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. 2021 Aug 2;13(15):19397–19414. doi: 10.18632/aging.203349

Association between CTLA-4 gene polymorphism and risk of rheumatoid arthritis: a meta-analysis

Chuankun Zhou 1, Shutao Gao 2, Xi Yuan 1, Zixing Shu 1, Song Li 1, Xuying Sun 1, Jun Xiao 1,✉, Hui Liu 3,✉
PMCID: PMC8386564  PMID: 34339393

Abstract

Cytotoxic T lymphocyte-associated protein 4 (CTLA-4) gene polymorphisms may be involved in the risk of Rheumatoid arthritis (RA). However, evidence for the association remains controversial. Therefore, we performed a meta-analysis to confirm the relationship between CTLA-4 gene polymorphisms and RA. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the strength of association. Stratified analysis was conducted by ethnicity. In total, 66 case-control studies including 21681 cases and 23457 controls were obtained. For rs3087243 polymorphism, significant association was detected in Asians (A vs. G: OR=0.77, 95%CI=0.65-0.90, P=0.001; AA vs. GG: OR=0.67, 95%CI=0.48-0.94, P=0.02) and Caucasians (A vs. G: OR=0.89, 95%CI=0.86-0.93, P<0.00001; AA vs. GG: OR=0.81, 95%CI=0.75-0.88, P<0.00001). For rs231775 polymorphism, significant association was observed in the overall (G vs. A: OR =1.16, 95%CI=1.08-1.25, P<0.0001; GG vs. AA: OR=1.29, 95%CI=1.12-1.50, P=0.0006), and in Asians (G vs. A: OR=1.27, 95%CI=1.10-1.47, P=0.001; GG vs. AA: OR=1.58, 95%CI=1.24-2.01, P=0.0002), but not in Caucasians. However, there was no association between rs5742909 polymorphism and RA. This meta-analysis confirmed that rs3087243 and rs231775 polymorphism were associated with the risk of RA in both overall population and ethnic-specific analysis, but there was no association between rs5742909 polymorphism and RA risk.

Keywords: CTLA-4, polymorphism, rheumatoid arthritis, meta-analysis

INTRODUCTION

Rheumatoid arthritis, one of the most common inflammatory joint diseases in humans, is characterized by inflammation in synovium, destruction of cartilage and bone, generation of autoantibody, and complications of systemic organs [1]. Although RA affects 0.5–1% of the Western populations, the worldwide incidence of RA is increasing with the aging trend of the population [2]. Because of the results of reduced physical function, declined work capacity, decreased quality of life, and increased comorbid risk, RA carries heavy socioeconomic burden [3]. RA is believed to be a consequence of both genetic factors and environmental factors though main etiology has not yet been clearly clarified. In twin studies 50–65% of the risk for developing RA is ascribed to its heritability [4], indicating genetic factors have a strong effect on RA. So far more than one hundred gene loci associated with RA risk have been identified by single nucleotide polymorphisms (SNPs) [5, 6]. Apart from the human leukocyte antigen (HLA) locus, a well-known genetic risk factor for RA, numbers of other susceptibility genes and loci have been characterized [6]. Recently, a growing body of non-HLA genetic predisposition studies have been conducted on the association with the risk of RA [7–9].

Cytotoxic T lymphocyte-associated protein 4 (CTLA-4), one of widely studied non-HLA susceptibility gene of RA, is mainly expressed on the surface of Treg cells and conventional T cells and suppresses self-reactive T cell responses via downregulating ligand availability for the costimulatory receptor CD28 to elicit inhibitory signals [10, 11]. Besides, the polymorphisms of CTLA-4 have already been proved to be candidates of the risk of the common autoimmune diseases at the genetic level [12–15]. As RA is a T cell mediated autoimmune disorder and CTLA-4 plays a vital role in regulating T cell function [11, 12, 16], it suggests that CTLA-4 expression or function is most likely associated with the pathogenesis of RA. Single nucleotide polymorphisms in the CTLA-4 gene may contribute to abnormal levels of CTLA-4, and subsequently play a leading part in the susceptibility to RA [12, 17, 18].

Among the identified SNPs in this gene, these three loci of CTLA-4, +49A/G (rs231775), -318C/T (rs5742909) and CT60 G/A(rs3087243), are most-often studied for the association with the predisposition of RA [18–20]. However, the conclusions which previous reports drew are inconsistent and incomprehensive. Although the association of CTLA-4 genetic polymorphisms and the risk of RA has been assessed in several meta-analyses [21–23], some recent studies also described this association in different populations in the past several years [9, 15, 24–27]. Hence these studies should be included to increase statistical power and obtain the reliable conclusion. On the other hand, all the three common loci should be included to embody the association comprehensively while the previous meta-analysis only researched one or two of the above loci. In view of these, it is necessary to incorporate the latest research into investigating the association of the three polymorphisms of CTLA-4 with susceptibility to RA. Here we use the latest case-control data to carry out an updated and comprehensive meta-analysis and obtain a more accurate estimation of the effect of the 3 SNPs (+49A/G (rs231775), CT60 G/A(rs3087243) and -318 C/T (rs5742909)) on RA risk.

RESULTS

Characteristics of the studies

Based on the predetermined inclusion criteria, 66 eligible case–control studies with 42 articles were enrolled ultimately in the current analysis [8, 9, 13–15, 17–20, 24–56]. These publications had a high methodological quality whose NOS stars were more than 6 in general. There were 22 studies with 16394 patients and 17453 controls for rs3087243 SNP [8, 9, 13–15, 18, 19, 26, 40, 41, 43, 46–49, 52, 53, 56], 34 studies with 11452 patients and 12444 controls for rs231775 SNP [9, 14, 17, 19, 20, 24, 25, 28–39, 41–45, 49–51, 54], and 10 studies with 2477 patients and 2941 controls for rs5742909 SNP [14, 20, 27, 29, 34, 37–39, 44, 56]. The references of all enrolled articles were subject to scrutiny and no more ones were available. The process of study selection according to the PRISMA principle was generalized in Figure 1. Quality assessment of included studies was shown in Supplementary Table 1. Details of included studies were listed in Table 1. Allele/genotype frequencies were displayed in Table 2.

Figure 1.

Figure 1

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Flow diagram of the literature retrieval and screen.

Table 1. Main characteristics of included studies.

Study Year Country Ethnicity Numbers Genotype
method 		Diagnostic criteria Quality
score
RA Con
Rs3087243(CT60)
Orozco 2004 Spain Caucasian 433 398 TaqMan ACR1987 7
Lei 2005 China Asian 326 250 DGGE ACR1987 8
Plenge (EIRA) 2005 Sweden European 1505 878 MALDI-TOF ACR1987 8
Plenge (NARAC) 2005 Sweden European 828 845 MALDI-TOF ACR1987 8
Zhernakova 2005 Dutch Caucasian 153 900 PCR-RFLP ACR1987 6
Suppiah 2006 Northern Ireland Caucasian 289 168 PCR-RFLP ACR1987 7
Costenbader 2008 USA Caucasian 423 420 TaqMan ACR1987 7
Tsukahara 2008 Japan Asian 1498 441 TaqMan ACR1987 8
Kelley 2009 USA African 505 712 TaqMan ACR1987 7
Daha 2009 Dutch Caucasian 867 863 Sequenom ACR1987 7
Barton 2009 UK European 3669 3049 TaqMan ACR1987 8
Walker 2009 Canada Caucasian 1140 1248 Sequenom ACR1987 8
Plant (1) 2010 France Caucasian 671 177 Sequenom ACR1987 8
Plant (2) 2010 Germany Caucasian 218 209 Sequenom ACR1987 8
Plant (3) 2010 Greece Caucasian 268 290 Sequenom ACR1987 8
Plant (4) 2010 UK Caucasian 1002 2725 Sequenom ACR1987 8
Danoy 2011 China Asian 1035 1702 Sequenom ACR1987 7
Torres-Carrillo 2013 Mexico Latin American 200 200 PCR–RFLP ACR1987 8
Luterek-Puszyńska 2016 Poland Caucasian 422 338 TaqMan ACR1987 7
Schulz 2020 Germany Caucasian 111 256 PCR–RFLP ACR2010 6
El-Gabalawy 2011 Canada Caucasian 332 490 Sequenom ACR1987 6
Vernerova 2016 Slovakia Caucasian 499 894 TaqMan ACR2010 9
Rs231775(49G/A)
AIFadhli 2013 Kuwait Asian 114 282 PCR–RFLP ACR1987 6
Barton (I) 2000 Spain Caucasian 136 144 PCR–RFLP ACR1987 7
Barton (II) 2000 UK Caucasian 192 96 PCR–RFLP ACR1987 7
Benhatchi 2011 Slovakia Caucasian 57 51 PCR–RFLP ACR1987 6
Elshazli 2015 Egypt Caucasian 112 122 PCR–RFLP ACR1987 6
Feng 2005 China Asian 50 60 PCR–RFLP ACR1987 6
Gonzalez-Escribano 1999 Spain Caucasian 138 305 PCR-ARMS ACR1987 6
Hadj 2001 Tunisia African 60 150 PCR–RFLP ACR1987 7
Lee 2002 2002 Korea Asian 86 86 PCR–RFLP ACR1987 6
Lee 2003 2003 China Asian 186 203 PCR–RFLP ACR1987 6
Lei 2005 China Asian 326 250 DGGE ACR1987 8
Liu 2004 2004 Taiwan Asian 65 81 PCR–RFLP ACR1987 6
Barton 2004 UK European 132 156 TaqMan ACR1987 7
Liu 2013 2013 China Asian 213 303 PCR–RFLP ACR1987 7
Luterek-Puszyńska 2016 Poland Caucasian 422 338 TaqMan ACR2010 7
Matsushita 1999 Japan Asian 461 150 PCR-SSCP ACR1987 7
Milicic 2001 UK Caucasian 421 452 PCR–RFLP ACR1987 8
Miterski 2004 Germany Caucasian 284 362 PCR–RFLP ACR1987 7
Munoz-Valle 2010 Mexico Mexican 199 199 PCR–RFLP ACR1987 6
Plant (1) 2010 France Caucasian 684 162 Sequenom ACR1987 8
Plant (2) 2010 Germany European 220 209 Sequenom ACR1987 8
Plant (3) 2010 Greece European 272 287 Sequenom ACR1987 8
Plant (4) 2010 UK European 1004 2659 Sequenom ACR1987 6
Seidl 1998 Germany Caucasian 258 456 RFLP-SSCP ACR1987 8
Suppiah 2006 UK European 289 475 PCR–RFLP ACR1987 7
Takeuchi 2006 Japan Asian 100 104 PCR–RFLP ACR1987 6
Tang 2013 China Asian 1489 1200 TaqMan ACR1987 8
Tsukahara 2008 Japan Asian 1490 448 TaqMan ACR1987 8
Kelley 2009 USA African 505 712 TaqMan ACR1987 7
Vaidya 2002 UK Caucasian 123 349 PCR–RFLP ACR1987 6
Walker 2009 Canada Caucasian 1140 1248 Sequenom ACR1987 8
Yanagawa 2000 Japan Asian 85 200 PCR–RFLP ACR1987 6
Zhou 2007 China Asian 39 44 PCR–RFLP ACR1987 6
Sameem 2015 Pakistani Asian 100 100 PCR–RFLP RF test 6
Rs5742909 (318C/T)
Gonzalez-Escribano 1999 Spain Caucasian 138 305 PCR-ARMS ACR1987 6
Lee 2002 2002 Korea Asian 86 86 PCR–RFLP ACR1987 6
Barton 2004 UK European 151 152 TaqMan ACR1987 7
Liu 2004 2004 Tainan Asian 65 81 PCR–RFLP ACR1987 6
Miterski 2004 Germany Caucasian 284 362 PCR–RFLP ACR1987 7
Takeuchi 2006 Japan Asian 100 104 PCR–RFLP ACR1987 6
Walker 2009 Canada Caucasian 1140 1248 Sequenom ACR1987 8
Liu 2013 2013 China Asian 213 303 PCR–RFLP ACR1987 7
Torres-Carrillo 2013 Mexico Latin American 200 200 PCR–RFLP ACR1987 7
Fattah 2017 Egypt Caucasian 100 100 PCR–RFLP ACR2010 6
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Table 2. Distribution of genotype and allele among RA patients and controls.

Study Cases Controls HEW
MM Mm mm M m MM Mm mm M m
Rs3087243(CT60)
Orozco 118 198 117 434 432 98 199 101 395 401 YES
Lei 33 137 156 203 449 32 131 87 195 305 YES
Plenge (EIRA) 230 680 595 1140 1870 145 396 337 686 1070 YES
Plenge (NARAC) 133 387 308 653 1003 165 426 254 756 934 YES
Zhernakova NA NA NA 133 173 NA NA NA 841 959 NA
Suppiah NA NA NA 234 344 NA NA NA 145 191 NA
Costenbader 82 201 140 365 481 87 195 138 369 471 YES
Tsukahara 87 538 873 712 2284 33 163 245 229 653 YES
Kelley NA NA NA NA 505 NA NA NA NA 712 NA
Daha NA NA NA 729 1005 NA NA NA 785 941 NA
Barton 677 1760 1232 3114 4224 634 1523 892 2791 3307 YES
Walker 207 518 415 932 1348 273 613 362 1159 1337 YES
Plant (1) 131 332 208 594 748 45 91 41 181 173 YES
Plant (2) 35 105 78 175 261 35 101 73 171 247 YES
Plant (3) 55 135 78 245 291 70 145 75 285 295 YES
Plant (4) 204 487 311 895 1109 542 1344 839 2428 3022 YES
Danoy NA NA NA 310 1760 NA NA NA 681 2723 NA
Torres-Carrillo 31 86 83 148 252 32 106 62 170 230 YES
Luterek-Puszyńska 53 193 176 299 545 45 174 119 264 412 YES
Schulz 13 49 49 75 147 42 124 90 208 304 YES
El-Gabalawy 45 161 126 251 413 66 226 198 358 622 YES
Vernerova NA NA NA 616 382 NA NA NA 1064 1064 NA
Rs231775(49G/A)
AIFadhli 10 30 74 50 178 14 86 182 114 450 YES
Barton (I) 14 57 65 85 187 12 70 62 94 194 YES
Barton (II) 38 86 68 162 222 19 51 26 89 103 YES
Benhatchi 6 33 18 45 69 5 25 21 35 67 YES
Elshazli 14 55 43 83 141 6 45 71 57 187 YES
Feng 20 21 9 61 39 9 32 19 50 70 YES
Gonzalez-Escribano 10 63 65 83 193 30 103 172 163 447 NO
Hadj 23 27 10 73 47 68 62 20 198 102 YES
Lee 2002 41 35 10 117 55 49 29 8 127 45 YES
Lee 2003 103 67 16 273 99 85 100 18 270 136 YES
Lei 148 138 40 434 218 86 125 39 297 203 YES
Liu 2004 14 42 9 70 60 21 50 10 92 70 NO
Barton 34 55 43 123 141 29 68 59 126 186 YES
Liu 2013 77 111 25 265 161 130 125 48 385 221 YES
Luterek-Puszyńska 79 210 133 368 476 63 160 115 286 390 YES
Matsushita 200 199 62 599 323 56 72 22 184 116 YES
Milicic 63 223 135 349 493 73 213 166 359 545 YES
Miterski NA NA NA 222 346 NA NA NA 269 455 NA
Munoz-Valle 42 102 55 186 212 34 82 83 150 248 YES
Plant (1) 96 315 273 507 861 15 75 72 105 219 YES
Plant (2) 37 111 72 185 255 32 94 83 158 260 YES
Plant (3) 26 133 113 185 359 33 107 147 173 401 YES
Plant (4) 146 451 407 743 1265 410 1255 994 2075 3243 YES
Seidl 37 138 83 212 304 68 210 179 346 568 YES
Suppiah 40 144 105 224 354 92 241 142 425 525 YES
Takeuchi 49 39 12 137 63 44 49 11 137 71 YES
Tang 652 642 195 1946 1032 474 535 191 1483 917 YES
Tsukahara 636 668 186 1940 1040 181 194 73 556 340 YES
Kelley NA NA NA NA 505 NA NA NA NA 712 NA
Vaidya 20 65 38 105 141 45 158 146 248 450 YES
Walker 177 554 409 908 1372 178 577 493 933 1563 YES
Yanagawa 29 50 6 108 62 78 88 34 244 156 YES
Zhou 22 9 8 53 25 8 14 22 30 58 YES
Sameem 54 26 20 134 66 28 31 41 87 113 NO
Rs5742909 (318C/T)
Gonzalez-Escribano 1 29 108 31 245 2 60 243 64 546 NO
Lee 2002 2 19 65 23 149 4 14 68 22 150 YES
Barton 1 18 132 20 282 3 27 122 33 271 YES
Liu 2004 0 15 50 15 115 0 23 58 23 139 NO
Miterski NA NA NA 64 504 NA NA NA 50 674 NA
Takeuchi 0 13 87 13 187 0 22 82 22 186 YES
Walker 13 219 908 245 2035 10 183 1055 203 2293 YES
Liu 2013 14 97 102 125 301 13 77 213 103 503 YES
Torres-Carrillo 2 16 182 20 380 0 20 180 20 380 YES
Fattah 7 52 41 66 134 2 32 66 36 164 YES
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M, minor allele; m, major allele; NA, not available; HWE, Hardy-Weinberg Equilibrium.

Efficiency analysis

Meta-analysis of CTLA-4 CT60(rs3087243) SNP and RA susceptibility

By analyzing quantitatively allele or genotype distribution of 16394 patients and 17453 controls, a significant association between RA and CTLA-4 CT60(rs3087243) SNP was observed in all genetic comparisons (A vs. G: OR = 0.87, 95% CI = 0.83-0.91, P<0.00001; AA vs. GG: OR = 0.80, 95% CI =0.74-0.87, P<0.00001; AG vs. AA: OR = 0.85, 95% CI =0.80-0.90, P<0.0001; AA + AG vs. GG: OR =0.83, 95% CI=0.77-0.90, P<0.0001, and AA vs. AG+ GG: OR =0.88, 95% CI=0.83-0.94, P=0.0003) (Table 3 and Figure 2). Among the 22 included studies, 17 studies were performed in Caucasians, 3 were in Asians, 1 was African and 1 was in Latin Americans. Likewise, we carried out a stratified analysis by race to evaluate the ethnicity effects. In Caucasians, a protective role of rs3087243 SNP on RA was detected in all the five genetic comparisons. Similarly, a decreased risk of RA was found among Asians in the allelic comparison (OR = 0.77, 95% CI =0.65-0.90, P=0.001) and the homozygote comparison (OR = 0.67, 95% CI = 0.48-0.94, P=0.02). The heterozygote model and dominant model detected also this correlation in Latin Americans and the allelic comparison detected this correlation in Africans, but both the two populations needed more enrolled studies to elevate statistical power because this analysis currently included individually only one study. The outcomes were shown in Table 3. Collectively, Subgroup analyses revealed a significant protective association in Caucasians and Asians. When the I2 > 50% and P>0.1, the Fix-effect model was used for the synthesis; otherwise, the Random-effect model was used.

Table 3. Results of different comparative genetic models on the association of CTLA-4 SNPs with RA.

Genetic model Population Cases Controls Association Heterogeneity
OR 95%CI P-value Model I2 P-value
Rs308724
A vs. G Total 16394 17453 0.87 0.83-0.91 <0.00001 REM 39 0.003
Caucasian 12830 14148 0.89 0.86-0.93 <0.00001 FEM 25 0.17
Asian 2859 2393 0.77 0.65-0.90 0.001 REM 56 0.10
Latin 200 200 0.79 0.60-1.06 0.11 ¯ ¯ ¯
African 505 712 0.83 0.67-1.02 0.08 ¯ ¯ ¯
AA vs. GG Total 13046 12214 0.80 0.74-0.87 <0.00001 FEM 22 0.20
Caucasian 11022 11323 0.81 0.75-0.88 <0.00001 FEM 32 0.13
Asian 1824 691 0.67 0.48-0.94 0.02 FEM 0 0.48
Latin 200 200 0.72 0.40-1.31 0.29 ¯ ¯ ¯
AG vs. GG Total 13046 12214 0.85 0.80-0.90 <0.0001 FEM 28 0.14
Caucasian 11022 11323 0.86 0.81-0.92 <0.0001 FEM 11 0.33
Asian 1824 691 0.75 0.48-1.18 0.21 REM 78 0.03
Latin 200 200 0.61 0.39-0.94 0.02 ¯ ¯ ¯
AA+GA vs. GG Total 13046 12214 0.83 0.77-0.90 <0.0001 REM 46 0.02
Caucasian 11022 11323 0.85 0.78-0.93 <0.0002 REM 40 0.07
Asian 1824 691 0.74 0.48-1.12 0.15 REM 77 0.04
Latin 200 200 0.60 0.40-0.90 0.01 ¯ ¯ ¯
AA vs. GA+GG Total 13046 12214 0.88 0.83-0.94 0.0003 FEM 0 0.75
Caucasian 11022 11323 0.89 0.83-0.95 0.0008 FEM 0 0.60
Asian 1824 691 0.76 0.55-1.06 0.10 FEM 0 0.98
Latin 200 200 0.96 0.56-1.65 0.89 ¯ ¯ ¯
Rs231775
G vs. A Total 11452 12444 1.16 1.08-1.25 <0.0001 REM 66 0.00001
Caucasian 5884 7872 1.09 1.01-1.19 0.04 REM 38 0.004
Asian 4804 3511 1.27 1.10-1.47 0.001 REM 71 <0.0001
African 565 862 1.06 0.68-1.65 0.81 REM 73 0.05
Latin 199 199 1.45 1.09-1.92 0.010 ¯ ¯ ¯
GG vs. AA Total 10663 11370 1.29 1.12-1.50 0.0006 REM 54 0.0002
Caucasian 5600 7510 1.11 0.94-1.31 0.21 FEM 25 0.17
Asian 4804 3511 1.58 1.24-2.01 0.0002 REM 51 0.01
African 60 150 0.68 0.28-1.65 0.39 ¯ ¯ ¯
Latin 199 199 1.24 1.09-1.42 0.03 ¯ ¯ ¯
GA vs. AA Total 10663 11370 1.19 1.07-1.32 0.001 REM 46 0.003
Caucasian 5600 7510 1.18 1.02-1.35 0.02 REM 59 0.001
Asian 4804 3511 1.20 1.05-1.38 0.08 FEM 3 0.42
African 60 150 0.87 0.36-2.11 0.76 ¯ ¯ ¯
Latin 199 199 1.88 1.20-2.94 0.006 ¯ ¯ ¯
GG+GA vs. AA Total 10663 11370 1.24 1.11-1.39 0.0001 FEM 56 0.001
Caucasian 5600 7510 1.17 1.02-1.34 0.02 REM 62 0.0006
Asian 4804 3511 1.33 1.17-1.51 <0.0001 FEM 31 0.12
African 60 150 0.77 0.34-1.76 0.53 ¯ ¯ ¯
Latin 199 199 1.87 1.23-2.85 0.003 ¯ ¯ ¯
GG vs. GA+AA Total 10663 11370 1.15 1.02-1.30 0.02 REM 57 <0.0001
Caucasian 5600 7510 1.01 0.91-1.12 0.80 FEM 10 0.34
Asian 4804 3511 1.34 1.08-1.65 0.008 REM 72 <0.0001
African 60 150 0.75 0.41-1.38 0.36 ¯ ¯ ¯
Latin 199 199 1.30 0.79-2.15 0.31 ¯ ¯ ¯
Rs5742909
T vs. C Total 2477 2941 1.21 0.93-1.57 0.15 REM 71 0.0003
Caucasian 1813 2167 1.31 0.94-1.84 0.11 REM 73 0.005
Asian 464 574 1.05 0.56-1.96 0.88 REM 80 0.002
Latin 200 200 1.00 0.53-1.89 1.00 ¯ ¯ ¯
TT vs. CC Total 2193 2579 1.71 1.08-2.73 0.08 FEM 17 0.30
Caucasian 1529 1805 1.58 0.60-4.17 0.35 REM 32 0.22
Asian 464 574 1.34 0.34-5.28 0.68 REM 56 0.13
Latin 200 200 4.95 0.24-103.73 0.30 ¯ ¯ ¯
TC vs. CC Total 2193 2579 1.19 0.84-1.69 0.33 FEM 76 <0.0001
Caucasian 1529 1805 1.27 0.81-1.99 0.29 REM 74 0.01
Asian 464 574 1.16 0.53-2.56 0.70 REM 83 0.0004
Latin 200 200 0.79 0.40-1.58 0.51 ¯ ¯ ¯
TT+TC vs. CC Total 2193 2579 1.19 0.84-1.69 0.33 FEM 77 <0.0001
Caucasian 1529 1805 1.28 0.79-2.07 0.32 REM 78 0.003
Asian 464 574 1.12 0.52-2.43 0.77 REM 84 0.0003
Latin 200 200 0.89 0.46-1.74 0.73 ¯ ¯ ¯
TT vs. TC+CC Total 2193 2579 1.43 0.90-2.27 0.13 FEM 0 0.52
Caucasian 1529 1805 1.46 0.77-2.78 0.25 FEM 0 0.39
Asian 464 574 1.27 0.63-2.54 0.51 FEM 32 0.23
Latin 200 200 5.05 0.24-105.86 0.30 ¯ ¯ ¯
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OR, odds ratio; CI, confidence interval; FEM, fix-effect model; REM, random-effect model.

Figure 2.

Figure 2

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Forest plot of the association between rs308724 polymorphism and RA risk under the homozygous (A) and recessive model (B).

Meta-analysis of CTLA-4 +49A/G (rs231775) SNP and RA susceptibility

By quantitative analysis of allele or genotype distribution of 11452 patients and 12444 controls, there was a significant risk association between RA and CTLA-4 +49A/G (rs231775) SNP. The overall pooled ORs of all the populations were as follows: G vs. A: OR =1.16, 95% CI =1.08-1.25, P<0.0001; GG vs. AA: OR =1.29, 95% CI =1.12-1.50, P=0.0006; GA vs. AA: OR =1.19, 95% CI =1.07-1.32, P=0.001; GG + GA vs. AA: OR =1.24, 95% CI=1.11-1.39, P=0.0001 and GG vs. GA+AA: OR =1.15, 95% CI=1.02-1.30, P=0.02. The main results of overall analyses were shown in Table 3. 17 studies were conducted on Caucasians, 14 on Asians, 2 on Africans and 1 on Latin Americans. Subsequently, stratified analysis by ethnicity was conducted to get more clarifications. In the subgroup analysis, a significantly increased risk of RA was observed among the Asian population in all genetic comparisons except heterozygote comparison (G vs. A: OR =1.27, 95% CI =1.10-1.47, P=0.001; GG vs. AA: OR =1.58, 95% CI =1.24-2.01, P=0.0002; GG + GA vs. AA: OR =1.33, 95% CI=1.17-1.51, P<0.0001; GG vs. GA+AA: OR = 1.15, 95% CI =1.02-1.30, P=0.02). In Latin American population, rs231775 SNP was a significant risk factor of RA, but it only included single study and the result might be incredible. Besides, no association of the rs231775 SNP with RA risk was found among the Caucasian population in all genetic comparisons when the Elshazli’s study [24] was excluded because of its heterogeneity (G vs. A: OR =1.07, 95%CI =0.99-1.15, P =0.08; GG vs. AA: OR = 1.07, 95% CI = 0.92–1.23, P=0.37; GA vs. AA: OR = 1.15, 95% CI =1.00-1.31, P=0.05; GG + GA vs. AA: OR =1.14, 95% CI=1.00-1.29, P=0.05 and GG vs. GA+AA: OR =1.00, 95% CI=0.90–1.11, P=0.98) (Table 3 and Figure 3). There was no remarkable association between rs231775 SNP and RA in Africans. The results were summarized in Table 3 and Figure 3. These data with moderate heterogeneity employed the random-effect model for the synthesis.

Figure 3.

Figure 3

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Forest plot of the association between rs231775 polymorphism and RA risk under the allelic model with Elshazli R et al.’s study excluded (A) and homozygous model (B).

Meta-analysis of CTLA-4 318C/T (rs5742909) SNP and RA susceptibility

Through the pooled analysis of genetic data of 2477 patients and 2941 controls in a total of 10 studies, of which 5 were conduct on Caucasians, 4 on Asians, and 1 on Latin Americans, no significant associations between rs5742909 SNP and RA in the overall pooled results were found among all populations for the allelic and genotypic comparisons (T vs. C: OR =1.21, 95% CI =0.93-1.57, P=0.15; TT vs. CC: OR =1.71, 95% CI =1.08-2.73, P=0.08; TC vs. CC: OR =1.19, 95% CI =0.84-1.69, P=0.33; TT+TC vs. CC: OR =1.19, 95% CI=0.84-1.69, P=0.33 and TT vs. TC+CC: OR =1.43, 95% CI=0.90-2.27, P=0.13) (Table 3 and Figure 4). Meanwhile, the subgroup analysis by ethnicity did not indicate any remarkable associations in all genetic models (Table 3). As the heterogeneity of genetic model existed, random effect model in this part was used to make a reliable result.

Figure 4.

Figure 4

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Forest plot of the association between rs574299 polymorphism and RA risk under the homozygous (A) and recessive model (B).

Heterogeneity analysis and publication bias

To ensure the reliability of the results, we first evaluate the heterogeneity (by I2) and found that heterogeneity existed in some genetic models of rs231775 SNP and rs5742909 SNP (Table 3). In order to minimize heterogeneity, the following methods were carried out in this meta-analysis. On the one hand, the random-effect models were exploited in the genetic models with moderate heterogeneity(I2>50%). On the other hand, sensitivity analysis was adopted to evaluate the effect of a single study on the pooled ORs by removing each study in turn from the pooled analysis. Although the heterogeneity had not changed obviously, the P values for pooled ORs under allelic comparison, heterozygous comparison and dominant comparison were reversed when the study [24] led by Elshazli R was removed. Therefore, we deleted this study and recalculated the relevant ORs and 95%CIs to harvest a stable and credible outcome (Figure 3). The funnel plots were used to investigate publication bias and the outlines of the funnel plots appear to be symmetrical (Figure 5). For rs231775 SNP, the asymmetry of the funnel plot was attributed to Zhou et al.’s study [45] which was published in Chinese. HWE estimation indicated that allele or genotype frequencies were deviant from HWE in control group in the Liu et al.’s, Gonzalez-Escribano et al.’s and Sameem et al.’s studies [25, 29, 38], but the results of synthesis analysis were not substantially inversed. Hence, we didn't remove these studies from the meta-analysis.

Figure 5.

Figure 5

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Funnel plot of the association between RA risk and rs308724 polymorphism under the allelic (A) and recessive model (B), rs231775 polymorphism under the allelic (C) and homozygous model (D), and rs574299 polymorphism under the homozygous (E) and recessive model (F).

DISCUSSION

To our knowledge, this was the first meta-analysis to investigate the association between the three most-often SNPs of CTLA-4 and RA susceptibility. From the data integration of 66 studies in 21681 cases and 23457 controls, we found that the rs3087243 SNP decreased the risk of RA risk in Caucasians and Asians, the rs231775 SNP of CTLA-4 increased RA risk in Asians but not in Caucasians and Africans, and the rs5742909 SNP was not significantly associated with RA risk in both Caucasians and Africans.

The CTLA-4 gene, located on chromosome 2q33, encodes a 223 amino acid receptor protein on T cell surface which is responsible for T cell immune regulation. As an antagonist of the costimulatory receptor CD28 which binds the same ligand B7 as CTLA-4, CTLA-4 with higher affinity transmits an inhibitory signal and subsequently plays a suppressive role in regulating T-cell activation [57], which suggests it is involved in the pathological processes of many autoimmune disorders [12–15]. It is widely believed that RA is a T cell-mediated autoimmune disease [58], of which the chronic inflammation and damage of the joints are typical [1]. Although a great many genes whose protein products are critical to T cell function don’t have genetic associations with RA, the effect of CTLA-4 on RA pathogenesis has attracted growing attentions.

Previous research had found that serum levels of soluble CTLA-4 were increased in RA patients and had a positive correlation with Disease Activity Score in RA patients and even proposed that serum levels of CTLA-4 could serve as a new marker of RA disease activity [59, 60]. Besides, function experiments in vivo indicated that gene delivery of CTLA4 by intra-articular injection could alleviate experimental arthritis [61]. Furthermore, CTLA-4Ig administration on RA synovial macrophages and T helper cells downregulated the production of proinflammatory cytokines, and these evidences suggested that CTLA-4 could be a treatment target for RA [62, 63]. In fact, blockade of CTLA-4 by CTLA-4Ig had been successfully applied to treatment for RA [64].

As we all know, the protein level, structure and function are determined in large part by gene. Apart from these function research, numerous studies on correlation between CTLA-4 and RA risk from gene level also had been conducted to investigate genetic factors [8, 9, 13–15, 17–20, 24–56]. However, the results were inconsistent or contrary likely due to the various ethnic background, disparate geographic environment, limited sample size, insufficient data and so on. Thus, it was urgently necessary to perform a comprehensive up-to-date meta-analysis as an effective methodology to draw an overall objective appraisal on the association between CTLA-4 polymorphism and RA susceptibility.

In the present meta-analysis, we extracted 66 studies with 21681 cases and 23457 controls to inspect the correlation between three most-often SNPs in the CTLA-4 gene and the risk of RA. There were 22 studies with 16394 cases and 17453 controls for rs3087243 SNP, 34 studies with 11452 cases and 12444 controls for rs231775 SNP, and 10 studies with 2477 cases and 2941 controls for rs5742909 SNP. For rs3087243 polymorphism, our findings demonstrated a decreased susceptibility of RA both in total and in Caucasians in any gene mode. In total, carriers with allele A reduced an approximate 13% risk of RA than ones with allele G and genotype AA reduced 20% or so than genotype GG. Moreover, a decreased susceptibility of RA was respectively also found among Asians in the allele and homozygote comparison and among Latin Americans in the heterozygote and dominant comparison. However, only one study was included in Latin Americans and Asians so it needed to enlarge sample size to further research. For rs231775 polymorphism, significant association did exist among the whole population in all genetic models except recessive model: compared with allele A and genotype AA, allele G and genotype GG and GA respectively was associated with an increased risk of RA. The same association was observed in Asians and Latin Americans in the subgroup analysis. On the contrary, no significant association between rs231775 SNP and RA risk could be detected in Caucasians and Africans using any gene model after excluding the Elshazli R’s study [24] with the apparent heterogeneity. Here, it should be noted that only one or two case–control study was included in Africans and Latin Americans, so the conclusions were not particularly convincing. For rs5742909 polymorphism, no significant association between this locus polymorphism and RA risk was observed among any population in any model. Although the heterogeneity existed in some genetic model, but no obvious change had happened in heterogeneity and P value for the pooled ORs when each study was individually removed by sensitivity analysis.

With regard to the diverse results of the same SNP on different populations, it might be attributed to clinical and genetic real heterogeneity of RA, interaction of genetic background and region environment, and even lack of vigorous statistical power. Besides, it was noteworthy that one important factor for the diverse and disparate results was linkage disequilibrium (LD). These CTLA-4 SNPs might be not definitely the causative alleles, but they were likely to be in LD with the causative alleles which were yet unidentified. And, LD was different between ethnic and racial groups.

It should be pointed out that previous several meta-analyses have summarized the effect of CTLA-4 polymorphism on RA risk [21–23, 65]. But a few points need to be taken notice. On one hand, the previous conclusions were discordant as the following: the conclusion of Li’s (2014) study [65] on the association of rs231775 SNP of CTLA-4 with RA was contrary to the others; the genetic models which indicated significant association were diverse in these analyses. These differences were mainly originated from divergent diagnostic criteria, limited number of studies and sample sizes. On the other hand, all these meta-analyses focused on only one of the three well-studied loci except Li’s study [23] on two. As we all know, the expression and function of the protein are determined by the whole gene. Therefore, it is of great necessity to investigate simultaneously the effect of all the 3 SNPs on RA risk to obtain an overall evaluation. Besides, the number of included studies in previous meta-analyses was small. Some original association studies [9, 15, 24–27] have emerged in the past few years and they can be incorporated. Taking these points into considerations, we updated the meta-analysis to achieve a more valid and comprehensive estimation on the association of CTLA-4 gene and RA susceptibility.

However, some limitations of our study should be acknowledged. Firstly, the small sample size in some studies and the limited studies for some stratified analysis were not sufficient enough to detect the relationship. Especially, the results of populations including only one study should be interpreted with caution. Secondly, we only investigated the role of three loci polymorphisms. As CTLA-4 gene had various SNPs, the function of protein CTLA-4 depended on the whole gene and RA was a multigene susceptibility disease, more SNPs of CTLA-4 should be included. Thirdly, certain degree of heterogeneity still existed in rs5742909 polymorphism and some genetic models. Although the elimination of each single study did not distinctly alter the P value, the results must still be treated cautiously. Fourthly, inadequate raw data in some studies result in the inability to calculate the number of the genotypes and perform stratified analysis by age, gender and autoantibody status such as RF etc. As a consequence, any potential gene-environment and gene-gene interactions could not be accessed.

In conclusion, this meta-analysis suggested that rs3087243 polymorphisms were corelated with a reduced RA risk in both Asian and Caucasian populations, rs231775 polymorphisms was associated with an increased risk of RA in Asians, and rs5742909 polymorphism had no significant association with RA risk. Larger-scale studies of populations with different ethnicities are encouraged to validate the role CTLA-4 played in the pathogenesis of RA.

MATERIALS AND METHODS

This meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [66].

Search strategy

From the databases PubMed, EMBASE, Web of Science and, the China National Knowledge Infrastructure (CNKI) and Wan Fang data, a comprehensive systematic literature retrieval was conducted to derive all relevant studies published before 10 October, 2020 (the search was constantly updated to submission). The following terms as Medical Subject Heading and free words were applied: “CTLA-4 or cytotoxic T lymphocyte antigen-4” and “single nucleotide polymorphism or polymorphism or variant or variation” and “rheumatoid arthritis or RA”. The bibliographic lists of included studies were also browsed for potential related studies. There were no restrictions on language and publication date in this study.

Inclusion and exclusion criteria

The current meta-analysis used the following inclusion criteria to screen available literatures: 1) case-control study; 2) evaluation of the associations between CTLA-4 (rs3087243, rs231775 and rs5742909)polymorphism and RA risk; 3) with sufficient data for extract odds ratios (ORs) and 95% confidence intervals(CIs); (4) with reported allele or genotype numbers or frequencies in cases and control group; 5) with a clear diagnostic criteria. Accordingly, we excluded meaninglessness literatures if they had the following trait: 1) case report, comment, animal studies and conference abstracts; 2) with no detailed allele or genotype data; 3) duplications or no controls.

Data extraction and assess of quality

Two independent investigators respectively conducted a literature search according to the above search strategy, screened each article based on the predesigned inclusion and exclusion criteria, and extracted data from these eligible studies. It would be settled by discussion with the third party when the disagreement between investigators occurred. The following information was collected from every paper: 1) first author's surname, 2) the year of publication, 3) country or region of origin, 4) ethnicity, 5) total numbers of cases and controls, 6) genotype method, 7) diagnostic criteria, 8) polymorphism locus, 9) allele distribution or/and genotype distribution.

The methodological quality of included studies was accessed in light of the Newcastle–Ottawa Scale (NOS) for the evaluation of observational studies [67]. In brief, three broad perspectives were evaluated using the Star system (http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp). Any divergence between two investigators was solved by discussion until agreement was reached.

Statistical analysis

The strength of association of rs231775, rs5742909 and rs3087243 SNPs with RA risk was appraised via estimating ORs with their corresponding 95% CIs. For each SNP, the pooled ORs were calculated individually for five gene models (allele model, homozygote model, heterozygote model, dominant model and recessive model). The Z test was used to evaluate the significance of the pooled ORs. p<0.05 was judged as statistically significant difference. Statistical Heterogeneity between studies was assessed by Chi square and I2 values which range from 0% to 100%. 25%, 50%, and 75% were regarded as respectively low, moderate, and high level [68, 69]. The random -effect model was employed when the value of I2 was more than 50%. If not, the fixed effect model was employed. Hardy–Weinberg equilibrium (HWE) was tested in the control group for all studies by Chi-square test to judge whether the selection bias existed. Potential publication bias was examined by funnel plots. Besides, the current meta-analysis had carried out subgroup analyses by the racial descent to assess the effects of ethnic background.

The above statistical analyses were performed using Review Manager 5.3 software (Nordic Cochrane Centre, Cochrane Collaboration, Copenhagen). All the P values were 2-sided and P<0.05 signified statistically significance.

Supplementary Material

Supplementary Table 1
aging-13-203349-s001.pdf (333.6KB, pdf)

Footnotes

AUTHOR CONTRIBUTIONS: J.X. and H. L. conceived and designed this study. C. Z., S.G, X. Y., Z. S. and S. L. performed the experiments. C. Z., S.G analyzed the data. C. Z. and H. L. draft the manuscript. X.S. and J.X. revised the paper. All authors have contributed to the final version and approved the final manuscript.

CONFLICTS OF INTEREST: The authors declare that they have no conflicts of interest.

FUNDING: This study is supported by National Natural Science Foundation of China, Nos.81772396.

REFERENCES

  • 1.Smolen JS, Aletaha D, McInnes IB. Rheumatoid arthritis. Lancet. 2016; 388:2023–38. 10.1016/S0140-6736(16)30173-8 [DOI] [PubMed] [Google Scholar]
  • 2.Minichiello E, Semerano L, Boissier MC. Time trends in the incidence, prevalence, and severity of rheumatoid arthritis: A systematic literature review. Joint Bone Spine. 2016; 83:625–30. 10.1016/j.jbspin.2016.07.007 [DOI] [PubMed] [Google Scholar]
  • 3.Cross M, Smith E, Hoy D, Carmona L, Wolfe F, Vos T, Williams B, Gabriel S, Lassere M, Johns N, Buchbinder R, Woolf A, March L. The global burden of rheumatoid arthritis: estimates from the global burden of disease 2010 study. Ann Rheum Dis. 2014; 73:1316–22. 10.1136/annrheumdis-2013-204627 [DOI] [PubMed] [Google Scholar]
  • 4.MacGregor AJ, Snieder H, Rigby AS, Koskenvuo M, Kaprio J, Aho K, Silman AJ. Characterizing the quantitative genetic contribution to rheumatoid arthritis using data from twins. Arthritis Rheum. 2000; 43:30–37. [DOI] [PubMed] [Google Scholar]
  • 5.Okada Y, Wu D, Trynka G, Raj T, Terao C, Ikari K, Kochi Y, Ohmura K, Suzuki A, Yoshida S, Graham RR, Manoharan A, Ortmann W, et al. , and RACI consortium, and GARNET consortium. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature. 2014; 506:376–81. 10.1038/nature12873 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Kim K, Bang SY, Lee HS, Bae SC. Update on the genetic architecture of rheumatoid arthritis. Nat Rev Rheumatol. 2017; 13:13–24. 10.1038/nrrheum.2016.176 [DOI] [PubMed] [Google Scholar]
  • 7.Leng RX, Di DS, Ni J, Wu XX, Zhang LL, Wang XF, Liu RS, Huang Q, Fan YG, Pan HF, Wang B, Ye DQ. Identification of new susceptibility loci associated with rheumatoid arthritis. Ann Rheum Dis. 2020; 79:1565–71. 10.1136/annrheumdis-2020-217351 [DOI] [PubMed] [Google Scholar]
  • 8.Costenbader KH, Chang SC, De Vivo I, Plenge R, Karlson EW. Genetic polymorphisms in PTPN22, PADI-4, and CTLA-4 and risk for rheumatoid arthritis in two longitudinal cohort studies: evidence of gene-environment interactions with heavy cigarette smoking. Arthritis Res Ther. 2008; 10:R52. 10.1186/ar2421 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Luterek-Puszyńska K, Malinowski D, Paradowska-Gorycka A, Safranow K, Pawlik A. CD28, CTLA-4 and CCL5 gene polymorphisms in patients with rheumatoid arthritis. Clin Rheumatol. 2017; 36:1129–35. 10.1007/s10067-016-3496-2 [DOI] [PubMed] [Google Scholar]
  • 10.Klocke K, Sakaguchi S, Holmdahl R, Wing K. Induction of autoimmune disease by deletion of CTLA-4 in mice in adulthood. Proc Natl Acad Sci USA. 2016; 113:E2383–92. 10.1073/pnas.1603892113 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Sansom DM. IMMUNOLOGY. Moving CTLA-4 from the trash to recycling. Science. 2015; 349:377–78. 10.1126/science.aac7888 [DOI] [PubMed] [Google Scholar]
  • 12.Ueda H, Howson JM, Esposito L, Heward J, Snook H, Chamberlain G, Rainbow DB, Hunter KM, Smith AN, Di Genova G, Herr MH, Dahlman I, Payne F, et al. Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease. Nature. 2003; 423:506–11. 10.1038/nature01621 [DOI] [PubMed] [Google Scholar]
  • 13.Zhernakova A, Eerligh P, Barrera P, Wesoly JZ, Huizinga TW, Roep BO, Wijmenga C, Koeleman BP. CTLA4 is differentially associated with autoimmune diseases in the Dutch population. Hum Genet. 2005; 118:58–66. 10.1007/s00439-005-0006-z [DOI] [PubMed] [Google Scholar]
  • 14.Walker EJ, Hirschfield GM, Xu C, Lu Y, Liu X, Lu Y, Coltescu C, Wang K, Newman WG, Bykerk V, Keystone EC, Mosher D, Amos CI, et al. CTLA4/ICOS gene variants and haplotypes are associated with rheumatoid arthritis and primary biliary cirrhosis in the Canadian population. Arthritis Rheum. 2009; 60:931–37. 10.1002/art.24412 [DOI] [PubMed] [Google Scholar]
  • 15.Schulz S, Zimmer P, Pütz N, Jurianz E, Schaller HG, Reichert S. rs2476601 in PTPN22 gene in rheumatoid arthritis and periodontitis-a possible interface? J Transl Med. 2020; 18:389. 10.1186/s12967-020-02548-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Yang J, McGovern A, Martin P, Duffus K, Ge X, Zarrineh P, Morris AP, Adamson A, Fraser P, Rattray M, Eyre S. Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis. Nat Commun. 2020; 11:4402. 10.1038/s41467-020-18180-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Barton A, Myerscough A, John S, Gonzalez-Gay M, Ollier W, Worthington J. A single nucleotide polymorphism in exon 1 of cytotoxic T-lymphocyte-associated-4 (CTLA-4) is not associated with rheumatoid arthritis. Rheumatology (Oxford). 2000; 39:63–66. 10.1093/rheumatology/39.1.63 [DOI] [PubMed] [Google Scholar]
  • 18.Plenge RM, Padyukov L, Remmers EF, Purcell S, Lee AT, Karlson EW, Wolfe F, Kastner DL, Alfredsson L, Altshuler D, Gregersen PK, Klareskog L, Rioux JD. Replication of putative candidate-gene associations with rheumatoid arthritis in >4,000 samples from North America and Sweden: association of susceptibility with PTPN22, CTLA4, and PADI4. Am J Hum Genet. 2005; 77:1044–60. 10.1086/498651 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Plant D, Flynn E, Mbarek H, Dieudé P, Cornelis F, Arlestig L, Dahlqvist SR, Goulielmos G, Boumpas DT, Sidiropoulos P, Johansen JS, Ørnbjerg LM, Hetland ML, et al. Investigation of potential non-HLA rheumatoid arthritis susceptibility loci in a European cohort increases the evidence for nine markers. Ann Rheum Dis. 2010; 69:1548–53. 10.1136/ard.2009.121020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Liu CP, Jiang JA, Wang T, Liu XM, Gao L, Zhu RR, Shen Y, Wu M, Xu T, Zhang XG. CTLA-4 and CD86 genetic variants and haplotypes in patients with rheumatoid arthritis in southeastern China. Genet Mol Res. 2013; 12:1373–82. 10.4238/2013.April.25.8 [DOI] [PubMed] [Google Scholar]
  • 21.Han S, Li Y, Mao Y, Xie Y. Meta-analysis of the association of CTLA-4 exon-1 +49A/G polymorphism with rheumatoid arthritis. Hum Genet. 2005; 118:123–32. 10.1007/s00439-005-0033-9 [DOI] [PubMed] [Google Scholar]
  • 22.Lee YH, Bae SC, Choi SJ, Ji JD, Song GG. Association between the CTLA-4 +49 A/G polymorphism and susceptibility to rheumatoid arthritis: a meta-analysis. Mol Biol Rep. 2012; 39:5599–605. 10.1007/s11033-011-1364-3 [DOI] [PubMed] [Google Scholar]
  • 23.Li X, Zhang C, Zhang J, Zhang Y, Wu Z, Yang L, Xiang Z, Qi Z, Zhang X, Xiao X. Polymorphisms in the CTLA-4 gene and rheumatoid arthritis susceptibility: a meta-analysis. J Clin Immunol. 2012; 32:530–39. 10.1007/s10875-012-9650-y [DOI] [PubMed] [Google Scholar]
  • 24.Elshazli R, Settin A, Salama A. Cytotoxic T lymphocyte associated antigen-4 (CTLA-4) +49 A>G gene polymorphism in Egyptian cases with rheumatoid arthritis. Gene. 2015; 558:103–07. 10.1016/j.gene.2014.12.046 [DOI] [PubMed] [Google Scholar]
  • 25.Sameem M, Rani A, Bashir R, Riaz N, Batool SA, Irfan S, Arshad M, Nawaz SK. CTLA-4+49 Polymorphism and Susceptibility to Rheumatoid Arthritis in Pakistani Population. Pak J Zool. 2015; 47:1731–37. [Google Scholar]
  • 26.Vernerova L, Spoutil F, Vlcek M, Krskova K, Penesova A, Meskova M, Marko A, Raslova K, Vohnout B, Rovensky J, Killinger Z, Jochmanova I, Lazurova I, et al. A Combination of CD28 (rs1980422) and IRF5 (rs10488631) Polymorphisms Is Associated with Seropositivity in Rheumatoid Arthritis: A Case Control Study. PLoS One. 2016; 11:e0153316. 10.1371/journal.pone.0153316 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Fattah SA, Ghattas MH, Saleh SM, Abo-Elmatty DM. Cytotoxic T-lymphocyte-associated protein 4 gene polymorphism is related to rheumatoid arthritis in Egyptian population. Arch Physiol Biochem. 2017; 123:50–53. 10.1080/13813455.2016.1230135 [DOI] [PubMed] [Google Scholar]
  • 28.Seidl C, Donner H, Fischer B, Usadel KH, Seifried E, Kaltwasser JP, Badenhoop K. CTLA4 codon 17 dimorphism in patients with rheumatoid arthritis. Tissue Antigens. 1998; 51:62–66. 10.1111/j.1399-0039.1998.tb02947.x [DOI] [PubMed] [Google Scholar]
  • 29.Gonzalez-Escribano MF, Rodriguez R, Valenzuela A, Garcia A, Garcia-Lozano JR, Nuñez-Roldan A. CTLA4 polymorphisms in Spanish patients with rheumatoid arthritis. Tissue Antigens. 1999; 53:296–300. 10.1034/j.1399-0039.1999.530311.x [DOI] [PubMed] [Google Scholar]
  • 30.Matsushita M, Tsuchiya N, Shiota M, Komata T, Matsuta K, Zama K, Oka T, Juji T, Yamane A, Tokunaga K. Lack of a strong association of CTLA-4 exon 1 polymorphism with the susceptibility to rheumatoid arthritis and systemic lupus erythematosus in Japanese: an association study using a novel variation screening method. Tissue Antigens. 1999; 54:578–84. 10.1034/j.1399-0039.1999.540607.x [DOI] [PubMed] [Google Scholar]
  • 31.Yanagawa T, Gomi K, Nakao EI, Inada S. CTLA-4 gene polymorphism in Japanese patients with rheumatoid arthritis. J Rheumatol. 2000; 27:2740–42. [PubMed] [Google Scholar]
  • 32.Hadj Kacem H, Kaddour N, Adyel FZ, Bahloul Z, Ayadi H. HLA-DQB1 CAR1/CAR2, TNFa IR2/IR4 and CTLA-4 polymorphisms in Tunisian patients with rheumatoid arthritis and Sjögren’s syndrome. Rheumatology (Oxford). 2001; 40:1370–74. 10.1093/rheumatology/40.12.1370 [DOI] [PubMed] [Google Scholar]
  • 33.Milicic A, Brown MA, Wordsworth BP. Polymorphism in codon 17 of the CTLA-4 gene (+49 A/G) is not associated with susceptibility to rheumatoid arthritis in British Caucasians. Tissue Antigens. 2001; 58:50–54. 10.1034/j.1399-0039.2001.580110.x [DOI] [PubMed] [Google Scholar]
  • 34.Lee YH, Choi SJ, Ji JD, Song GG. No association of polymorphisms of the CTLA-4 exon 1(+49) and promoter(-318) genes with rheumatoid arthritis in the Korean population. Scand J Rheumatol. 2002; 31:266–70. 10.1080/030097402760375142 [DOI] [PubMed] [Google Scholar]
  • 35.Vaidya B, Pearce SH, Charlton S, Marshall N, Rowan AD, Griffiths ID, Kendall-Taylor P, Cawston TE, Young-Min S. An association between the CTLA4 exon 1 polymorphism and early rheumatoid arthritis with autoimmune endocrinopathies. Rheumatology (Oxford). 2002; 41:180–83. 10.1093/rheumatology/41.2.180 [DOI] [PubMed] [Google Scholar]
  • 36.Lee CS, Lee YJ, Liu HF, Su CH, Chang SC, Wang BR, Chen TL, Liu TL. Association of CTLA4 gene A-G polymorphism with rheumatoid arthritis in Chinese. Clin Rheumatol. 2003; 22:221–24. 10.1007/s10067-003-0720-7 [DOI] [PubMed] [Google Scholar]
  • 37.Barton A, Jury F, Eyre S, Bowes J, Hinks A, Ward D, Worthington J. Haplotype analysis in simplex families and novel analytic approaches in a case-control cohort reveal no evidence of association of the CTLA-4 gene with rheumatoid arthritis. Arthritis Rheum. 2004; 50:748–52. 10.1002/art.20118 [DOI] [PubMed] [Google Scholar]
  • 38.Liu MF, Wang CR, Chen PC, Lin TL. CTLA-4 gene polymorphism in promoter and exon-1 regions is not associated with Chinese patients with rheumatoid arthritis. Clin Rheumatol. 2004; 23:180–81. 10.1007/s10067-003-0776-4 [DOI] [PubMed] [Google Scholar]
  • 39.Miterski B, Drynda S, Böschow G, Klein W, Oppermann J, Kekow J, Epplen JT. Complex genetic predisposition in adult and juvenile rheumatoid arthritis. BMC Genet. 2004; 5:2. 10.1186/1471-2156-5-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Orozco G, Torres B, Núñez-Roldán A, González-Escribano MF, Martín J. Cytotoxic T-lymphocyte antigen-4-CT60 polymorphism in rheumatoid arthritis. Tissue Antigens. 2004; 64:667–70. 10.1111/j.1399-0039.2004.00318.x [DOI] [PubMed] [Google Scholar]
  • 41.Lei C, Dongqing Z, Yeqing S, Oaks MK, Lishan C, Jianzhong J, Jie Q, Fang D, Ningli L, Xinghai H, Daming R. Association of the CTLA-4 gene with rheumatoid arthritis in Chinese Han population. Eur J Hum Genet. 2005; 13:823–28. 10.1038/sj.ejhg.5201423 [DOI] [PubMed] [Google Scholar]
  • 42.Feng ZL. [CTLA-4 gene A/G(49) polymorphism association with SLE and RA and expression of soluble CTLA-4 in patients with SLE and with RA].Shandong University. 2005. [Google Scholar]
  • 43.Suppiah V, O’Doherty C, Heggarty S, Patterson CC, Rooney M, Vandenbroeck K. The CTLA4+49A/G and CT60 polymorphisms and chronic inflammatory arthropathies in Northern Ireland. Exp Mol Pathol. 2006; 80:141–46. 10.1016/j.yexmp.2005.09.004 [DOI] [PubMed] [Google Scholar]
  • 44.Takeuchi F, Kawasugi K, Mori M, Nakaue N, Kobayashi N, Kuwata S, Murayama T, Matsuta K. The genetic contribution of CTLA-4 dimorphisms in promoter and exon 1 regions in Japanese patients with rheumatoid arthritis. Scand J Rheumatol. 2006; 35:154–55. 10.1080/03009740500407651 [DOI] [PubMed] [Google Scholar]
  • 45.Zhou Y, Xiao LS. [Association of the polymorphism of CTLA-4 gene with systemic lupus erythematosus or rheumatoid arthitis in the Chinese population]. Immunol J. 2007; 3:349–50. [Google Scholar]
  • 46.Tsukahara S, Iwamoto T, Ikari K, Inoue E, Tomatsu T, Hara M, Yamanaka H, Kamatani N, Momohara S. CTLA-4 CT60 polymorphism is not an independent genetic risk marker of rheumatoid arthritis in a Japanese population. Ann Rheum Dis. 2008; 67:428–29. 10.1136/ard.2007.079186 [DOI] [PubMed] [Google Scholar]
  • 47.Barton A, Eyre S, Ke X, Hinks A, Bowes J, Flynn E, Martin P, Wilson AG, Morgan AW, Emery P, Steer S, Hocking LJ, Reid DM, et al. , and YEAR Consortium, and BIRAC Consortium. Identification of AF4/FMR2 family, member 3 (AFF3) as a novel rheumatoid arthritis susceptibility locus and confirmation of two further pan-autoimmune susceptibility genes. Hum Mol Genet. 2009; 18:2518–22. 10.1093/hmg/ddp177 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Daha NA, Kurreeman FA, Marques RB, Stoeken-Rijsbergen G, Verduijn W, Huizinga TW, Toes RE. Confirmation of STAT4, IL2/IL21, and CTLA4 polymorphisms in rheumatoid arthritis. Arthritis Rheum. 2009; 60:1255–60. 10.1002/art.24503 [DOI] [PubMed] [Google Scholar]
  • 49.Kelley JM, Hughes LB, Faggard JD, Danila MI, Crawford MH, Edberg Y, Padilla MA, Tiwari HK, Westfall AO, Alarcón GS, Conn DL, Jonas BL, Callahan LF, et al. An African ancestry-specific allele of CTLA4 confers protection against rheumatoid arthritis in African Americans. PLoS Genet. 2009; 5:e1000424. 10.1371/journal.pgen.1000424. Retraction in: PLoS Genet. 2009; 5. [DOI] [PMC free article] [PubMed] [Google Scholar] [Retracted]
  • 50.Muñoz-Valle JF, Valle Y, Padilla-Gutiérrez JR, Parra-Rojas I, Rangel-Villalobos H, Vázquez del Mercado M, Ledezma-Lozano IY, Villafan-Bernal JR, Armendáriz-Borunda J, Pereira-Suárez AL. The +49A>G CTLA-4 polymorphism is associated with rheumatoid arthritis in Mexican population. Clin Chim Acta. 2010; 411:725–28. 10.1016/j.cca.2010.02.001 [DOI] [PubMed] [Google Scholar]
  • 51.Benhatchi K, Jochmanová I, Habalová V, Wagnerová H, Lazúrová I. CTLA4 exon1 A49G polymorphism in Slovak patients with rheumatoid arthritis and Hashimoto thyroiditis-results and the review of the literature. Clin Rheumatol. 2011; 30:1319–24. 10.1007/s10067-011-1752-z [DOI] [PubMed] [Google Scholar]
  • 52.Danoy P, Wei M, Johanna H, Jiang L, He D, Sun L, Zeng X, Visscher PM, Brown MA, Xu H. Association of variants in MMEL1 and CTLA4 with rheumatoid arthritis in the Han Chinese population. Ann Rheum Dis. 2011; 70:1793–97. 10.1136/ard.2010.144576 [DOI] [PubMed] [Google Scholar]
  • 53.El-Gabalawy HS, Robinson DB, Daha NA, Oen KG, Smolik I, Elias B, Hart D, Bernstein CN, Sun Y, Lu Y, Houwing-Duistermaat JJ, Siminovitch KA. Non-HLA genes modulate the risk of rheumatoid arthritis associated with HLA-DRB1 in a susceptible North American Native population. Genes Immun. 2011; 12:568–74. 10.1038/gene.2011.30 [DOI] [PubMed] [Google Scholar]
  • 54.AlFadhli S. Overexpression and secretion of the soluble CTLA-4 splice variant in various autoimmune diseases and in cases with overlapping autoimmunity. Genet Test Mol Biomarkers. 2013; 17:336–41. 10.1089/gtmb.2012.0391 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Tang MJ, Zhou ZB. Association of the CTLA-4 +49A/G polymorphism with rheumatoid arthritis in Chinese Han population. Mol Biol Rep. 2013; 40:2627–31. 10.1007/s11033-012-2349-6 [DOI] [PubMed] [Google Scholar]
  • 56.Torres-Carrillo N, Ontiveros-Mercado H, Torres-Carrillo NM, Parra-Rojas I, Rangel-Villalobos H, Ramírez-Dueñas MG, Gutiérrez-Ureña SR, Valle Y, Muñoz-Valle JF. The -319C/+49G/CT60G haplotype of CTLA-4 gene confers susceptibility to rheumatoid arthritis in Mexican population. Cell Biochem Biophys. 2013; 67:1217–28. 10.1007/s12013-013-9640-6 [DOI] [PubMed] [Google Scholar]
  • 57.Walker LS, Sansom DM. Confusing signals: recent progress in CTLA-4 biology. Trends Immunol. 2015; 36:63–70. 10.1016/j.it.2014.12.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Cope AP, Schulze-Koops H, Aringer M. The central role of T cells in rheumatoid arthritis. Clin Exp Rheumatol. 2007. (Suppl 46); 25:S4–11. [PubMed] [Google Scholar]
  • 59.Cao J, Zou L, Luo P, Chen P, Zhang L. Increased production of circulating soluble co-stimulatory molecules CTLA-4, CD28 and CD80 in patients with rheumatoid arthritis. Int Immunopharmacol. 2012; 14:585–92. 10.1016/j.intimp.2012.08.004 [DOI] [PubMed] [Google Scholar]
  • 60.Choi IS, Yoo HS, Collisson EW. Evaluation of expression patterns of feline CD28 and CTLA-4 in feline immunodeficiency virus (FIV)-infected and FIV antigen-induced PBMC. J Vet Sci. 2000; 1:97–103. 10.4142/jvs.2000.1.2.97 [DOI] [PubMed] [Google Scholar]
  • 61.Zhang W, Wang F, Wang B, Zhang J, Yu JY. Intraarticular gene delivery of CTLA4-FasL suppresses experimental arthritis. Int Immunol. 2012; 24:379–88. 10.1093/intimm/dxs041 [DOI] [PubMed] [Google Scholar]
  • 62.Cutolo M, Soldano S, Montagna P, Sulli A, Seriolo B, Villaggio B, Triolo P, Clerico P, Felli L, Brizzolara R. CTLA4-Ig interacts with cultured synovial macrophages from rheumatoid arthritis patients and downregulates cytokine production. Arthritis Res Ther. 2009; 11:R176. 10.1186/ar2865 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Körmendy D, Hoff H, Hoff P, Bröker BM, Burmester GR, Brunner-Weinzierl MC. Impact of the CTLA-4/CD28 axis on the processes of joint inflammation in rheumatoid arthritis. Arthritis Rheum. 2013; 65:81–87. 10.1002/art.37714 [DOI] [PubMed] [Google Scholar]
  • 64.Kremer JM, Westhovens R, Leon M, Di Giorgio E, Alten R, Steinfeld S, Russell A, Dougados M, Emery P, Nuamah IF, Williams GR, Becker JC, Hagerty DT, Moreland LW. Treatment of rheumatoid arthritis by selective inhibition of T-cell activation with fusion protein CTLA4Ig. N Engl J Med. 2003; 349:1907–15. 10.1056/NEJMoa035075 [DOI] [PubMed] [Google Scholar]
  • 65.Li G, Shi F, Liu J, Li Y. The effect of CTLA-4 A49G polymorphism on rheumatoid arthritis risk: a meta-analysis. Diagn Pathol. 2014; 9:157. 10.1186/s13000-014-0157-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Moher D, Liberati A, Tetzlaff J, Altman DG, and PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009; 339:b2535. 10.1136/bmj.b2535 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010; 25:603–05. 10.1007/s10654-010-9491-z [DOI] [PubMed] [Google Scholar]
  • 68.Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002; 21:1539–58. 10.1002/sim.1186 [DOI] [PubMed] [Google Scholar]
  • 69.Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003; 327:557–60. 10.1136/bmj.327.7414.557 [DOI] [PMC free article] [PubMed] [Google Scholar]

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Supplementary Materials

Supplementary Table 1
aging-13-203349-s001.pdf (333.6KB, pdf)

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