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Circulating adiponectin levels in various malignancies: an updated meta-analysis of 107 studies

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Oncotarget. 2016; 7:48671-48691. https://doi.org/10.18632/oncotarget.8932

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Tai Wei, Peng Ye, Xin Peng, Li-Ling Wu and Guang-Yan Yu _

Abstract

Tai Wei1,*, Peng Ye1,*, Xin Peng1, Li-Ling Wu2 and Guang-Yan Yu1

1 Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology, Beijing, China

2 Department of Physiology and Pathophysiology, Peking University Health Science Center, Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, and Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing, China

* These authors have contributed equally to this work

Correspondence to:

Li-Ling Wu, email:

Guang-Yan Yu, email:

Keywords: adiponectin, malignancy, biomarker, diagnosis, meta-analysis

Received: December 15, 2015 Accepted: April 16, 2016 Published: April 22, 2016

Abstract

Early detection of cancers is challenging for lack of specific biomarkers. Adiponectin is an adipokine predominantly derived from adipocytes and hypoadiponectinemia has been reported to associate with risk of many types of cancers. However, available evidence is controversial. Some studies show that increased adiponectin levels correlate with cancer risk. Therefore, we performed a meta-analysis of the association between circulating adiponectin levels and cancer development. A systematic search of PubMed, EMBASE, Wiley Online Library and Cochrane Library was conducted for eligible studies involving circulating adiponectin and malignancies from inception to August 8, 2015. Standard mean differences (SMDs) with 95% confidence intervals (95% CIs) were calculated by use of a random-effect model. Funnel plot and Egger’s linear regression test were conducted to examine the risk of publication bias. 107 studies were included with 19,319 cases and 25,675 controls. The pooled analysis indicated that circulating adiponectin levels were lower in patients with various cancers than in controls, with a pooled SMD of -0.334 μg/ml (95% CI, -0.465 to -0.203, P = 0.000). No evidence of publication bias was observed. Circulating high molecular weight adiponectin levels were also lower in cancer patients than in controls, with a pooled SMD of -0.502 μg/ml (95% CI, -0.957 to -0.047, P = 0.000). This meta-analysis provides further evidence that decreased adiponectin levels is associated with risk of various cancers. Hypoadiponectinemia may represent a useful biomarker for early detection of cancers.


INTRODUCTION

Cancer, a major cause of human mortality, has been a worldwide public health problem. A variety of factors such as genetic lesions, environmental aspect and increasing adoption of unhealthy lifestyle are considered as crucial causes of cancer [1]. Among them, obesity is an important factor contributing to the occurrence and development of malignancies. According to the literature in 2005, 396 and 937 million people suffer from obese and overweight worldwide, respectively [2]. Epidemiological research reveals that obesity increases the risk of cancer with evidence that obese women have 50% higher incidence rate than normal weight women [3]. In the process of obesity, dysregulated circulating hormones and growth factors may play an important role in carcinogenesis [4]. Among them, aberrant adiponectin concentration is reported to be a vital link between obesity and cancer.

Adiponectin, firstly discovered by Scherer et al. in 1995, is an adipokine predominantly produced by adipocytes with the monomeric subunit containing 244 amino-acids in human and circulates abundantly in plasma [5, 6]. Three bioactive forms of adiponectin are produced after post-transcriptional process known as trimeric low molecular weight (90 kD, LMW), hexameric medium molecular weight (180 kD, MMW) and oligomeric high molecular weight (> 400 kD, HMW) adiponectin. Among them, HMW-adiponectin is the dominant form in plasma and has the most biological activity than the other two isoforms [7]. Adiponectin mainly acts on two seven-transmembrane adiponectin receptors, AdipoR1 and AdipoR2. Besides, T-cadherin is also responsible for mediating the role of adiponectin in certain tissues [8, 9]. Adiponectin exerts pleiotropic functions in human health such as anti-inflammation, anti-atherosclerosis, and anti-angiogenesis. It also has the properties of insulin-sensitizing and balancing glucose and lipid metabolism in various cells [10]. A number of studies reveal that circulating adiponectin levels decrease in metabolic syndrome, whereas overexpression of it can counteract metabolic dysfunctions [10]. Besides, increased weight reduces the plasma adiponectin level and decreased weight upregulates circulating adiponectin level [11].

It was first reported that circulating adiponectin level was lower in patients with breast cancer in 2003 [12]. Since then, the most clinical studies have indicated that hypoadiponectinemia is associated with risk of various cancers including prostate, endometrial, and colorectal cancers [13-16]. In addition, adiponectin has anti-proliferative and pro-apoptotic effects on cultured cancer cell lines [17, 18]. These results suggest that adiponectin might be an important regulator in carcinogenesis and progression of cancers. However, unchanged or increased circulating adiponectin levels in pancreatic and hepatocellular carcinoma are also reported [19, 20]. Therefore, understanding the exact role of adiponectin in cancer may offer a novel target in tumor diagnosis and therapeutic strategy. In order to gain a more explicit and evidence-based conclusion on the association between circulating adiponectin levels and carcinogenesis, we conducted a comprehensive meta-analysis of current available studies.

RESULTS

Literature selection

The initial comprehensive search yielded 1486 articles, of which 235 articles were excluded for duplication. Then 997 studies were ruled out because of apparent irrelevance after reading titles and/or abstracts. The remaining 254 studies were included for full-text reading, of which 151 studies were removed for one of the following reasons: (i) reviews, comments or letters (n = 37); (ii) shared population (n = 13); (iii) no report of adiponectin levels and/or SDs for both patients and controls or there was not enough information to calculate them (n = 25); (iv) not case-control study (n = 76). 4 additional studies were included from checking the references list. Finally, 107 studies met the inclusion criteria and were used for further analysis [12, 13, 15, 16, 20-112]. The flow diagram of this selection process was showed in Figure 1.

Flow diagram of the included studies.

Figure 1: Flow diagram of the included studies.

Study characteristics

Among the 107 studies, a total of 25,675 controls and 19,319 cases were enrolled until August, 2015. Geographic regions were various, among which 46 studies from Asia, 39 studies from Europe, 19 studies from America, and 3 studies from Africa. 16 types of malignancies were investigated in this meta-analysis, with digestive system cancers accounting for the largest percentage (43 studies); other types included: breast cancer (20 studies), prostate cancer (13 studies), endometrial carcinoma (11 studies), lung cancer (5 studies), renal cancer (3 studies), acute leukemia (3 studies), non-Hodgkin’s lymphoma (3 studies), Hodgkin’s lymphoma (1 study), multiple myeloma (2 studies), melanoma (1 study), thyroid cancer (1 study), and tongue cancer (1 study). Circulating samples included serum (65 studies) and plasma (37 studies), while 5 studies did not mention the exact one. Most researches provided the mean concentrations of circulating adiponectin levels and the SDs of them. SDs from 11 studies were calculated based on the sample size and P values. 96 studies had NOS scores greater than 6 along with 11 studies had scores of 5. The main characteristics of eligible articles were listed in Table 1.

Table 1: Characteristics of all the included studies in the meta-analysis.

Author

Year

Type

Country

Ethnicity

Sample

Mean age (Case/control)

Number (Case/control)

Study design

Assay method

Assay source

Study quality

Petridou et al.

2006

Acute leukemia

Greece/USA

Caucasian

Serum

NR

201/201

Case-control

RIA

Beth Israsel Deaconess Medical Center

8

Moschovi et al.

2010

Acute leukemia

Greece

Caucasian

Plasma

4.3/5.2

9/9

Prospective case-control

Other

Linco Research

7

Aref et al.

2013

Acute leukemia

Egypt

African

Serum

42.8/49.1

80/20

Case-control

Elisa

R&D Systems

5

Miyoshi et al.

2003

Breast cancer

Japan

Asian

Serum

54.0/52.8

102/100

Case-control

Elisa

NR

7

Mantzoros et al.

2004

Breast cancer

Greece

Caucasian

Serum

NR

174/167

Case-control

RIA

Beth Israsel Deaconess Medical Center

8

Chen et al.

2006

Breast cancer

Taiwan

Asian

Serum

49.9/48.9

100/100

Case-control

RIA

Linco Research

7

Korner et al.

2007

Breast cancer

Greece

Caucasian

Serum

62.5/55.6

74/76

Case-control

RIA

ALPCO Diagnostics

7

Kang et al.

2007

Breast cancer

Korea

Asian

Serum

47.4/47.8

41/43

Case-control

Elisa

AdipoGen

7

Hou et al.

2007

Breast cancer

China

Asian

Serum

48/49

80/50

Case-control

Elisa

R&D Systems

6

Tworoger et al.

2007

Breast cancer

USA

Caucasian

Blood

57.1/58.1

1166/1575

Nested case-control

RIA

Linco Research

7

Tworoger et al.

2007

Breast cancer

USA

Caucasian

Blood

45.4/45.1

311/621

Nested case-control

RIA

Linco Research

7

Hancke et al.

2010

Breast cancer

Switzerland

Caucasian

Serum

59.5/49.0

159/41

Case-control

Elisa

BioVendor Laboratory Medicine

6

Cust et al.

2009

Breast cancer

Sweden

Caucasian

Plasma

52.5/NR

561/561

Case-control

RIA

Linco Research

7

Shahar et al.

2010

Breast cancer

Malaysia

Asian

Serum

47.3/46.2

70/138

Case-control

Elisa

Linco Research

7

Dalamaga et al.

2011

Breast cancer

Greece

Caucasian

Serum

61.5/62.8

102/102

Case-control

Elisa

Avibion

7

Al Khaldi et al.

2011

Breast cancer

Kuwait

Asian

Plasma

49/60

60/68

Case-control

Elisa

Linco Research

7

Touvier et al.

2013

Breast cancer

France

Caucasian

Plasma

49.2/51.5

218/436

Nested case-control

Elisa

R&D Systems

9

Gulcelik et al.

2012

Breast cancer

Turkey

Asian

Serum

51.4/52.4

83/40

Case-control

Elisa

B-Bridge International Inc.

7

Al Awadhi et al.

2012

Breast cancer

Kuwait

Asian

Plasma

50.3/50.7

144/77

Case-control

Elisa

Linco Research

7

Alokail et al.

2013

Breast cancer

Saudi Arabia

Asian

Serum

46.4/43.1

56/53

Case-control

Other

Luminex Corporation

7

Ollberding et al.

2013

Breast cancer

USA

Caucasian

Serum

67.8/67.8

706/706

Nested case-control

Elisa

R&D Systems

8

Gross et al.

2013

Breast cancer

USA

Caucasian

Plasma

62.6/62.5

272/272

Case-control

Elisa

ALPCO Diagnostics

7

Minatoya et al.

2014

Breast cancer

Japan

Asian

Serum

NR

66/66

Case-control

Other

SRL

7

Gulcelik et al.

2012

Colon cancer

Turkey

Asian

Serum

52.1/52.4

27/40

Case-control

Elisa

B-Bridge International Inc.

7

Otake et al.

2005

Colorectal adenoma

Japan

Asian

Plasma

59.0/58.0

51/52

Case-control

Elisa

Otsuka Pharmaceutical

8

Fukumoto et al.

2008

Colorectal adenoma

Japan

Asian

Plasma

NR

656/648

Case-control

Elisa

Otsuka Pharmaceutical

7

Kumor et al.

2009

Colorectal adenoma

Poland

Caucasian

Serum

62.4/60.1

37/25

Case-control

Elisa

R&D Systems

7

Erarslan et al.

2009

Colorectal adenoma

Turkey

Asian

Plasma

63.0/59.0

31/50

Case-control

Elisa

RayBio

8

Nakajima et al.

2010

Colorectal adenoma

Japan

Asian

Plasma

66.8/66.7

72/72

Case-control

Elisa

Otsuka Pharmaceutical

7

Otake et al.

2010

Colorectal adenoma

Japan

Asian

Plasma

65.1/67.9

47/26

Case-control

Elisa

Otsuka Pharmaceutical

7

Yamaji et al.

2010

Colorectal adenoma

Japan

Asian

Plasma

NR

778/735

Case-control

Elisa

Sekisui Medical

6

Danese et al.

2013

Colorectal adenoma

Italy

Caucasian

Serum

63.0/59.5

40/40

Case-control

Elisa

Mediagnost

7

Wei et al.

2005

Colorectal cancer

USA

Caucasian

Plasma

66.6/66.5

179/356

Nested case-control

RIA

Linco Research

8

Stocks et al.

2008

Colorectal cancer

Sweden

Caucasian

Plasma

59.7/NR

306/595

Nested case-control

Elisa

R&D Systems

6

Guadagni et al.

2009

Colorectal cancer

Italy

Caucasian

Serum

63.0/59.0

90/30

Case-control

Elisa

BioVendor Laboratory Medicine

8

Kumor et al.

2009

Colorectal cancer

Poland

Caucasian

Serum

58.6/60.1

36/25

Case-control

Elisa

R&D Systems

7

Erarslan et al.

2009

Colorectal cancer

Turkey

Asian

Plasma

57.0/59.0

23/50

Case-control

Elisa

RayBio

8

Nakajima et al.

2010

Colorectal cancer

Japan

Asian

Plasma

63.7/63.5

115/115

Case-control

Elisa

Otsuka Pharmaceutical

7

Otake et al.

2010

Colorectal cancer

Japan

Asian

Plasma

66.7/67.9

51/26

Case-control

Elisa

Otsuka Pharmaceutical

7

Kemik et al

2010

Colorectal cancer

Turkey

Asian

Serum

43.5/40.4

126/38

Case-control

RIA

Linco Research

7

Gonullu et al.

2010

Colorectal cancer

Turkey

Asian

Serum

56.6/51.0

36/37

Case-control

Elisa

BioSource

8

Catalan et al.

2011

Colorectal cancer

Spain

Caucasian

Plasma

66.0/44.0

11/18

Case-control

Elisa

R&D Systems

8

Chen et al.

2012

Colorectal cancer

China

Asian

Plasma

61.9/58.3

165/102

Case-control

Elisa

Adlitteram Diagnostic Laboratories. Inc.

7

Touvier et al.

2012

Colorectal cancer

France

Caucasian

Plasma

51.8/52.1

50/100

Nested case-control

Elisa

R&D Systems

9

Aleksandrova et al.

2012

Colorectal cancer

Germany

Caucasian

Serum

58.3/58.3

1206/1206

Case-control

Elisa

ALPCO Diagnostics

9

Song et al.

2013

Colorectal cancer

USA

Caucasian

Plasma

61.9/61.9

616/1205

Case-control

Elisa

ALPCO Diagnostics

9

Cust et al.

2007

Endometrical carcinoma

UK

Caucasian

Plasma

56.9/56.9

284/548

Nested case-control

Elisa

R&D Systems

8

Soliman et al.

2006

Endometrical carcinoma

USA

Caucasian

Serum

66.6/61.2

117/238

Case-control

Elisa

R&D Systems

5

Ashizawa et al.

2010

Endometrical carcinoma

Japan

Asian

Serum

59.9/57.5

146/150

Case-control

RIA

Linco Research

8

Dossus et al.

2013

Endometrical carcinoma

Germany

Caucasian

Serum

57.7/57.7

233/446

Case-control

Elisa

R&D Systems

8

Friedenreich et al.

2012

Endometrical carcinoma

USA

Caucasian

Serum

59/59

514/962

Case-control

Elisa

ALPCO Diagnostics

9

Luhn et al.

2013

Endometrical carcinoma

USA

Caucasian

Serum

NR

167/327

Nested case-control

RIA

Linco Research

8

Erdogan et al.

2013

Endometrical carcinoma

Turkey

Asian

Serum

56.6/49.7

60/70

Case-control

Elisa

eBioscience

6

Ma et al.

2013

Endometrical carcinoma

China

Asian

Serum

53.2/53.3

206/310

Case-control

Elisa

Bender MedSystems

9

Dallal et al.

2013

Endometrical carcinoma

USA

Caucasian

Serum

67.4/67.5

62/124

Nested case-control

Elisa

Millipore

8

Mihu et al.

2013

Endometrical carcinoma

Romania

Caucasian

Serum

60.2/58.5

44/44

Case-control

Elisa

R&D Systems

6

Ohbuchi et al.

2014

Endometrical carcinoma

Japan

Asian

Serum

61.2/58.1

43/62

Case-control

Elisa

Daiichi Co. Ltd.

8

Diao et al.

2009

Esophageal cancer

China

Asian

Plasma

58.0/49.0

43/33

Case-control

Elisa

Adlitteram Diagnostic Laboratories. Inc.

6

Nakajima et al.

2010

Esophageal cancer

Japan

Asian

Blood

63.6/63.6

117/117

Case-control

Elisa

Otsuka Pharmaceutical

6

Yildirim et al.

2009

Esophageal cancer

Turkey

Asian

Serum

64/61

62/30

Case-control

Elisa

Avibion

6

Ishikawa et al.

2005

Gastric cancer

Japan

Asian

Plasma

64.2/59.3

75/52

Case-control

Elisa

Otsuka Pharmaceutical

6

Nakajima et al.

2009

Gastric cancer

Japan

Asian

Blood

61.0/60.8

156/156

Case-control

Elisa

Otsuka Pharmaceutical

8

Seker et al.

2010

Gastric cancer

Turkey

Asian

Plasma

60.0/38.6

40/43

Case-control

Elisa

Linco Research

5

Diakowska et al.

2014

Gastroesophageal cancer

Poland

Caucasian

Serum

60.0/58.0

85/60

Case-control

Elisa

R&D Systems

7

Kotani et al.

2009

Hepatacellular carcinoma

Japan

Asian

Serum

63.5/62.7

59/334

Nested case-control

Elisa

Daiichi Co. Ltd.

8

Liu et al.

2009

Hepatacellular carcinoma

Taiwan/China

Asian

Serum

50.7/53.8

120/116

Case-control

Elisa

B-Bridge International Inc.

5

Sumie et al.

2011

Hepatacellular carcinoma

Japan

Asian

Serum

67.4/61.2

97/97

Case-control

Elisa

EikenChenical Co. Ltd.

7

Sadik et al

2012

Hepatacellular carcinoma

Egypt

African

Serum

58.9/55.7

69/121

Case-control

Elisa

Assaypro

7

Chen et al.

2012

Hepatacellular carcinoma

Taiwan/China

Asian

Serum

52.4/52.2

65/165

Case-control

RIA

Linco Research

6

Khattab et al.

2012

Hepatacellular carcinoma

Egypt

African

Plasma

43.9/42.9

147/320

Case-control

Other

Linco Research

5

Chen et al.

2014

Hepatacellular carcinoma

Taiwan/China

Asian

Plasma

NR

185/373

Nested case-control

Elisa

B-Bridge International Inc.

8

Petridou et al.

2010

Hodgkin lymphoma

Greece

Caucasian

Serum

11.5/11.2

75/75

Case-control

RIA

Linco Research

7

Jamieson et al.

2004

Lung cancer

UK

Caucasian

Serum

64.0/65.0

20/13

Case-control

RIA

Linco Research

7

Karapanagiotou et al.

2008

Lung cancer

Greece

Caucasian

Serum

64.2/55.5

101/51

Case-control

Elisa

BioVendor

6

Petridou et al.

2007

Lung cancer

Greece

Caucasian

Serum

NR

85/170

Case-control

RIA

Beth Israsel Deaconess Medical Center

8

Gulen et al.

2012

Lung cancer

Turkey

Asian

Serum

65.6/63.5

63/25

Case-control

Elisa

BioVendor

7

Kerenidi et al.

2013

Lung cancer

Greece

Caucasian

Serum

62.9/NR

80/40

Case-control

Elisa

Linco Research

7

Antoniadis et al.

2011

Melanoma

Greece/Canada

Caucasian

Serum

52.7/53.3

55/165

Case-control

RIA

Beth Israsel Deaconess Medical Center

8

Dalamaga et al.

2009

Multiple myeloma

Greece/Canada

Caucasian

Serum

NR

73/73

Case-control

Elisa

Avibion

8

Hofmann et al.

2012

Multiple myeloma

USA

Caucasian

Plasma

NR

174/348

Case-control

Elisa

R&D Systems

7

Pamuk et al.

2006

Non-Hodgkin's lymphoma

Turkey

Asian

Serum

63.2/58.5

28/17

Case-control

Elisa

OtsukaCo.Ltd

5

Petridou et al.

2009

Non-Hodgkin's lymphoma

Greece

Caucasian

Serum

8.8/8.8

121/121

Case-control

RIA

NR

7

Conroy et al.

2013

Non-Hodgkin's lymphoma

USA

Caucasian

Plasma

70.0/70.0

272/541

Nested case-control

Elisa

R&D Systems

7

Chang et al.

2007

Pancreatic cancer

Taiwan/China

Asian

Serum

64.6/49.5

72/290

Case-control

Elisa

R&D Systems

8

Dalamaga et al.

2009

Pancreatic cancer

Greece

Caucasian

Serum

69.0/70.1

81/81

Case-control

RIA

Linco Research

7

Solomon et al.

2008

Pancreatic cancer

USA

Caucasian

Serum

58.0/58.0

311/510

Case-control

Elisa

Millipore

8

Krechler et al.

2011

Pancreatic cancer

Czech Republic

Caucasian

Plasma

51.9/64.5

64/64

Case-control

RIA

DRG Inc.

8

Grote et al.

2012

Pancreatic cancer

Germany

Caucasian

Serum

58.0/60.0

452/452

Nested case-control

Other

R&D Systems

8

Bao et al.

2013

Pancreatic cancer

USA

Caucasian

Plasma

NR

468/1080

Nested case-control

Elisa

ALPCO Diagnostics

8

Goktas et al.

2005

Prostate cancer

Turkey

Asian

Plasma

65.8/62.2

30/36

Case-control

RIA

Linco Research

8

Goktas et al.

2005

Prostate cancer

Turkey

Asian

Plasma

65.8/65.0

30/41

Case-control

RIA

Linco Research

8

Baillargeon et al.

2006

Prostate cancer

USA

Caucasian

Serum

63.5/63.2

125/125

Nested case-control

Other

Luminex

7

Michalakis et al.

2007

Prostate cancer

Greece

Caucasian

Serum

74.0/64.0

75/150

Case-control

RIA

Linco Research

5

Michalakis et al.

2007

Prostate cancer

Greece

Caucasian

Serum

74.0/70.0

75/75

Case-control

RIA

Linco Research

5

Housa et al.

2008

Prostate cancer

Czech Republic

Caucasian

Serum

63.6/70.5

43/25

Case-control

RIA

Linco Research

5

Grosman et al.

2010

Prostate cancer

Argentina

Caucasian

Serum

NR

25/25

Case-control

RIA

Linco Research

7

Li et al.

2010

Prostate cancer

USA

Caucasian

Plasma

59.0/58.6

620/599

Nested case-control

RIA

Linco Research

7

Dhillon et al.

2011

Prostate cancer

USA

Caucasian

Plasma

57.9/57.5

1286/1267

Nested case-control

RIA

Linco Research

8

Lopez Fontana et al.

2011

Prostate cancer

Argentina

Caucasian

Serum

63.8/64.9

35/35

Case-control

Elisa

Linco Research

6

Al Khaldi et al.

2011

Prostate cancer

Kuwait

Asian

Plasma

59.0/60.0

14/68

Case-control

Elisa

Linco Research

7

Touvier et al.

2013

Prostate cancer

France

Caucasian

Plasma

54.9/51.5

156/1024

Nested case-control

Elisa

R&D Systems

9

Tewari et al.

2013

Prostate cancer

India

Asian

Blood

66.5/65.7

95/95

Case-control

Other

NR

5

Spyridopoulos et al.

2012

Renal cancer

Greece

Caucasian

Serum

61.5/60.7

60/236

Case-control

RIA

Beth Israsel Deaconess Medical Center

8

Liao et al.

2013

Renal cancer

Finland/USA

Caucasian

Serum

57/57

273/273

Nested case-control

Elisa

Millipore

9

Liao et al.

2013

Renal cancer

Canada/USA

Caucasian

Serum

NR

768/917

Case-control

Elisa

Millipore

9

Mitsiades et al.

2011

Thyroid cancer

USA

Caucasian

Serum

51.2/55.4

175/107

Case-control

RIA

Beth Israsel Deaconess Medical Center

5

Guo et al.

2013

Tongue cancer

China

Asian

Serum

57.2/52.7

59/50

Case-control

Elisa

Adipobiotech

8

Abbreviations: NR, not reported; Elisa, enzyme-linked immunosorbent assay; RIA, radioimmunoassay.

Circulating adiponectin levels and carcinogenesis

Data from 107 studies were analyzed in a random-effect model to compare circulating adiponectin levels in people with different cancers and controls. Results showed that circulating adiponectin levels in cancer cases were significantly lower than in the controls with a pooled SMD of -0.334 μg/ml (95% CI, -0.465 to -0.203, P = 0.000). Statistically significant amount of heterogeneity was observed across these studies (I2 = 97.6%, P < 0.0001), so subgroup analysis was carried out next. These results were presented in Figure 2.

Forest plot of studies in circulating total adiponectin and cancer risk.

Figure 2: Forest plot of studies in circulating total adiponectin and cancer risk. The combined SMD and 95% CIs were calculated through a random-effect model.

HMW-adiponectin is the dominant form of adiponectin in plasma and correlates with cardiovascular disease, insulin resistance, and obesity [7, 113, 114]. But few studies have evaluated the relationship between circulating HMW-adiponectin levels and cancer risk. We analyzed data from 8 studies in a random-effect model to compare circulating HMW-adiponectin levels in people with different cancers [33, 56, 58, 72, 83, 94, 107, 108]. Results showed that circulating HMW-adiponectin levels in cancer cases were significantly lower than in the controls with a pooled SMD of -0.502 μg/ml (95% CI, -0.957 to -0.047, P = 0.000), which is consistent with the results derived from total adiponectin levels. Statistically significant amount of heterogeneity was observed across these studies (I2 = 97.0%, P < 0.0001). These results were presented in Figure 3.

Forest plot of studies in circulating high molecular weight adiponectin and cancer risk.

Figure 3: Forest plot of studies in circulating high molecular weight adiponectin and cancer risk. The combined SMD and 95% CIs were calculated through a random-effect model.

Subgroup analysis and meta-regression

Stratified subgroup analysis was performed to evaluate the potential sources of heterogeneity including ethnicity, cancer type, study design, blood sample, assay method, study size, study quality and mean age of cancer patients (Table 2). Lower levels of circulating adiponectin were observed in both Asian (SMD -0.555, 95% CI, -0.812 to -0.298) and Caucasian people (SMD -0.269, 95% CI, -0.400 to -0.138). Similar results were also presented in people with breast (SMD -0.334, 95% CI, -0.543 to -0.126), colorectal (SMD -0.496, 95% CI, -0.653 to -0.339), endometrial (SMD -0.594, 95% CI, -0.825 to -0.363), prostate (SMD -0.892, 95% CI, -1.345 to -0.438), thyroid (SMD -0.358, 95% CI, -0.601 to -0.116), tongue (SMD -1.172, 95% CI, -1.580 to -0.764), gastroesophageal (SMD -0.278, 95% CI, -0.553 to -0.004) cancer, multiple myeloma (SMD -0.621, 95% CI, -0.966 to -0.276), and acute leukemia (SMD -0.594, 95% CI, -0.825 to -0.363). Notably, circulating adiponectin levels were higher in the patients with hepatocellular cancer than in controls among 7 studies included (SMD 1.385, 95% CI, 0.240 to 2.530).

Additionally, adiponectin was significantly lower in patients who used serum as test samples (SMD -0.335, 95% CI, -0.483 to -0.186), and in 37 studies who used plasma as testing samples, 26 studies showed the inverse relation of adiponectin to cancer risk. Assay method (radioimmunoassay or enzyme-linked immunosorbent assay) did not affect the results that circulating adiponectin was lower in cancer patients with pooled SMD of -0.316 and -0.266. Study size (more or less than 100 patients) did not change the result of estimated SMD either (SMD -0.135, 95% CI, -0.299 to -0.030; SMD -0.549, 95% CI, -0.825 to -0.273, respectively). Besides, no matter the mean age of cancer patients is older or younger than 60 years, decreased adiponectin levels were still exist in cancer patients (SMD -0.489, 95% CI, -0.689 to -0.288; SMD -0.194, 95% CI, -0.383 to -0.004, respectively).

Next we performed meta-regression to evaluate the effect of the above factors on the estimate of SMD. In meta-regression, none of the examined factors, such as ethnicity, cancer type, study design, blood sample, assay method, study size, study quality and mean age of cancer patients was proved to be significant contributing factors.

Table 2: Subgroup analysis of the relationships between circulating adiponectin levels and study characteristics.

Characteristics

Number of studies

Number

(Case/control)

SMD

95% CI

Heterogeneity (I2)

Ethnicity

Caucasian

58

14178/19758

-0.269

-0.400 to -0.138

96.8%

Asian

46

4845/5456

-0.555

-0.812 to -0.298

97.1%

African

3

296/461

1.821

-2.201 to 5.843

99.6%

Cancer Types

Acute leukemia

3

290/230

-2.236

-4.418 to -0.054

97.3%

Multiple myeloma

2

247/421

-0.621

-0.966 to -0.276

69.7%

Breast cancer

20

4545/5292

-0.334

-0.543 to -0.126

95.5%

Colorectal cancers

23

4749/5591

-0.496

-0.653 to -0.339

91.3%

Endometrial cancer

11

1876/3281

-0.594

-0.825 to -0.363

92.8%

Prostate cancer

13

2609/3565

-0.892

-1.345 to -0.438

97.9%

Thyroid cancer

1

175/107

-0.358

-0.601 to -0.116

NA

Tongue cancer

1

59/50

-1.172

-1.580 to -0.764

NA

Hepatocellular cancer

7

742/1526

1.385

0.240 to 2.530

99.2%

Gastroesophageal cancer

7

578/491

-0.278

-0.553 to -0.004

78.1%

Hodgkin lymphoma

1

75/75

0.28

-0.041 to 0.602

NA

Non-Hodgkin lymphoma

3

421/679

0.316

-0.048 to 0.68

79.7%

Lung cancer

5

349/299

-0.085

-0.58 to 0.409

87.1%

Melanoma

1

55/165

-0.112

-0.418 to 0.193

NA

Pancreatic cancer

6

1448/2477

0.037

-1.207 to 1.281

99.6%

Renal cancer

3

1101/1426

0.021

-0.246 to 0.288

86.6%

Study Design

Case-control study

86

11965/14210

-0.346

-0.505 to -0.188

97.2%

Nested case-control study

21

7354/11465

-0.290

-0.553 to -0.026

98.5%

Blood samples

Serum

65

9171/11101

-0.335

-0.483 to -0.186

95.8%

Plasma

37

8303/12010

-0.238

-0.497 to 0.022

98.6%

NR

5

1845/2564

-1.072

-1.775 to -0.369

98.8%

Assay methods

RIA

29

6190/7587

-0.316

-0.459 to -0.172

93.0%

Elisa

71

12179/16968

-0.266

-0.426 to -0.106

97.4%

Others

7

950/1120

-1.305

-3.113 to 0.502

99.5%

Study size

≥100 patients

48

16057/21437

-0.135

-0.299 to-0.030

98.3%

<100 patients

59

3262/4238

-0.549

-0.825 to -0.273

96.5%

Study quality

≥6

96

16352/22425

-0.334

-0.465 to -0.203

97.3%

<6

11

2967/3250

-0.267

-0.700 to 0.165

98.2%

Patients’ age (mean)

≥60

44*

4770/6414*

-0.489

-0.689 to -0.288

95.6%

<60

47*

9782/12935*

-0.194

-0.383 to -0.004

97.7%

Abbreviations: NA, not assessable. *There are 91 studies with 14,552 cases and 19,349 controls reported the mean age of cancer patients.

Sensitivity analysis

Sensitivity analysis was performed by excluding one study at a time and calculating the pooled SMDs for the remaining studies. It was found that the combined SMDs were similar to one another and statistically significant. None of the studies influence the pooled results substantially in this analysis (Table 3).

Table 3: The pooled SMDs and 95% CIs of the included studies through sensitivity analysis.

Study omitted

Estimate

95% CI

Miyoshi et al. (2003)

-0.33362126

-.46549249 to -.20175007

Jamieson et al. (2004)

-0.32790136

-.45929646 to -.19650623

Mantzoros et al. (2004)

-0.3366529

-.46877834 to -.20452745

Goktas et al. (2005)

-0.31018904

-.44067159 to -.1797065

Goktas et al. (2005)

-0.31467217

-.4453963 to -.18394804

Wei et al. (2005)

-0.33543056

-.46779135 to -.20306975

Otake et al. (2005)

-0.32370359

-.45491788 to -.19248928

Ishikawa et al. (2005)

-0.33179379

-.4634814 to -.20010617

Petridou et al. (2006)

-0.33611172

-.4683494 to -.20387407

Baillargeon et al. (2006)

-0.33559188

-.46757615 to -.2036076

Chen et al. (2006)

-0.32800215

-.45950019 to -.1965041

Pamuk et al. (2006)

-0.34167045

-.47312284 to -.21021806

Soliman et al. (2006)

-0.32821506

-.45972851 to -.19670163

Cust et al. (2007)

-0.33429027

-.46701819 to -.20156233

Korner et al. (2007)

-0.33221245

-.4639549 to -.20046999

Kang et al. (2007)

-0.33505732

-.46672907 to -.20338558

Tworoger et al. (2007)

-0.33802846

-.47386777 to -.20218913

Tworoger et al. (2007)

-0.3405844

-.47277904 to -.20838977

Chang et al. (2007)

-0.35825887

-.48626736 to -.2302504

Michalakis et al. (2007)

-0.32968622

-.46133375 to -.19803868

Michalakis et al. (2007)

-0.33015183

-.46179458 to -.19850905

Hou et al. (2007)

-0.33114624

-.46280947 to -.19948301

Petridou et al. (2007)

-0.33918613

-.47100937 to -.20736288

Fukumoto et al. (2008)

-0.33727011

-.47093907 to -.20360115

Solomon et al. (2008)

-0.3375347

-.47031215 to -.20475723

Housa et al. (2008)

-0.33494586

-.46656513 to -.2033266

Karapanagiotou et al. (2008)

-0.337192

-.46895465 to -.20542936

Stocks et al. (2008)

-0.33803195

-.47080877 to -.20525511

Dalamaga et al. (2009)

-0.34321341

-.47464448 to -.21178232

Dalamaga et al. (2009)

-0.32902971

-.46060005 to -.19745934

Petridou et al. (2009)

-0.34161058

-.47322133 to -.2099998

Kotani et al. (2009)

-0.33791459

-.46976718 to -.20606196

Guadagni et al. (2009)

-0.31941918

-.45032975 to -.18850861

Kumor et al. (2009)

-0.32856214

-.46004361 to -.1970806

Erarslan et al. (2009)

-0.33168712

-.46326634 to -.20010787

Kumor et al. (2009)

-0.3339898

-.4655939 to -.2023856

Erarslan et al. (2009)

-0.33251002

-.46413583 to -.20088424

Cust et al. (2009)

-0.33854863

-.47171903 to -.20537826

Nakajima et al. (2009)

-0.33416247

-.4662253 to -.20209965

Diao et al. (2009)

-0.33897933

-.47058302 to -.2073756

Yildirim et al. (2009)

-0.3268407

-.45826575 to -.19541568

Li et al. (2009)

-0.34737712

-.47806501 to -.21668923

Moschovi et al. (2010)

-0.31926209

-.45011383 to -.18841037

Hancke et al. (2010)

-0.33801222

-.46974581 to -.20627865

Seker et al. (2010)

-0.34004903

-.47163537 to -.2084627

Nakajima et al. (2010)

-0.33507797

-.46703228 to -.20312366

Petridou et al. (2010)

-0.33972663

-.47141987 to -.20803338

Grosman et al. (2010)

-0.32690996

-.45831883 to -.19550107

Li et al. (2010)

-0.3373847

-.47090244 to -.20386696

Nakajima et al. (2010)

-0.3372006

-.46912611 to -.2052751

Otake et al. (2010)

-0.3304036

-.46196187 to -.19884537

Kemik et al (2010)

-0.3278496

-.45933568 to -.19636351

Gonullu et al. (2010)

-0.3353405

-.46698609 to -.20369488

Nakajima et al. (2010)

-0.33436027

-.46614832 to -.20257224

Ashizawa et al. (2010)

-0.33154425

-.4634259 to -.19966258

Shahar et al. (2010)

-0.3222657

-.4640207 to -.20043245

Otake et al. (2010)

-0.3297922

-.46132797 to -.19825645

Yamaji et al. (2010)

-0.33636427

-.47040036 to -.20232819

Antoniadis et al. (2011)

-0.3360277

-.46786067 to -.2041948

Dhillon et al. (2011)

-0.33877328

-.47420669 to -.20333987

Al Khaldi et al. (2011)

-0.3581396

-.48865175 to -.22762746

Sumie et al. (2011)

-0.33623996

-.46812296 to -.20435697

Catalan et al. (2011)

-0.3270525

-.4584052 to -.19569978

Dalamaga et al. (2011)

-0.33432293

-.46621501 to -.20243084

Al Khaldi et al. (2011)

-0.34966454

-.48045498 to -.21887414

Krechler et al. (2011)

-0.33685401

-.46860847 to -.20509957

Mitsiades et al. (2011)

-0.33370164

-.46567562 to -.20172767

Lopez Fontana et al. (2011)

-0.3409504

-.47248313 to -.20941767

Spyridopoulos et al. (2012)

-0.33505121

-.46693206 to -.20317033

Hofmann et al. (2012)

-0.33265379

-.46483427 to -.2004733

Gulen et al. (2012)

-0.33108562

-.46266881 to -.1995024

Sadik et al (2012)

-0.35871589

-.48782459 to -.2296071

Chen et al. (2012)

-0.32368076

-.45458078 to -.1927807

Gulcelik et al. (2012)

-0.32346013

-.45471603 to -.19220424

Aleksandrova et al. (2012)

-0.33816311

-.47353563 to -.20279059

Friedenreich et al. (2012)

-0.33428073

-.46782497 to -.20073651

Touvier et al. (2012)

-0.3405067

-.47251758 to -.20849583

Gulcelik et al. (2012)

-0.31726849

-.44793424 to -.18660273

Al Awadhi et al. (2012)

-0.34153

-.47313255 to -.2099274

Grote et al. (2012)

0.33630246

-.46936187 to -.20324306

Chen et al. (2012)

-0.34161338

-.47320184 to -.2100249

Khattab et al. (2012)

-0.38207525

-.50227177 to -.2618787

Dossus et al. (2013)

-0.33401754

-.46652448 to -.20151059

Bao et al. (2013)

-0.30136451

-.41626969 to -.18645933

Guo et al. (2013)

-0.3258861

-.45724642 to -.1945257

Touvier et al. (2013)

-0.33433828

-.46610662 to -.2025699

Liao et al. (2013)

-0.33713764

-.46957946 to -.20469585

Liao et al. (2013)

-0.3403554

-.47350773 to -.20720309

Conroy et al. (2013)

-0.33808553

-.47072488 to -.2054462

Touvier et al. (2013)

-0.3296572

-.46145904 to -.19785538

Kerenidi et al. (2013)

-0.3439351

-.4753255 to -.21254471

Danese et al. (2013)

-0.34142008

-.47294763 to -.20989256

Song et al. (2013)

-0.33765575

-.47181916 to -.20349233

Luhn et al. (2013)

-0.33139816

-.46341154 to -.19938481

Ma et al. (2013)

-0.32076678

-.45034227 to -.1911912

Dallal et al. (2013)

-0.33651593

-.4683443 to -.20468754

Alokail et al. (2013)

-0.30377382

-.43343174 to -.17411587

Ollberding et al. (2013)

-0.33671638

-.47059336 to -.20283943

Gross et al. (2013)

-0.33571425

-.46818775 to -.20324075

Aref et al. (2013)

-0.31502652

-.4457356 to -.18431742

Tewari et al. (2013)

-0.28841972

-.41580069 to -.16103874

Erdogan et al. (2013)

-0.33102214

-.46268752 to -.19935676

Mihu et al. (2013)

-0.3298324

-.46139839 to -.1982664

Chen et al. (2014)

-0.33950841

-.47162384 to -.20739301

Ohbuchi et al. (2014)

-0.33285877

-.46454135 to -.20117618

Minatoya et al. (2014)

-0.32982665

-.46143582 to -.19821748

Diakowska et al. (2014)

-0.33376125

-.46553349 to -.20198898

Combined

-0.33375105

-.46467104 to -.20283107

Publication bias

Publication bias was assessed by funnel plot and Egger’s regression test. Funnel plot shapes demonstrated a marginally asymmetrical distribution (Figure 4), accordingly we performed further analysis with Egger’s test. The tested result (Figure 5) showed no evidence of publication bias (P = 0.123).

Funnel plot of lower adiponectin expression and cancer risk.

Figure 4: Funnel plot of lower adiponectin expression and cancer risk. Circles indicate included studies.

Egger&#x2019;s linear regression test for publication bias detection.

Figure 5: Egger’s linear regression test for publication bias detection.

DISCUSSION

By integrating 107 studies, our meta-analysis revealed that lower circulating adiponectin levels were associated with higher risk of cancers. Despite the existence of heterogeneity, the disparity of adiponectin levels between malignant individuals and controls reveals the potential ability of adiponectin to serve as a biomarker for early detection of cancers.

Aberrant adiponectin secretion is associated with tumor progression, metastasis and overall prognosis. Two previous meta-analysis indicated that lower adiponectin levels were associated with higher risk of breast cancer, colorectal cancer and colorectal adenoma [115, 116]. By synthesizing 107 studies involving 19,319 cases with different malignancies, the present meta-analysis estimate the inverse association between circulating adiponectin levels and cancer risk. Moreover, through subgroup analysis, we identified that this inverse relation of adiponectin to cancer risk might be more meaningful in breast, colon, endometrial, prostate, and gastroesophageal cancers. Besides, adiponectin levels tend to decrease as tumor stage increases in gastric cancer [62]. Kang et al. also indicate that breast cancer patients with less than the median adiponectin levels are easy to develop lymph node metastasis [82]. Low adiponectin level is the independent predictor of unfavorable prognosis in colorectal cancer [117]. These findings demonstrate that adiponectin is not only associated with cancer risk, but also correlated with tumor progression. Additionally, in our included 107 studies, 8 studies evaluated the relationship between circulating levels of adiponectin subtypes and cancer risk. The changing trend of total adiponectin was almost same with the three adiponectin subtypes in cancer patients, especially with HMW-adiponectin, that it is inversely associated with cancer risk.

Circulating adiponectin levels are affected by various factors, including inflammatory, dietary, hormonal, genetic, and medicine. One of possible explanations for decreased adiponectin levels in malignancies is the sustained inflammatory status of cancer patients leads to the increased proinflammatory cytokines such as TNF-α and IL-6, which are all reported to suppress adiponectin transcription and translation in adipocyte cell line [118, 119]. Besides, in obesity-related cancers, adiponectin may control its own production through a negative feedback loop during the development of obesity [120]. Moreover, dietary with lower intake of fiber and magnesium can also reduce circulating adiponectin levels [121].

However, elevated adiponectin levels are also reported in hepatocellular carcinoma. Since adiponectin is mainly degraded in the liver and adiponectin levels are elevated in advanced disease including cirrhosis and virus-related cancer [61, 122]. One possible explanation for increased adiponectin level in hepatocellular carcinoma might be due to deteriorated hepatic metabolism resulted from repeated necroinflammation and regeneration. Besides, conflicting results also exist in clinical studies of pancreatic cancer that both higher and lower adiponectin levels are reported to be associated with cancer risk [45, 50]. After reviewing the pancreatic cancer studies with higher levels of adiponectin, we found that almost half of them were accompanied with jaundice [45]. Since cholestasis would lead to the chronic liver deterioration, it is possible that increased adiponectin levels might be due to the reduced degradation.

The peripheral functions of adiponectin are mainly mediated through AdipoR1 and AdipoR2. The expression levels of AdipoRs vary between malignant tissues and their peritumoral normal counterparts. The upregulation of AdipoR1 and AdipoR2 are reported in gastric carcinoma [123], whereas decreased in prostate cancer tissues compared with the nonmalignant tissues [36]. Increased expression of AdipoRs may be the response of reduced circulating as well as local adiponectin levels and reduced expression suggests that the sensitivity of AdipoRs to adiponectin is decreased in tumor tissues. Yabushita et al. indicate that poor expression of AdipoR1 is associated with tumor invasion and lymph node metastasis, as well as poor prognosis in endometrial cancer patients [124]. A study of non-small cell lung cancer also indicates that patients with higher expression of AdipoR1 have longer overall survival and AdipoR2 expression is inversely correlated with tumor size [125]. Those findings further illustrate the protective role of adiponectin as well as AdipoRs and shed light on exploiting them for cancer therapy. Recently, AdipoRs agonist called 355ADP is identified and might represent a new strategy to replace low adiponectin level in cancer [126].

Despite the inverse correlation between adiponectin and various cancers, the underlying mechanisms of adiponectin in potential cancer suppression are still need to elucidate. Adiponectin decreases low density lipoprotein (LDL) receptor expression in breast cancer cells through promoting autophagic flux and inhibits LDL-cholesterol-induced tumor cell proliferation [127]. Adiponectin induces the phosphorylation of p53, a tumor suppressor, which renders cell cycle arrest and apoptosis in cancer cell lines [128]. Adiponectin also inhibits leptin-induced metastasis by downregulating JAK/STAT3 pathway, displaying an inverse correlation with cancer development [129]. In contrast, adiponectin promotes the angiogenesis in human chondrosarcoma by increasing vascular endothelial growth factor-A expression [130]. It is also reported to exert anti-apoptotic effects on pancreatic cancer cells through activation of AMPK/Sirtuin-1 signaling pathway [131]. Taken together, adiponectin might play a complicated role in carcinogenesis and progression of cancers.

Our study has some limitations that need to be addressed when interpreting the results. The significant heterogeneity was observed among the studies thus the conclusion should be more conservative. Although stratified analysis was conducted, none of the factors including ethnicity, cancer type, study design, blood sample, assay method, study size, study quality, and mean age of cancer patients were confirmed to contributing factors. Some possible reasons may partially explain this heterogeneity. Adiponectin levels are changed along with the tumor development. The tumor type, size, histological grade, and lymph node metastasis are the possible contributors caused heterogeneity. It is difficult for us to acquire the detailed information from the included studies. Besides, the subjects were from different regions and the lifestyle combined with diet was varied, which might influence the level of adiponectin. Since adiponectin is mainly secreted from adipose tissue, variables such as age, hormone receptor expression, menopausal status and BMI could contribute to the secretion and those factors were not fully deliberated for the complexity of tumor environment.

CONCLUSIONs

In summary, the present study shows significant difference in circulating adiponectin levels between patients with malignancies and controls. Low circulating adiponectin level is associated with increased cancer risk, which suggests that adiponectin may serve as a potential biomarker for early detection of cancers considering its abundance in blood. Thorough understanding the roles of adiponectin and its receptors in the progression of cancers is helpful to cancer screening and promote individualized treatment.

MATERIALs AND METHODS

Search strategy

Based on the standard guidelines, a systematic search of English literature from Cochrane library, Wiley online library, PubMed was conducted to retrieve eligible studies until August 8, 2015. Searching terms included Medical Subject Heading (Mesh) and free text words “adiponectin”, “ADPN”, “Acrp 30”, “AdipoQ”, “GBP 28” or “apM1” in combination with “neoplasm”, “cancer”, “carcinoma”, “malignancy” or “tumor”. Furthermore, we manually searched references of relevant studies to add potential research to this meta-analysis.

Inclusion and exclusion criteria

Studies were included if they met the following criteria: (i) full text case-control studies published in peer-reviewed journals evaluating the relationship between circulating adiponectin concentration and carcinogenesis; (ii) all cases were diagnosed as cancer by pathological biopsy or other medical methods with blood sample obtained before any therapies and all the controls were people without any cancers. (iii) circulating adiponectin level and standard deviation (SD) of it were provided or there were enough information to estimate them. Reviews, letters or animal experiments were excluded and articles without key information to carry on further analysis were also beyond consideration. Meanwhile, if replicated patient cohort was published in different studies, only the most recent or complete one was chosen. Since all the studies included were acquired from literature, ethics committee approval was not needed.

Data extraction

Based on the checklist of MOOSE (Meta-analysis Of Observational Studies in Epidemiology) [132], two reviewers (Tai W and Peng Y) extracted the following data independently from eligible studies: the last name of first author, year of publication, geographic region, ethnicity, tumor type, study design, sample type, adiponectin assay method, number of patients and controls, assay source, mean ± SD of adiponectin concentration. Disagreement was resolved by discussion until the two reviewers reached a consensus.

Quality assessment of included studies

Two reviewers (Tai W and Peng Y) independently assessed the quality of each included study according to the Newcastle-Ottawa Quality Assessment Scale (NOS) [133] ranges from 0 to 9 stars. Studies with more than 6 stars were considered as high-quality studies. Any disagreement was resolved by discussion and reevaluation.

Statistical analysis

We acquired the mean ± SD of circulating adiponectin levels from cases and controls through three ways. The most accurate method was extracted them from the original research directly. However, a few studies presented the results as median values or standard error. In that case, we regarded median value as mean value considering the large sample size and calculated the SD value by using standard error and population number. If necessary, we contacted the author for detailed information. Standard mean differences (SMDs) and the corresponding 95% confidence intervals (CIs) of circulating adiponectin were calculated for all the eligible studies. Cochran’s Q-test was performed to test the heterogeneity of included studies and P < 0.05 was considered statistically significant. Higgins I-squared statistic was applied to offer evidence of heterogeneity with I2 > 50% suggesting significant heterogeneity. The pooled SMD and 95% CI was calculated using a fixed-effects model if the heterogeneity was not significant, otherwise a random-effect model was employed and subgroup analyses and meta-regression were adopted to detect the potential cause of heterogeneity.

Sensitivity analysis was executed to detect the robustness of the results. Publication bias was evaluated by use of funnel plot and Egger’s linear regression test. The Stata 13.0 software (Stata Corporation, College Station, TX, USA) was used to perform all the statistical analysis. All P values were two-sided.

conflicts of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial conflict with any materials discussed in the paper. All authors declare that there is no conflict of interest regarding the publication of this work.

GRANT SUPPORT

This study was supported by the National Natural Science Foundation of China (No. 81472527) and National Supporting Program for Science and Technology of China (No. 2014BAI04B06).

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