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. 2019 May 15;39(5):BSR20190309. doi: 10.1042/BSR20190309

Associations between cytotoxic T-lymphocyte-associated antigen 4 gene polymorphisms and diabetes mellitus: a meta-analysis of 76 case–control studies

Min Chen 1,✉, ShuMin Li 1,✉
PMCID: PMC6522704  PMID: 30988065

Abstract

Background: Several genetic association studies already investigated potential roles of cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) gene polymorphisms in diabetes mellitus (DM), with inconsistent results. Therefore, we performed this meta-analysis to better assess the relationship between CTLA-4 gene polymorphisms and DM in a larger pooled population.

Methods: PubMed, Embase, Web of Science, and CNKI were systematically searched for eligible studies. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to estimate the strength of associations between CTLA-4 gene polymorphisms and DM in all possible genetic models.

Results: A total of 76 studies were finally included in our analyses. Significant associations with susceptibility to type 1 diabetes mellitus (T1DM) were detected for rs231775 (dominant model: P=0.008, OR = 0.83, 95%CI 0.73–0.95; recessive model: P=0.003, OR = 1.27, 95%CI 1.09–1.50; allele model: P=0.004, OR = 0.85, 95%CI 0.77–0.95) and rs5742909 (recessive model: P=0.02, OR = 1.50, 95%CI 1.05–2.13) polymorphisms in overall population. Further subgroup analyses revealed that rs231775 polymorphism was significantly associated with susceptibility to T1DM in Caucasians and South Asians, and rs5742909 polymorphism was significantly associated with susceptibility to T1DM in South Asians. Moreover, rs231775 polymorphism was also found to be significantly associated with susceptibility to type 2 diabetes mellitus (T2DM) in East Asians and South Asians.

Conclusions: Our findings indicated that rs231775 and rs5742909 polymorphisms may serve as genetic biomarkers of T1DM, and rs231775 polymorphism may also serve as a genetic biomarker of T2DM.

Keywords: Cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), Diabetes mellitus (DM), Gene polymorphisms, Meta-analysis

Introduction

Diabetes mellitus (DM), characterized by chronic hyperglycemia caused by deficiency in insulin secretion or resistance against insulin, is the most prevalent metabolic disorder worldwide, and it currently affects over 350 million people globally [1,2]. So far, the exact underlying pathogenic mechanism of DM is still not fully understood. Nevertheless, the fact that over 100 genetic loci were already found to be correlated with an increased susceptibility to DM by past genome-wide association studies suggested that genetic factors were crucial for the occurrence and development of DM [3,4].

Cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) is mainly expressed on activated T cells, and it serves a negative regulator of T cell activation and proliferation [5]. Previous studies showed that CTLA-4 could induce T cell tolerance and attenuate T cell mediated immune responses by binding with co-stimulating molecules, B7-1 (CD80) and B7-2 (CD86) [6], and dysfunction of CTLA-4 was demonstrated to be implicated in various autoimmune diseases including type 1 diabetes mellitus (T1DM) [7,8]. Consequently, CTLA-4 gene polymorphisms were intensively studied with regard to their associations with T1DM [9–12]. Recently, some pilot studies also analyzed potential associations between CTLA-4 gene polymorphisms and the much more prevalent type 2 diabetes mellitus (T2DM) [13,14]. Nevertheless, whether CTLA-4 gene polymorphisms were associated with T1DM and T2DM or not remain controversial, especially when they were conducted in different populations. Therefore, we performed the present meta-analysis to pool the data of all relevant studies, and obtain more conclusive results on associations of CTLA-4 gene polymorphisms with T1DM and T2DM.

Materials and methods

Literature search and inclusion criteria

The current meta-analysis was complied with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement [15]. Potentially relevant articles were searched in PubMed, Medline, Web of Science, and CNKI using the following key words: ‘Cytotoxic T-lymphocyte antigen 4’, ‘CTLA-4’, ‘polymorphism’, ‘variant’, ‘mutation’, ‘genotype’, ‘allele’, ‘diabetes mellitus’, ‘diabetes’, and ‘DM’. The initial literature search was conducted in October 2018 and the latest update was performed in January 2019. We also screened the reference lists of all retrieved articles to identify other potentially relevant studies.

Included studies should met all the following criteria: (1) case–control study on associations between CTLA-4 gene polymorphisms and individual susceptibility to DM; (2) provide adequate data to calculate odds ratios (ORs) and 95% confidence intervals (CIs); (3) full text in English or Chinese available. For duplicate reports, only the most complete one was included. Family-based association studies, case reports, case series, reviews, comments, letters, and conference presentations were excluded.

Data extraction and quality assessment

The following data were extracted from included studies: (1) name of first author; (2) year of publication; (3) country and ethnicity of participants; (4) type of disease; (5) the number of cases and controls; and (6) genotypic distributions of CTLA-4 gene polymorphisms in cases and controls. The probability value (p value) of Hardy–Weinberg equilibrium (HWE) test was also calculated.

The Newcastle–Ottawa scale (NOS) was used to assess the quality of eligible studies from three aspects: (1) selection of cases and controls; (2) comparability between cases and controls; and (3) exposure in cases and controls [16]. The NOS has a score range of 0–9, and studies with a score of more than 7 were assumed to be of high quality.

Two reviewers conducted data extraction and quality assessment independently. When necessary, the reviewers wrote to the corresponding authors for extra information. Any disagreement between two reviewers was solved by discussion until a consensus was reached.

Statistical analyses

All statistical analyses in the present study were conducted with Review Manager Version 5.3.3 (The Cochrane Collaboration, Software Update, Oxford, United Kingdom). ORs and 95% CIs were used to assess potential associations of CTLA-4 gene polymorphisms with the susceptibility to DM in dominant, recessive, over-dominant, and allele models, and a P value of 0.05 or less was considered to be statistically significant. Between-study heterogeneity was evaluated by I2 statistic. If I2 was greater than 50%, random-effect models (REMs) would be used for analyses due to the existence of significant heterogeneities. Otherwise, fixed-effect models (FEMs) would be employed for analyses. Subgroup analyses by ethnicity of participants were subsequently performed. Sensitivity analyses were carried out to test the stability of the results. Funnel plots were applied to evaluate possible publication biases.

Results

Characteristics of included studies

Our systematic literature search yielded 842 results. After exclusion of irrelevant and duplicate articles by reading titles and abstracts, 135 potentially relevant articles were retrieved for further evaluation. Another 59 articles were subsequently excluded after reading the full text. Finally, a total of 76 studies that met the inclusion criteria of our meta-analysis were included (see Figure 1). Characteristics of included studies are shown in Table 1.

Figure 1. Flowchart of study selection for the present study.

Figure 1

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Table 1. The characteristics of included studies.

First author, year Country Ethnicity Type of disease Sample size Genotypes (wtwt/wtmt/mtmt) P value for HWE NOS score
Cases Controls
rs231775 A/G
Abe 1999 Japan East Asian T1DM 111/445 50/45/16 177/207/61 0.969 7
Ahmadi 2013 Iran South Asian T1DM 60/107 25/32/3 67/36/4 0.757 7
Ahmedov 2006 Azerbaijan Republic Caucasian T1DM 160/271 80/58/22 143/103/25 0.307 7
Awata 1998 Japan East Asian T1DM 173/425 72/80/21 170/197/58 0.938 7
Balic 2009 Chile Mixed T1DM 300/310 125/136/39 138/131/41 0.267 7
Baniasadi 2006 India South Asian T1DM 130/180 50/62/18 76/79/25 0.541 8
Benmansour 2010 Tunisia South Asian T1DM 228/193 98/83/47 104/69/20 0.102 7
Bouqbis 2003 Morocco Caucasian T1DM 118/114 59/52/7 59/47/8 0.742 7
Caputo 2005 Argentina Mixed T1DM 186/168 76/84/26 71/76/21 0.924 7
Çelmeli 2013 Turkey Caucasian T1DM 91/99 38/40/13 43/49/7 0.161 7
Chen 2011 China East Asian T1DM 360/728 199/136/25 329/319/80 0.839 8
Cinek 2002 Czech Republic Caucasian T1DM 305/289 123/125/57 106/133/50 0.458 8
Cosentino 2002 Italy Caucasian T1DM 80/85 21/55/4 40/40/5 0.219 7
Dallos 2008 Slovakia Caucasian T1DM 171/231 33/72/66 55/126/50 0.164 8
Ding 2010 China East Asian T1DM 23/33 2/14/7 28/4/1 0.126 7
Djilali-Saiah 1998 France Caucasian T1DM 112/100 37/41/34 47/37/16 0.070 7
Donner 1997 Germany Caucasian T1DM 293/325 91/147/55 135/149/41 0.990 7
Douroudis 2009 Estonia Caucasian T1DM 170/230 45/79/46 68/125/37 0.104 7
Douroudis 2009 Finland Caucasian T1DM 404/725 69/203/132 159/378/188 0.232 7
Ei Wafai 2011 Saudi Arabia South Asian T1DM 39/46 9/21/9 25/21/0 0.045 7
Fajardy 2002 France Caucasian T1DM 134/273 41/76/17 96/146/31 0.027 7
Ferreira 2009 Brazil Mixed T1DM 49/48 26/20/3 22/21/5 0.997 7
Genc 2004 Turkey Caucasian T1DM 48/80 24/20/4 43/34/3 0.233 8
Haller 2007 Estonia Caucasian T1DM 131/252 27/62/42 77/135/40 0.131 7
Hauache 2005 Brazil Mixed T1DM 124/75 42/63/19 30/34/11 0.787 8
Hayashi 1999 Japan East Asian T1DM 117/141 54/42/21 72/47/22 0.005 7
Ide 2004 Japan East Asian T1DM 116/114 56/49/11 34/59/21 0.603 7
Ihara 2001 Japan East Asian T1DM 160/200 NA NA NA 7
Ikegami 2006 Japan East Asian T1DM 767/715 439/285/43 395/283/37 0.131 7
Jin 2015 China East Asian T1DM 402/482 182/194/26 169/241/72 0.354 7
Jung 2009 Korea East Asian T1DM 176/90 94/58/24 46/31/13 0.053 7
Kamoun 2001 Tunisia South Asian T1DM 74/49 32/38/4 11/28/10 0.316 7
Kawasaki 2008 Japan East Asian T1DM 91/369 48/36/7 122/186/61 0.484 7
Khoshroo 2017 Iran South Asian T1DM 39/40 11/10/18 13/15/12 0.114 7
Kikuoka 2001 Japan East Asian T1DM 125/200 57/62/6 78/88/34 0.287 8
Klitz 2002 USA Mixed T1DM 94/90 NA NA NA 7
Korolija 2009 Croatia Caucasian T1DM 102/193 48/36/18 96/84/13 0.345 7
Kumar 2015 India South Asian T1DM 232/305 95/101/36 169/116/20 0.987 7
Lee 2000 Taiwan East Asian T1DM 253/91 150/85/18 37/45/9 0.378 7
Lemos 2009 Portugal Caucasian T1DM 207/249 82/95/30 111/108/30 0.637 7
Liang 2004 Japan East Asian T1DM 29/40 19/10/0 10/27/3 0.013 7
Ma 2002 China East Asian T1DM 31/36 5/11/15 19/9/8 0.007 7
McCormack 2001 UK Caucasian T1DM 144/307 NA NA NA 7
Mochizuki 2003 Japan East Asian T1DM 97/60 44/36/17 21/27/12 0.539 7
Mojtahedi 2005 Iran South Asian T1DM 109/331 21/78/10 146/149/36 0.826 7
Momin 2009 USA Mixed T1DM 261/280 113/112/36 131/119/30 0.702 7
Mosaad 2012 Egypt South Asian T1DM 104/78 37/59/8 38/39/1 0.010 7
Nisticò 1996 Italy Caucasian T1DM 483/529 161/248/74 236/242/51 0.329 8
Ongagna 2002 France Caucasian T1DM 62/84 49/10/3 43/27/14 0.013 7
Osei-Hyiaman 2001 Japan East Asian T1DM 350/420 110/166/74 201/177/42 0.741 8
Padma-Malini 2018 India South Asian T1DM 196/196 78/93/25 128/61/7 0.936 8
Pérez 2009 Chile Mixed T1DM 260/255 116/110/34 110/106/39 0.115 7
Philip 2011 India South Asian T1DM 53/53 5/30/18 32/15/6 0.064 7
Ranjouri 2016 Iran South Asian T1DM 50/50 36/12/2 41/7/2 0.044 8
Saleh 2008 Egypt South Asian T1DM 396/396 166/175/55 215/150/31 0.501 7
Song 2012 China East Asian T1DM 108/100 73/25/10 45/39/16 0.138 7
Steck 2005 USA Mixed T1DM 102/198 NA NA NA 7
Takara 2000 Japan East Asian T1DM 74/107 16/25/33 34/43/30 0.044 7
Tavares 2015 Brazil Mixed T1DM 204/305 82/91/31 127/140/38 0.952 7
Van der Auwera 1997 Belgium Caucasian T1DM 525/530 NA NA NA 7
Wang 2002 China East Asian T1DM 90/84 13/54/23 32/42/10 0.500 7
Wang 2008 China East Asian T1DM 48/192 4/29/15 124/52/16 0.004 8
Wood 2002 Germany Caucasian T1DM 176/220 59/84/33 99/95/26 0.662 7
Xiang 2006 China East Asian T1DM 179/290 79/86/14 87/153/50 0.216 8
Yanagawa 1999 Japan East Asian T1DM 110/200 45/46/19 78/88/34 0.287 7
Yang 2006 China East Asian T1DM 34/71 23/8/3 32/28/11 0.253 7
Zalloua 2004 USA Mixed T1DM 190/102 91/75/24 53/45/4 0.137 7
Ahmadi 2013 Iran South Asian T2DM 56/107 35/18/3 67/36/4 0.757 7
Ding 2010 China East Asian T2DM 34/33 21/11/2 28/4/1 0.126 7
Gu 2007 China East Asian T2DM 111/39 35/71/5 15/20/4 0.475 7
Haller 2007 Estonia Caucasian T2DM 244/252 76/122/46 77/135/40 0.131 7
Jin 2015 China East Asian T2DM 330/482 128/171/31 169/241/72 0.354 7
Khoshroo 2017 Iran South Asian T2DM 71/40 39/17/18 13/15/12 0.114 7
Kiani 2016 Iran South Asian T2DM 111/100 60/42/9 41/39/20 0.066 7
Ma 2002 China East Asian T2DM 31/36 7/17/7 19/9/8 0.007 7
Rau 2001 Germany Caucasian T2DM 300/466 126/140/34 183/215/68 0.707 8
Shih 2018 Taiwan East Asian T2DM 278/287 118/127/33 101/150/36 0.084 7
Uzer 2010 Turkey Caucasian T2DM 72/169 43/24/5 113/45/11 0.035 7
Wang 2008 China East Asian T2DM 192/192 59/102/31 124/52/16 0.004 8
Yu 2006 China East Asian T2DM 121/39 35/71/5 15/20/4 0.475 7
rs5742909
Almasi 2015 Iran South Asian T1DM 153/189 143/10/0 174/14/1 0.235 7
Balic 2009 Chile Mixed T1DM 300/310 243/50/7 253/47/10 <0.001 7
Baniasadi 2006 India South Asian T1DM 130/180 113/15/2 170/10/0 0.701 8
Benmansour 2010 Tunisia South Asian T1DM 228/193 159/52/17 156/29/8 <0.001 7
Bouqbis 2003 Morocco Caucasian T1DM 118/114 106/12/0 110/4/0 0.849 7
Caputo 2007 Argentina Mixed T1DM 178/136 149/28/1 110/26/0 0.218 7
Chen 2011 China East Asian T1DM 359/728 281/71/7 550/164/14 0.664 8
Douroudis 2009 Estonia Caucasian T1DM 61/230 52/8/1 178/49/3 0.857 7
Ihara 2001 Japan East Asian T1DM 160/200 NA NA NA 7
Lee 2001 Taiwan East Asian T1DM 347/260 303/42/2 201/56/3 0.681 7
Saleh 2008 Egypt South Asian T1DM 396/396 180/178/38 214/164/18 0.053 7
Steck 2005 USA Mixed T1DM 102/198 NA NA NA 7
Wang 2008 China East Asian T1DM 48/189 30/18/0 155/34/0 0.174 8
Zouidi 2014 Tunisia South Asian T1DM 76/162 68/7/1 145/15/2 0.040 7
Kiani 2016 Iran South Asian T2DM 111/100 75/26/10 88/10/2 0.020 7
Shih 2018 Taiwan East Asian T2DM 278/287 227/49/2 215/67/5 0.933 7
Uzer 2010 Turkey Caucasian T2DM 72/169 55/14/3 116/43/10 0.036 7
Wang 2008 China East Asian T2DM 192/189 157/35/0 155/34/0 0.174 8
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Abbreviations: wt, wild type; mt, mutant type; NA, not available.

CTLA-4 gene polymorphisms and the susceptibility to DM

Significant associations with susceptibility to T1DM were detected for rs231775 (dominant model: P=0.008, OR = 0.83, 95%CI 0.73–0.95; recessive model: P=0.003, OR = 1.27, 95%CI 1.09–1.50; allele model: P=0.004, OR = 0.85, 95%CI 0.77–0.95) and rs5742909 (recessive model: P=0.02, OR = 1.50, 95%CI 1.05–2.13) polymorphisms in overall population. Nevertheless, no any positive results were detected for T2DM in overall population.

Further subgroup analyses revealed that rs231775 polymorphism was significantly associated with susceptibility to T1DM in Caucasians (dominant, recessive, and allele models) and South Asians (dominant, recessive, over-dominant, and allele models), but not in East Asians. Moreover, rs231775 polymorphism was also significantly associated with susceptibility to T2DM in East Asians (over-dominant model) and South Asians (recessive and allele models), but not in Caucasians. Additionally, we also found that rs5742909 polymorphism was significantly associated with susceptibility to T1DM in South Asians (dominant, recessive, over-dominant, and allele models), but not in East Asians and Caucasians (see Table 2).

Table 2. Overall and subgroup analyses for CTLA-4 gene polymorphisms and DM.

Variables Sample size Dominant comparison Recessive comparison Over-dominant comparison Allele comparison
P value OR (95%CI) P value OR (95%CI) P value OR (95%CI) P value OR (95%CI)
rs231775 A/G
T1DM
Overall 11420/14674 0.008* 0.83 (0.73–0.95) 0.003* 1.27 (1.09–1.50) 0.59 1.03 (0.93–1.13) 0.004* 0.85 (0.77–0.95)
Caucasian 3854/5102 <0.0001† 0.74 (0.67–0.81) <0.0001† 1.61 (1.42–1.83) 0.76 0.99 (0.90–1.08) <0.0001† 0.77 (0.72–0.82)
East Asian 4024/5633 0.73 1.05 (0.80–1.37) 0.78 0.95 (0.69–1.32) 0.32 0.92 (0.77–1.09) 0.79 1.03 (0.83–1.28)
South Asian 1710/2024 <0.0001† 0.52 (0.38–0.70) 0.005* 1.79 (1.19–2.70) 0.001* 1.47 (1.17–1.86) <0.0001† 0.60 (0.48–0.75)
T2DM
Overall 1951/2242 0.34 0.85 (0.61–1.19) 0.12 1.16 (0.96–1.40) 0.14 1.22 (0.94–1.59) 0.58 0.94 (0.74–1.19)
Caucasian 616/887 0.82 1.03 (0.83–1.27) 0.75 0.95 (0.70–1.29) 0.99 1.00 (0.81–1.23) 0.75 1.03 (0.88–1.20)
East Asian 1097/1108 0.08 0.58 (0.32–1.07) 0.59 0.88 (0.54–1.42) 0.04‡ 1.66 (1.03–2.68) 0.15 0.74 (0.49–1.12)
South Asian 238/247 0.06 0.59 (0.34–1.02) 0.02‡ 1.56 (1.08–2.27) 0.36 0.84 (0.57–1.23) 0.003* 0.65 (0.49–0.87)
rs5742909 C/T
T1DM
Overall 2656/3485 0.37 0.87 (0.65–1.18) 0.02‡ 1.50 (1.05–2.13) 0.51 1.10 (0.83–1.45) 0.36 0.89 (0.70–1.13)
Caucasian 179/344 0.77 0.78 (0.15–3.96) 0.84 1.26 (0.13–12.34) 0.80 1.25 (0.23–6.72) 0.72 0.76 (0.17–3.36)
East Asian 914/1377 0.99 1.00 (0.47–2.14) 0.74 0.87 (0.38–1.98) 1.00 1.00 (0.47–2.13) 0.80 1.07 (0.65–1.73)
South Asian 983/1120 0.0004§ 0.68 (0.55–0.84) 0.002§ 2.05 (1.30–3.23) 0.04‡ 1.27 (1.02–1.58) <0.0001† 0.69 (0.58–0.82)
T2DM
Overall 653/745 0.80 0.92 (0.48–1.77) 0.89 1.11 (0.27–4.65) 0.93 1.02 (0.61–1.73) 0.76 0.90 (0.47–1.74)
East Asian 470/476 0.13 1.28 (0.93–1.75) 0.29 0.41 (0.08–2.12) 0.20 0.81 (0.59–1.12) 0.11 1.27 (0.95–1.71)
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*

P < 0.01.

†

P < 0.0001.

‡

P < 0.05.

§

P < 0.001.

Sensitivity analyses

Sensitivity analyses were carried out to test the stability of meta-analysis results by eliminating studies that deviated from HWE. No changes of results were detected for investigated CTLA-4 gene polymorphisms in any comparisons, which indicated that our findings were quite statistically reliable.

Publication biases

Potential publication biases in the present study were evaluated with funnel plots. No obvious asymmetry of funnel plots was observed in any comparisons, which suggested that our findings were unlikely to be impacted by severe publication biases.

Discussion

Despite enormous advancements in pharmacotherapy over the past few decades, DM and its associated vascular complications are still leading causes of death and disability all over the world [17,18]. To date, the exact cause of DM is still largely unclear in spite of extensive investigations. However, the obvious familial aggregation tendency of DM indicated that genetic factors may significantly contribute to its occurrence and development [19]. Thus, identify potential genetic biomarkers is of particularly importance for an early diagnosis and a better prognosis of DM patients.

Previous studies showed that interferon α and its associated pathways could induce autoantigen presentation, active autoreactive monocytes, cytotoxic T-lymphocytes and NK cells, elicit endoplasmic reticulum stress of human islet B cells, and impair insulin production [20,21]. These results indicated that autoimmunity might result in destruction of islet B cells, contribute to less insulin production, and give rise to the development of DM. As far as we know, this is so far the most comprehensive meta-analysis about CTLA-4 gene polymorphisms and DM, and our pooled analyses revealed that rs231775 and rs5742909 polymorphisms may serve as genetic biomarkers of T1DM, and rs231775 polymorphism may also serve as a genetic biomarker of T2DM. The stabilities of synthetic results were evaluated by sensitivity analyses, and no alterations of results were observed in any comparisons, which suggested that our findings were statistically stable. As for evaluation of heterogeneities, significant heterogeneities were detected for rs231775 polymorphism in every comparison of overall analyses for T1DM, and thus all analyses were performed with REMs. But in further subgroup analyses, a reduction tendency of heterogeneity was found in South Asians, which suggested that differences in ethnicity could partially explain observed heterogeneities between studies.

There are several points that need to be addressed about the present study. First, our findings indicated that rs231775 and rs5742909 polymorphisms could be used to identify individuals at higher risk of developing T1DM, and rs231775 polymorphism could also be used to identify individuals at higher risk of developing T2DM. There are two possible explanations for our positive findings. First, rs231775 and rs5742909 polymorphisms of the CTLA-4 gene may lead to alternations in gene expression or changes in CTLA-4 protein structure, which may subsequently affect biological functions of CTLA-4, result in immune dysfunction and ultimately impact individual susceptibility to DM, especially T1DM. Second, it is noteworthy that several analyses were still based on limited number of studies, and therefore, further replication studies, especially in T2DM are still warranted to confirm these findings. Third, the pathogenic mechanism of DM is extremely complex, and hence despite our positive findings, it is unlikely that a single genetic polymorphism could significantly contribute to its development [22,23]. Fourth, due to lack of raw data, we failed to explore possible interactions of investigated CTLA-4 gene polymorphisms. But to better illustrate the potential associations of CTLA-4 gene polymorphisms with DM, we strongly recommend further studies to perform haplotype analyses and explore potential gene–gene interactions.

Our meta-analysis certainly has some limitations. First, although the general methodology qualities of included studies were good, it should be noted that we did not have access to genotypic distributions of investigated polymorphisms according to base characteristics of study subjects. Therefore, our results were derived from unadjusted estimations, and failure to conduct further adjusted analyses for baseline characteristics of participants such as age, gender, and co-morbidity conditions may influence the authenticity of our findings [24]. Second, significant heterogeneities were detected in certain subgroup comparisons, which indicated that the inconsistent results of included studies could not be fully explained by differences in ethnic background, and other unmeasured characteristics of participants may also partially attribute to between-study heterogeneities [25]. Third, associations between CTLA-4 gene polymorphisms and DM may also be influenced by gene–environmental interactions. However, the majority of studies did not consider these potential interactions, which impeded us to perform relevant analyses accordingly [26]. Fourth, since only published articles were eligible for analyses, although funnel plots revealed no obvious publication biases, we still could not rule out the possibility of potential publication biases. Taken these limitations into consideration, the results of the present study should be interpreted with caution.

In conclusion, our findings indicated that rs231775 and rs5742909 polymorphisms may serve as genetic biomarkers of T1DM, and rs231775 polymorphism may also serve as a genetic biomarker of T2DM. Further well-designed studies, especially in T2DM are still warranted to confirm our findings, and future investigations also need to explore possible roles of other CTLA-4 gene polymorphisms in DM.

Abbreviations

CI

confidence interval

CTLA-4

cytotoxic T-lymphocyte-associated antigen 4

DM

diabetes mellitus

HWE

Hardy–Weinberg equilibrium

NOS

Newcastle–Ottawa scale

OR

odds ratio

REM

random-effect model

T1DM

type 1 diabetes mellitus

T2DM

type 2 diabetes mellitus

Author Contribution

Min Chen and ShuMin Li conceived of the study, participated in its design, conducted the systematic literature review, performed data analyses, and drafted the manuscript. Both the authors have read and approved the final manuscript.

Competing Interests

The authors declare that there are no competing interests associated with the manuscript.

Funding

The authors declare that there are no sources of funding to be acknowledged.

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