Multiple sclerosis (MS) is a serious, incurable neurological disease. In 2009, the ANZgene studies detected the suggestive association of located upstream of CD40 gene in chromosome 20q13 (p = 1.3×10−7). Identification of the causal variant(s) in the CD40 locus leads to a better understanding of the mechanism underlying the development of autoimmune pathologies. We determined the genotypes of rs6074022, rs1883832, rs1535045, and rs11086996 in patients with MS (n = 1684) and in the control group (n = 879). Two SNPs were significantly associated with MS: rs6074022 (additive model C allele OR = 1.27, 95% CI = [1.12–1.45], p = 3×10−4) and rs1883832 (additive model T allele OR = 1.20, 95% CI = [1.05–1.38], p = 7×10−3). In the meta-analysis of our results and the results of four previous studies, we obtain the association p-value of 2.34×10−12, which confirmed the association between MS and rs6074022 at a genome-wide significant level. Next, we demonstrated that the model including rs6074022 only sufficiently described the association. From our analysis, we can speculate that the association between rs1883832 and MS was induced by LD, whereas rs6074022 was a marker in stronger LD with the functional variant or was the functional variant itself. Our results indicated that the functional variants were located in the upstream region of the gene CD40 and were in higher LD with rs6074022 than LD with rs1883832.
Citation: Sokolova EA, Malkova NA, Korobko DS, Rozhdestvenskii AS, Kakulya AV, Khanokh EV, et al. (2013) Association of SNPs of CD40 Gene with Multiple Sclerosis in Russians. PLoS ONE 8(4): e61032. https://doi.org/10.1371/journal.pone.0061032
Editor: Yong-Gang Yao, Kunming Institute of Zoology, Chinese Academy of Sciences, China
Received: October 25, 2012; Accepted: March 5, 2013; Published: April 22, 2013
Copyright: © 2013 Sokolova et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The study was supported by The Ministry of Education and Science of Russian Federation, project number 2012-1.5-12-000-1002-010 (government contract number 8490) and the grant of Presidium SBRAS (number 91). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Multiple sclerosis (MS) is a serious, incurable neurological disease. The etiology of MS is linked to various genetic and environmental factors. Fifteen genome-wide association studies (GWASs) on MS have been conducted so far, and more than 50 loci have been identified –. The Australia and New Zealand Multiple Sclerosis Genetics Consortium (ANZgene) conducted a GWAS in 2009 and confirmed a number of previously reported associations. These associations include HLA-DR15 (p = 7.0×10−184), CD58 (p = 9.6×10−8), EVI5-RPL5 (p = 2.5×10−6), IL2RA (p = 7.4×10−6), CLEC16A (p = 1.1×10−4), IL7R (p = 1.3×10−3), and TYK2 (p = 3.5×10−3). The ANZgene study also detected the suggestive association of two single nucleotide polymorphisms (SNPs) located upstream of CD40 gene in chromosome 20q13 (rs6074022, p = 1.3×10−7; rs1569723, p = 2.9×10−7) . An association between rs6074022 and MS was also identified in a GWAS based on a cohort from the United Kingdom . However, in the meta-analysis reported in 2011, the association between SNP rs6074022 and MS did not reach the GWAS significance level (p = 4.91×10−6) .
Association with the CD40 gene region has been implicated in a number of human autoimmune diseases such as systemic lupus erythematosus (SLE) , rheumatoid arthritis (RA) , Crohn's disease , and Grave's disease . The participation of CD40 in autoimmune processes is clearly demonstrated in experimental animal models. A non-obese diabetic (NOD) mouse line is one of the most studied models of autoimmune diabetes. The disruption of CD40-CD40L interactions by antagonistic antibodies to CD40L prevents the development of diabetes in NOD mice, which confirms the critical function of the CD40-CD40L complex in the development of this disease .
In the mouse line K/BxN, RA spontaneously develops with many characteristics similar to the clinical course of RA in humans. CD40 knockout (K/BxN-CD40-/-) mice do not develop RA . If a CIA mouse model of RA is treated with antagonistic antibodies such as CD40L mAb before the onset of collagen-induced arthritis, the mouse do not develop RA  or the disease decreases in severity . However, if the therapy is started after the development of arthritis, no improvement occurs , .
CD40 contributes to the susceptibility to human autoimmune diseases, in which the B and T cell pathways play key roles. The role of CD40-CD40L interactions is identified in the development of type-1 diabetes. The CD40 signaling pathway induces the production of proinflammatory cytokines in the islet cells of primates and humans . Increased expression of CD40L+ cells has been observed in the brains of patients with MS .
Also, the expression of CD40 in keratinocytes and endothelial cells in psoriatic plaques, as well as the increased expression of CD40L in the peripheral blood T cells , have been shown in patients with psoriatic arthritis. An elevated level of circulating CD40L has been found in patients with RA, SLE, and Sorgena syndrome during exacerbation . In fact, the interaction between CD40 and CD40L triggers the immune response.
The potential association of the CD40 region with MS is in accordance with the theory that MS has an autoimmune origin. Data from animal models also suggest similarities among the molecular mechanisms underlying the development of various immune disorders. Identification of the causal variant(s) in the CD40 locus will lead to a better understanding of the mechanism underlying the development of autoimmune pathologies. This study aimed to replicate a previously reported association of rs6074022 with MS in a Russian population and to study the association of MS with some other SNPs of the CD40 region.
Materials and Methods
Among a group of Russian-ethnicity patients with MS, 1684 people (1124 women and 560 men; mean age±SD = 36.7±11.2 years) were included based on the McDonald criteria for MS . A total of 1176 patients had relapsing remitting MS (RRMS), 73 had primary progressive MS (PPMS), 403 had secondary-progressive MS (SPMS), and 32 patients had clinically isolated syndrome (CIS). The following centers were involved in the recruitment of patients: Moscow Multiple Sclerosis Center at the City Hospital No. 11, n = 508; Omsk Regional Clinical Hospital, n = 305; State Budget Institution of Healthcare “Kemerovo Regional Clinical Hospital”, n = 224; Department of Neurology and Neurosurgery, Siberian State Medical University, Federal Agency for Health and Social Development (Tomsk), n = 152; Territorial Clinical Hospital (Barnaul), n = 146; Novosibirsk Regional State Clinical Hospital, n = 248; and Republican Hospital No. 2 of the Ministry of Health of the Republic of Sakha, n = 101.
The control group included individuals (n = 879) without inflammatory diseases of the central nervous system living in Novosibirsk (n = 567), Barnaul (n = 118), Moscow (n = 112), Yakutsk (n = 60), and Omsk (n = 22). The group consisted of 346 men and 533 women (mean age±SD = 33.0±12.0 years).
This study was approved by the ethics committees of all participating centers. All participants signed a written informed consent.
Selection of SNPs
The CD40 region has two blocks of linkage disequilibrium (LD) according to the result of the HapMap 3 panel for Utah residents of Northern and Western European descent and for Toscans in Italy (Fig. 1). In our study, we selected the following four SNPs: rs6074022 and rs1883832 from the first block of LD, rs11086998 from the second block, as well as rs1535045 from the space between the two blocks.
According to the result of the HapMap Project (v.3). union panel for Utah residents with Northern and Western European (CEU) and Toscans in Italy (TSI). SNPs from our study are shown in red frame.
The two SNPs previously associated with MS lie in the first block of LD. SNP rs6074022 T->C was associated with MS at a genome-wide suggestive level (p = 1.3×10−7) . SNP rs1883832 C->T is located in the −1 position relative to the start of the transcription of CD40 gene. In previous candidate gene studies, the association of the minor allele T of SNP rs1883832 with a number of diseases has been examined. Such diseases include lymphoma , non-Hodgkins lymphoma , osteoporosis , multiple sclerosis , Crohn's disease , sporadic breast cancer , Behcet's syndrome , and rheumatoid arthritis .
In the second block, we selected SNP rs11086998 based on its potential function. The presence of minor G allele in rs11086998 leads to a proline-to-alanine substitution (P227A) in the intracellular region of CD40. The P227A site is 3 amino acid residues proximal to the TRAF6 binding site, and leds to increased TNF-α and IL-6 production in murine cell lines . Notably, the rs11086998[G] allele has rather different frequencies in different ethnic groups, from 29% in Mexicans and South Americans to <2% in others. SNP rs1535045 was chosen to tag the gap between the two blocks of LD.
DNA was extracted from venous blood using standard procedures, including selection and lysis of blood cells, the hydrolysis of proteins with proteinase K, DNA purification by extraction with phenol-chloroform, and the DNA precipitated with ethanol. Genotyping of SNPs rs6074022, rs1883832, rs1535045 and rs11086996 was performed by TaqMan real-time PCR (ICBFM SB RAS, Novosibirsk, Russia).
Statistical data analysis
Tests for the Hardy-Weinberg equilibrium were performed using the DeFinetti program available from the website of the Institute of Human Genetics (Munich, Germany; http://ihg2.helmholtz-muenchen.de/cgi-bin/hw/hwa1.pl). Associations of genotype with the disease was studied using logistic regression analysis, as implemented in “glm” function of the R package for statistical analysis (www.r-project.org). The likelihood ratio test (LRT) was used to test the statistical hypotheses and the Akaike Information Criterion (AIC) was used to decide on “best model” describing the association of MS with SNPs. Meta-analysis and Q-test were carried out using the ‘rmeta' package for R (http://cran.r-project.org/web/packages/rmeta/rmeta.pdf). Haplotype analysis was carried out using the ‘haplo.stats' package for R (http://cran.r-project.org/web/packages/haplo.stats/haplo.stats.pdf). Results were considered statistically significant for all statistical calculations if P<0.05.
We determined the genotypes of rs6074022, rs1883832, rs1535045, and rs11086996 in patients with MS and in the control group (Table 1). The call rate was≥99.9% for all SNPs. Five patients were excluded from further analysis because of missing data in at least one locus. Genotypic distribution did not significantly deviate from the Hardy–Weinberg equilibrium expectations for all four studied SNPs in the MS and control groups. The Q-test for heterogeneity of the minor allele frequency between sub-samples from different cities did not show significant differences (Table S1).
Analysis of the associations of MS was performed using logistic regression under the additive, dominant, recessive, and genotypic (two degrees of freedom, 2df) models (Table 1). Two SNPs were significantly associated with MS: rs6074022 (additive model C allele OR = 1.27, 95% CI = [1.12–1.45], p = 3×10−4) and rs1883832 (additive model T allele OR = 1.20, 95% CI = [1.05–1.38], p = 7×10−3). According to the Akaike information criterion (AIC) for each of these SNPs, the additive model was the best. Neither rs1535045 nor rs11086998 was associated with MS.
Additionally, we performed stratified analysis to exclude a potential confounding by genetic substructure in our study. Sub-samples from each city were assigned a stratum in the stratified analysis (Figure S1). The summary OR, its 95% confidence interval, significant level, and p-level of heterogeneity are shown in Table S2 for each SNP. The results of stratified analysis were in accordance with the association analysis in the entire group. Despite the smaller sample size (the Kemerovo and Tomsk groups were excluded in the meta-analysis because they contained only cases), we observed in the joint analysis that rs6074022 (p = 0.02) and rs1883832 (p = 4×10−3) were associated with MS. The risk alleles were the same as those found in the association analysis in the entire group.
We also analyzed the association of clinical sub-phenotypes of MS (RRMS, PPMS, SPMS, and CIS) with all SNPs (Table S3). After correction for multiple testing RRMS–the most common sub-type–was associated with rs6074022 (OR = 1.26, p = 0.0008) and with rs1883832 (OR = 1.24, p = 0.003).
We performed a haplotype analysis for rs6074022 and rs1883832. The haplotype frequency, OR, its 95% confidence interval, and significant level are shown in Table 2. Two haplotypes were associated with MS: rs6074022[C]-rs1883832[C] (OR = 2.38, 95% CI = 1.76–3.22, empirical p = 1.8×10−8) and rs6074022[T]-rs1883832[T] (OR = 2.68, 95% CI = 1.79–4.02, empirical p = 1.7×10−6).
We estimated the LD between the studied SNPs of CD40 gene (Figure S2). Relatively high values of D′ were detected in all SNP pairs. However, the r2 between SNPs was weak at <0.1, except for rs6074022-rs1883832 (r2 = 0.59).
We used the LRT to compare three models of association of rs6074022 and rs1883832 with MS: the general model (where we estimated the effects of genotypes of both SNPs rs1883832 and rs6074022) and two nested (effects estimated for only one SNP). According to the LRT, the nested model including rs6074022 only did not significantly differ from the more general model, including both SNPs rs6074022 and rs1883832 (p = 0.99), whereas the nested model including rs1883832 only was significantly worse than the general model (p = 0.01). The model including rs6074022 only was also the best according to the AIC (AIC = 3284.4, 3282.4, and 3288.4 for the general, rs6074022, and rs1883832 models, respectively). We conclude that the association of MS with the CD40 locus can be described in terms of the involvement of rs6074022 only.
We also performed a meta-analysis of our results with previously published data on the association between rs6074022 and MS: GenMSA (NL), GenMSA (US), GenMSA (CH) , IMSGC (UK), IMSGC (US) , BWH/TT , and ANZgene . Table 3 summarizes the results of previous studies used for this meta-analysis. In the meta-analysis (Figure 2), the total OR for all studies was 1.17 (95% CI = 1.10–1.23) with a statistical significance of p = 2.24×10−12. The heterogeneity test (Q-test) did not find significant differences between the studies (χ2 (7) = 12.16, p = 0.10). These data confirmed the association of marker locus rs6074022 and MS at a level of significance accepted for GWASs.
Abbreviation: GenMSA (NL), GenMSA (US), GenMSA (CH), IMSGC (UK), IMSGC (US), BWH/TT, and ANZgene. In the meta-analysis the total OR for all studies was 1.17 (95% CI = 1.10–1.23) with a statistical significance of p = 2.24×10−12. The heterogeneity test (Q-test) did not find significant differences between the studies (χ2 (7) = 12.16, p = 0.10).
CD40-CD40L is reportedly a common link in the pathogenesis of autoimmune diseases. This hypothesis is supported by the established role of the CD40–CD40L interaction in the development of several autoimmune conditions in animal models – and by the association of CD40 SNPs with the risk for a number of autoimmune diseases –. Moreover, the successfully completed Phase 1 of the clinical trial of SLE treatment by CD40L (http://www.biogenidec.com/research_product_pipeline.aspx?ID=5778) provides evidence of the important role of the CD40–CD40L interaction in the pathogenesis of SLE. The CD40–CD40L interaction is known to result in the switch to antigen-specific Th2 type response . Therefore, the CD40–CD40L complex is an extremely attractive and promising target for the development of drugs for suppressing autoimmune attack. However, for the successful creation of drugs, the molecular mechanism underlying the initiation of autoimmune inflammation through CD40–CD40L in humans must be studied.
In this work, we aimed to replicate in the Russian population the previously reported association of rs6074022[C] with MS . We observed a statistically significant association of the allele rs6074022[C] with the development of MS (per C allele OR = 1.27, CI = 1.12–1.45, p = 3×10−4). Our results were in accordance with those of ANZgene (Table S4). The minor allele C of rs6074022 had a similar frequency both in the case and control groups. Also, the minor allele was the risk-associated allele in both studies. SNP rs1883832 was less significantly associated with MS than rs6074022 in both studies.
In a previous meta-analysis of GWASs, rs6074022 has been implicated at a suggestive level at most . In the meta-analysis of our results and the results of four previous studies, we obtain the association p-value of 2.24×10−12, which confirmed the association between MS and rs6074022 at a genome-wide significant level.
Our findings of the association between MS and CD40 gene are in accordance with the hypothesis of the autoimmune nature of MS. However, the molecular mechanism underlying the involvement of SNPs of CD40 gene in the autoimmune processes was unclear for MS and other autoimmune diseases. The first step in solving this problem is to determine functional SNPs in the gene.
Haplotype analysis revealed two haplotypes associated with MS: rs6074022[C]-rs1883832[C] (OR = 2.38, 95% CI = 1.76–3.22, empirical p = 1.8×10−8) and rs6074022[T]-rs1883832[T] (OR = 2.68, 95% CI = 1.79–4.02, empirical p = 1.7×10−6). Each haplotype contains one of the “risk” alleles as identified in single-SNP analyses. Interestingly, the haplotype containing both risk alleles was not associated with MS in our analysis. We can speculate that this finding is consistent with the hypothesis of two functional polymorphisms located close to the marker SNPs, one increasing the risk of developing MS whereas the second being protective.
In our study, both SNPs rs6074022 and rs1883832 were significantly associated with MS (per C allele OR = 1.27, CI = 1.12–1.45, p = 3×10−4; per T allele OR = 1.20, CI = 1.05–1.38, p = 7×10−3). We also demonstrated that the model including rs6074022 only sufficiently described the association. A large proportion of polymorphisms located in the same block of LD with a causal variant are likely to show an association with a disease. However, the polymorphisms that are in greater LD with the functional variant should on average have a stronger association. From our analysis, we can speculate that the association between rs1883832 and MS is induced by LD, whereas rs6074022 is a marker in stronger LD with the functional variant or is the functional variant itself. We may speculate that the functional variant(s) is likely to be located in the upstream region of the gene CD40 and is in higher LD with rs6074022 than with rs1883832.
Our results confirmed the association of SNP rs6074022 with the risk of MS development. Our estimates suggeste that the functional variant(s) is located in the upstream region of the gene. Further empirical studies are required to find the functional variant.
Stratified analysis. Stratified analysis for rs6074022., B. Stratified analysis for rs1883832, C. Stratified analysis for rs1535045, D. Stratified analysis for rs1186998. Abbreviations: Nsk–Novosibirsk.
LD between the studied SNPs of CD40 gene.
Minor allele frequency in control sub-groups from different cities.
Results of stratified analysis of association between MS and SNPs from CD40 gene. Significant associations are shown in italic and bold. Abbreviations: 95% CI, 95% confidence interval; OR, odds ratio; NA, not applicable; Heterogeneity p-value-p-value of test of heterogeneity (Q-test).
Analysis of association between the clinical sub-phenotypes of MS with SNPs. Abbreviations: OR, odds ratio, RRMS-relapsing remitting multiple sclerosis, PPMS-primary progressive multiple sclerosis, SPMS-secondary-progressive multiple sclerosis, CIS-clinically isolated syndrome. Significant association are shown in bold.
Conceived and designed the experiments: YSA MLF ANB. Performed the experiments: EAS. Analyzed the data: YSA EAS. Contributed reagents/materials/analysis tools: NAM DSK ASR AVK EVK RAD FAP TYP EGA NNZ VMA MAT IVS SAE AVP VPP OGK EYT OOF SGS NYL NFP EVP EIG ANB. Wrote the paper: YSA EAS MLF.
- 1. Baranzini SE, Wang J, Gibson RA, Galwey N, Naegelin Y, et al. (2009) Genome-wide association analysis of susceptibility and clinical phenotype in multiple sclerosis. Human molecular genetics 18: 767–778.
- 2. De Jager PL, Jia X, Wang J, De Bakker PIW, Ottoboni L, et al. (2009) Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci. Nature genetics 41: 776–782.
- 3. Hafler DA, Compston A, Sawcer S, Lander ES, Daly MJ, et al. (2007) Risk alleles for multiple sclerosis identified by a genomewide study. The New England journal of medicine 357: 851–862.
- 4. Aulchenko YS, Hoppenbrouwers IA, Ramagopalan SV, Broer L, Jafari N, et al. (2008) Genetic variation in the KIF1B locus influences susceptibility to multiple sclerosis. Nature genetics 40: 1402–1403.
- 5. Comabella M, Craig DW, Camiña-Tato M, Morcillo C, Lopez C, et al. (2008) Identification of a novel risk locus for multiple sclerosis at 13q31.3 by a pooled genome-wide scan of 500,000 single nucleotide polymorphisms. PloS one 3: e3490.
- 6. Jakkula E, Leppä V, Sulonen A-M, Varilo T, Kallio S, et al. (2010) Genome-wide association study in a high-risk isolate for multiple sclerosis reveals associated variants in STAT3 gene. American journal of human genetics 86: 285–291.
- 7. The Australia and New Zealand Multiple Sclerosis Genetics Consortium (2009) Genome-wide association study identifies new multiple sclerosis susceptibility loci on chromosomes 12 and 20. Nature genetics 41: 824–828.
- 8. Matesanz F, González-Pérez A, Lucas M, Sanna S, Gayán J, et al. (2012) Genome-wide association study of multiple sclerosis confirms a novel locus at 5p13.1. PloS one 7: e36140.
- 9. Martinelli-Boneschi F, Esposito F, Brambilla P, Lindström E, Lavorgna G, et al. (2012) A genome-wide association study in progressive multiple sclerosis. Multiple sclerosis (Houndmills, Basingstoke, England) 18: 1384–1394.
- 10. Sanna S, Pitzalis M, Zoledziewska M, Zara I, Sidore C, et al. (2010) Variants within the immunoregulatory CBLB gene are associated with multiple sclerosis. Nature genetics 42: 495–497.
- 11. Diekstra FP, Saris CGJ, Van Rheenen W, Franke L, Jansen RC, et al. (2012) Mapping of gene expression reveals CYP27A1 as a susceptibility gene for sporadic ALS. PloS one 7: e35333.
- 12. Nischwitz S, Cepok S, Kroner A, Wolf C, Knop M, et al. (2010) Evidence for VAV2 and ZNF433 as susceptibility genes for multiple sclerosis. Journal of neuroimmunology 227: 162–166.
- 13. Briggs FB, Shao X, Goldstein BA, Oksenberg JR, Barcellos LF DJP (2011) Genome-wide association study of severity in multiple sclerosis. Genes and immunity 12: 615–625.
- 14. Burton PR, Clayton DG, Cardon LR, Craddock N, Deloukas P, et al. (2007) Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants. Nature genetics 39: 1329–1337.
- 15. Sawcer S, Hellenthal G, Pirinen M, Spencer CCa, Patsopoulos Na, et al. (2011) Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature 476: 214–219.
- 16. Vazgiourakis VM, Zervou MI, Choulaki C, Bertsias G, Melissourgaki M, et al. (2011) A common SNP in the CD40 region is associated with systemic lupus erythematosus and correlates with altered CD40 expression: implications for the pathogenesis. Annals of the rheumatic diseases 70: 2184–2190.
- 17. Orozco G, Eyre S, Hinks A, Ke X, Wilson AG, et al. (2010) Association of CD40 with rheumatoid arthritis confirmed in a large UK case-control study. Annals of the rheumatic diseases 69: 813–816.
- 18. Blanco-Kelly F, Matesanz F, Alcina A, Teruel M, Díaz-Gallo LM, et al. (2010) CD40: novel association with Crohn's disease and replication in multiple sclerosis susceptibility. PloS one 5: e11520.
- 19. Jacobson EM, Concepcion E, Oashi T, Tomer Y (2005) A Graves' disease-associated Kozak sequence single-nucleotide polymorphism enhances the efficiency of CD40 gene translation: a case for translational pathophysiology. Endocrinology 146: 2684–2691.
- 20. Balasa B, Krahl T, Patstone G, Lee J, Tisch R, et al. (1997) CD40 ligand-CD40 interactions are necessary for the initiation of insulitis and diabetes in nonobese diabetic mice. Journal of immunology (Baltimore, Md/: 1950) 159: 4620–4627.
- 21. Grammer AC, Slota R, Fischer R, Gur H, Girschick H, et al. (2003) Abnormal germinal center reactions in systemic lupus erythematosus demonstrated by blockade of CD154-CD40 interactions. The Journal of clinical investigation 112: 1506–1520.
- 22. Durie FH, Fava RA, Foy TM, Aruffo A, Ledbetter JA, et al. (1993) Prevention of collagen-induced arthritis with an antibody to gp39, the ligand for CD40. Science (New York, NY) 261: 1328–1330.
- 23. Kyburz D, Carson DA, Corr M (2000) The role of CD40 ligand and tumor necrosis factor alpha signaling in the transgenic K/BxN mouse model of rheumatoid arthritis. Arthritis and rheumatism 43: 2571–2577.
- 24. Barbé-Tuana FM, Klein D, Ichii H, Berman DM, Coffey L, et al. (2006) CD40-CD40 ligand interaction activates proinflammatory pathways in pancreatic islets. Diabetes 55: 2437–2445.
- 25. Gerritse K, Laman JD, Noelle RJ, Aruffo A, Ledbetter JA, et al. (1996) CD40-CD40 ligand interactions in experimental allergic encephalomyelitis and multiple sclerosis. Proceedings of the National Academy of Sciences of the United States of America 93: 2499–2504.
- 26. Denfeld RW, Hollenbaugh D, Fehrenbach A, Weiss JM, Von Leoprechting A, et al. (1996) CD40 is functionally expressed on human keratinocytes. European journal of immunology 26: 2329–2334.
- 27. Toubi E, Shoenfeld Y (2004) The role of CD40-CD154 interactions in autoimmunity and the benefit of disrupting this pathway. Autoimmunity 37: 457–464.
- 28. McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, et al. (2001) Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Annals of neurology 50: 121–127.
- 29. Skibola CF, Nieters A, Bracci PM, Curry JD, Agana L, et al. (2008) A functional TNFRSF5 gene variant is associated with risk of lymphoma. Blood 111: 4348–4354.
- 30. Nieters A, Bracci PM, De Sanjosé S, Becker N, Maynadié M, et al. (2011) A functional TNFRSF5 polymorphism and risk of non-Hodgkin lymphoma, a pooled analysis. International journal of cancer Journal international du cancer 128: 1481–1485.
- 31. Pineda B, Tarín JJ, Hermenegildo C, Laporta P, Cano A, et al. (2011) Gene-gene interaction between CD40 and CD40L reduces bone mineral density and increases osteoporosis risk in women. Osteoporosis international/: a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA 22: 1451–1458.
- 32. Shuang C, Dalin L, Weiguang Y, Zhenkun F, Fengyan X, et al. (2011) Association of CD40 gene polymorphisms with sporadic breast cancer in Chinese Han women of Northeast China. PloS one 6: e23762.
- 33. Chen F, Hou S, Jiang Z, Chen Y, Kijlstra A, et al. (2012) CD40 gene polymorphisms confer risk of Behcet's disease but not of Vogt-Koyanagi-Harada syndrome in a Han Chinese population. Rheumatology (Oxford, England) 51: 47–51.
- 34. Liu R, Xu N, Wang X, Shen L, Zhao G, et al. (2012) Influence of MIF, CD40, and CD226 polymorphisms on risk of rheumatoid arthritis. Molecular biology reports 39: 6915–6922.
- 35. Peters AL, Plenge RM, Graham RR, Altshuler DM, Moser KL, et al. (2008) A novel polymorphism of the human CD40 receptor with enhanced function. Blood 112: 1863–1871.
- 36. MacDonald AS, Straw AD, Dalton NM, Pearce EJ (2002) Cutting edge: Th2 response induction by dendritic cells: a role for CD40. Journal of immunology (Baltimore, Md/: 1950) 168: 537–540.
- 37. Patsopoulos NA, Esposito F, Reischl J, Lehr S, Bauer D, et al. (2011) Genome-wide meta-analysis identifies novel multiple sclerosis susceptibility loci. Annals of neurology 70: 897–912.