received: 2014.12.31 association between genetic … · 2018-12-07 · background digestive...

Received: 2014.12.31Accepted: 2015.03.12

Published: 2015.08.02

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Association between Genetic Polymorphisms in DEFB1 and Susceptibility to Digestive Diseases

AEF 1 Yin-Peng Huang BCD 2 Tian-Yi Wang BEF 1 Wei Wang BDE 1 Hong-Zhi Sun

Corresponding Author: Hong-Zhi Sun, e-mail: [email protected] Source of support: Departmental sources

Background: Aberrant expression of defensins is implicated in the pathogenesis of digestive diseases. However, the contri-bution of specific defensins and the influence of their genetic polymorphisms on the progression of digestive diseases remain controversial. In the present meta-analysis, we investigated the association between DEFB1 SNPs and the susceptibility to digestive diseases.

Material/Methods: Case-control studies that reported the correlation between DEFB1 SNPs and the susceptibility to digestive dis-eases were identified through electronic databases searches, and high-quality studies that satisfied our inclu-sion criteria were selected for this meta-analysis. Statistical analyses were performed utilizing STATA software version 12.0.

Results: The present meta-analysis revealed that patients with digestive diseases exhibited higher frequencies of the DEFB1 genetic variants rs11362G>A, rs1800972C>G, and rs1799946G>A compared to healthy controls under the allele model. Subgroup analysis based on country showed that the rs1800972C>G variant under allele model and rs1799946G>A are associated with the susceptibility to digestive diseases in Hungarian and Italian populations, respectively. Subgroup analysis based on disease type showed that: (1) rs11362G>A variant was strongly associated with severe acute pancreatitis (SAP) and chronic gastritis, (2) frequency of rs1800972C>G variant was higher in SAP subgroup, and (3) frequency of rs1799946G>A variant was positively associated with the susceptibility to Crohn’s disease (CD) under the allele model and with SAP.

Conclusions: Our meta-analysis provides evidence that DEFB1 genetic polymorphisms rs11362G>A, rs1800972C>G and rs1799946G>A are important contributing factors to the development of digestive diseases.

MeSH Keywords: Digestive System Abnormalities • Disease Susceptibility • Meta-Analysis • Polymorphism, Genetic

Full-text PDF: http://www.medscimonit.com/abstract/index/idArt/893453

Authors’ Contribution: Study Design A

Data Collection B Statistical Analysis CData Interpretation D

Manuscript Preparation E Literature Search FFunds Collection G

1 Department of General Surgery, The First Affiliated Hospital of Liaoning Medical University, Jinzhou, Liaoning, P.R. China

2 Department of Oncology, The First Affiliated Hospital of Liaoning Medical University, Jinzhou, Liaoning, P.R. China

e-ISSN 1643-3750© Med Sci Monit, 2015; 21: 2240-2250

DOI: 10.12659/MSM.893453

2240Indexed in: [Current Contents/Clinical Medicine] [SCI Expanded] [ISI Alerting System] [ISI Journals Master List] [Index Medicus/MEDLINE] [EMBASE/Excerpta Medica] [Chemical Abstracts/CAS] [Index Copernicus]

This work is licensed under a Creative CommonsAttribution-NonCommercial-NoDerivs 3.0 Unported License

META-ANALYSIS

Background

Digestive diseases are described as the disorders of gastroin-testinal (GI) tract, which includes esophagus, stomach, small intestine, large intestine and rectum, liver, gallbladder, pan-creas and accessory digestive organs [1]. Cancers affecting the digestive system are the most frequent malignancies around the world and approximately 3 000 000 new digestive can-cer cases are diagnosed each year, accounting for 30% of all cancers, with 2 200 000 deaths each year [2]. The prevalence of digestive cancers are on the rise globally largely due to the rapidly increasing trends in gastric, colorectal, and hepatocel-lular carcinoma, which are among the 5 most common can-cers in the Asian region [3,4]. Non-malignant digestive diseas-es can have a very complex origin and course of development, with a strong involvement of both genetic and environmental factors [5,6]. Lifestyle factors such as tea consumption, smok-ing, and alcohol intake are implicated in the pathogenesis of digestive diseases, and other factors, including inflammation and bacterial and viral infections, also play crucial roles in the disease development [6,7]. Previous studies showed that ge-netic variations in interferon regulatory factor 5 (IRF5), toll-like receptor 4 (TLR4), and vitamin D receptor (VDR) are strongly associated with digestive diseases [8]. Recent evidence also suggests that genetic polymorphisms in genes encoding anti-microbial peptides, such as beta defensins, may also contrib-ute to the etiology of digestive diseases [9,10].

The b-defensins exhibit a broad spectrum of activity against various bacteria, fungi, and enveloped viruses. They are a sub-group of cationic antimicrobial peptides that contain 6-cyste-ine motifs that form 3 intra-molecular disulfide linkages to provide stability against proteases, which presumably is im-portant for their biological activity [11,12]. Further, the cation-ic nature of the b-defensins allows them to directly interact with the membranes of invading pathogens and dramatical-ly alter their membrane stability. DEFB1 is a member of the defensin family and possesses the ability to kill or inactivate a wide spectrum of bacteria and fungi directly and indirectly by triggering innate and adaptive immune responses [13,14]. Human DEFB1 gene is located on chromosome 8p23.2-p23.1, contains 2 small exons and 1 intron and spans approximately 7.0 kb in length [15]. Three functional single nucleotide poly-morphisms (-52 G>A, rs1799946; -44 C>G, rs1800972; -20 G>A, rs11362) were demonstrated to alter DEFB1 gene expression in a variety of cellular models [16,17]. DEFB1 is normally highly expressed in respiratory epithelium, gastric epithelium, intes-tinal epithelium, and in immune cells such as monocytes and macrophages [18]. It has been proposed that the antimicrobi-al response by host epithelial cells plays a crucial role in bac-terial adherence to the epithelium exposed to environmental pathogens and in the development of H. pylori-induced gastri-tis. DEFB1 is an important antimicrobial peptide in epithelial

tissues and functions as a primary and broad-spectrum re-sponse by the host innate defense system [5,19,20]. However, DEFB1 genetic polymorphisms that impair the expression and function of DEFB1 have been linked to the etiology of inflam-matory bowel disease [9]. Multiple studies reported that the low expression of DEFB1, due to genetic polymorphisms, is as-sociated with the pathogenesis of digestive diseases [5,10]. In contrast, other studies showed no such correlation between DEFB1 genetic polymorphisms and digestive diseases [8,21]. In light of this debate, we investigated the association between DEFB1 genetic polymorphisms and the susceptibility to diges-tive diseases using a meta-analysis framework.

Material and Methods

Data sources and keywords

Scientific articles published before April 1st, 2014, which as-sessed the correlation between DEFB1 genetic polymorphisms and the susceptibility to digestive diseases, were identified through electronic database search using PubMed, Embase, Web of Science, China BioMedicine (CBM), and China National Knowledge Infrastructure (CNKI). The common keywords used were: (“DEFB1 protein, human” or “DEFB1” or “beta-defen-sin-1” or “hBD-1 protein” or “hBD-1” or “beta defensin 1” or “beta-defensin 1” or “beta defensin-1” or “b-defensin 1”) and (“Polymorphism, Genetic” or “polymorphism” or “poly-morphisms” or “variants” or “SNP” or “mutation” or “genet-ic variants”). We also manually searched cross-references to identity additional relevant studies.

Selection criteria

The studies included in this meta-analysis fulfilled the following selection criteria: (1) contained patients with digestive diseases; (2) were human case-control studies reporting the role of DEFB1 genetic variants in the risk of digestive diseases; (3) provided gen-otype data for DEFB1 genetic variants; (4) reported the adjusted odd ratios (ORs) and 95% confidence intervals (CI) for DEFB1 ge-netic polymorphisms; (5) supplied the sample numbers; (6) con-formed with Hardy-Weinberg equilibrium (HWE) in the control group; and (6) the sample size was greater than 120. Additionally, if 2 or more studies were published by the same authors, only the latest or the most comprehensive study was included.

Data extraction

Two investigators (Zhou WH and Zhang YF) separately extract-ed the required data from the 6 selected papers. The extracted data included: first author, time of publication, source of pub-lication, study design, source of controls, age, sex, study type, disease type, sample size, ethnicity and country of subjects,


Huang Y.P. et al.: DEFB1 and digestive diseases© Med Sci Monit, 2015; 21: 2240-2250


META-ANALYSIS

genotyping method, available genotype, genotype and muta-tion frequencies, and HWE evidence in controls.

Quality assessment

Two investigators (Zhou WH and Zhang YF) used the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) score system to independently assess the quality of the studies [22]. The STROBE consists of 40 as-sessment items associated with quality appraisal, with scores ranging from 0 to 40. Based on the STROBE scores, the included studies were assessed as: low quality (0~19), moderate qual-ity (20~29), or high quality (30~40). Discrepancies in STROBE scores of the enrolled publications between the 2 investiga-tors were resolved through discussion involving all authors.

Statistical analysis

STATA 12.0 (Stata Corp, College Station, TX, USA) software was used for meta-analysis. The summary ORs with its 95% CI were used under allele model ([M] allele versus [W] allele) and dominant model (WW + WM versus MM) with the utiliza-tion of Z test. A random-effects model or a fixed-effects mod-el was used to evaluate the correlation between DEFB1 genet-ic polymorphisms and the susceptibility to digestive diseases among the included studies. The Cochran’s Q-statistic and

I2 test were also applied to reflect the heterogeneity among studies [23,24]. Heterogeneity on non-threshold effects was performed by quantitative evaluation of I2 test, the value of which ranged between 0% and 100% and was positively cor-related to heterogeneity. If significant heterogeneity was ob-served (P<0.05 or I2>50%), a random-effect model was em-ployed, otherwise a fixed-effect model was utilized [25,26]. The meta-regression analysis and subgroup meta-analyses by country and disease type were conducted to explore poten-tial influencing factors. Sensitivity analysis was conducted by deleting each enrolled study to estimate the effect of a single study on the overall results. The funnel plot and Egger’s linear regression test were implemented to assess whether publica-tion bias existed to further confirm the original result [27,28].

Results

Included studies

Our present meta-analysis was based on a total of 6 select-ed studies, published between 2008 and 2014, that supplied sufficient information on the association of DEFB1 genetic polymorphisms with the susceptibility to digestive diseases [5,8–10,29,30]. Demographic information of the subjects, study characteristics, and methodological quality of the extracted

First author Year Country DiseaseSample size Gender (M/F) Age (years) Genotyping

methodsSNP

Case Control Case Control Case Control

Wilson TJ [10] 2014 Brazil IBD 149 200 75/74 100/100 – – DSrs11362 G>Ars1800972 C>Grs1799946 G>A

Li P [8] 2013 China UC 300 302 161/139 157/145 40.4±13.8 42.0±14.6 Mass Array rs1799946 G>A

Zanin V-a [9] 2012 Italy CD 108 130 – – 36.5±14.0 31.3±12.4 DSrs11362 G>Ars1800972 C>Grs1799946 G>A

Zanin V-b [9] 2012 Italy UC 37 130 – – 38.2±15.7 31.3±12.4 DSrs11362 G>Ars1800972 C>Grs1799946 G>A

Tiszlavicz Z [30] 2010 Hungary SAP 124 100 75/49 65/35 58.0±6.9 45.0±8.9TaqMan assay

rs11362 G>Ars1800972 C>Grs1799946 G>A

Kocsis AK [5] 2009 HungaryChronic gastritis

150 100 – 53/47 – 26.0±15.0 PCR-RFLPrs11362 G>Ars1800972 C>Grs1799946 G>A

Kocsis AK [29] 2008 Hungary CD 190 95 108/82 50/45 36.4±12.9 26.0±15.0 PCR-RFLPrs11362 G>Ars1800972 C>Grs1799946 G>A

Table 1. Baseline characteristics of included studies. Six case-control studies were included in this meta-analysis.

M – male; F – female; IBD – inflammatory bowel disease; UC – ulcerative colitis; CD – Crohn’s disease; SAP – severe acute pancreatitis; a and b represent two different diseases in one study; DS – direct sequencing.


Huang Y.P. et al.: DEFB1 and digestive diseases

© Med Sci Monit, 2015; 21: 2240-2250


META-ANALYSIS

studies are presented in Table 1. Five studies were performed in whites and 1 study was performed in Asians. The 6 studies in-cluded a combined total of 2115 subjects (1058 digestive diseas-es cases and 1057 healthy controls). The studies were conduct-ed in Brazil (n=1), China (n=1), Italy (n=1), and Hungary (n=3). In relation to the disease types, 5 digestive disease types were reported in the studies included in our meta-analysis: inflamma-tory bowel disease (IBD), ulcerative colitis (UC), Crohn’s disease (CD), severe acute pancreatitis (SAP), and chronic gastritis. The source of the control subjects in this meta-analysis was popula-tion-based (PB) sample. Genotyping methods included PCR-RFLP (n=2), Mass Array (n=1), direct sequencing (n=2), and TaqMan as-say (n=1). The available SNPs of DEFB1 gene in this meta-analy-sis were rs11362 G>A, rs1800972 C>G, and rs1799946 G>A. The procedure for the selection of studies for this meta-analysis is displayed in Figure 1. A total of 177 papers were initially iden-tified from electronic database searches, which was followed by excluding 2 duplicates; 26 letters, reviews, or meta-analy-ses; 37 non-human studies; and 40 studies unrelated to the re-search topic. After further review of the remaining 72 studies, an additional 63 studies were excluded for not being case-con-trol studies (n=15), not relevant to DEFB1 gene (n=19), and not relevant to digestive tract diseases (n=29). A thorough examina-tion of the remaining 9 studies led to the elimination of 3 stud-ies for insufficient information. Thus, a total of 6 studies were finally enrolled in the meta-analysis. The quality scores of these selected eligible studies were all higher than 30 (high quality).

Association between DEFB1 genetic polymorphisms and susceptibility of digestive diseases

As shown in Figure 2, the major finding of the present meta-analysis was a significantly higher frequency of DEFB1 genetic

variants rs11362G>A, rs1800972C>G, and rs1799946G>A in pa-tients with digestive diseases compared to healthy controls un-der the allele model (rs11362G>A: OR=1.33, 95%CI: 1.07~1.65, P=0.011; rs1800972C>G: OR=1.26, 95%CI: 1.08~1.46, P=0.003; rs1799946G>A: OR=1.18, 95%CI: 1.06~1.32, P=0.003). However, the same association was not observed under the dominant model (all P>0.05).

Subgroup analysis by country showed no correlation between the frequency of rs11362G>A genetic polymorphism and the risk of digestive diseases among Brazilian, Italian, or Hungarian pop-ulations under both the allele model and the dominant model (all P>0.05). Interestingly, rs1800972C>G variant was associat-ed with a significantly higher risk for digestive diseases in the Hungarian population under the allele model (OR=1.41, 95%CI: 1.11~1.80, P=0.006), but a similar association did not exist in the Brazilian or Italian populations under the allele model, as well as the Brazilian, Italian, or Hungarian populations under the dominant model (all P>0.05). Subgroup analysis by coun-try also suggested that the frequency of rs1799946G>A poly-morphism was significantly higher in patients with digestive diseases, compared to the controls, in the Italian population (allele model: OR=1.39, 95%CI: 1.11~1.74, P=0.004; dominant model: OR=1.62, 95%CI: 1.15~2.29, P=0.006), but a similar rela-tionship was not seen in Brazilian, Chinese, or Hungarian pop-ulations under both the allele model and the dominant mod-el (all P>0.05) (Figure 3).

Subgroup analysis based on the disease type revealed that rs11362G>A genetic polymorphism was strongly associated with severe acute pancreatitis (SAP) (allele model: OR=2.17, 95%CI: 1.48~3.17, P<0.001; dominant model: OR=3.09, 95%CI: 1.68~5.69, P<0.001) and chronic gastritis (allele model: OR=2.54,

Figure 1. Flow chart shows the study selection procedure. Six case-control studies were included in this meta-analysis.

Articles identified throughelectronic database searching(N=176)

Additional articles identifiedthrough a manual search(N=1)

Articles reviewed for duplicates(N=177)

Iden

tifica

tion

Scre

enin

gEli

gibi

lity

Inclu

ded

Studies were excluded, due to:(N=26) Letters, reviews, meta-analysis(N=37) Not human studies(N=40) Not related to research topics

Articles after duplicates removed(N=175)

Full-text articles assessed for eligibility(N=72)

Studies included in qualitative synthesis(N=9)

Studies included in qualitative synthesis(meta analysis) (N=6)

Studies were excluded, due to:(N=15) Not case-control or cohort study(N=19) Not relevant to DEFB1 gene(N=29) Not relevant to diseases ofdigestive tract




META-ANALYSIS

95%CI: 1.75~3.70, P<0.001; dominant model: OR=4.19, 95%CI: 2.37~7.39, P<0.001), but not with Crohn disease (CD), ulcerative colitis (UC), and inflammatory bowel disease (IBD) under both the allele model and the dominant model (all P>0.05), as shown in Figure 3. In addition, subgroup analysis based on the disease type (Figure 3) showed that the frequency of rs1800972C>G genetic variant is positively correlated with the susceptibili-ty to SAP (allele model: OR=1.77, 95%CI: 1.12~2.79, P=0.014; dominant model: OR=6.03, 95%CI: 1.27~28.60, P=0.024), but a similar association was not found with CD, UC, IBD, and chronic

gastritis under both the allele model and the dominant mod-el (all P>0.05). Furthermore, the positive association between the frequency of rs1799946G>A variant and the susceptibil-ity to digestive diseases, as shown in Figure 3, was evident in the CD subgroup under the allele model (OR=1.28, 95%CI: 1.04~1.58, P=0.022) and SAP subgroup (allele model: OR=1.62, 95%CI: 1.11~2.35, P=0.012; dominant model: OR=2.20, 95%CI: 1.17~4.15, P=0.014), but not in the CD subgroup under domi-nant model or in UC, IBD, or chronic gastritis subgroups under both the allele model and the dominant model (all P>0.05).

Included study

0.27 3.71 0.135 7.391

0.358 2.791 0.0064 1561

Wilson TJ-a (2014)Wilson TJ-b (2014)Wilson TJ-c (2014)Zanin V-a (2012)Zanin V-b (2012)Zanin V-c (2012)Tiszlavicz Z (2010)Kocsis AK (2009)Kocsis AK (2008)

1.13 (0.78, 1.64)1.15 (0.78, 1.71)1.14 (0.84, 1.55)1.29 (0.89, 1.87)1.09 (0.65, 1.85)1.19 (0.85, 1.68)2.17 (1.48, 3.17)2.54 (1.75, 3.70)0.93 (0.65, 1.32)1.33 (1.07, 1.65)

11.2010.8612.5811.28

8.5111.8011.0911.1711.52

100.00Heterogeneity test (I2=67.8%, P=0.002)Z test (Z=2.54, P=0.011)

rs11362 G>A(W allele versus M allele) OR (95% CI) Weight %

Random effects analysis Random effects analysis


0.69 (0.35, 1.38)0.71 (0.35, 1.47)0.70 (0.40, 1.25)1.06 (0.51, 2.20)0.73 (0.28, 1.91)0.86 (0.43, 1.70)3.09 (1.68, 5.69)4.19 (2.37, 7.39)0.89 (0.45, 1.76)1.14 (0.70, 1.87)

11.1210.8911.9210.83

9.2711.1711.6711.9611.15

100.00Heterogeneity test (I2=79.1%, P<0.001)Z test (Z=0.52, P=0.604)


1.02 (0.62, 1.68)1.14 (0.67, 1.94)1.07 (0.72, 1.61)1.36 (0.86, 2.15)1.10 (0.58, 2.09)1.29 (0.84, 1.96)1.77 (1.12, 2.79)1.16 (0.77, 1.76)1.43 (0.95, 2.15)

1.26 (1.08, 1.46)

9.448.16

13.9710.96

5.6913.1511.1113.6813.85



0.65 (01.5, 2.78)0.57 (0.13, 2.46)06.1 (0.18, 2.04)

5.96 (0.30, 116.60)2.06 (0.10, 40.76)

7.99 (0.41, 156.13)6.03 (1.27, 28.60)

10.4 (0.43, 2.54)2.98 (1.16, 7.68)

1.49 (0.79, 2.81)

11.9311.9014.87

3.973.943.97

10.9419.7218.76


OR (95% CI) Weight %Included studyrs11362 G>A

(WW+WM versus MM)

Included studyrs1800972 C>G

(W allele versus M allele) OR (95% CI) Weight % OR (95% CI) Weight %Included studyrs1800972 C>G

(WW+WM versus MM)

0.358 2.791 0.241 4.151

Wilson TJ-a (2014)Wilson TJ-b (2014)Wilson TJ-c (2014)Li P (2013)Zanin V-a (2012)Zanin V-b (2012)Zanin V-c (2012)Tiszlavicz Z (2010)Kocsis AK (2009)Kocsis AK (2008)

1.03 (0.71, 1.50)11.3 (0.76, 1.66)1.08 (0.80, 1.45)1.04 (0.83, 1.30)1.48 (1.03, 2.13)1.19 (0.70, 2.02)1.40 (1.00, 1.97)1.62 (1.11, 2.35)0.93 (0.65, 1.33)1.37 (0.95, 1.97)1.18 (1.06, 1.32)

8.587.93

12.6221.24

8.784.39

10.068.409.048.96


Wilson TJ-a (2014)Wilson TJ-b (2014)Wilson TJ-c (2014)Li P (2013)Zanin V-a (2012)Zanin V-b (2012)Zanin V-c (2012)Tiszlavicz Z (2010)Kocsis AK (2009)Kocsis AK (2008)

0.94 (0.52, 1.65)0.74 (0.41, 1.31)0.83 (0.53, 1.32)1.06 (0.73, 1.53)1.88 (1.06, 3.33)1.18 (0.54, 2.56)1.65 (0.99, 2.77)2.20 (1.17, 4.15)0.93 (0.54, 1.60)1.74 (1.05, 2.88)1.21 (0.96, 1.53)

9.459.30

11.8314.24

9.376.32

10.498.319.93

10.78100.00Heterogeneity test (I2=46.2%, P=0.053)

Z test (Z=1.63, P=0.103)

Included studyrs1799946 G>A

(W allele versus M allele) OR (95% CI) Weight % OR (95% CI) Weight %Included studyrs1799946 G>A

(WW+WM versus MM)

Figure 2. Frequency of DEFB1 genetic variants (rs11362G>A, rs1800972C>G, rs1799946G>A) in patients with digestive diseases compared with the healthy controls.



© Med Sci Monit, 2015; 21: 2240-2250


META-ANALYSIS

Included study

0.27 3.71

Brazil Wilson TJ-a (2014) Wilson TJ-b (2014) Wilson TJ-c (2014)Heterogeneity test (I2=0.00%, P=0.997)Z test (Z=1.29, P=0.198)Italy Zanin V-a (2012) Zanin V-b (2012) Zanin V-c (2012)Heterogeneity test (I2=0.00%, P=0.873)Z test (Z=1.64, P=0.101)Hungary Tiszlavicz Z (2010) Kocsis AK (2009) Kocsis AK (2008)Heterogeneity test (I2=88.3%, P<0.001)Z test (Z=1.69, P=0.091)Heterogeneity test (I2=67.8%, P=0.002)Z test (Z=2.54, P=0.011)

1.13 (0.78, 1.64)1.15 (0.78, 1.71)1.14 (0.84, 1.55)1.14 (0.93, 1.40)

1.29 (0.89, 1.87)1.09 (0.65, 1.85)1.19 (0.85, 1.68)1.21 (0.96, 1.52)

2.17 (1.48, 3.17)2.54 (1.75, 3.70)0.93 (0.65, 1.32)1.72 (0.92, 3.21)

1.33 (1.07, 1.66)

11.2010.8612.5834.64

11.288.51

11.8031.59

11.0911.1711.5233.77

100.00

rs11362 G>A(Country: W allele versus M allele) OR (95% CI) Weight %

Random effects analysis

Included study

0.27 3.71

CD Wilson TJ-a (2014) Zanin V-a (2012) Kocsis AK (2008)Heterogeneity test (I2=0.00%, P=0.440)Z test (Z=0.89, P=0.374)UC Wilson TJ-b (2014) Zanin V-b (2012)Heterogeneity test (I2=0.00%, P=0.868)Z test (Z=0.78, P=0.438)IBD Wilson TJ-c (2014) Zanin V-c (2012)Heterogeneity test (I2=0.00%, P=0.854)Z test (Z=1.31, P=0.091)SAP Tiszlavicz Z (2010) Z test (Z=3.99, P<0.001)Chronic gastritis Kocsis AK (2009) Z test (Z=4.87, P<0.001)

Heterogeneity test (I2=67.8%, P=0.002)Z test (Z=2.54, P=0.011)

1.13 (0.78, 1.64)1.29 (0.89, 1.87)0.93 (0.65, 1.32)1.10 (0.89, 1.36)

1.15 (0.78, 1.71)1.09 (0.65, 1.85)1.13 (0.83, 1.55)

1.14 (0.84, 1.55)1.19 (0.85, 1.68)1.16 (0.93, 1.46)

2.17 (1.48, 3.17)2.17 (1.48, 3.17)

2.54 (1.75, 3.70)2.54 (1.75, 3.70)

1.33 (1.07, 1.66)

11.2011.2811.5233.99

10.868.519.37

12.5811.8024.38

11.0911.09

11.1711.17

100.00

rs11362 G>A(Disease: W allele versus M allele) OR (95% CI) Weight % Included study

0.135 7.391

CD Wilson TJ-a (2014) Zanin V-a (2012) Kocsis AK (2008)Heterogeneity test (I2=0.00%, P=0.707)Z test (Z=0.72, P=0.470)UC Wilson TJ-b (2014) Zanin V-b (2012)Heterogeneity test (I2=0.00%, P=0.964)Z test (Z=1.11, P=0.266)IBD Wilson TJ-c (2014) Zanin V-c (2012)Heterogeneity test (I2=0.00%, P=0.666)Z test (Z=1.21, P=0.227)SAP Tiszlavicz Z (2010) Z test (Z=3.62, P<0.001)Chronic gastritis Kocsis AK (2009) Z test (Z=4.94, P<0.001)

Heterogeneity test (I2=79.1%, P<0.001)Z test (Z=0.52, P=0.604)

0.69 (0.35, 1.38)1.06 (0.51, 2.20)0.89 (0.45, 1.76)0.86 (0.57, 1.29)

0.71 (0.35, 1.47)0.73 (0.28, 1.91)0.72 (0.41, 1.28)

0.70 (0.40, 1.25)0.86 (0.43, 1.70)0.76 (0.49, 1.18)

3.09 (1.68, 5.69)3.09 (1.68, 5.69)

4.19 (2.37, 7.39)4.19 (2.37, 7.39)

1.14 (0.70, 1.87)

11.1210.8311.1533.11

10.899.27

20.16

11.9211.1723.10

11.6711.67

11.9611.96

100.00

rs11362 G>A(Disease: WW+WM versus MM) OR (95% CI) Weight %

0.135 7.391

Brazil Wilson TJ-a (2014) Wilson TJ-b (2014) Wilson TJ-c (2014)Heterogeneity test (I2=0.00%, P=0.999)Z test (Z=1.83, P=0.067)Italy Zanin V-a (2012) Zanin V-b (2012) Zanin V-c (2012)Heterogeneity test (I2=0.00%, P=0.822)Z test (Z=0.49, P=0.627)Hungary Tiszlavicz Z (2010) Kocsis AK (2009) Kocsis AK (2008)Heterogeneity test (I2=83.9%, P=0.002)Z test (Z=1.83, P=0.068)Heterogeneity test (I2=79.1%, P<0.001)Z test (Z=0.52, P=0.604)

0.69 (0.35, 1.38)0.71 (0.35, 1.47)0.70 (0.40, 1.25)0.70 (0.48, 1.03)

1.06 (0.51, 2.20)0.73 (0.28, 1.91)0.86 (0.43, 1.70)0.90 (0.58, 1.39)

3.09 (1.68, 5.69)4.19 (2.37, 7.39)0.89 (0.45, 1.75)2.29 (0.94, 5.59)

1.14 (0.70, 1.87)

11.1210.8911.9233.94

10.839.27

11.1731.27

11.6711.9611.1534.79

100.00

Random effects analysis

OR (95% CI) Weight %Included studyrs11362 G>A

(Country: WW+WM versus MM)

Included study

0.358 2.791

Brazil Wilson TJ-a (2014) Wilson TJ-b (2014) Wilson TJ-c (2014)Heterogeneity test (I2=0.00%, P=0.957)Z test (Z=0.52, P=0.602)Italy Zanin V-a (2012) Zanin V-b (2012) Zanin V-c (2012)Heterogeneity test (I2=0.00%, P=0.874)Z test (Z=1.70, P=0.089)Hungary Tiszlavicz Z (2010) Kocsis AK (2009) Kocsis AK (2008)Heterogeneity test (I2=0.00%, P=0.409)Z test (Z=2.76, P=0.006)Heterogeneity test (I2=0.00%, P=0.828)Z test (Z=2.94, P=0.003)

1.02 (0.62, 1.68)1.14 (0.67, 1.94)1.07 (0.72, 1.61)1.07 (0.82, 1.41)

1.36 (0.86, 2.15)1.10 (0.58, 2.09)1.29 (0.84, 1.96)1.27 (0.96, 1.68)

1.77 (1.12, 2.79)1.16 (0.77, 1.76)1.43 (0.95, 2.15)1.41 (1.11, 1.80)

1.26 (1.08, 1.46)

9.448.16

13.9731.57

10.965.69

13.1529.79

11.1113.6813.8538.63

100.00

rs1800972 C>G(Country: W allele versus M allele) OR (95% CI) Weight %

0.0064 1561

Brazil Wilson TJ-a (2014) Wilson TJ-b (2014) Wilson TJ-c (2014)Heterogeneity test (I2=0.00%, P=0.993)Z test (Z=1.23, P=0.217)Italy Zanin V-a (2012) Zanin V-b (2012) Zanin V-c (2012)Heterogeneity test (I2=0.00%, P=0.803)Z test (Z=1.74, P=0.081)Hungary Tiszlavicz Z (2010) Kocsis AK (2009) Kocsis AK (2008)Heterogeneity test (I2=57.1%, P=0.097)Z test (Z=1.72, P=0.085)Heterogeneity test (I2=37.8%, P=0.117)Z test (Z=1.24, P=0.215)

0.65 (0.15, 2.78)0.57 (0.13, 2.46)0.61 (0.18, 2.04)0.61 (0.28, 1.34)

5.96 (0.30, 116.60)2.06 (0.10, 40.76)

7.99 (0.41, 156.13)4.62 (0.83, 25.78)

6.03 (1.27, 28.60)1.04 (0.43, 2.54)2.98 (1.16, 7.68)2.32 (0.89, 6.07)

1.49 (0.79, 2.81)

11.9311.9014.8738.69

3.973.943.97

11.89

10.9419.7218.7649.42

100.00

OR (95% CI) Weight %Included studyrs1800972 C>G

(Country: WW+WM versus MM)




META-ANALYSIS

Included study

0.358 2.791

CD Wilson TJ-a (2014) Zanin V-a (2012) Kocsis AK (2008)Heterogeneity test (I2=0.00%, P=0.567)Z test (Z=1.87, P=0.062)UC Wilson TJ-b (2014) Zanin V-b (2012)Heterogeneity test (I2=0.00%, P=0.940)Z test (Z=0.57, P=0.572)IBD Wilson TJ-c (2014) Zanin V-c (2012)Heterogeneity test (I2=0.00%, P=0.549)Z test (Z=1.06, P=0.288)SAP Tiszlavicz Z (2010) Z test (Z=2.45, P=0.014)Chronic gastritis Kocsis AK (2009) Z test (Z=0.72, P=0.473)


1.02 (0.62, 1.68)1.36 (0.86, 2.15)1.43 (0.95, 2.15)1.28 (0.99, 1.66)

1.14 (0.67, 1.94)1.10 (0.58, 2.09)1.13 (0.75, 1.69)

1.07 (0.72, 1.61)1.29 (0.84, 1.96)1.17 (0.87, 1.57)

1.77 (1.12, 2.79)1.77 (1.12, 2.79)

1.16 (0.77, 1.76)1.16 (0.77, 1.76)

1.26 (1.08, 1.46)

9.4410.9613.8534.24

8.165.69

13.85

13.9713.1527.12

11.1111.11

13.6813.68

100.00

rs1800972 C>G(Disease: W allele versus M allele) OR (95% CI) Weight % Included study

0.0064 1561

CD Wilson TJ-a (2014) Zanin V-a (2012) Kocsis AK (2008)Heterogeneity test (I2=42.7%, P=0.175)Z test (Z=1.07, P=0.285)UC Wilson TJ-b (2014) Zanin V-b (2012)Heterogeneity test (I2=0.00%, P=0.450)Z test (Z=0.47, P=0.642)IBD Wilson TJ-c (2014) Zanin V-c (2012)Heterogeneity test (I2=59.4%, P=0.116)Z test (Z=0.34, P=0.733)SAP Tiszlavicz Z (2010) Z test (Z=2.26, P=0.024)Chronic gastritis Kocsis AK (2009) Z test (Z=0.99, P=0.927)


0.65 (0.15, 2.78)5.96 (0.30, 116.60)

2.98 (1.16, 7.68)1.90 (0.59, 6.17)

0.57 (0.13, 2.46)2.06, 0.10, 40.76)

0.73 (0.20, 2.72)

0.61 (0.18, 2.04)7.99 (0.41, 156.13)

1.52 (0.14, 16.93)

6.03 (1.27, 28.60)6.03 (1.27, 28.60)

1.04 (0.43, 2.54)1.04 (0.43, 2.54)

1.49 (0.79, 2.81)

11.933.97

18.7834.66

11.903.94

15.85

14.873.97

18.84

10.9410.94

19.7219.72

100.00

rs1800972 C>G(Disease: WW+WM versus MM) OR (95% CI) Weight %

Included study

0.425 2.351

CD Wilson TJ-a (2014) Zanin V-a (2012) Kocsis AK (2008)Heterogeneity test (I2=0.5%, P=0.366)Z test (Z=2.29, P=0.022)UC Wilson TJ-b (2014) Li P (2013) Zanin V-b (2012)Heterogeneity test (I2=0.00%, P=0.868)Z test (Z=0.79, P=0.430)IBD Wilson TJ-c (2014) Zanin V-c (2012)Heterogeneity test (I2=22.4%, P=0.256)Z test (Z=1.47, P=0.143)SAP Tiszlavicz Z (2010) Z test (Z=2.51, P=0.012)Chronic gastritis Kocsis AK (2009) Z test (Z=0.41, P=0.685)


1.03 (0.71, 1.50)1.48 (1.03, 2.13)1.37 (0.95, 1.97)1.28 (1.04, 1.58)

1.13 (0.76, 1.66)1.04 (0.83, 1.30)1.19 (0.70, 2.02)1.08 (0.90, 1.29)

1.08 (0.80, 1.45)1.40 (1.00, 1.97)1.21 (0.94, 1.57)

1.62 (1.11, 2.35)1.62 (1.11, 2.35)

0.93 (0.65, 1.33)0.93 (0.65, 1.33)

1.18 (1.06, 1.32)

8.588.788.96

26.32

7.9321.24

4.3933.57

12.6210.0622.67

8.408.40

9.049.04

100.00

0.241 4.151

CD Wilson TJ-a (2014) Zanin V-a (2012) Kocsis AK (2008)Heterogeneity test (I2=43.8%, P=0.169)Z test (Z=1.77, P=0.077)UC Wilson TJ-b (2014) Li P (2013) Zanin V-b (2012)Heterogeneity test (I2=0.00%, P=0.511)Z test (Z=0.13, P=0.897)IBD Wilson TJ-c (2014) Zanin V-c (2012)Heterogeneity test (I2=73.5%, P=0.052)Z test (Z=0.44, P=0.662)SAP Tiszlavicz Z (2010) Z test (Z=2.45, P=0.014)Chronic gastritis Kocsis AK (2009) Z test (Z=0.28, P=0.782)


0.94 (0.53, 1.65)1.88 (1.06, 3.33)1.74 (1.05, 2.88)1.46 (0.96, 2.23)

0.74 (0.41, 1.31)1.06 (0.73, 1.53)1.18 (0.54, 2.56)0.98 (0.74, 1.31)

0.83 (0.53, 1.32)1.65 (0.99, 2.77)1.16 (0.59, 2.27)

2.20 (1.17, 4.15)2.20 (1.17, 4.15)

0.93 (0.54, 1.60)0.93 (0.54, 1.60)

1.21 (0.96, 1.53)

9.459.37

10.7829.59

9.3014.24

6.3229.85

11.8310.4922.32

8.318.31

9.939.93

100.00

rs1799946 G>A(Disease: W allele versus M allele) OR (95% CI) Weight % Included study

rs1799946 C>G(Disease: WW+WM versus MM) OR (95% CI) Weight %

Included study

0.27 3.71

Brazil Wilson TJ-a (2014) Wilson TJ-b (2014) Wilson TJ-c (2014)Heterogeneity test (I2=0.00%, P=0.952)Z test (Z=0.72, P=0.472)China Li P (2013)Z test (Z=0.34, P=0.731)Italy Zanin V-a (2012) Zanin V-b (2012) Zanin V-c (2012)Heterogeneity test (I2=0.00%, P=0.802)Z test (Z=2.85, P=0.004)Hungary Tiszlavicz Z (2010) Kocsis AK (2009) Kocsis AK (2008)Heterogeneity test (I2=57.0%, P=0.098)Z test (Z=1.44, P=0.150)Heterogeneity test (I2=6.1%, P=0.385)Z test (Z=2.94, P=0.003)

1.03 (0.71, 1.50)1.13 (0.76, 1.66)1.08 (0.80, 1.45)1.08 (0.88, 1.31)

1.04 (0.83, 1.30)1.04 (0.83, 1.30)

1.48 (1.03, 2.13)1.19 (0.70, 2.02)1.40 (1.00, 1.97)1.39 (1.11, 1.74)

1.62 (1.11, 2.35)0.93 (0.65, 1.33)1.37 (0.95, 1.97)1.27 (0.92, 1.75)

1.18 (1.06, 1.32)

8.587.93

12.6229.13

21.2421.24

8.784.39

10.0623.23

8.409.048.96

26.40

100.00

0.241 4.151

Brazil Wilson TJ-a (2014) Wilson TJ-b (2014) Wilson TJ-c (2014)Heterogeneity test (I2=0.00%, P=0.843)Z test (Z=1.19, P=0.235)China Li P (2013)Z test (Z=0.30, P=0.763)Italy Zanin V-a (2012) Zanin V-b (2012) Zanin V-c (2012)Heterogeneity test (I2=0.00%, P=0.635)Z test (Z=2.75, P=0.006)Hungary Tiszlavicz Z (2010) Kocsis AK (2009) Kocsis AK (2008)Heterogeneity test (I2=58.1%, P=0.092)Z test (Z=1.61, P=0.107)Heterogeneity test (I2=46.2%, P=0.053)Z test (Z=1.63, P=0.103)

0.94 (0.53, 1.65)0.74 (0.41, 1.31)0.83 (0.53, 1.32)0.83 (0.61, 1.13)

1.06 (0.73, 1.53)1.06 (0.73, 1.53)

1.88 (1.06, 3.33)1.18 (0.54, 2.56)1.65 (0.99, 2.77)1.62 (1.15, 2.29)

2.20 (1.17, 4.15)0.93 (0.54, 1.60)1.74 (1.05, 2.88)1.51 (0.92, 2.48)

1.21 (0.96, 1.53)

9.459.30

11.8330.57

14.2414.24

9.376.32

10.4926.17

8.319.93

10.7829.02

100.00

rs1799946 G>A(Country: W allele versus M allele) OR (95% CI) Weight % OR (95% CI) Weight %Included study

rs1799946 G>A(Country: WW+WM versus MM)

Figure 3. Subgroup analyses by country and the frequency of DEFB1 genetic variants by disease type (rs11362G>A, rs1800972C>G, rs1799946G>A) under both allele model and dominant model.



© Med Sci Monit, 2015; 21: 2240-2250


META-ANALYSIS

Lower CI limit Upper CI limitEstimateWilson TJ-a (2014)

Wilson TJ-b (2014)

Wilson TJ-c (2014)

Zanin V-a (2012)

Zanin V-b (2012)

Zanin V-c (2012)

Tiszlavicz Z (2010)

Kocsis AK (2009)

Kocsis AK (2008)

1.01 1.07 1.33 1.66 1.75

rs11362 G>A(W allele versus M allele)


Wilson TJ-b (2014)

Wilson TJ-c (2014)

Zanin V-a (2012)

Zanin V-b (2012)

Zanin V-c (2012)

Tiszlavicz Z (2010)

Kocsis AK (2009)

Kocsis AK (2008)

0.62 0.70 1.14 1.87 2.08

rs11362 G>A(WW+WM versus MM)


Wilson TJ-b (2014)

Wilson TJ-c (2014)

Zanin V-a (2012)

Zanin V-b (2012)

Zanin V-c (2012)

Tiszlavicz Z (2010)

Kocsis AK (2009)

Kocsis AK (2008)

1.02 1.08 1.26 1.46 1.52

rs1800972 C>G(W allele versus M allele)


Wilson TJ-b (2014)

Wilson TJ-c (2014)

Zanin V-a (2012)

Zanin V-b (2012)

Zanin V-c (2012)

Tiszlavicz Z (2010)

Kocsis AK (2009)

Kocsis AK (2008)

0.64 0.79 1.49 2.81 3.57

rs1800972 C>G(WW+WM versus MM)


Wilson TJ-b (2014)

Wilson TJ-c (2014)

Li P (2013)

Zanin V-a (2012)

Zanin V-b (2012)

Zanin V-c (2012)

Tiszlavicz Z (2010)

Kocsis AK (2009)

Kocsis AK (2008)

Wilson TJ-a (2014)

Wilson TJ-b (2014)

Wilson TJ-c (2014)

Li P (2013)

Zanin V-a (2012)

Zanin V-b (2012)

Zanin V-c (2012)

Tiszlavicz Z (2010)

Kocsis AK (2009)

Kocsis AK (2008)

1.02 1.08 1.18 1.32 1.38


Lower CI limit Upper CI limitEstimate

0.87 0.91 1.07 1.26 1.33


Figure 4. Sensitivity analysis of the correlations between digestive diseases and the frequency of DEFB1 genetic variants (rs11362G>A, rs1800972C>G, rs1799946G>A) under both allele model and dominant model.




META-ANALYSIS

Sensitivity analysis and publication bias

Sensitivity analysis results illustrated that all included studies had no influence on the pooled ORs of relationship of DEFB1 gene polymorphism and the susceptibility to digestive diseases (Figure 4). The graphical funnel plots of the 6 studies involving

DEFB1 rrs11362G>A, rs1800972C>G and rs1799946G>A genet-ic variants were symmetrical and Egger’s test showed no pub-lication bias (all P>0.05) (Figure 5).


(Egger’s test: t=0.25, P=0.812) (Egger’s test: t=–1.50, P=0.176)

0.0 0.1 0.2 0.3

0.0 0.1 0.2 0.3

Log[

OR]

SE Log[OR]

1.0

0.5

0.0

–0.5

0.0 0.1 0.2 0.3

0.0 0.2 0.4

Log[

OR]

SE Log[OR]

1.0

0.5

0.0

–0.5


rs1800972 C>G(W allele versus M allele)

(Egger’s test: t=–0.58, P=0.581) (Egger’s test: t=0.81, P=0.447)

0.0 0.2 0.4

Log[

OR]

SE Log[OR]

1.0

0.5

0.0

–0.5

0.0 0.5 1.0 1.5

Log[

OR]

SE Log[OR]

4

2

0

–2

–4

rs1800972 C>G(WW+WM versus MM)


(Egger’s test: t=1.16, P=0.280) (Egger’s test: t=0.74, P=0.482)

Log[

OR]

SE Log[OR]

1.0

0.5

0.0

–0.5

1.0

0.5

0.0

–0.5

Log[

OR]

SE Log[OR]


Figure 5. Evaluation of publication bias for the correlation between digestive diseases and DEFB1 genetic variants (rs11362G>A, rs1800972C>G, rs1799946G>A) under both allele model and dominant model.



© Med Sci Monit, 2015; 21: 2240-2250


META-ANALYSIS

Discussion

In this study we investigated the association between DEFB1 gene polymorphisms and the susceptibility to digestive diseas-es using a systematic meta-analysis–based approach. Our main result indicates a significant correlation between rs11362G>A, rs1800972C>G, and rs1799946G>A polymorphisms in DEFB1 gene and the susceptibility to CD, chronic gastritis, and SAP. Defensins are small, acid-stable, amphipathic, antimicrobial peptides with a largely b-sheet structure, which is important for their activities against bacteria, fungi, viruses, and some parasites [31]. DEFB1 was the first defensin to be discovered and is an important member of the defensin family. DEFB1 has 3 conserved disulfide bonds, which apparently is impor-tant for the structural stability and its stability against prote-ases, and exhibits broad-spectrum activities against infectious agents [10]. DEFB1 is expressed in multiple cell types of the immune system such as macrophages, monocytes, dendritic cells, and leukocytes. More importantly, epithelial cells in many organs such as pancreas, skin, kidney, respiratory system, and digestive tract express high levels of DEFB1 [32,33]. Initially, DEFB1 was thought to be constitutively expressed in the body, but subsequent evidence suggested that its expression is regu-lated under specific conditions. Additionally, DEFB1 has strong chemoattractant properties towards memory T cells and den-dritic cells, through the CC chemokine receptor, suggesting an important role for DEFB1 in inflammation [19,34]. DEFB1 is also implicated in the activation of cellular apoptosis, and several cancers such as prostate and renal cancer down-regulate de-fensin gene expression to inhibit apoptosis and promote cancer progression. Therefore, DEFB1 gene expression and the role of DEFB1 polymorphisms are of significant importance to human health [35,36]. Not surprisingly, DEFB1 gene polymorphisms are linked to other infection and inflammatory diseases such as chronic obstructive pulmonary disease (COPD), asthma, oral candida infections, periodontitis, and atopic dermatitis [18]. DEFB1 expression in the digestive tract epithelium protects against intestinal pathogens and DEFB1 gene polymorphisms influencing DEFB1 expression have been previously implicat-ed in digestive tract diseases [8]. Accordingly, SNPs located within the DEFB1regulatory region have been associated with chronic gastritis, CD, and SAP, particularly the 3 SNPs at the 5’-untranslated region, rs11362 (G-20A), rs1800972 (C-44G), and rs1799946 (G-52A) [37]. A higher frequency of GA and AA genotypes of the G-52A SNP was found in chronic active gas-tritis patients, and both inducible and constitutive forms of human defensins are involved in the development of H. pylori-induced gastritis, with DEFB1 expression induced by infection of AGS cells with cagPAI strain [5]. Further, a lower frequency of GG genotype in DEFB1 C-44G SNP, which harbors a nuclear factor-kB binding site, is reported in CD patients, suggesting that a change from C allele to G allele may increase antimi-crobial activity of DEFB1 and that the GG phenotype may be

a protective factor for CD [29]. In agreement with our analy-sis, Tiszlavicz et al. found higher frequencies of AA genotype of G–20A and G–52A SNPs and lower frequency of GG geno-type of C–44G SNP in SAP patients compared to the control group, showing that DEFB1 polymorphisms at different sites might influence SAP differently [30].

We also considered the influence of country and disease types on our results involving rs11362, rs1800972, and rs1799946 DEFB1 gene polymorphisms and the susceptibility to digestive diseases. In a stratified analysis based on country, the rs11362 polymorphism was not significantly associated with digestive diseases among Brazilian, Italian, and Hungarian populations, while the rs1800927 polymorphism was associated with the increased risk for digestive diseases in the Hungarian popula-tion in the allele model, and rs1799946 SNP was linked with digestive disease susceptibility in the Italian population. It is possible that different lifestyles, diet, pathogen exposure, and access to health care in different countries might influence the results seen with these genetic variants. Importantly, in our disease-stratified analysis, we observed a significant associa-tion of rs11362 DEFB1 polymorphism with the susceptibility to SAP and chronic gastritis, along with a strong association between rs1800972 and SAP progression, and an association of rs1799946 with the pathogenesis of CD and SAP.

It is important to highlight the strengths of our meta-analy-sis and acknowledge its weaknesses. The central advantage of this meta-analysis is the rigorous statistical review of data from the literature that cannot be achieved by any single study [38–40]. An unambiguous and strong association between DEFB1 SNPs and digestive diseases cannot be drawn from the results of a single study, but our approach confirmed this re-lationship by analyzing the results from multiple studies. Our meta-analysis has several weaknesses. First, the enrollment of a relatively small sample size (only 6 studies) may lack suf-ficient statistical power to assess the results. Second, of the 6 eligible studies, most were performed in whites, and only 1 study was conducted in Asians, indicating a selection bias. Third, the origin and progression of digestive diseases depends on the interaction of a variety of genetic factors such as IRF5, TLR4, DEFB1, and VDR, and DEFB1 is only 1 of the main fac-tors contributing to the pathological course of these digestive diseases. Thus, the conclusions drawn from this study should not be viewed as if DEFB1 is the sole contributor in disease pathogenesis. In this context, we could not ascertain the po-tential clinical value of DEFB1 SNPs as biomarkers and this will require further studies. Lastly, the genotyping methods used in the 6 selected studies were different, which may in-fluence our study results.




META-ANALYSIS

Conclusions

In summary, our results provide evidence that the DEFB1 genetic polymorphisms rs11362G>A, rs1800972C>G, and rs1799946G>A are strongly associated with the susceptibility to digestive dis-eases, indicating that DEFB1 is an important player in the patho-genesis of digestive diseases and may be a target for therapeutic intervention. However, further studies with larger sample sizes and diverse populations are required to confirm our findings.

Acknowledgement

We thank Zhou WH and Zhang YF for their inclusion and qual-ity evaluation of the included papers, and the reviewers for their professional comments on this paper.

Competing interests

The authors declared no interest conflicts and the authors alone are accountable for the writing and content of the paper.

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