Journal of Diabetes Research
Volume 2016 (2016), Article ID 3694957, 19 pages
http://dx.doi.org/10.1155/2016/3694957

Research Article

Changes of Regulatory T Cells and of Proinflammatory and Immunosuppressive Cytokines in Patients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis

Yong-chao Qiao,1,2 Jian Shen,¹ Lan He,³ Xue-zhi Hong,¹ Fang Tian,² Yan-hong Pan,¹ Ling Liang,¹ Xiao-xi Zhang,1,4 and Hai-lu Zhao1,2,4

¹Diabetic Systems Medicine, Guangxi Key Laboratory of Excellence, Guilin Medical University, Guilin 541004, China
²Department of Immunology, School of Basic Medical Sciences, Central South University, Changsha, Hunan 410078, China
³Department of Microbiology, The Chinese University of Hong Kong, Shatin, Hong Kong
⁴Department of Immunology, Faculty of Basic Medicine, Guilin Medical University, Guilin 541004, China

Received 21 March 2016; Revised 9 August 2016; Accepted 30 August 2016

Academic Editor: Bernard Portha

Copyright © 2016 Yong-chao Qiao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Objective. The aim of this study was to investigate the changes of regulatory T cells (Treg), interleukin-6 (IL-6), IL-10, transforming growth factor-β (TGF-β), and tumor necrosis factor-alpha (TNF-α) in patients with type 2 diabetes mellitus (T2DM). Methods. We performed a comprehensive search up to July 2016 for all clinical studies about the changes of Treg, IL-6, IL-10, IL-17, TGF-β, and TNF-α in T2DM patients versus healthy controls. Results. A total of 91 articles (5642 cases and 7378 controls) were included for this meta-analysis. Compared with the controls (all ), the patients had increased serum levels of IL-6, TGF-β, and TNF-α but decreased the percentage of peripheral CD4⁺CD25⁺Foxp3⁺Treg and serum IL-10 level. Furthermore, the percentage of peripheral CD4⁺CD25⁺Foxp3⁺Treg () and serum IL-10 level () were significantly lower in the patients with complication and in the patients without complication, respectively. No significant changes about the percentage of CD4⁺CD25⁺Treg () and serum IL-17 level () were found in T2DM patients. Conclusions. T2DM patients have decreased the percentage of peripheral CD4⁺CD25⁺Foxp3⁺Treg and levels of serum IL-10 but elevated serum levels of IL-6, TGF-β, and TNF-α. Presence of diabetic complications further lowers the peripheral CD4⁺CD25⁺Foxp3⁺Treg number.

1. Introduction

Type 2 diabetes mellitus (T2DM) is one of the most common noncommunicable diseases characterized by insulin resistance and impaired insulin secretion [1, 2]. Metabolic proinflammatory disorder including chronic hyperglycemia and increased levels of circulating cytokines suggests immunological disturbances [3–7], which seriously affects the quality of life of the patients and imposes a large economic burden on the national health care system [8]. Genetic and environmental factors are blamed for T2DM and up to 25% of first-degree relatives of T2DM patients may develop this disease [9]. The origin and development of T2DM were involved in multiple risk factors [10]. Regulatory T cells (Treg) and cytokines play important roles in the development of T2DM.

Treg is a subset of CD4⁺ T cells that maintain peripheral tolerance and suppress antigen specific immune responses by secreting transforming growth factor-β (TGF-β), interleukin-10 (IL-10), and IL-4 to inhibit autoimmunity [11]. It was found that the ratios of cells and cells were significantly decreased in T2DM patients [12]. Expression of Foxp3, a key player for the development and function of Treg, correlates well with regulatory activity and number of Treg. Indeed, Foxp3 is exclusively expressed in CD4⁺CD25⁺Treg [13–16]. A positive correlation between CD4⁺CD25⁺Foxp3⁺Treg and the enhanced expression of IL-6 on CD4⁺ T cells was observed in T2DM patients [17]. IL-10, as a multifunctional cytokine and secretion of Treg, plays a key role in the inflammatory response that is associated with insulin resistant states and T2DM [18]. Increased levels of IL-17 were found to protect against autoimmune mediated T1DM in nonobese diabetic mice [19]. On the other hand, loss of IL-17 has been associated with disease susceptibility in part because it has been suggested that the absence of IL-17 results in enhanced production of other proinflammatory cytokines [20]. TGF-β is also a multifunctional cytokine circulating as a biologically inactive form in human plasma [21, 22]. The TGF-β family includes multifunctional molecules that exert specific effects on cell proliferation, differentiation, migration, development, tissue remodeling, and repair [23]. TNF-α inhibits the insulin signaling cascade through regulating several pivotal regulatory proteins, such as the insulin receptor substrate (IRS) and Akt substrate 160 in human skeletal muscle in vitro [24] and in vivo [25]. It has reported that polymorphism of immune genes such as TNF-α [26] and TGF-β [27] was associated with the development of T2DM. Intriguingly, increased renal production of TGF-β was a distinct feature of diabetes [28–31].

Within the past few years, many clinical studies have been focusing on the association of Treg with proinflammatory and immunosuppressive cytokines in T2DM. Despite intensive research efforts, results of these studies have been inconsistent. Therefore, we performed this meta-analysis synthesizing the data from case-control studies to evaluate changes of Treg, IL-6, IL-10, IL-17, TGF-β, and TNF-α in T2DM patients.

2. Materials and Methods

2.1. Study Identification and Search Strategy

Our study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria [32]. We identified relevant studies of Treg, IL-6, IL-10, IL-17, TGF-β, and TNF-α in T2DM patients by systematically searching PubMed, Wanfang database, Chinese-Cqvip, and CNKI databases from February 1, 1991, to July 15, 2016. The search terms used were as follows: (“interleukin-6” or “IL-6”) or (“interleukin-10” or “IL-10”) or (“interleukin-17” or “IL-17”) or (“transforming growth factor beta” or “TGF-β”) or (“tumor necrosis factor alpha” or “TNF-α”) or (“regulatory T cells” or “Treg” or “CD4⁺CD25⁺ T cell” or “CD4⁺CD25⁺Foxp3⁺ T cell”) and (“type 2 diabetes mellitus” or “type 2 diabetes” or “diabetes mellitus” or “diabetic patients” or “T2DM” or “DM”). In addition, we also conducted an extensive literature search and articles were further identified in reference lists. Data published in either English or Chinese were included.

2.2. Inclusion Criteria

We reviewed all relevant articles using the following inclusion criteria: (1) the study should evaluate the relationship of CD4⁺CD25⁺Foxp3⁺Treg, CD4⁺CD25⁺Treg, IL-6, IL-10, IL-17, TGF-β, or TNF-α with T2DM patients; (2) the design had to be a case-control study; (3) original data were displayed or could be converted to as mean ± SD; and (4) original report showed no duplicated data.

2.3. Quality Assessment and Data Extraction

The data were extracted independently by two reviewers (Yong-chao Qiao and Jian Shen) by using predefined data extraction forms and the quality of all eligible studies was evaluated according to the Newcastle-Ottawa Scale (NOS) [33]. The following information was extracted: (1) name of the first author; (2) date of publication; (3) country of the study; (4) study design; (5) sample size of patients and controls; (6) mean age of the sample; and (7) mean ± SD of patients and controls. In case of disagreement, a third investigator (Hai-lu Zhao) was invited to assess such articles and the disagreements were resolved through discussion.

2.4. Statistical Analysis

We presented the data (sample size, mean ± SD) to illustrate the changes of Treg, IL-6, IL-10, IL-17, TGF-β, and TNF-α in T2DM patients versus healthy controls, and Chi-squared test and statistics were used to assess heterogeneity. When or , the heterogeneity was considered significant and a random effect model was used; otherwise, a fixed-effect model was used. Considering the influence of diabetic complications, patients were divided into two groups (T2DM with complication and T2DM without complication) for subgroup analysis. Regression analysis is also an important method for exploring sources of heterogeneity. We performed sensitivity analysis by limiting the studies of NOS score ≥ 7 or excluding studies with a high risk of bias. Publication bias was examined graphically by constructing Egger’s test and was considered to be representative of statistically significant publication bias. Stata 12.0 software was performed in this meta-analysis.

3. Results

3.1. The Process and Results of Selection

The flow chart of the article search and inclusion process was displayed in Figure 1. Based on the search strategy, a total of 5,064 articles were collected and 332 were removed after our initial screening. Furthermore, 3,954 articles were excluded because they were not DM relevant, have no controls, or were animal studies or review articles. Then, we excluded 687 studies because of duplicated data, no original data, or original data expressed with figures. Eventually, this meta-analysis included 91 articles involving 138 case-control studies of 5642 T2DM patients and 7378 healthy controls: 13 for IL-6 [34–46], 22 for TGF-β [23, 47–67], 7 for TNF-α [34–36, 38, 45, 68, 69], 6 for CD4⁺CD25⁺Foxp3⁺Treg [70–75], 15 for IL-10 [76–90], 18 for CD4⁺CD25⁺Treg [70, 72, 74, 75, 91–104], and 10 for IL-17 [105–114]. Main characteristics of the 91 included studies were listed in Tables 1–7. The case-control study of T2DM with complication was labelled with “”. NOS results showed high methodological quality.

Table 1: Characteristics of studies about IL-6 (pg/mL) included in this meta-analysis.

Author
Year
Country
Case
Control
NOS score

SZ
M/F
Mean
SD
SZ
M/F
Mean
SD

Plomgaard [34]
2007
Denmark
96
72/24
1.63
1.22
103
70/33
1.27
1.04
7

Volpe [35]
2014
Brazil
29
10/19
119.1
23.3
16
5/11
97.6
13.5
8

Yeo [36]
2010
Korea
55
27/28
2.3
0.35
488
257/231
1.8
0.11
8

Kado [37]
1999
Japan
57
NR
3.48
3.29
15
NR
0.784
0.9
7

Lukic [38]
2014
Serbia
30
NR
11.77
6.09
15
NR
3.48
1.48
8

Lukic [38]
2014
Serbia
30
NR
15.46
5.15
15
NR
3.48
1.48
8

Hansen [39]
2012
Denmark
8
NR
4.6
5.2
8
NR
1.4
1.15
7

Andriankaja [40]
2009
USA
30
NR
1.5
1.4
310
NR
1.8
2.3
8

Andriankaja [40]
2009
USA
50
NR
2.9
3.2
310
NR
1.8
2.3
8

Guzel [41]
2013
Turkey
28
NR
3.21
1.24
30
19/14
1.73
0.93
8

Guzel [41]
2013
Turkey
17
NR
6.67
2.67
30
19/14
1.73
0.93
8

Aso [42]
2003
Japan
42
22/20
3.15
1.53
48
NR
1.29
0.52
7

Lim [43]
2004
England
56
31/25
1.9
8.02
39
21/18
1
1.59
8

Lim [43]
2004
England
41
30/11
2.6
26.95
39
21/18
1
1.59
7

Hui [44]
2015
China
48
20/28
16.17
8.36
20
13/7
5.2
2.03
8

Daniele [45]
2014
USA
17
13/4
2.1
0.4
15
7/8
1.7
0.4
8

Głowińska [46]
2003
Polish
28
NR
6.5
1.4
15
NR
2.3
2.3
7

DM: diabetes mellitus; SZ: sample size; M/F: man/female; SD: standard deviation; NR: not reported. T2DM with complication and data (mean ± SD) converted from mean (95% CI).

Table 2: Characteristics of studies about TGF-β (g/L) included in this meta-analysis.

Author
Year
Country
Case
Control
NOS score

SZ
M/F
Mean
SD
SZ
M/F
Mean
SD

Azar [47]
1999
Lebanon
26
8/18
0.558
0.107
27
10/17
0.593
0.064
8

Azar [48]
2000
Lebanon
8
3/5
10.8
2.3
15
9/6
4.1
0.5
8

Azar [48]
2000
Lebanon
9
2/7
9.9
2.8
15
9/6
4.1
0.5
8

Azar [48]
2000
Lebanon
8
5/3
10.7
2.2
15
9/6
4.1
0.5
8

Jun-Wen [49]
2007
China
61
35/26
315.9
224.59
19
10/9
68.47
31.75
7

Chi [50]
2013
China
20
11/9
18.55
2.67
18
10/8
8.97
4.087
8

Chi [50]
2013
China
20
9/11
19.04
2.87
18
10/8
8.97
4.087
8

Chi [50]
2013
China
21
13/8
18.12
3.17
18
10/8
8.97
4.087
8

Ehnert [51]
2015
Germany
14
7/7
35.3
2.4
13
7/6
39.5
1.4
8

Changxin [52]
2007
China
34
24/10
36.2
8.8
35
24/11
34.4
8.2
7

Changxin [52]
2007
China
31
21/10
69.4
12.8
35
24/11
34.4
8.2
7

Hellmich [53]
2000
Germany
35
16/19
9.5
2.1
12
5/7
0.24
0.03
8

Hellmich [53]
2000
Germany
23
8/15
10.8
2.1
12
5/7
0.24
0.03
8

Herder [54]
2009
Germany
460
255/205
35.8
0.4
1474
724/750
35
0.2
8

Hai-bing [55]
2001
China
14
7/7
35.02
6.7
15
7/8
23.95
8.01
6

Hai-bing [55]
2001
China
13
5/8
58.58
9.56
15
7/8
23.95
8.01
6

Hai-bing [55]
2001
China
18
9/9
39.31
5.35
15
7/8
23.95
8.01
6

Zhen-zuo [56]
2005
China
27
14/13
41
15.57
18
9/9
10.04
5.33
7

Zhen-zuo [56]
2005
China
12
7/5
66.35
18.04
18
9/9
10.04
5.33
7

Zhen-zuo [56]
2005
China
18
9/9
53.31
15.64
18
9/9
10.04
5.33
7

Rui-Ji [57]
2011
China
32
NR
35
5
20
NR
25
5
6

Rui-Ji [57]
2011
China
31
NR
69
7
20
NR
25
5
6

Rui-Ji [57]
2011
China
32
NR
54
6
20
NR
25
5
6

Da-wei [58]
2013
China
15
NR
234.2
29.8
45
NR
69.4
12.5
7

Da-wei [58]
2013
China
32
NR
155.6
19.3
45
NR
69.4
12.5
7

Pfeiffer [59]
1996
Germany
44
22/22
7.9
1
28
16/12
3.1
0.4
8

Yan-Jun [60]
2002
China
34
16/18
147.03
22.57
35
17/18
136.97
37.96
7

Yan-Jun [60]
2002
China
31
15/16
170.65
18.74
35
17/18
136.97
37.96
7

Yaping [61]
2008
China
44
NR
35.4
7.1
35
NR
32.5
6.8
7

Yaping [61]
2008
China
32
NR
68.2
12.5
35
NR
32.5
6.8
7

Ye-Sheng [62]
2005
China
92
42/50
36.89
9.75
105
50/55
25.46
7.88
6

Ye-Sheng [62]
2005
China
91
40/51
41.57
10.55
105
50/55
25.46
7.88
6

Ming-bin [63]
2002
China
15
NR
25.85
6.09
15
8/7
21.4
5.62
6

Ming-bin [63]
2002
China
18
NR
38.53
3.98
15
8/7
21.4
5.62
6

Ming-bin [63]
2002
China
16
NR
31.15
3.51
15
8/7
21.4
5.62
6

Chun-Yan [64]
2005
China
92
NR
45.57
21.78
20
NR
24.58
12.61
7

Yener [23]
2008
Turkey
39
18/21
29.84
7.04
30
16/14
11.37
4.06
8

Yuan [65]
2011
China
51
37/14
1.7399
0.4846
55
40/15
2.1045
0.5327
7

Wei-jie [66]
2007
China
36
19/17
23.35
3.7
40
23/17
20.35
3.7
7

Wei-jie [66]
2007
China
45
25/20
55.28
6.8
40
23/17
20.35
3.7
7

Wei-jie [66]
2007
China
45
23/22
41.31
4.3
40
23/17
20.35
3.7
7

Zhou [67]
2005
China
30
NR
31.12
12.39
30
NR
29.4
10.62
8

Zhou [67]
2005
China
30
NR
136.6
21.45
30
NR
29.4
10.62
8

Zhou [67]
2005
China
30
NR
79.63
15.96
30
NR
29.4
10.62
8

DM: diabetes mellitus; SZ: sample size; M/F: man/female; SD: standard deviation; NR: not reported. T2DM with different complication; T2DM with different duration limited.

Table 3: Characteristics of studies about TNF- (pg/mL) included in this meta-analysis.

Author
Year
Country
Case
Control
NOS score

SZ
M/F
Mean
SD
SZ
M/F
Mean
SD

Plomgaard [34]
2007
Denmark
96
72/24
2.72
0.8
103
70/33
2.4
0.54
8

Yaturu [68]
2008
USA
50
NR
4
0.36
59
NR
3.4
0.29
7

Yaturu [68]
2008
USA
26
NR
4.2
0.47
39
NR
3.2
0.32
8

Lin [69]
2015
China
42
20/22
5.49
1.48
30
14/16
3.46
0.58
8

Lin [69]
2015
China
45
25/20
6.82
2.97
30
14/16
3.46
0.58
8

Volpe [35]
2014
Brazil
29
10/19
78.7
32.7
16
5/11
58.5
29.5
7

Yeo [36]
2010
Korea
55
27/28
1.5
0.95
488
257/231
1.1
0.31
7

Lukic [38]
2014
Serbia
30
NR
1.53
0.42
15
NR
0.71
0.3
8

Lukic [38]
2014
Serbia
30
NR
1.54
0.41
15
NR
0.71
0.3
8

Daniele [45]
2014
USA
17
13/4
2.5
0.3
15
7/8
1.5
0.3
7

DM: diabetes mellitus; SZ: sample size; M/F: man/female; SD: standard deviation; NR: not reported. T2DM with complication and data (mean ± SD) converted from mean (95% CI).

Table 4: Characteristics of studies about the percentage of CD4⁺CD25⁺Foxp3⁺Tregs (%) in the CD4⁺ lymphocyte included in this meta-analysis.

Author
Year
Country
Case
Control
NOS score

SZ
M/F
Mean
SD
SZ
M/F
Mean
SD

Haseda [70]
2013
Japan
20
8/12
4.94
1.78
30
10/20
5.36
1.54
8

Li [71]
2011
China
18
14/4
2.8
8.54
18
12/6
5.01
0.13
7

Li [72]
2014
China
15
NR
2.32
0.5
21
13/8
4.07
1.39
8

Li [72]
2014
China
23
NR
2.91
0.73
21
13/8
4.07
1.39
8

Jing [73]
2009
China
60
33/27
3.2733
1.5835
15
8/7
3.6216
0.6938
8

Zhang [74]
2009
China
17
9/8
5.02
3.59
15
8/7
5.07
3.26
7

Zhang [75]
2012
China
16
11/5
2.21
0.92
19
7/12
2.32
0.6
6

DM: diabetes mellitus; SZ: sample size; M/F: man/female; SD: standard deviation; NR: not reported. T2DM with different complication.

Table 5: Characteristics of studies about IL-10 (pg/mL) included in this meta-analysis.

Author
Year
Country
Case
Control
NOS score

SZ
M/F
Mean
SD
SZ
M/F
Mean
SD

Acharya [76]
2015
India
15
NR
11.35
0.97
15
NR
15.83
2.52
8

Dworacka [77]
2015
Poland
30
17/13
4.1
1.5
30
12/13
3.8
0.9
7

You-fei [78]
2009
China
30
14/16
45.859
7.34
30
13/17
18.181
5.145
7

Ling-Xia [79]
2013
China
20
10/10
8.41
1.22
20
10/10
17.56
1.13
7

Li [80]
2014
China
63
4/6
15.69
3.22
57
5/5
24.13
2.17
8

Chen [81]
2014
China
24
NR
5.8
0.9
25
19/11
6.93
0.89
7

Lu [81]
2014
China
22
NR
3.12
1.03
25
19/11
6.93
0.89
7

Hong [82]
2007
China
46
22/24
4.61
1.2
39
19/20
4.36
0.84
7

Al-Shukaili [83]
2013
Oman
57
28/29
6.95
6
30
20/10
2.9
5.15
8

Xiaojing [84]
2008
China
42
27/15
4.36
2.64
40
25/15
3.64
3.15
7

Yue-Ying [85]
2010
China
34
19/15
4
1.4
50
22/28
4.5
1.6
8

Yue-Ying [85]
2010
China
50
24/26
2.7
0.9
50
22/28
4.5
1.6
8

Wei [86]
2013
China
39
NR
5.11
1.33
40
NR
4.56
1.27
7

Wei [86]
2013
China
39
NR
10.52
2.43
40
NR
4.56
1.27
7

Jing [87]
2013
China
20
11/9
5
2.16
30
NR
5.07
1.32
7

Jing [87]
2013
China
30
19/11
7.58
2.67
30
NR
5.07
1.32
7

Yaghini [88]
2011
Iran
131
NR
9.53
2.27
120
NR
16.11
2.27
7

Hua [89]
2015
China
61
NR
6.98
2.84
40
NR
5.83
1.37
8

Hua [89]
2015
China
52
NR
30.7
9.28
40
NR
5.83
1.37
8

Zhao-Hui [90]
2014
China
50
26/24
8.39
1.18
50
24/26
17.63
1.22
8

Zhao-Hui [90]
2014
China
50
28/22
1.86
0.33
50
24/26
17.63
1.22
8

DM: diabetes mellitus; SZ: sample size: M/F: man/female; SD: standard deviation; NR: not reported. T2DM with complication.

Table 6: Characteristics of studies about the percentage of CD4⁺CD25⁺Tregs (%) in the CD4⁺ lymphocyte included in this meta-analysis.

Author
Year
Country
Case
Control
NOS score

SZ
M/F
Mean
SD
SZ
M/F
Mean
SD

Afzal [91]
2014
Pakistan
30
5/25
14.68
6.21
30
21/9
14.53
4.84
8

Afzal [91]
2014
Pakistan
152
51/101
16.47
6.56
30
21/9
14.53
4.84
8

Chi [92]
2011
China
52
30/22
9.39
2.12
40
20/20
10.43
2.07
7

Chi [92]
2011
China
68
39/29
8.99
2.03
40
20/20
10.43
2.07
7

Haseda [70]
2013
Japan
20
8/12
27.7
11.1
30
10/20
24.9
6.5
7

Ling [93]
2006
China
25
12/13
1.3
0.6
27
13/14
1.3
0.4
8

Ling [93]
2006
China
20
13/7
13.76
3.27
21
10/11
12.98
3.14
8

Kukreja [94]
2002
USA
15
2/13
6.3
0.48
26
12/14
6.9
0.4
8

Hong [95]
2011
China
20
10/10
5.35
2.12
25
15/10
4.06
1.39
7

Hong [95]
2011
China
18
10/8
9.8
7.27
25
15/10
4.06
1.39
7

Li [96]
2012
China
20
10/10
6.24
1.96
30
18/12
4.24
1.5
7

Ye-Hai [97]
2011
China
81
NR
6.05
1.2
38
NR
2.01
0.73
7

Li [72]
2014
China
15
NR
9.14
2.21
21
13/8
15.18
3.6
7

Li [72]
2014
China
13
NR
10.69
2.75
21
13/8
15.18
3.6
7

Wu [98]
2015
China
10
NR
2.1
1.5
20
12/8
2.3
2.2
8

Yang [99]
2007
China
30
18/12
9.84
4.78
30
18/12
8.16
3.65
8

Yang [100]
2014
China
43
19/24
2.02
0.43
52
28/24
2.89
0.39
6

Xue-he [101]
2009
China
22
9/13
6.79
1.75
17
8/9
7.84
1.45
7

Zhang [74]
2009
China
17
9/8
8.5
4.16
15
8/7
8.83
3.87
8

Zhang [102]
2010
China
37
24/13
0.5
0.8
38
21/17
0.7
1
7

Zhang [102]
2010
China
40
26/14
4.7
2.3
38
21/17
0.7
1
7

Tao [103]
2011
China
20
NR
3.74
0.89
20
NR
3.78
0.95
8

Zhang [75]
2012
China
16
11/5
5.29
2.6
19
7/12
9.75
2.13
7

Zhang [104]
2013
China
36
19/17
8.8
3.6
20
11/9
12.4
1.5
7

Zhang [104]
2013
China
30
16/14
6.05
1.06
20
11/9
12.4
1.5
7

DM: diabetes mellitus; SZ: sample size; M/F: man/female; SD: standard deviation; NR: not reported. T2DM with different complication.

Table 7: Characteristics of studies about IL-17 (pg/mL) included in this meta-analysis.

Author
Year
Country
Case
Control
NOS score

SZ
M/F
Mean
SD
SZ
M/F
Mean
SD

Pernet Hara [105]
2016
Brazil
15
0/15
6.98
1.11
10
0/10
16.2
4.39
8

Suzuki [106]
2011
Japan
56
25/31
147.39
113.83
30
2/28
154.52
117.99
7

Afzal [107]
2014
Pakistan
30
5/25
415.01
483.4
30
21/9
718.05
756.55
7

Afzal [107]
2014
Pakistan
152
51/101
375.95
468.19
30
21/9
718.05
756.55
7

Arababadi [108]
2010
Iran
100
41/59
13.7
2.34
100
40/60
4.43
0.54
8

Arababadi [108]
2010
Iran
100
38/62
0.94
0.29
100
40/60
4.43
0.54
8

Liu [109]
2016
China
19
10/9
21.4
5.9
20
8/12
17.3
6.2
7

Roohi [110]
2014
India
38
19/19
6.61
4.97
40
22/18
6.22
4.64
8

Zhan [111]
2015
China
30
14/16
42.24
67.7
30
14/16
9.33
8.15
8

Kologrivova [112]
2014
Russia
35
17/18
100.83
42.7
24
NR
45.29
54.85
7

Bilir [113]
2016
Turkey
33
15/18
466.1
183.075
33
15/18
205.2
67.725
6

Bilir [113]
2016
Turkey
37
17/20
454.9
189.825
33
15/18
205.2
67.725
6

Vasanthakumar [114]
2015
India
65
38/27
59.8
2.8
88
35/53
94.7
12.75
6

Vasanthakumar [114]
2015
India
97
57/40
67.4
2.275
88
35/53
94.7
12.75
6

DM: diabetes mellitus; SZ: sample size; M/F: man/female; SD: standard deviation; NR: not reported. T2DM with complication; data converted from median (interquartile); data converted from median (range); data converted from geometrical mean (range).

Figure 1: A flow chart of the article search and inclusion process.

3.2. Results of Meta-Analysis

Compared with the controls, T2DM patients had significantly increased levels of serum IL-6 (SMD, 1.28; 95% CI, 0.73 to 1.83; ) (Figure 2), TGF-β (SMD, 2.88; 95% CI, 2.37 to 3.40; ) (Figure 3), and TNF-α (SMD, 1.56; 95% CI, 1.10 to 2.02; ) (Figure 4) but significantly decreased the percentage of CD4⁺CD25⁺Foxp3⁺Treg (SMD, −0.47; 95% CI, −0.72 to −0.23; ) (Figure 5) and the level of serum IL-10 (SMD, −1.37; 95% CI, −2.32 to −0.42; ) (Figure 6). Changes in the percentage of CD4⁺CD25⁺Treg (SMD, −0.24; 95% CI, −0.76 to 0.28; ) (Figure 7) and IL-17 (SMD, −0.51; 95% CI, −1.87 to 0.84; ) (Figure 8) were not significant. Some but not all the results of the meta-analysis displayed significant heterogeneity.

Figure 2: Forest plots for serum IL-6 in T2DM patients and controls with random effects model (T2DM without complication, ; T2DM with complication, ; overall, ). with complication.

Figure 3: Forest plots for serum TGF-β in T2DM patients and controls with random effects model (T2DM without complication, ; T2DM with complication, ; overall, ). with complication. with different complication.

Figure 4: Forest plots for serum TNF-α in T2DM patients and controls with random effects model (T2DM without complication, ; T2DM with complication, ; overall, ). with complication.

Figure 5: Forest plots for the frequency of CD4⁺CD25⁺Foxp3⁺Treg in T2DM patients and controls with random effects model (T2DM without complication, ; T2DM with complication; overall, ). with complication. with different complication.

Figure 6: Forest plots for serum IL-10 in T2DM patients and controls with random effects model (T2DM without complication, ; T2DM with complication, ; overall, ). with complication.

Figure 7: Forest plots for the frequency of CD4⁺CD25⁺Treg in T2DM patients and controls with random effects model (T2DM without complication, ; T2DM with complication, ; overall, ). with complication. with different complication.

Figure 8: Forest plots for serum IL-17 in T2DM patients and controls with random effects model (T2DM without complication, ; T2DM with complication, ; overall, ). with complication.

3.3. Subgroup Analysis and Regression Analysis

Subgroup analysis was performed to explore the impact of diabetic complication on the changes in Treg and cytokines. As shown in Figures 2–8, both T2DM patients with complication and the patients without complication had significantly increased levels of serum IL-6 (Figure 2), TGF-β (Figure 3), and TNF-α (Figure 4), while not significant changes were found in the percentage of peripheral CD4⁺CD25⁺Treg (Figure 7) and IL-17 (Figure 8). Intriguingly, T2DM patients with complication showed lower percentage of peripheral CD4⁺CD25⁺Foxp3⁺Treg () (Figure 5), whereas patients without complication had decreased levels of serum IL-10 () (Figure 6).

The high heterogeneity existed in some subgroup analysis. In order to explore the source of heterogeneity, we further conducted regression analysis according to the complication as covariate. The results were as follows: TGF-β (; ; 95% CI, 1.23 to 3.65), IL-6 (; ; 95% CI, −1.09 to 1.18), TNF-α (; ; 95% CI, −1.23 to 1.67), CD4⁺CD25⁺Foxp3⁺Treg (; ; 95% CI, −1.55 to 0.18), IL-10 (; ; 95% CI, −5.33 to 3.77), CD4⁺CD25⁺Treg (; ; 95% CI, −0.96 to 1.81), and IL-17 (; ; 95% CI, −4.84 to 2.86). Therefore, diabetic complication was a key influencing factor for the high heterogeneity in the meta-analysis of TGF-β but not the others.

3.4. Sensitivity Analysis

Sensitivity analysis was used to assess the stability of the results by excluding studies with high risk of bias and no significant changes in the results were found. We further conducted sensitivity analysis by including studies with high NOS score (≥7) and found that all the results remained consistent.

3.5. Publication Bias

Egger’s test showed significant publication bias in the meta-analysis of TNF-α but not the others (Figure 9).

(a)

(b)

(c)

(d)

(e)

(f)

(g)

Figure 9: Egger’s test about the Treg and cytokines for publication bias ((a) IL-6, t = 1.31, p = 0.209, CI, −2.46 to 10.33; (b) TGF-β, t = 1.20, p = 0.238, CI, −1.20 to 4.69; (c) TNF-α, t = 3.98, p = 0.004, CI, 2.52 to 9.49; (d) CD4⁺CD25⁺Foxp3⁺Treg, t = −1.22, p = 0.277, CI, −22.58 to 8.05; (e) IL-10, t = −1.26, p = 0.223, CI, −15.80 to 3.93; (f) CD4⁺CD25⁺Treg, t = −0.95, p = 0.351, CI, −11.97 to 4.43; (g) IL-17, t = −0.20, p = 0.845, CI, −26.99 to 22.44).

4. Discussion

In this study, we found that the patients with T2DM had increased serum levels of IL-6, TGF-β, and TNF-α but decreased percentage of peripheral CD4⁺CD25⁺Foxp3⁺Treg and serum IL-10 level. Furthermore, the percentage of peripheral CD4⁺CD25⁺Foxp3⁺Treg and serum IL-10 level were influenced by diabetic complication.

The expression of inflammatory and proinflammatory cytokines from peripheral blood T lymphocyte plays an important role in the development of diabetes and diabetic complications [17]. Many studies have proved the maintenance of immunological self-tolerance by CD4⁺CD25⁺Treg and CD4⁺CD25⁺Foxp3⁺Treg [115]. Treg could suppress inflammatory response through contact inhibition [116]. In this study, the finding of decreased percentage of peripheral CD4⁺CD25⁺Foxp3⁺Treg in T2DM patients indicates that Foxp3 might be a key player for the development and function of Treg. CD4⁺CD25⁺Foxp3⁺Treg differs from CD4⁺CD25⁺Treg. CD4⁺CD25⁺Treg might not sufficiently represent the negative regulatory Treg. Some researchers also considered that the differentiation and function maintenance of Treg were dependent on the expression of the Foxp3, and, consequently, Foxp3 is considered as the key transcriptional factor in Treg cells [117–119].

IL-10 and TGF-β secreted by Treg [116, 120] are the biomarkers in T2DM patients [2, 116]. Previous studies suggested that IL-10 could suppress the proliferation of T leukomonocyte and the secretion of cytokines [121], whereas TGF-β may sustain the expression of Foxp3 in CD4⁺CD25⁺Treg to enhance immunosuppressive function [122, 123]. Consistent with our findings, several studies have shown a significantly decreased level of serum IL-10 in T2DM patients [88, 124]. Correlation of T2DM with Treg cells and TGF-β is generally negative [116].

IL-6 can be released from macrophages and adipocytes in adipose tissue [125–127]. Adipose tissue also produces TNF-α to stimulate IL-6 gene expression [128]. A recent investigation has showed that IL-6 could enhance Treg in mice [129]. In the present meta-analysis of T2DM patients, increased levels of serum IL-6, TGF-β, and TNF-α coexisted with decreased levels of IL-10 and decreased percentage of CD4⁺CD25⁺Foxp3⁺Treg. This finding highlights that the cytokines and growth factors may originate from multiple sources such as macrophages, T cells, and other tissue cells rather than Treg alone. Furthermore, chronic persistent activation of innate immunity and IL-6 secretion occurring in T2DM might inhibit the development of inducible Treg cells.

Th17 cells could produce IL-17, TNF-α, and IL-6 and induce inflammation in the pathogenesis of autoimmune diseases [130]. Th17 cells are a major T cell subset implicated in the pathogenesis of multiple sclerosis, rheumatoid arthritis, and psoriasis [131]. A previous study has revealed that not only Th1/Th2 imbalance but also Th17/Treg imbalance can contribute to the pathogenesis of autoimmune diseases such as T1DM as well as proinflammatory disorders and such as T2DM [2]. T2DM patients have elevated serum levels of IL-6, IL-1β, and TGF-β, the cytokines known to induce Th17 differentiation [131]. Enhanced production of IL-6 and TNF-α and decreased levels of serum IL-10 that occurred in T2DM patients may suppress Treg cells and ratios of Treg to Th17 and Th1 cells [132, 133]. The immunocompromised effects on macrophages and lymphocytes likely drive an inflammatory state to contribute to the occurrence of diabetic complications [12]. Here, in this study, no significant changes of Foxp3⁺Treg cells and serum IL-17 levels were found in T2DM subjects without complication. In contrast, decreased Foxp3⁺Treg cells were evident in T2DM subjects with complication. These findings indicate a close correlation of CD4⁺CD25⁺Foxp3⁺Treg and diabetic complication in T2DM.

There is an intimate relationship of the differentiation of Th17 cells with the relative abundance of peripheral CD4⁺CD25⁺Foxp3⁺Treg cells and the serum levels of IL-6, IL-10, and TGF-β. Although changes of serum levels of IL-17 were not significant in this meta-analysis of T2DM patients versus controls, IL-17 may be a clue to the possible involvement of Th17 cells in T2DM pathogenesis. Firstly, a decrease of Treg cells might be accompanied by an increase of Th17 cells. The study by Guan et al. has indicated the existence of a developmental switch between Th1/Th17 cells, on one hand, and Th2/Treg cells, on the other hand [134]. Secondly, in the presence of high serum levels of IL-6 and TGF-β, as we reported here, differentiation of Th17 cells might be favoured. Lastly, Th17 cells might be, together with innate cells, a primary source of the increased IL-6 levels and might be actively orchestrating the immunity-driven, chronic inflammation of target tissues and organs in T2DM. In this systematic review, the studies examining the number of Th17 cells in T2DM were too scarce for being included in the meta-analysis. Future studies are required to focus on the role of Th17/Treg and products of the Th17 cells in the pathogenesis of T2DM and associated complications.

Diabetic complications such as retinopathy, nephropathy, and cardiovascular disease affect immune cells and cytokines in type 2 diabetes [135, 136]. Actually, urinary TGF-β levels are elevated in the presence of microalbuminuria and overt proteinuria [137]. Additionally, elevated plasma TGF-β may reflect the state of hyperglycemia in T2DM patients [48]. Systemic inflammation in T2DM is linked to the development of diabetic complications [138, 139]. Yet, the mechanism of immune alteration in T2DM and diabetic complication remains unclear. In this meta-analysis, diabetic complication indeed has an impact on the percentage of peripheral CD4⁺CD25⁺Foxp3⁺Treg and level of serum IL-10. The percentage of Treg cells and levels of cytokines in T2DM may also depend on ethnicity, sex, weight, age, and disease duration.

Publication bias might influence the interpretation of our final results. The results of Egger’s tests explain that no publication bias existed in all comparisons except for TNF-α. The publication bias in this meta-analysis might be attributed to studies of small samples and positive results published more easily than negative reports.

There are some limitations in this meta-analysis when interpreting the findings. Firstly, we have selected random effect model to synthesize SMD because of the high heterogeneity existing in some comparisons, but this selection may affect the accuracy of outcome. Secondly, we could not conduct further subgroup analysis of gender, weight, and disease duration because most of the included studies lack sufficient original data. Thirdly, articles published in Chinese or English are included, while unpublished data and papers published in other languages are unknown.

5. Conclusions

In summary, T2DM patients and the patients with diabetic complication have decreased immunosuppressive CD4⁺CD25⁺Foxp3⁺Treg cells and increased proinflammatory IL-10, TGF-β, and TNF-α. The presence of diabetic complication has an impact on the compromised immunosuppression. Significant interaction exists between immune and metabolic homeostasis.

Abbreviations

T2DM: | Type 2 diabetes mellitus
Treg: | Regulatory T cells
IL-6: | Interleukin-6
IL-10: | Interleukin-10
IL-17: | Interleukin-17
TGF-β: | Transforming growth factor-beta
TNF-α: | Tumor necrosis factor-alpha.

Competing Interests

The authors declare that they have no competing interests.

Authors’ Contributions

Yong-chao Qiao designed the study, implemented the study protocol, collected and analyzed data, and wrote the first daft. Jian Shen directed statistical analyses of the data and designed the study. Lan He, Xue-zhi Hong, Fang Tian, Yan-hong Pan, Ling Liang, and Xiao-xi Zhang analyzed and interpreted the data. Hai-lu Zhao designed the study, wrote the manuscript, and revised the submission. All authors contributed to the discussion and approved the submission of the final manuscript. Yong-chao Qiao and Jian Shen contributed equally to this paper.

Acknowledgments

The authors would like to thank Mr. Golden Wilson for his English proofing. Funding for this work was provided by the National Natural Science Foundation of China (81471054) and the Innovation Project of Guangxi Graduate Education (JGY2015128).

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