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Contribution of CD24 polymorphisms to autoimmune disease: A meta-analysis
Computers in Biology and Medicine, September 2015, Pages 268 - 275
To determine the relationship between two CD24 polymorphisms, rs8734/rs52812045 and rs3838646, and autoimmune disease.
The Medline, EMBASE, Web of Science, and Cochrane Library databases were searched for studies reporting the association between CD24 polymorphisms and autoimmune disease. Two of the authors selected eligible studies and extracted and analyzed the data independently.
Compared with carriers of the C allele (CC, CT, CT+CC), individuals homozygous for the T allele (TT) and heterozygous (CT+TT) at rs8734/rs52812045 have a higher incidence of autoimmune disease, whereas rs3838646 is not associated with autoimmune disease. Subgroup analysis found an increased risk of multiple sclerosis with the TT vs. CC, TT vs. CT, and TT vs. CC+CT alleles.
The CD24 polymorphism rs8734/rs52812045 contributes to the development of autoimmune disease.
- CD24 polymorphism, rs8734/rs52812045 is associated with autoimmune disease.
- T allele carriers have a higher risk of autoimmune diseases than C allele carriers.
- CD24 polymorphism, rs3838646 is not associated with autoimmune diseases.
Keywords: CD24, Polymorphism, Genetic variants, Autoimmune disease, Meta-analysis.
Autoimmune disease occurs when the immune system produces antibodies against the body׳s own tissues  and . Although many archetypes exist, autoimmune disease is classified into two major categories: tissue-specific and non-tissue-specific. Multiple sclerosis (MS), autoimmune thyroid diseases such as Grave׳s disease and Hashimoto׳s thyroiditis, and inflammatory bowel diseases including Crohn׳s disease (CD) and ulcerative colitis (UC) are tissue specific, whereas systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), sarcoidosis, systemic sclerosis, and giant cell arteritis are non-tissue-specific autoimmune diseases  .
The pathogenesis and factors affecting the severity of autoimmune disease are elusive, but numerous reports have suggested their association with genetic and environmental factors , , , , and . Because the occurrence of MS, SLE, UC, and RA is linked with familial clustering and the frequency of monozygotic twins, the presence of genetic factors has drawn attention, and many studies have reported associations between autoimmune disease and genetic polymorphisms , , and . For example, relationships between the following autoimmune diseases and specific genes have been examined: autoimmune thyroid disease and interleukin-5 (IL-5), IL-6, and IL-13; CD and the IL-23 receptor gene, NOD2, and PTPN2; UC and NOD2, human leukocyte antigen-DR (HLA-DR), and PTPN2; MS and HLA-DRB1, HLA-DR2, the IL-2 receptor gene, and IL-1; and RA and IL-18, IRF5, and PTPN22, , , , , , , , , and .
CD24, or heat-stable antigen, is a small, highly glycosylated glycophosphatidylinositol-anchored cell surface protein  . CD24 is expressed in most hematopoietic cells, including activated T cells, B cells, dendritic cells, macrophages, and mature granulocytes, as well as non-hematopoietic cells such as astrocytes , , , , , and . CD24 was first identified as a lymphoid differentiation marker, but its diverse functions are only now being revealed. For example, it promotes the differentiation and activation of B cells and the activation and clonal expansion of T cells , , and . It also functions as a checkpoint for T-cell homeostasis by protecting autoreactive T cells from clonal deletion and by maintaining T cells during their migration to the central nervous system  and . When overexpressed in solid tumors, CD24 acts as an adhesion molecule in endothelial cells; promotes the proliferation, metastasis, and dissemination of tumor cells; and affects survival rates in cancer patients , , and . Furthermore, many in vivo studies have reported the association of CD24 with autoimmune disease. CD24 is required for the induction of experimental autoimmune encephalomyelitis (EAE) in an animal model of MS, and thus, EAE induced by myelin-based, protein-pulsed dendritic cells is inhibited when CD24 is down-regulated , , and . In addition, CD24 is upregulated in CD, which increases the colony-forming capability and motility of cells, whereas the initial phase of experimental autoimmune thyroiditis is more severe in CD24-deficient mice  and .
The human CD24 gene is located in the chromosome 6q21 region and comprises a 0.24-kb open reading frame and a 1.8-kb 3′ untranslated region  and . This chromosome is associated with susceptibility to RA, MS, and SLE , , and . Single-nucleotide polymorphisms (SNPs) in CD24 influence the occurrence and seriousness of autoimmune diseases, and all of the SNPs are in linkage disequilibrium , , , and . The currently known SNPs in the CD24 gene are rs1058818, rs1058881, rs1136210, rs1136221, rs3840378, rs3810761, rs3838646, rs3950479, rs4030413, rs4030414, rs4030415, rs6530597, rs6530598, rs6530599, rs6530602, rs6530600, rs6530603, rs7892940, rs10465459, rs10482600, rs10482601, rs11545327, rs11545328, rs11545329, rs1136498, rs7892847, rs35795274, rs7892996, rs7893001, rs7893092, rs34905207, rs6530596, rs8734/rs52812045, rs58481495, rs7892847, rs7892864, rs1059138, and rs1136498 (all of which are found in the National Institutes of Health/National Center for Biotechnology Information SNP database: http://www.ncbi.nlm.nih.gov/projects/SNP/ ).
Among these SNPs, rs8734/rs52812045 and rs3838646 in particular been studied for their association with the onset of autoimmune disease, but studies of polymorphisms in other regions are limited , , , , and . The change in an amino acid from alanine to valine in rs8734/rs52812045, which is a glycophosphatidylinositol-anchor cleavage site (ω-1 position) in CD24 exon 2, upregulates CD24 expression and increases the probability of autoimmune disease  . Dinucleotide deletion of TG at rs3838646 in the human CD24 3′ untranslated region destabilizes the messenger RNA and decreases CD24 expression, which reduces the risk of autoimmune disease  . However, the association of these polymorphisms with autoimmune predisposition is still under debate. Not all case-controlled studies have led to the same conclusions, and the lack of statistical power in most reports has precluded the generation of reliable results. Therefore, we conducted a meta-analysis to obtain comprehensive results.
2. Materials and methods
2.1. Identification and collection of eligible studies
We searched for relevant studies in the Medline (U.S. National Library of Medicine, National Institutes of Health), Web of Science, EMBASE, and Cochrane Library databases using the following words: (“polymorphism” or “genetic polymorphism” or “polymorphism, genetic” or “single nucleotide polymorphism” or “SNP” or “mutation” or “variant”) and (“CD24 antigen” or “CD24” or “antigen, CD24” or “Ly52” or “heat stable antigen” or “ ba-1”). All studies published before November 15, 2014, were available, and there were no language restrictions. All studies reporting associations between CD24 polymorphisms and autoimmune disease risk were retrieved with the exception of several regional reports. In addition, the references cited in retrieved studies were scanned to avoid missing eligible studies.
Studies included in the meta-analysis satisfied the following criteria: (1) the association between CD24 genetic polymorphisms and autoimmune disease was assessed, (2) the odds ratio (OR) with 95% confidence interval (CI) values or adequate data to infer these associations was presented, (3) genotyping and statistical methods were clearly described, and (4) the P values for Hardy–Weinberg equilibrium in the control group were shown or could be calculated. Studies were excluded if they were (1) non-case-control studies, (2) based on partial data, (3) duplicates of previous reports, (4) unassociated with autoimmune disease, or (5) meta-analyses, letters, or reviews. The database search and study selection were performed by two of the authors (J.B. and H.B.) independently.
2.2. Data extraction
The following data were extracted from each study: first author׳s name, publication year, country, subject ethnicity, disease studied, genotyping method, source of the controls, frequency of genotypes, sample size, and P value of Hardy–Weinberg equilibrium and minor allele frequency in the controls.
2.3. Statistical analyses
All statistical tests were performed with Review Manager (version 5.2; The Cochrane Collaboration, Oxford, UK) and Comprehensive Meta-Analysis (Biostat, Englewood, USA) software. ORs with 95% CI were used to assess the strength of the association between the CD24 rs8734/rs52812045 and rs3838646 polymorphisms and autoimmune disease. Fixed- and random-effects models were used to calculate a pooled OR, and the statistical significance (P<0.05) of pooled ORs was determined with the Z-test. Heterogeneity among studies was evaluated with Higgins׳ I2 statistic and the chi-squared-based Q-test. A P value of <0.10 for the Q-test indicated significant heterogeneity, and in this case, the random-effects model was used to calculate pooled ORs; otherwise, the fixed-effects model was used. Publication bias was assessed with either a funnel plot for visual inspection of asymmetry or Egger׳s linear regression test. Sensitivity analysis was performed by extracting a single study each time to check the stability of the result.
The genetic models evaluated for pooled ORs of rs8734/rs52812045 were CT vs. CC, TT vs. CC, TT vs. TC, CT+TT vs. CC, TT vs. CC+CT, and T vs. C. The genetic models for rs3838646 were TGDel vs. TGTG, DelDel vs. TGTG, DelDel vs. TGDel, TGDel+DelDel vs. TGTG, DelDel vs. TGTG+TGDel, and Del vs. TG.
3.1. Study selection and description
A total of 861 studies reporting CD24 polymorphisms were initially retrieved ( Fig. 1 ). After the evaluation of titles and keywords, 795 articles were excluded, and 42 were further excluded via abstract review. The remaining 24 articles were then reviewed more thoroughly based on the inclusion and exclusion criteria, and 14 and 6 articles were finally chosen for the meta-analysis of the CD24 rs8734/rs52812045 and rs3838646 polymorphisms, respectively. All of the data required for analysis were available in the original publications. The autoimmune diseases studied included CD, UC, MS, GD, HD, SLE, and others. All of the DNA samples were extracted from blood, and several genotyping methods were used, including polymerase chain reaction (PCR)-restriction fragment length polymorphism and competitive allele-specific PCR. Table 1 summarizes the characteristics of each report used in the meta-analysis.
|Diaz-Gallo LM 2011 ||Spain||Spanish||CD||AD||ND: HB||200||134||32||317||270||41||0.28||0.10|
|Diaz-Gallo LM 2011 ||Spain||Spanish||UC||AD||ND: HB||161||126||35||317||270||41||0.28||0.59|
|González SJ 2011 ||Argentina||South American||MS||PCR-RFLP||ND: HB||43||50||9||96||91||18||0.31||0.71|
|Goris A 2006 ||UK||Belgium||MS||PCR-RFLP||ND: HB||162||133||39||159||134||29||0.30||0.92|
|Goris A 2006 ||UK||English||MS||SNP||ND: HB||411||361||74||368||380||98||0.34||0.99|
|Inoue N 2013 ||Japan||Asian||GD||PCR-RFLP||ND: HB||61||103||30||48||41||14||0.33||0.28|
|Inoue N 2013 ||Japan||Asian||HD||PCR-RFLP||ND: HB||45||80||19||48||41||14||0.33||0.28|
|Kollaee A 2011 ||Iran||Iranian||MS||PCR-RFLP||PB||56||40||24||63||49||8||0.27||0.71|
|Otaegui D 2006 ||Northern Spain||Spanish||MS||PCR-RFLP||PB||59||69||7||145||136||4||0.25||0.00|
|Piotrowski P 2010 ||Poland||Polish||SLE||PCR-RFLP||HB||91||125||34||166||153||31||0.31||0.61|
|Ronaghi M 2009 ||Iran||Iranian||MS||PCR-RFLP||PB||102||68||47||114||66||20||0.27||0.03|
|Rueda B 2008 ||Northern Spain||Spanish||GCA||AD||ND: HB||53||57||10||93||90||2||0.25||0.00|
|Sánchez E 2007 ||Spain||German||SLE||AD||PB||356||269||71||305||211||23||0.24||0.07|
|Sánchez E 2007 ||Spain||Spanish||SLE||AD||PB||129||105||23||161||138||18||0.27||0.10|
|Sánchez E 2007 ||Spain||Swedish||SLE||AD||PB||141||142||27||117||108||22||0.31||0.68|
|Sánchez E 2008 ||Spain||Spanish||RA||AD||ND: HB||508||431||76||447||372||23||0.25||0.00|
|Tanizawda K 2010 ||Japan||Japanese||Sarcoidosis||PCR-RFLP||HB||71||79||36||52||69||25||0.41||0.80|
|Vidal DD 2009 ||Mexico||Mexican||MS||PCR-RFLP||HB||25||23||2||30||20||0||0.20||0.08|
|Zhou Q 2003 ||USA||American||MS||PCR-RFLP||PB||113||97||32||109||85||13||0.27||0.51|
|Dawidowicz K 2011 ||France||Caucasian||SSc||cast PCR||ND: HB||729||131||5||815||140||9||0.08||0.28|
|Diaz-Gallo LM 2011 ||Spain||Spanish||CD||AD||ND: HB||301||60||10||547||76||6||0.07||0.07|
|Diaz-Gallo LM 2011 ||Spain||Spanish||UC||AD||ND: HB||270||40||0||547||76||6||0.07||0.07|
|González SJ 2011 ||Argentina||South American||MS||PCR-RFLP||ND: HB||94||7||1||182||23||0||0.06||0.39|
|Rueda B 2008 ||Northwest Spain||Spanish||GCA||AD||ND: HB||86||32||1||159||23||3||0.08||0.06|
|Sánchez E 2008 ||Spain||Spanish||RA||AD||ND: HB||859||150||6||727||107||8||0.07||0.07|
|Wang L 2007 ||America||North American||MS||PCR-RFLP||PB||242||32||1||354||84||5||0.11||0.99|
|Wang L 2007 ||America||North American||SLE||PCR-RFLP||PB||240||24||0||214||50||6||0.11||0.14|
3.2. Meta-analysis results
In total, 5906 and 3321 autoimmune disease cases and 6323 and 4167 controls from 14 and 8 case control studies were retrieved for the analysis of CD24 polymorphisms rs8734/rs52812045 and rs3838646, respectively. Evidence of an association between the CD24 rs8734/rs52812045 polymorphism and overall risk of autoimmune disease was observed for every model in the study except CT vs. CC. This result indicated a strong association between the rs8734/rs52812045 polymorphism and autoimmune disease ( Table 2 and Fig 2, Fig 3, and Fig 4). However, none of the models tested showed a significant association between the rs3838646 polymorphism and autoimmune disease ( Table 3 ). In the subgroup analysis, an increased risk of MS was observed for TT vs. CC (OR, 1.82; 95% CI, 1.05–3.82; P=0.03), TT vs. CT (OR, 1.68; 95% CI, 1.06–2.67; P=0.03), and TT vs. CC+CT (OR, 1.76; 95% CI, 1.06–2.92; P=0.03; see Fig 2, Fig 3, and Fig 4). The results of the meta-analysis are summarized in Table 2 and Table 3.
|Polymorphism||Genetic model||Case/control||OR (95% CI)||Z||P||I2 (%)||P Het||P Egg||Effect model|
|rs8734/ rs52812045||CT vs. CC||5279/5879||1.05 (0.95, 1.17)||0.94||0.35||38||0.05||0.115||Random|
|TT vs. CC||3414/3599||1.74 (1.34, 2.27)||4.13||<0.0001||68||<0.00001||0.027||Random|
|TT vs. CT||3119/3168||1.58 (1.24, 2.02)||3.66||0.0003||62||0.0002||0.106||Random|
|CT+TT vs. CC||5906/6323||1.16 (1.04, 1.29)||2.64||0.008||48||0.01||0.014||Random|
|TT vs. CC+CT||5906/6323||1.65 (1.29, 2.11)||3.96||<0.0001||67||<0.0001||0.039||Random|
|T vs. C||11,812/12646||1.20 (1.09, 1.31)||3.76||0.0002||60||0.0005||0.031||Random|
CI, confidence interval; I2, Higgin׳s I2 statistic for heterogeneity; OR, odds ratio; PEgg, P value determined with Egger׳s regression model; PHet, P value determined with Q-test for heterogeneity; Z, test for overall effect.
|Polymorphism||Genetic model||Case/control||OR (95% CI)||Z||P||I2 (%)||P Het||P Egg||Effect model|
|rs3838646||TGDel vs. TGTG||3297/4124||0.98 (0.71, 1.34)||0.13||0.9||79||<0.0001||0.544||Random|
|DelDel vs. TGTG||2845/3588||0.72 (0.31, 1.68)||0.77||0.44||48||0.06||0.297||Random|
|DelDel vs. TGDel||500/622||0.70 (0.34, 1.43)||0.99||0.32||29||0.29||0.488||Random|
|TGDel+DelDel vs. TGTG||3321/4167||0.95 (0.69, 1.32)||0.28||0.78||81||<0.00001||0.535||Random|
|DelDel vs. TGTG+TGDel||3321/4167||0.71 (0.31, 1.63)||0.8||0.42||46||0.08||0.305||Random|
|Del vs. TG||6642/8334||0.93 (0.68, 1.28)||0.43||0.67||83||<0.00001||0.501||Random|
CI, confidence interval; I2, Higgin׳s I2 statistic for heterogeneity; OR, odds ratio; PEgg, P value determined with Egger׳s regression model; PHet, P value determined with Q-test for heterogeneity; Z, test for overall effect.
3.3. Tests for publication bias, sensitivity, and heterogeneity
Publication bias was assessed with funnel plots and Egger׳s test. Funnel plots in which the standard error of the log(OR) of each study was plotted against the associated standard error were visualized ( Fig. 5 ). Some of the funnel plots had an asymmetrical distribution that suggested a possible publication bias. Therefore, Egger׳s test was also performed to confirm the presence of publication bias. The results of Egger׳s test showed that the TT vs. CC (P=0.027), CT+TT vs. CC (P=0.014), and T vs. C (0.031) models had publication bias, whereas the other models did not. The sensitivity analysis indicated no significant change when a single study was excluded from the pooling data. This outcome showed that our results were stable. In addition, a heterogeneity test was performed to determine the similarity among the 14 studies before they were combined for the meta-analysis. The model CT vs. CC (P=0.05; I2=38%) had an insignificant level of heterogeneity, and CT+TT vs. CC (P=0.01; 48%) and T vs. C (P<0.001; I2=60%) showed moderate heterogeneity. The other models showed substantial heterogeneity, with I2 values of >60% as determined by Higgins׳ I2 statistic.
Proper discrimination between self and non-self antigens is critical for balancing immune tolerance and protective immune response. The failure of the immune system to tolerate self-antigens often causes autoimmune disease, which results from a combination of genetic and environmental factors. Multiple genes, including CD28, cytotoxic T-lymphocyte antigen-4, inducible T-cell co-stimulator, HLA, and major histocompatibility antigen, have been shown to impact the onset of autoimmune disease , , and .
CD24 serves as a T-cell costimulatory molecule that regulates homeostasis and proliferation, and recent studies have shown that CD24 polymorphisms may be associated with an increased risk of autoimmune disease. Thirty eight SNPs have been reported, and the affected disease types include CD, UC, MS, GD, HD, and SLE. However, the association of these polymorphisms with autoimmune predisposition remains under debate. Therefore, to produce more precise results, we performed a meta-analysis for the genetic association between CD24 rs8734/rs52812045 and rs3838646 polymorphisms and autoimmune disease. The results demonstrated strong evidence of an association between CD24 rs8734/rs52812045 and autoimmune disease, whereas rs3838646 was not implicated. Among the six genetic models tested, five (TT vs. CC, TT vs. CT, CT+TT vs. CC, TT vs. CC+CT, and T vs. C) showed an association between the CD24 rs8734/rs52812045 polymorphism and autoimmune disease.
In addition, we observed that compared with carriers of the C allele (CC, CT, CT+CC), heterozygous (CT+TT) carriers and individuals homozygous for the T allele (TT) have a higher incidence of autoimmune disease. Furthermore, the subgroup analysis showed an increased risk of MS in the TT vs. CC, TT vs. CT, and TT vs. CC+CT models, which confirmed the results of a recent report by Huang et al.  . Due to the overall increase in the number of studies and sample sizes enrolled, this meta-analysis has greater statistical power and improves on the previous reports.
MS is characterized by demyelination, axonal loss, and inflammation caused by interactions among autoreactive T cells, myelin antigens, and proteolipid proteins  . CD24 is required for the development of EAE in a mouse model, and the induction of CD24 expression in T cells is a key factor in the pathogenesis of MS in humans. The rs52812045 SNP located at CD24 exon 2 changes an amino acid from alanine (CD24a) to valine (CD24v), and compared with the original, the resulting CD24 allele is expressed differentially  . Compared with CD24a complementary DNA, transfected CD24v complementary DNA is expressed at significantly higher levels, and the T cells in the peripheral blood of CD24a/v patients express levels of CD24 that are higher than those in CD24a/a patients, which supports the importance of CD24 in MS risk and progression  . In addition to the SNP in rs52812045, SNPs in the CD24 promoter induce the transcription of CD24 by encoding a promoter for SP1, a transcription factor that has been implicated in the susceptibility to MS and other autoimmune diseases and enhances messenger RNA stability  . Collectively, CD24 variations in both coding and non-coding regions are associated with MS and other autoimmune diseases, and their effects are mostly to enhance disease onset and progression through gain of function mutations, as confirmed by our meta-analysis.
Numerous genome-wide association studies (GWAS) have been conducted to find novel sources of genetic susceptibility to autoimmune diseases , , , , , , and . However, few GWAS have reported the association between CD24 and autoimmune disease, even though many candidate gene analyses have demonstrated the contribution of CD24 SNPs to autoimmune disorders. In addition, the GWAS central database ( www.gwascentral.org ) contains no studies reporting an association between rs8734/rs52812045 and rs3838646 polymorphisms and autoimmune disease. Discrepancies often arise between the results of candidate gene analyses and GWAS findings because current GWAS technology is limited to the detection of low-frequency variants. Candidate gene analysis and GWAS overlapped by less than 10% in a study of cancer by Chang et al.  . Future GWAS with improved features will likely detect genetic associations between CD24 and autoimmune disorders and support the results of this meta-analysis.
The use of different methods to genotype CD24 polymorphisms is potentially problematic. CD24 is located on Chr6q21, but the sequence of CD24 exon 2, which includes the rs8734/rs52812045 and rs3838646 polymorphisms, is also found in pseudogenes on Chr3p26, 15q21, 15q22, 20q11.2, and Yq11.1  and . A nested PCR-restriction fragment length polymorphism was designed to detect CD24 specifically by using a forward primer in intron 1 in the first round of PCR  and . However, TaqMan allelic discrimination assay (AD) directly targets the CD24 exon 2 sequence, which presents the risk of detecting sequences within pseudogenes , , and . To resolve this issue of non-specific detection, we performed another meta-analyses by excluding studies with AD analyses. The results of the new meta-analysis were very similar to those that included studies with AD analysis and suggested the same conclusion (data not shown). Hence, despite the potential problem of including studies with AD analyses, the results of this meta-analysis are statistically reliable.
Other limitations of this study must also be mentioned. We included only published reports, and accordingly, negative or non-significant findings, which are infrequently published, may have been excluded from the analysis, thereby introducing unavoidable publication bias in the results. Furthermore, a sufficient number of studies with diverse ethnic groups and adequate information, such as age and gender, would allow for stratified analyses. Last, gene–gene and gene–environment interactions could not be taken into account in our analysis. Despite these limitations, the results of our meta-analysis suggest that CD24 polymorphism contributes to genetic susceptibility to autoimmune diseases. Nonetheless, additional studies with larger sample sizes are required for a more exact and comprehensive analysis.
Conflict of interests
This research was supported by the Public Welfare & Safety Research Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT, and Future Planning (Grant number 2010-0020842).
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College of Pharmacy, Chung-Ang University, Seoul 156-756, Korea
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