification each month of new susceptibility factors such as STAT4, IRF5, TNFAIP3, TRAF1-C5, CD40 and, very recently, REL [11,28].
4. Rheumatoid arthritis 4.2. Environmental factors 4.1. Genetic susceptibility factors The prevalence of RA among first-degree relatives of patients ranges from 2 to 12%, instead of 0.2 to 1% in the general population [4]. In RA, λS is estimated at 3 to 15 [5–7]. Concordance rates range from 12 to 30% for monozygotic twins and from 5
The main studies of environmental factors associated with RA focused on diet, smoking, and hormones [29]. Only a few environmental factors were identified. The main environmental factor is smoking. Although a role for smoking was reported over 15 years ago [30], recent studies have established that it is
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confined to RA with production of anticitrullinated peptide antibodies (ACPA) [31,32]. The RA risk correlates with smoking duration and intensity [33]. A prospective study in a vast population of women (Nurse’s Health Study) showed that smoking duration and intensity correlated linearly with the risk of RA [34]. A smoking history of more than 40 pack-years was associated with a two-fold risk increase compared to nonsmokers, and the risk increase was still present 20 years after smoking cessation [34]. Several studies found evidence of a gene–environment interaction between smoking and HLA-DRB1*SE, illustrating the mechanisms involved in complex genetic diseases. In a casecontrol study of patients with RA onset within the last year (EIRA cohort), smokers without HLADRB1*SE alleles (SE negative) were 1.5 times more likely to develop ACPA-positive RA compared to nonsmokers who were SE negative [35]. The risk of ACPA-positive RA in individuals having two SE copies was increased 21-fold compared to SE-negative nonsmokers [35]. Subsequently, this interaction was demonstrated in numerous independent cohorts [36]. Alcohol consumption may protect against the development of RA. Although the underlying pathogenic mechanisms remain obscure, results from a Swedish cohort (EIRA) and a Danish cohort (CACORA) establish that drinking more than 80 mg of alcohol per day (about five drinks) decreases the risk of RA by 40 to 50% compared to nondrinkers. Again, the protective effect against ACPA-positive RA was substantially stronger among SE-positive patients, suggesting an interaction between alcohol use and HLADRB1*SE [37]. Many other environmental factors such as vitamin D intake, oral contraception, and a high intake of red meat have been suspected to affect the risk of RA, although discrepancies across study results preclude definitive conclusions [36]. A recent study confirmed earlier evidence that breastfeeding for longer than 12 months protects against RA [38]. 5. Systemic lupus erythematosus 5.1. Genetic factors Evidence supporting a strong role for genetic factors in susceptibility to SLE include λS values ranging from 20 to 29 and a concordance rate of 24 to 57% among monozygotic twins compared to 2 to 5% among dizygotic twins [39,40]. Again, the HLA locus was the first susceptibility factor to be identified [41]. However, the association between the HLA locus and SLE involves the immunological abnormalities rather than the clinical phenotype of the disease [42,43]. Over the past decade, our understanding of the genetic background of SLE has made considerable progress, as highlighted recently by a literature review [44]. To date, two GWA studies have been conducted. They identified a large number of susceptibility factors, including IRF5, STAT4, BLK, ITGAM, and MCH [45]. IRF5 encodes Interferon Regulatory Factor 5 (IRF5), a transcription factor crucial to the interferon type 1 pathway. Transcriptome studies, most notably those done on peripheral blood mononuclear cells, have shown that an interferon signature is present not only in SLE, but also in many other
autoimmune diseases, underlying the major pathophysiological role for the interferon type 1 pathway [46,47]. Several functional IRF5 variants have been identified as risk factors for SLE [48,49]. The susceptibility alleles of these polymorphisms have functional effects consisting in either IRF5 mRNA stabilization or increased IRF5 mRNA expression [49–52]. STAT4 encodes Signal Transducer and Activator of Transcription 4 (STAT4), a transcription factor involved in transducing signals from interleukins (IL) 23 and 12 and from interferons type 1. Although initially a single nonfunctional variant was identified as an SLE susceptibility factor, evidence obtained later on suggested that several STAT4 haplotypes might be associated with an increased risk of developing SLE [45,53,54]. Candidate gene case-control studies identified other genes such as PTPN22, PDCD1, BANK1, FCGR2A, TNFSF4, C4 [44]. The female predominance of SLE has generated interest in the sex chromosomes X and Y as genetic susceptibility factors for RA. A very interesting study showed that men with SLE had a far higher prevalence of Klinefelter syndrome (47, XXY) compared to the general population, suggesting an effect of the X chromosome [55]. 5.2. Environmental factors Most of the studies of environmental risk factors for SLE focused on the role for hormones, because of the far higher prevalence of the disease among females than males. In a recent population-based case-control study, breastfeeding was found to protect against SLE, the risk of SLE being correlated with both the number of breast-fed babies and total breastfeeding duration [56]. Although several hormonal factors seem to affect the risk of SLE, there is no convincing proof that hormone replacement therapy or oral contraception play a role [57]. Alcohol use has been suggested as a protective factor [58]. Chemical exposures have been investigated in many studies. Using lipstick more than three times a week was associated with an increased risk of SLE in one study, the suggested explanation being absorption of 2-octyanoid acid and phtalane through the oral mucosa [59]. No gene–environment interaction studies have been reported to date. 6. Systemic sclerosis 6.1. Genetic factors A study of familial clustering of SS in three North American cohorts showed a significant increase in the prevalence of SS compared to the general population (2.6% vs. 0.026%, respectively), with a λR value in first-degree relatives of about 13 [60]. In twin studies, concordance for antinuclear antibodies was significantly greater among monozygotic twins than among same-sex dizygotic twins but concordance for the disease phenotype was similarly low in both groups [61]. Thus, the genetic component may have a stronger influence on the dysimmunity phenotype than on the SS phenotype. The genetic factors involved in SS have been reviewed in detail elsewhere [62], and we will therefore focus on the main recently identified susceptibility factors that support a stronger
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role for the genetic component in the dysimmunity phenotype. Given the shared genetic background in several autoimmune diseases (as discussed below) and the clinical symptom overlap between SLE and SS, recent genetic studies of SS used the candidate gene approach to test various factors associated with susceptibility to SLE. The results showed that susceptibility to SS was conferred by PTPN22, IRF5, STAT4 and, based on more recent data, BANK1 [63–67]. BANK1 encodes the B-cell-specific scaffold protein and LYN tyrosine kinase substrate involved in phosphorylating the inositol 1,4,5-trisphosphate receptors. Two functional BANK1 polymorphisms, previously identified as risk factors for SLE, were found to be associated with diffuse cutaneous SS [67]. No GWA studies of SS have been reported to date. However, two European groups and one North American group have just completed a first genome-wide scan whose results will probably be presented at upcoming international meetings.
Table 1 Main shared genetic factors in autoimmune diseases.
6.2. Environmental factors
8.1. Usefulness of establishing a population of patients exhibiting individual clustering of multiple autoimmune diseases
A high prevalence of SS has been found in specific locations, supporting a role for environmental factors. Most of the environmental factors identified to date are inhaled chemicals, most notably silica. Scleroderma related to the inhalation of silica dust is known as Erasmus syndrome [68]. Many studies have confirmed the role for silica in SS [69,70]. A metaanalysis established that exposure to solvents (including vinyl chloride) increases the risk of SS [71]. Many other chemicals can probably affect the risk of SS. For instance, the increased prevalence of the disease near airports suggests a role for kerosene combustion products [72]. 7. The shared genetic background concept The clustering of autoimmune disorders within families and/or individuals supports a role for shared genetic factors. However, studies designed to investigate this possibility are scarce, and most of them focused on common autoimmune diseases such as RA or type 1 diabetes. The results usually showed familial clustering of some groups of autoimmune diseases, supporting a role for common genetic factors. Overall, findings from genetic studies are consistent with a shared genetic background in dysimmunity/autoimmunity. For instance, many genes including PTPN22, STAT4, and IRF5 are involved in the genetic susceptibility to RA, SLE, and SS (Table 1). Interestingly, although these genetic factors are shared by diseases that differ phenotypically, risk variants can exert a major influence on the phenotype of a given disease. In other words, although these variants are not specific of the disease to which they confer susceptibility, they are highly specific of a disease subgroup [19,20,63,64,67]. One hypothesis is that a common genetic background confers susceptibility to autoimmunity and that environmental factors play the main role in the development of a specific autoimmune phenotype. Thus, smoking superimposed on the common genetic background would lead to ACPA-positive RA and exposure to solvents or silica to the SS phenotype.
Disease
T-cell differentiation
Cell activation and signaling
Innate immunity and signaling
Autoimmune thyroiditis
None
NALP1
Rheumatoid arthritis
STAT4
CTLA4 PTPN22 CTLA4 PTPN22
Systemic lupus erythematosus
STAT4
Systemic sclerosis
STAT4
CTLA4 PTPN22 BANK1 PTPN22 BANK1
IRF5 TNFAIP3 TRAF1-C5 IRF5 TNFAIP3 IRF5
8. Perspectives
In a population that exhibits a single autoimmune phenotype, the contribution of each factor is modest. A population of patients with multiple autoimmune diseases would be expected to contain a larger “dose” of susceptibility factors. To date, a single genetic linkage study in such a population has been published [73]. The results led to the identification of NALP1, the gene for NACTH leucine-rich-repeat protein 1, as probably conferring susceptibility not only to vitiligo but also to various autoimmune disorders such as RA, SLE, autoimmune thyroiditis, and Biermer’s anemia [73]. A few publications suggest that studying patients who have at least two autoimmune diseases may increase the likelihood of detecting genetic factors that confer susceptibility to autoimmunity [74–76]. These association studies underline the usefulness of populations characterized by individual clustering of multiple autoimmune diseases for investigating genes associated with susceptibility to autoimmunity. 8.2. Usefulness of collecting information on environmental factors Genetic studies cannot fully explain the occurrence of complex diseases. In future genetic studies, data on environmental exposures must be collected. The next step in the genetic evaluation of complex diseases will focus on gene–gene and gene–environment interactions. The genetic studies conducted to date have chiefly investigated simple genetic variants (insertion-deletion, single-nucleotide polymorphisms). However, variability in the number of gene copies is emerging as a major source of human genome polymorphism that will have to be taken into account in future studies [77]. 8.3. Epigenetics The term “epigenetics” refers to transmissible and reversible changes in gene expression that are not caused by changes in
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the underlying DNA sequence. These changes are related to modifications affecting either the DNA molecule (e.g., cytosine methylation) or the proteins linked to DNA (e.g., histones). These modifications may occur spontaneously, in response to an environmental factor or to the presence of a specific allele, even when this allele is not found in the descendants. Thus, epigenetics is to genetics what reading (interpreting) is to writing. Epigenetics is one of the fundamental sources of biological diversity and is generating growing interest among researchers working on the determinism of dysimmune/autoimmune complex diseases [78,79].
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