Figures
Abstract
Background
Polymorphisms in immunity-related GTPase family M (IRGM) gene may be associated with inflammatory bowel disease (IBD) by affecting autophagy. However, the genetic association studies on three common variants in IRGM gene (rs13361189, rs4958847 and rs10065172) have shown inconsistent results.
Methodology/ Principal Findings
The PubMed and Embase were searched up to June 5, 2013 for studies on the association between three IRGM polymorphisms and IBD risk. Data were extracted and the odd ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Finally, we performed a meta-analysis of 25 eligible studies in 3 SNPs located at IRGM gene by using a total of 20590 IBD cases and 27670 controls. The analysis showed modest significant association for the rs13361189, rs4958847 and rs10065172 variants in Crohn’s disease (CD): the risk estimates for the allele contrast were OR=1.306 (1.200-1.420), p=5.2×10-10, OR=1.182 (1.082-1.290), p=0.0002, and OR=1.248 (1.057-1.473), p=0.009 respectively (still significant when the p value was Bonferroni adjusted to 0.017). When stratified by ethnicity, significantly increased CD risk was observed in Europeans, but not in Asians. Conversely, there was no association of rs13361189 or rs4958847 variant with risk of ulcerative colitis (UC).
Citation: Lu XC, Tao Y, Wu C, Zhao PL, Li K, Zheng JY, et al. (2013) Association between Variants of the Autophagy Related Gene – IRGM and Susceptibility to Crohn’s Disease and Ulcerative Colitis: A Meta-Analysis. PLoS ONE 8(11): e80602. https://doi.org/10.1371/journal.pone.0080602
Editor: Emiko Mizoguchi, Massachusetts General Hospital, United States of America
Received: July 6, 2013; Accepted: October 4, 2013; Published: November 13, 2013
Copyright: © 2013 Lu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was supported by grants from the National Natural Science Foundation of China (No. 30973092 and No. 81178147), “Xingwei Project” Key Personal Medical Research Foundation of Health Department of Jiangsu Province (No. RC201156), “Six Categories of Key Person” Research Foundation of Jiangsu Province (No. 069), Program Sponsored for Scientific Innovation Research of College Graduate in Jiangsu Province (No. CXZZ12_0583), and Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (No. JX10231801). grants from the National Natural Science Foundation of China (No. 30973092 and No. 81178147)", replace 81178147 with 81171147. - In ACs, add author Kai Li to "analyzed the data" and "contributed reagents. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Inflammatory bowel disease (IBD), a chronic inflammatory disease of the gastrointestinal tract, is usually classified into two clinical forms: Crohn’s disease (CD) and ulcerative colitis (UC) [1,2]. CD generally involves the ileum and colon, and it can affect any region of the intestine in a continuous manner. UC involves the rectum and may affect part of the colon or the entire colon, often uninterruptedly. The etiology of IBD most likely involves a complex interaction of genetic and environmental factors. Although the etiology remains poorly understood, epidemiologic and linkage studies suggest that genetic factors are implicated in the pathogenesis of IBD [3-9].
Recent progress in the genetics of IBD has advanced understanding of disease pathogenesis. GWAS meta-analysis identified 71, 47 and 163 susceptibility loci of CD, UC and IBD, respectively. These genes involved in intestinal barrier function (GNA12 and LAMB1), transcriptional regulation (NKX2-3 and IRF5) and immune response (IL23R and IL12B). Recently, studies in animal models and IBD patients suggested that autophagy related genes (ATG16L1 and IRGM) may play an important role in the pathogenesis of IBD[10–12]. The immunity-related GTPase family M (IRGM) gene, located on chromosome 5q33.1, encodes a GTP-binding protein that induces autophagy, which is involved in elimination of intracellular pathogens[13,14]. Association of three common polymorphisms in IRGM gene (rs13361189, rs4958847 and rs10065172) with IBD has been recently reported [12,15-18]. However, the genetic association studies that investigated the association between IBD and rs13361189, rs4958847 or rs10065172 variant have produced inconclusive results. For instance, an accumulating number of studies suggested a positive association between IRGM polymorphisms and CD susceptibility [12,18,19], which, nevertheless, could not be replicated in several studies [16,20,21]. This inconsistency may be due to studies with limited sample sizes, inadequate statistical power, or ethnic differences.
Meta-analysis is a proper method to deal with these ambiguities and overcome the problem of small sample sizes and inadequate statistical power in different genetic studies. In the present study, we performed a meta-analysis of all eligible case control and cohort studies to clarify the associations between three common polymorphisms (rs13361189, rs4958847 and rs10065172) in the IRGM gene and IBD (CD or UC) susceptibility.
Materials and Methods
Identification and eligibility of relevant studies
Electronic searches in Medline, Embase, CNKI (China National Knowledge Infrastructure) and Chinese Biomedicine databases were performed using the following search terms: ‘Inflammatory Bowel Disease’ or ‘IBD’, ‘Crohn’s disease’ or ‘CD’, ‘ulcerative colitis’ or ‘UC’, ‘IRGM’, ‘polymorphism’ or ‘variant’, ‘rs13361189’, ‘rs4958847’ or ‘rs10065172’, and ‘single nucleotide polymorphism’ or ‘SNP’( the last search update was 5 June 2013). In addition, the reference lists of all retrieved articles were checked for additional potential studies. A study was included in the analysis if (1) reported the relationship between the polymorphisms of IRGM rs13361189, rs4958847 or rs10065172and the risk of IBD; (2) the genetic information of included studies was from unrelated populations (studies of which the design was not based on family data). Major reasons for exclusion of studies: (1) no control population; (2) studies that contained overlapping data; (3) comments, letters, review articles, or articles only with an abstract. Additionally, when a study reported the results on different subpopulations or panels, we treated them as separate studies in the meta-analysis.
Data extraction
The following data was extracted independently from each study by two authors: first author, journal, year of publication, country of origin, ethnicity of the individuals involved (Europeans, Asians, or Africans), genotype frequency, sex and mean age in cases and controls. Of the studies with the overlapping data of the same population resource, we selected the most recent ones with the largest number of participants. If the article did not provide sufficient genotype distribution, the corresponding author was contacted for the detailed data. In addition, disagreements were resolved by discussion between the two investigators.
Statistical analysis
The strength of the association between IRGM polymorphisms and CD or UC risk was evaluated by the odds ratios (ORs) with 95% confidence intervals (CIs). For the rs13361189 polymorphism, we examined the allelic effect of C (minor allele) versus T (common allele), and also examined the contrast of CC versus TT, CT versus TT, CC+CT versus TT (dominant model), as well as CC versus CT+TT (recessive model). Similar models were analyzed for the rs4958847 and rs10065172 polymorphisms. The association between rs10065172 and UC risk was not evaluated for the lack of sufficient data. The significance of the pooled OR was determined by the Z-test; and the P values were adjusted using Bonferroni correction by the number of compared SNPs. (P=0.05/3=0.017) In addition, for each genetic contrast, stratified analysis was performed according to ethnicity. The Hardy-Weinberg equilibrium (HWE) in the control group was assessed, and P<0.05 was considered as significant disequilibrium.
The heterogeneity between studies was assessed by Chi-square based Q test [22] and I2 test. Heterogeneity was considered significant when P<0.10, and then the random effect model was applied for meta-analysis, otherwise, a fixed-effects model was used [23]. I2 takes values between 0% and 100% with higher values denoting a greater degree of heterogeneity [24]. In addition, a meta-regression model was performed to explore the possible heterogeneity among different kinds of studies.
Cumulative meta-analyses were carried out for all three variants in association with CD and two variants (rs13361189 and rs4958847) with UC to evaluate the trend of the genetic risk effect (OR) of the allele contrast as evidence accumulating over time. To assess the stability of the results, sensitivity analysis was carried out after sequential removal of each study or by excluding those studies deviated from HWE.
Publication bias was investigated using graphical evaluation of funnel plots. However, the funnel plot may be not considered strictly as a test of publication bias. Then, the Egger’s test was used to provide statistical evidence of funnel plot symmetry [25]. If significant publication bias was detected, ORs and 95% CIs would be adjusted by trim and fill methods. All statistical analyses were performed by STATA software (version 12).
Results
Main characteristics of eligible studies
The literature review identified 62 articles in PubMed, Embase, CNKI and Chinese Biomedicine databases that met the search criteria. The abstracts and full articles of the retrieved studies were read to assess their appropriateness for meta-analysis. Finally, a total of 23 relevant articles with IRGM polymorphisms (rs13361189, rs4958857 or rs10065172) and IBD (UC or CD) were included in this meta-analysis. Figure 1 showed a flow chart of the retrieved studies and the excluded studies. Among them, one publication [16] contained data on two different subpopulations, one [18] included Wellcome Trust Case Control Consortium (WTCCC) samples and replication Crohn's disease (RCD) samples and we treated them independently. Therefore, 25 studies that comprised a total of 20590 IBD cases and 27670 controls were considered in our meta-analysis.
A list of details of the studies included in the meta-analysis was provided in Table 1. The studies were published from 2007 to 2013. Studies were conducted in various populations of ethnic descent: 17 Europeans [12,15-19,21,26-35], 4 Asians [36–39], 1 Africans [20] and 1 Jewishs [40]. Because of the insufficient samples available for African and Jewish groups, we have performed subgroup analysis in Europeans and Asians. Although the allele frequency of the IRGM polymorphisms was extracted from 25 studies, 4 studies [19,28,30,31] did not include genotype distributions, but one [19] was included after we contacted the authors directly, who provided sufficient data. In 2 studies [18,21], the distribution of the genotypes in control group was not in HWE (P<0.05). Then, a sensitivity analysis was performed by excluding these studies from the analysis.
| Cases | Controls | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Author, Year of publication | Ethnicity | IRGM variant | Phenotype Studied | Number | Males (%) | Age or Age at diagnosis | Number | Males (%) | Age | Matching | |
| Wang, 2012 | African | rs13361189 | CD | CD:354 | 34.2 | 37.4±14.3 and 26.7±12.9 at diagnosis | 354 | 42.6 | 39.8±12.7 | nr | |
| rs4958847 | |||||||||||
| rs10065172 | |||||||||||
| Meggyesi1, 2010 | European | rs13361189 | CD and UC separately | CD: 456 UC: 274 | CD:53.6 | CD: 37.1±12.6 and 26.5±10.6 at diagnosis | 271 | nr | nr | Age and sex | |
| Meggyesi2, 2010 | European | rs13361189 | CD and UC separately | CD:352 UC: 154 | UC:47.2 | UC: 43.7±15.0 and 31.3±13.4 at diagnosis | 198 | nr | nr | ||
| Peter, 2011 | Jewish | rs13361189 | CD | CD:369 | nr | nr | 503 | nr | nr | nr | |
| Dema, 2009 | European | rs4958847 | CD | CD:725 | nr | nr | 956 | nr | nr | nr | |
| rs10065172 | |||||||||||
| Frank, 2008 | European | rs13361189 | CD and UC separately | CD: 1850 | CD:32 | CD: 38 and 21 at diagnosis (median) | 1817 | nr | nr | Age and sex | |
| rs4958847 | UC: 1103 | UC:42.8 | UC: 40 and 26 at diagnosis (median) | ||||||||
| rs10065172 | |||||||||||
| Wolfkamp, 2010 | European | rs13361189 | CD | CD: 530 | nr | nr | 529 | nr | nr | nr | |
| rs4958847 | |||||||||||
| Palomino-Morales,2009 | European | rs13361189 | CD and UC separately | CD: 557 | nr | nr | 672 | nr | nr | Age and sex | |
| rs4958847 | UC: 425 | ||||||||||
| Yamazaki, 2009 | Asian | rs13361189 | CD | CD: 484 | 72.5 | 22.4(7–55) | 470 | 50.2 | 38.7(21–77) | nr | |
| rs4958847 | |||||||||||
| Prager, 2012 | European | rs13361189 | CD and UC separately | CD: 464 | CD:37.5 | CD:29.5±11.6 at diagnosis | 508 | 42 | 60±16.2 | nr | |
| rs4958847 | UC: 292 | UC:44.8 | UC:34.3±14.2 at diagnosis | ||||||||
| Fisher, 2008 | European | rs13361189 | UC | UC: 1841 | nr | nr | 1470 | nr | nr | nr | |
| rs4958847 | |||||||||||
| Parkes (RCD), 2007 | European | rs13361189 | CD | CD:1182 | 40.3 | CD: 43.9 and 25.5 at diagnosis (median) | 2024 | nr | nr | nr | |
| rs4958847 | |||||||||||
| Parkes (WTCCC), 2007 | European | rs13361189 | CD | CD:1748 | 39.2 | CD: 45.7 and 26.1 at diagnosis (median) | 8655 | nr | nr | nr | |
| rs4958847 | |||||||||||
| Roberts, 2009 | European | rs13361189 | CD and UC separately | CD: 507 | nr | nr | 576 | nr | nr | nr | |
| rs4958847 | UC: 475 | ||||||||||
| Latiano, 2009 | European | rs4958847 | CD and UC separately | CD: 823 | CD: 30 ± 15 at diagnosis | 578 | nr | nr | nr | ||
| UC: 353 | UC: 25 ± 16 at diagnosis | ||||||||||
| Zheng, 2012 | Asian | rs13361189 | CD | CD:318 | 48.4 | CD: 37.2±11.4 | 318 | 49.1 | 36.7±12.3 | nr | |
| Prescott, 2010 | European | rs13361189 | CD | CD:1848 | nr | nr | 2025 | nr | nr | nr | |
| rs10065172 | |||||||||||
| Pang, 2011 | Asian | rs13361189 | CD | CD:66 | 48.5 | CD:36.3±11.8 | 66 | 50.0 | 35.4±13.1 | nr | |
| Limbergen, 2009 | European | rs13361189 | CD | CD:630 | nr | nr | 3283 | nr | nr | nr | |
| rs4958847 | |||||||||||
| rs10065172 | |||||||||||
| Weersma, 2009 | European | rs13361189 | CD and UC separately | CD: 1656 | nr | nr | 1086 | nr | nr | nr | |
| rs4958847 | UC: 1075 | ||||||||||
| Eglinton, 2012 | European | rs4958847 | CD | CD: 507 | 37.1 | 45±17.9 | 507 | nr | nr | nr | |
| Amre, 2009 | European | rs10065172 | CD | CD: 289 | 55.4 | CD: 12.1± 3.5 at diagnosis | 290 | 52.4 | 11.4± 6.8 | nr | |
| Duraes, 2013 | European | rs13361189 | CD | CD: 511 | 46.2 | CD: 28.6± 11.2 at diagnosis | 626 | 38.5 | 30.5(9-83) | sex | |
| Glas, 2013 | European | rs13361189 | CD and UC separately | CD: 817 | CD: 46.0 | CD: 40.7±13.3 and 27.9±12.0 at diagnosis | 961 | 63.6 | 47.4±9.06 | nr | |
| rs4958847 | UC: 283 | UC: 53.0 | UC: 43.8±14.4 and 31.3±13.7 at diagnosis | ||||||||
| rs10065172 | |||||||||||
| Moon, 2013 | Asian | rs4958847 | CD and UC separately | CD: 253 | CD:60.9 | CD:25.9±10.4 at diagnosis | 520 | 56.5 | 39.3±15.8 | Age and sex | |
| rs10065172 | UC: 257 | UC:50.6 | UC:37.1±12.4 at diagnosis | ||||||||
Table 1. Characteristics of Studies Included in the Meta-analysis.
Quantitative synthesis
Crohn’s disease.
The relevant studies included 38369 individuals (13043 cases and 25326 controls) for rs13361189 variant, 34397 individuals (10924 cases and 23473 controls) for rs4958847 variant, and 16972 individuals (6766 cases and 10206 controls) for rs10065172 variant. We observed a wide spectrum of the rs13361189 C allele and rs4958847 A allele frequencies across different ethnicities. Compared with Europeans controls (8.32%, 95% CI=7.07-9.58), Asian controls carried a higher frequency (35.37%, 95%CI= 31.13-39.60; p=2.5×10-13) of rs13361189 C allele. Similar result was observed in rs4958847 (p=1.8×10-10). For rs10065172 variant, as only one study carried out in Asians was included, one sample T-test was used to compare the differences of allele frequencies between Asian and European controls (p=9.9×10-7). (Figure 2)
Each data point represents a separate study for the indicated association. Horizontal line represents the mean value.
Table 2 showed the meta-analysis results of the association between the allele contrast and genetic models of the different gene polymorphisms and the risk of CD. Significantly elevated CD risk was associated with rs13361189, rs4958847 or rs10065172 for the allele contrast. (OR=1.306 (1.200-1.420), p=5.2×10-10, OR=1.182 (1.082-1.290), p=0.0002 and OR=1.248 (1.057-1.473), p=0.009 respectively, significant even after Bonferroni correction). Moreover, significant correlation was also found in the three polymorphisms under other genetic models (homozygote, heterozygote, dominant and recessive models). (Table 2, Figure 3)
| Variant | Comparison | Variables | Data NO. | Sameple Size | Test of association | Model | Test of heterogeneity | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Case | Control | OR (95% CI) | P-value | I2 (%) P-value | |||||||
| rs13361189 | C vs T | Overall | 18 | 13043 | 25326 | 1.306 (1.200-1.420) | 5.2×10-10* | R | 55.5 | 0.002 | |
| Europeans | 13 | 11806 | 24118 | 1.396 (1.314-1.483) | 4.2×10-27* | F | 35.2 | 0.101 | |||
| Asians | 3 | 868 | 854 | 1.084 (0.942-1.248) | 0.26 | F | 0.00 | 0.984 | |||
| All in HWE | 15 | 9483 | 11364 | 1.300(1.169-1.446) | 1.4×10-6* | R | 62.5 | 0.001 | |||
| CC vs TT | Overall | 17 | 12413 | 22043 | 1.565 (1.218-2.010) | 0.0004* | R | 38.7 | 0.053 | ||
| Europeans | 12 | 11176 | 20835 | 2.042 (1.581-2.638) | 4.6×10-8* | F | 11.1 | 0.336 | |||
| Asians | 3 | 868 | 854 | 1.064 (0.781-1.450) | 0.695 | F | 0.00 | 0.763 | |||
| All in HWE | 15 | 9483 | 11364 | 1.636 (1.220-2.193) | 0.001* | R | 45.8 | 0.027 | |||
| CT vs TT | Overall | 17 | 12413 | 22043 | 1.360 (1.279-1.448) | 2.8×10-22* | F | 27.8 | 0.138 | ||
| Europeans | 12 | 11176 | 20835 | 1.390 (1.298-1.488) | 3.2×10-21* | F | 21.5 | 0.232 | |||
| Asians | 3 | 868 | 854 | 1.239 (1.010-1.520) | 0.040 | F | 0.00 | 0.550 | |||
| All in HWE | 15 | 9483 | 11364 | 1.320 (1.198-1.454) | 1.9×10-8* | R | 34.9 | 0.090 | |||
| CC+CT vs TT | Overall | 17 | 12413 | 22043 | 1.362 (1.255-1.479) | 1.3×10-13* | R | 37.3 | 0.061 | ||
| Europeans | 12 | 11176 | 20835 | 1.421 (1.329-1.519) | 5.0×10-25* | F | 29.7 | 0.155 | |||
| Asians | 3 | 868 | 854 | 1.199 (0.987-1.455) | 0.068 | F | 0.00 | 0.816 | |||
| All in HWE | 15 | 9483 | 11364 | 1.345 (1.214-1.489) | 1.3×10-8* | R | 44.6 | 0.032 | |||
| CC vs CT+TT | Overall | 17 | 12413 | 22043 | 1.448 (1.129-1.856) | 0.004* | R | 41.5 | 0.038 | ||
| Europeans | 12 | 11176 | 20835 | 1.919 (1.486-2.447) | 5.7×10-7* | F | 9.40 | 0.353 | |||
| Asians | 3 | 868 | 854 | 0.941 (0.705-1.256) | 0.682 | F | 0.00 | 0.478 | |||
| All in HWE | 15 | 9483 | 11364 | 1.506 (1.128-2.012) | 0.006* | R | 48.3 | 0.019 | |||
| rs4958847 | A vs G | Overall | 14 | 9854 | 21892 | 1.182 (1.082-1.290) | 0.0002* | R | 66.6 | 0.0002 | |
| Europeans | 11 | 9016 | 21068 | 1.228 (1.117-1.349) | 0.00002* | R | 64.0 | 0.002 | |||
| Asians | 2 | 737 | 970 | 1.062(0.925-1.220) | 0.395 | F | 33.6 | 0.220 | |||
| All in HWE | 11 | 7578 | 19398 | 1.195 (1.076-1.328) | 0.001* | R | 72.1 | 0.00009 | |||
| AA vs GG | Overall | 13 | 9224 | 18609 | 1.312 (1.045-1.647) | 0.019 | R | 55.7 | 0.008 | ||
| Europeans | 10 | 8386 | 17785 | 1.449 (1.084-1.936) | 0.012* | R | 55.6 | 0.016 | |||
| Asians | 2 | 737 | 970 | 1.120 (0.844-1.485) | 0.434 | F | 24.2 | 0.251 | |||
| All in HWE | 11 | 7578 | 19398 | 1.373 (1.057-1.783) | 0.017 | R | 61.6 | 0.004 | |||
| AG vs GG | Overall | 13 | 9224 | 18609 | 1.205 (1.097-1.323) | 0.0001* | R | 51.2 | 0.017 | ||
| Europeans | 10 | 8386 | 17785 | 1.251 (1.138-1.376) | 3.8×10-6* | R | 49.5 | 0.037 | |||
| Asians | 2 | 737 | 970 | 0.986 (0.766-1.268) | 0.911 | F | 0.00 | 0.426 | |||
| All in HWE | 11 | 7578 | 19398 | 1.192 (1.071-1.326) | 0.001* | R | 54.6 | 0.015 | |||
| AA+AG vs GG | Overall | 13 | 9224 | 18609 | 1.220 (1.106-1.347) | 0.00007* | R | 59.1 | 0.004 | ||
| Europeans | 10 | 8386 | 17785 | 1.269 (1.147-1.403) | 3.6×10-6* | R | 58.1 | 0.011 | |||
| Asians | 2 | 737 | 970 | 1.028 (0.810-1.304) | 0.820 | F | 12.9 | 0.284 | |||
| All in HWE | 11 | 7578 | 19398 | 1.216 (1.085-1.363) | 0.001* | R | 63.4 | 0.002 | |||
| AA vs AG+GG | Overall | 13 | 9224 | 18609 | 1.248 (1.028-1.515) | 0.025 | R | 48.7 | 0.025 | ||
| Europeans | 10 | 8386 | 17785 | 1.367 (1.037-1.802) | 0.026 | R | 51.7 | 0.028 | |||
| Asians | 2 | 737 | 970 | 1.132 (0.912-1.406) | 0.260 | F | 0.00 | 0.402 | |||
| All in HWE | 11 | 7578 | 19398 | 1.300 (1.043-1.619) | 0.019 | R | 55.1 | 0.014 | |||
| rs10065172 | T vs C | Overall | 8 | 5407 | 8435 | 1.248 (1.057-1.473) | 0.009* | R | 79.4 | 0.00002 | |
| Europeans | 6 | 5053 | 8081 | 1.284 (1.055-1.564) | 0.013 | R | 80.3 | 0.0001 | |||
| TT vs CC | Overall | 7 | 4777 | 5152 | 1.543 (1.078-2.207) | 0.018 | R | 48.9 | 0.068 | ||
| Europeans | 5 | 4423 | 4798 | 1.717 (1.197-2.464) | 0.003* | F | 12.6 | 0.334 | |||
| TC vs CC | Overall | 7 | 4777 | 5152 | 1.244 (1.012-1.530) | 0.038 | R | 78.3 | 0.0001 | ||
| Europeans | 5 | 4423 | 4798 | 1.271 (0.988-1.636) | 0.062 | R | 83.2 | 0.00009 | |||
| TT+TC vs CC | Overall | 7 | 4777 | 5152 | 1.273 (1.030-1.573) | 0.025 | R | 80.6 | 0.00003 | ||
| Europeans | 5 | 4423 | 4798 | 1.298 (1.008-1.673) | 0.043 | R | 84.1 | 0.00004 | |||
| TT vs TC+CC | Overall | 7 | 4777 | 5152 | 1.335 (1.078-1.653) | 0.008* | F | 33.4 | 0.173 | ||
| Europeans | 5 | 4423 | 4798 | 1.668 (1.162-2.393) | 0.006* | F | 0.00 | 0.463 | |||
Table 2. Pooled analysis for the associations between the polymorphism of IRGM and the risk of Crohn’s disease.
The sizes of the squares reflect the weighting of included studies; the centre of diamonds reflect summary effect, the left and right extremes of diamonds reflect 95% confidence intervals; CI, confidence interval; OR, odds ratio.
In the subgroup analysis by ethnicity, for rs13361189 T>C, significantly increased CD risk was found among European populations in the allelic and all genetic models. (CC+CT vs TT: OR=1.421 (1.329-1.519), p=5.0×10-25, significant after Bonferroni correction) However, these associations were not observed in the Asian populations (CC+CT vs TT: OR=1.199 (0.987-1.455), p=0.068). Similarly, statistical association was observed between rs4958847 or rs10065172 variant and CD risk among European population. (AA+AG vs GG: OR=1.269 (1.147-1.403), p=3.6×10-6, still significant after Bonferroni correction) and TT+TC vs TT: OR=1.298 (1.008-1.673), p=0.043, non-significant after Bonferroni correction) In addition, the OR for rs13361189 T>C was 1.565 (1.218-2.010) in carriers of two risk C alleles compared with non-risk allele carriers (CC vs TT), which was higher than the risk of one T allele carriers (CT vs TT, OR= 1.360 (1.279-1.448)), suggesting a dose–response with increasing number of the variant allele. The same pattern was seen for either rs4958847 or rs10065172 variant.
Ulcerative colitis.
Meta-analysis findings of associations between rs13361189 and rs4958847 in the IRGM gene and the risk of UC were shown in Table 3. A total of 4847 (5029) UC patients and 6473 (7202) controls for rs13361189 (rs4958847) polymorphism were investigated. No significant association was observed between the polymorphism of rs13361189 and the risk of UC in all comparisons (C vs T: OR=1.088 (0.989-1.198); p=0.083, CC vs TT: OR=1.428 (0.959-2.126), p=0.079; CT vs TT: OR=1.062 (0.955-1.180), p=0.266; dominant model: OR=1.079 (0.973-1.197), p=0.149; and recessive model: OR=1.395 (0.938-2.075), p=0.100.) (Figure S1) Similarly, for rs4955847 variant and UC risk, no obvious association was observed in allelic and genetic models. (Figure S1, Table 3)
| Variant | Comparison | Ethnicity | Data NO. | Sample Size | Test of association | Model | Test of heterogeneity | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Case | Control | OR (95% CI) | P-value | I2 P-value | |||||||
| rs13361189 | C vs T | Overall (Europeans) | 8 | 4564 | 5512 | 1.088 (0.989-1.198) | 0.083 | F | 0.00 | 0.462 | |
| CC vs TT | Overall (Europeans) | 8 | 4564 | 5512 | 1.428 (0.959-2.126) | 0.079 | F | 5.90 | 0.385 | ||
| CT vs TT | Overall (Europeans) | 8 | 4564 | 5512 | 1.062 (0.955-1.180) | 0.266 | F | 0.00 | 0.459 | ||
| CC+CT vs TT | Overall (Europeans) | 8 | 4564 | 5512 | 1.079 (0.973-1.197) | 0.149 | F | 0.00 | 0.456 | ||
| CC vs CT+TT | Overall (Europeans) | 8 | 4564 | 5512 | 1.395 (0.938-2.075) | 0.100 | F | 7.60 | 0.372 | ||
| rs4958847 | A vs G | Overall | 8 | 4489 | 5621 | 1.031 (0.955-1.112) | 0.438 | F | 0.50 | 0.425 | |
| Europeans | 7 | 4232 | 5101 | 1.023 (0.943-1.109) | 0.590 | F | 11.3 | 0.343 | |||
| All in HWE | 7 | 4197 | 5113 | 1.028 (0.950-1.112) | 0.491 | F | 13.9 | 0.324 | |||
| AA vs GG | Overall | 8 | 4489 | 5621 | 1.195 (0.937-1.525) | 0.151 | F | 0.00 | 0.863 | ||
| Europeans | 7 | 4232 | 5101 | 1.142 (0.860-1.518) | 0.359 | F | 0.00 | 0.821 | |||
| All in HWE | 7 | 4197 | 5113 | 1.250 (0.973-1.607) | 0.081 | F | 0.00 | 0.975 | |||
| AG vs GG | Overall | 8 | 4489 | 5621 | 1.075 (0.921-1.254) | 0.361 | R | 59.9 | 0.015 | ||
| Europeans | 7 | 4232 | 5101 | 1.039 (0.894-1.208) | 0.621 | R | 56.7 | 0.031 | |||
| All in HWE | 7 | 4197 | 5113 | 1.057 (0.895-1.248) | 0.514 | R | 62.7 | 0.013 | |||
| AA+AG vs GG | Overall | 8 | 4489 | 5621 | 1.066 (0.935-1.215) | 0.343 | R | 48.0 | 0.062 | ||
| Europeans | 7 | 4232 | 5101 | 1.015 (0.927-1.111) | 0.751 | F | 43.6 | 0.100 | |||
| All in HWE | 7 | 4197 | 5113 | 1.058 (0.916-1.222) | 0.446 | R | 53.6 | 0.044 | |||
| AA vs AG+GG | Overall | 8 | 4489 | 5621 | 1.053 (0.852-1.302) | 0.631 | F | 0.00 | 0.747 | ||
| Europeans | 7 | 4232 | 5101 | 1.137 (0.857-1.508) | 0.375 | F | 0.00 | 0.727 | |||
| All in HWE | 7 | 4197 | 5113 | 1.086 (0.875-1.348) | 0.445 | F | 0.00 | 0.848 | |||
Table 3. Pooled analysis for the associations between the polymorphisms of IRGM and the risk of ulcerative colitis.
Test of heterogeneity
There was significant heterogeneity in most comparisons of three IRGM SNPs in the total analysis of CD. (Table 2) Then meta-regression was carried out to assess the source of heterogeneity for dominant model comparison by year of publication, ethnicity and sample size (individuals more than 500 in both cases and controls). The results showed that ethnicity could explain 41.37% and 19.77% of the τ2 in rs13361189 and rs4958847 variants, respectively. Moreover, sample size could explain 63.28% of τ2 under dominant model in rs13361189 variant. However, for rs10065172 variant, meta-regression analyses did not show any sources that contribute to the substantial heterogeneity.
Sensitivity analyses and cumulative meta-analysis
Sensitivity analyses indicated that the pooled ORs were consistently significant in CD by omitting one study at a time, suggesting robustness of our results. (Figure 4, Figure S2) Although there were two studies (18,21) which deviated from HWE, the corresponding pooled ORs were not materially altered with or without including these two studies in all comparisons. (Table 2, 3)
Results were computed by omitting each study (left column) in turn, Bars: 95% confidence interval.
In addition, sensitivity analyses showed that three independent studies [19,21,32] were the potential origin of heterogeneity in association between rs13361189 variant and CD risk. The heterogeneity was effectively removed by exclusion of these four studies (C vs T: Ph=0.121, CC vs TT: Ph=0.190, CT vs TT: Ph=0.700, CC+CT vs TT: Ph=0.595, and CC vs CT+TT: Ph=0.145). For rs4958847 variant, three studies [20,32,33] were responsible for the heterogeneity. The Q-test of heterogeneity was decreased or removed after exclusion of three studies: A vs G: Ph=0.086, AA vs GG: Ph=0.283, AG vs GG: Ph=0.315, AA+AG vs GG: Ph=0.259, and AA vs AG+GG: Ph=0.409. Two studies [20,33] were the possible sources of heterogeneity of rs10065172, when excluding, the heterogeneity was removed. (T vs C: Ph=0.596, TT vs CC: Ph=0.930, TC vs CC: Ph=0.677, TT+TC vs CC: Ph=0.727, TT vs TC+CC: Ph=0.810)
In the cumulative meta-analysis, the pooled ORs tended to be stable and the associations tended toward significant with accumulation of more data over time between rs13361189, rs4958847 or rs10065172 polymorphism and CD risk. (Figure 5) However, Figure S3 presented that the associations remained non-significant with accumulation of more data over time in rs13361189 or rs4958847 variant and risk of UC.
Publication bias
Funnel plots and Egger’s test were performed to assess publication bias. The shapes of the funnel plots did not reveal evidence of obvious asymmetry in all comparison models. Then, the Egger’s test was used to provide statistical evidence of funnel plot symmetry. Egger’s test did not show any evidence of publication bias of rs13361189 variant (P=0.237 for CC+CT vs TT in CD, P=0.631 for CC+CT vs TT in UC), rs4958847 variant (P=0.278 for AA+AG vs GG in CD, P=0.108 for AA+AG vs GG in UC), or rs10065172 variant (P=0.479 for TT+TC vs CC in CD). Figure S4 and Figure S5 showed the funnel plots of dominant models in the three IRGM SNPs.
Discussion
IRGM gene, located on chromosome 5q33.1, plays an important role in autophagy. Autophagy has a central function in physiological and pathological processes, involving in innate and adaptive immunity by delivering intracellular pathogens and other antigens. Singh et al demonstrated that IRGM can induce autophagy to eliminate intracellular mycobacterium tuberculosis [41]. Moreover, IRGM 1 -deficient mice have a reduced defense against intracellular pathogens such as Toxoplasma gondii and Listeria monocytogenes [42]. The presence of bacterial flora is essential for IBD formation in animal models [43]. In addition, autophagy plays an important role in the elimination of apoptotic bodies, and the failure of which might contribute to persistent inflammation in CD [44]. In the recent GWAS meta-analysis, Frank provided strong evidence for the association between IRGM rs7714584 and the risk of IBD (P<10-8, meeting genome-wide significance). Parkes et al [18] found two immediately flanking IRGM variants (rs13361189 and rs4958847) associated with CD in two different British cohorts. Thus, IRGM may appear to be a good candidate for IBD. However, the results of associations between three IRGM variants (rs13361189, rs4958847 and rs10065172) and risk of IBD were contradictory. Therefore, we saw the need to perform pooled analyses with larger sample size by summarizing previous case-control studies in order to understand the association between IRGM variants and IBD risk better.
Our meta-analysis showed significant susceptibility of CD from rs13361189 in the overall population in all genetic contrasts. When stratified by ethnicity, a significant association with rs13361189 was observed in European population, but not in Asians. Similar results were also found between the rs4958847 or rs10065172 variant and risk of CD in overall and European population. It is widely accepted that genetic markers in predisposition to IBD vary across ethnic groups. For instance, nucleotide oligomerization domain 2 (NOD2) polymorphisms have been strongly association with CD in Europeans [45,46], but not in Asian population [47-49]. These results suggested that rs13361189 and rs4958847 variants might be ethnic population-specific risk factors for CD. However, the lack of association in the Asian population from this study might not be very conclusive owing to the relatively small number of Asian populations used in the analysis (only 2 studies for rs4955847 and 3 studies for rs13361189 in Asian population). Therefore, further studies in Asian populations with larger sample sizes might need to be performed to clarify possible roles of IRGM polymorphisms in CD. Since these SNPs are close to each other, we used 1000 Genomes Pilot sequence data to identify whether these SNPs were in linkage disequilibrium (LD) (r2>0.8). The results showed that rs13361189 was in perfect LD with 2 other IRGM SNPs (rs10065172 and rs1000113, r2=1.000) in Europeans. However, rs4958847 was not in LD with 3 other IRGM SNPs (rs13361189, rs10065172 and rs1000113, r2=0.304).
Overall, no significant association between rs13361189 or rs4958847variant and susceptibility to UC was found in this meta-analysis in any genetic model. To date, there was lack of association of these two SNPs with UC in all the individual studies. Recently, twin studies and familial clustering of cases suggested that genetic factors were likely to play a more prominent role in CD than in UC [3]. This observation was also supported by the finding that both NOD2 and ATG16L1 were associated with CD, but not with UC [50,51].
Heterogeneity was significant for the most comparisons of rs13361189 polymorphism in overall population. To identify the source of heterogeneity, meta-regression and subgroup analysis were carried out. We found that ethnicity was identified as a potential source of between-study heterogeneity. Meta-regression indicated that ethnicity could explain 41.37% of τ2. Moreover, the heterogeneity was remarkably decreased among Asian and European population, (CC vs TT: P=0.763, P=0.336, respectively), which may be attributed that IBD is a complex disease and different genetic backgrounds or different environments existed among different ethnicities. Moreover, the sample size could explain 63.28% of τ2 under dominant model. In addition, the pooled OR did not change in the sensitivity analysis by excluding studies departed from HWE.
Our meta-analysis significantly increased statistical power by pooling data from different studies, while several limitations should be considered in the present meta-analysis. First, only 2 and 3 studies were performed in Asians for rs4955847 and rs13361189 variants, respectively. Therefore validation of association is required in other population. Second, significant heterogeneity between studies was detected in the current meta-analysis, whereas difference in ethnicity was identified as potential sources of heterogeneity. Third, gene–environment and gene-gene interactions were not analyzed because of insufficient data.
In conclusion, despite these limitations, our meta-analysis still yields statistically significant results. The present data synthesis indicated that rs13361189, rs4958847 and rs10065172 were considered to be risk factors of CD in Europeans but not of UC. In addition, subgroups analysis suggested that this increased risk may be ethno-specific. Further studies in other ethnic groups (e.g. Asians and Africans) are needed to clarify possible roles of IRGM polymorphisms in CD or UC. To identify the exact role of IRGM polymorphisms in the pathogenesis of CD, more studies such as animal disease modeling are of great importance.
Supporting Information
Figure S1.
OR estimates with the corresponding 95% CI for the associations between IRGM polymorphisms ((A) rs13361189 and (B) rs4958847) and the risk of UC (dominate model).
https://doi.org/10.1371/journal.pone.0080602.s002
(TIF)
Figure S2.
Sensitivity analysis on the associations between IRGM polymorphisms ((A) rs13361189 and (B) rs4958847) and UC risk (dominate model).
https://doi.org/10.1371/journal.pone.0080602.s003
(TIF)
Figure S3.
Cumulative meta-analysis: pooled OR with the corresponding 95% CI at the end of each year information step is shown for IRGM polymorphisms ((A) rs13361189 and (B) rs4958847) and risk of UC (dominate model).
https://doi.org/10.1371/journal.pone.0080602.s004
(TIF)
Figure S4.
Funnel plots of the association between IRGM polymorphisms ((A) rs13361189, (B) rs4958847, and (C) rs10065172) and CD risk (dominant model).
https://doi.org/10.1371/journal.pone.0080602.s005
(TIF)
Figure S5.
Funnel plots of the association between IRGM polymorphisms ((A) rs13361189 and (B) rs4958847) and UC risk (dominate model).
https://doi.org/10.1371/journal.pone.0080602.s006
(TIF)
Author Contributions
Conceived and designed the experiments: XL YT. Performed the experiments: XL XW PZ. Analyzed the data: XL JZ. Contributed reagents/materials/analysis tools: Xl YT CW. Wrote the manuscript: XL LL.
References
- 1. Abraham C, Cho JH (2009) Inflammatory bowel disease. N Engl J Med 361: 2066-2078. doi:https://doi.org/10.1056/NEJMra0804647. PubMed: 19923578.
- 2. Hancock L, Beckly J, Geremia A, Cooney R, Cummings F et al. (2008) Clinical and molecular characteristics of isolated colonic Crohn's disease. Inflamm Bowel Dis 14: 1667-1677. PubMed: 18521924.
- 3. Cho JH, Weaver CT (2007) The genetics of inflammatory bowel disease. Gastroenterology 133: 1327-1339. doi:https://doi.org/10.1053/j.gastro.2007.08.032. PubMed: 17919503.
- 4. Scharl M, Mwinyi J, Fischbeck A, Leucht K, Eloranta JJ et al. (2012) Crohn's disease-associated polymorphism within the PTPN2 gene affects muramyl-dipeptide-induced cytokine secretion and autophagy. Inflamm Bowel Dis 18: 900-912. doi:https://doi.org/10.1002/ibd.21913. PubMed: 22021207.
- 5. Xue LN, Xu KQ, Zhang W, Wang Q, Wu J et al. (2013) Associations between vitamin D receptor polymorphisms and susceptibility to ulcerative colitis and Crohn's disease: a meta-analysis. Inflamm Bowel Dis 19: 54-60. doi:https://doi.org/10.1002/ibd.22966. PubMed: 22467262.
- 6. Glas J, Seiderer J, Wagner J, Olszak T, Fries C et al. (2012) Analysis of IL12B gene variants in inflammatory bowel disease. PLOS ONE 7: e34349. doi:https://doi.org/10.1371/journal.pone.0034349. PubMed: 22479607.
- 7. Fransen K, Mitrovic M, van Diemen CC, Thelma BK, Sood A et al. (2012) Limited evidence for parent-of-origin effects in inflammatory bowel disease associated loci. PLOS ONE 7: e45287. doi:https://doi.org/10.1371/journal.pone.0045287. PubMed: 23028907.
- 8. Glas J, Wagner J, Seiderer J, Olszak T, Wetzke M et al. (2012) PTPN2 gene variants are associated with susceptibility to both Crohn's disease and ulcerative colitis supporting a common genetic disease background. PLOS ONE 7: e33682. doi:https://doi.org/10.1371/journal.pone.0033682. PubMed: 22457781.
- 9. Zhang ZF, Yang N, Zhao G, Zhu L, Wang LX (2012) Association between the Pro12Ala polymorphism of peroxisome proliferator-activated receptor gamma 2 and inflammatory bowel disease: a meta-analysis. PLOS ONE 7: e30551.
- 10. Márquez A, Núñez C, Martínez A, Mendoza JL, Taxonera C et al. (2009) Role of ATG16L1 Thr300Ala polymorphism in inflammatory bowel disease: a Study in the Spanish population and a meta-analysis. Inflamm Bowel Dis 15: 1697-1704. doi:https://doi.org/10.1002/ibd.21001. PubMed: 19575361.
- 11. Fowler EV, Doecke J, Simms LA, Zhao ZZ, Webb PM et al. (2008) ATG16L1 T300A shows strong associations with disease subgroups in a large Australian IBD population: further support for significant disease heterogeneity. Am J Gastroenterol 103: 2519-2526. PubMed: 18671817.
- 12. Franke A, Balschun T, Karlsen TH, Hedderich J, May S et al. (2008) Replication of signals from recent studies of Crohn's disease identifies previously unknown disease loci for ulcerative colitis. Nat Genet 40: 713-715. doi:https://doi.org/10.1038/ng.148. PubMed: 18438405.
- 13. Fritz T, Niederreiter L, Adolph T, Blumberg RS, Kaser A (2011) Crohn's disease: NOD2, autophagy and ER stress converge. Gut 60: 1580-1588. doi:https://doi.org/10.1136/gut.2009.206466. PubMed: 21252204.
- 14. Xavier RJ, Huett A, Rioux JD (2008) Autophagy as an important process in gut homeostasis and Crohn's disease pathogenesis. Gut 57: 717-720. doi:https://doi.org/10.1136/gut.2007.134254. PubMed: 18272545.
- 15. Latiano A, Palmieri O, Cucchiara S, Castro M, D’Incà R et al. (2009) Polymorphism of the IRGM gene might predispose to fistulizing behavior in Crohn's disease. Am J Gastroenterol 104: 110-116. doi:https://doi.org/10.1038/ajg.2008.3. PubMed: 19098858.
- 16. Meggyesi N, Kiss LS, Koszarska M, Bortlik M, Duricova D et al. (2010) NKX2-3 and IRGM variants are associated with disease susceptibility to IBD in Eastern European patients. World J Gastroenterol 16: 5233-5240. doi:https://doi.org/10.3748/wjg.v16.i41.5233. PubMed: 21049557.
- 17. Palomino-Morales RJ, Oliver J, Gómez-García M, López-Nevot MA, Rodrigo L et al. (2009) Association of ATG16L1 and IRGM genes polymorphisms with inflammatory bowel disease: a meta-analysis approach. Genes Immun 10: 356-364. doi:https://doi.org/10.1038/gene.2009.25. PubMed: 19491842.
- 18. Parkes M, Barrett JC, Prescott NJ, Tremelling M, Anderson CA et al. (2007) Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn's disease susceptibility. Nat Genet 39: 830-832. doi:https://doi.org/10.1038/ng2061. PubMed: 17554261.
- 19. Prescott NJ, Dominy KM, Kubo M, Lewis CM, Fisher SA et al. (2010) Independent and population-specific association of risk variants at the IRGM locus with Crohn's disease. Hum Mol Genet 19: 1828-1839. doi:https://doi.org/10.1093/hmg/ddq041. PubMed: 20106866.
- 20. Wang MH, Okazaki T, Kugathasan S, Cho JH, Isaacs KL et al. (2012) Contribution of higher risk genes and European admixture to Crohn's disease in African Americans. Inflamm Bowel Dis 18: 2277-2287. doi:https://doi.org/10.1002/ibd.22931. PubMed: 22411504.
- 21. Prager M, Büttner J, Haas V, Baumgart DC, Sturm A et al. (2012) The JAK2 variant rs10758669 in Crohn's disease: altering the intestinal barrier as one mechanism of action. Int J Colorectal Dis 27: 565-573. doi:https://doi.org/10.1007/s00384-011-1345-y. PubMed: 22065112.
- 22. Trikalinos TA, Salanti G, Zintzaras E, Ioannidis JP (2008) Meta-analysis methods. Adv Genet 60: 311-334. doi:https://doi.org/10.1016/S0065-2660(07)00413-0. PubMed: 18358326.
- 23. DerSimonian R, Laird N (1986) Meta-analysis in clinical trials. Control Clin Trials 7: 177-188. doi:https://doi.org/10.1016/0197-2456(86)90046-2. PubMed: 3802833.
- 24. Zintzaras E, Lau J (2008) Synthesis of genetic association studies for pertinent gene-disease associations requires appropriate methodological and statistical approaches. J Clin Epidemiol 61: 634-645. doi:https://doi.org/10.1016/j.jclinepi.2007.12.011. PubMed: 18538260.
- 25. Egger M, Davey Smith G, Schneider M, Minder C (1997) Bias in meta-analysis detected by a simple, graphical test. BMJ 315: 629-634. doi:https://doi.org/10.1136/bmj.315.7109.629. PubMed: 9310563.
- 26. Amre DK, Mack DR, Morgan K, Krupoves A, Costea I et al. (2009) Autophagy gene ATG16L1 but not IRGM is associated with Crohn's disease in Canadian children. Inflamm Bowel Dis 15: 501-507. doi:https://doi.org/10.1002/ibd.20785. PubMed: 18985712.
- 27. Durães C, Machado JC, Portela F, Rodrigues S, Lago P et al. (2013) Phenotype-genotype profiles in Crohn's disease predicted by genetic markers in autophagy-related genes (GOIA study II). Inflamm Bowel Dis 19: 230-239. doi:https://doi.org/10.1002/ibd.23007. PubMed: 22573572.
- 28. Eglinton TW, Roberts R, Pearson J, Barclay M, Merriman TR et al. (2012) Clinical and genetic risk factors for perianal Crohn's disease in a population-based cohort. Am J Gastroenterol 107: 589-596. doi:https://doi.org/10.1038/ajg.2011.437. PubMed: 22158027.
- 29. Glas J, Seiderer J, Bues S, Stallhofer J, Fries C et al. (2013) IRGM variants and susceptibility to inflammatory bowel disease in the German population. PLOS ONE 8: e54338. doi:https://doi.org/10.1371/journal.pone.0054338. PubMed: 23365659.
- 30. Van Limbergen J, Russell RK, Nimmo ER, Drummond HE, G D et al. (2009) Germline variants of IRGM in childhood-onset Crohn's disease. Gut 58: 610-611. doi:https://doi.org/10.1136/gut.2008.160721. PubMed: 19299395.
- 31. Weersma RK, Stokkers PC, Cleynen I, Wolfkamp SC, Henckaerts L et al. (2009) Confirmation of multiple Crohn's disease susceptibility loci in a large Dutch-Belgian cohort. Am J Gastroenterol 104: 630-638. doi:https://doi.org/10.1038/ajg.2008.112. PubMed: 19174780.
- 32. Wolfkamp SC, Te Velde AA, Weersma RK, Ponsioen CY, Stokkers PC (2010) Is there a role for Crohn's disease-associated autophagy genes ATG16L1 and IRGM in formation of granulomas? Eur J Gastroenterol Hepatol 22: 933-937. doi:https://doi.org/10.1097/MEG.0b013e32833775e6. PubMed: 20395867.
- 33. Dema B, Fernández-Arquero M, Maluenda C, Polanco I, Figueredo MA et al. (2009) Lack of association of NKX2-3, IRGM, and ATG16L1 inflammatory bowel disease susceptibility variants with celiac disease. Hum Immunol 70: 946-949. doi:https://doi.org/10.1016/j.humimm.2009.08.004. PubMed: 19683022.
- 34. Fisher SA, Tremelling M, Anderson CA, Gwilliam R, Bumpstead S et al. (2008) Genetic determinants of ulcerative colitis include the ECM1 locus and five loci implicated in Crohn's disease. Nat Genet 40: 710-712. doi:https://doi.org/10.1038/ng.145. PubMed: 18438406.
- 35. Roberts RL, Hollis-Moffatt JE, Gearry RB, Kennedy MA, Barclay ML et al. (2008) Confirmation of association of IRGM and NCF4 with ileal Crohn's disease in a population-based cohort. Genes Immun 9: 561-565. doi:https://doi.org/10.1038/gene.2008.49. PubMed: 18580884.
- 36. Moon CM, Shin DJ, Kim SW, Son NH, Park A et al. (2013) Associations between genetic variants in the IRGM gene and inflammatory bowel diseases in the Korean population. Inflamm Bowel Dis 19: 106-114. doi:https://doi.org/10.1002/ibd.22972. PubMed: 22508677.
- 37. Yamazaki K, Takahashi A, Takazoe M, Kubo M, Onouchi Y et al. (2009) Positive association of genetic variants in the upstream region of NKX2-3 with Crohn's disease in Japanese patients. Gut 58: 228-232. doi:https://doi.org/10.1136/gut.2007.140764. PubMed: 18936107.
- 38. Pang Z, Zheng LM, Yin SP, Huang FZ, Shi RH (2011) Correlation of NOD2, IRGM, ATG16L1 and STAT4 Gene Polymorphism with Crohn’s Disease in Chinese Han Population. Chin J Gastroenterol 16: 473-477.
- 39. Zheng LM, Pang Z (2012) Association of IRGM and ATG16L1 gene polymorphisms with Crohn’s disease in the Chinese Han population. Chin J Gastroenterol Hepatol 21: 437-440.
- 40. Peter I, Mitchell AA, Ozelius L, Erazo M, Hu J et al. (2011) Evaluation of 22 genetic variants with Crohn's disease risk in the Ashkenazi Jewish population: a case-control study. BMC Med Genet 12: 63. doi:https://doi.org/10.1186/1471-2350-12-63. PubMed: 21548950.
- 41. Singh SB, Davis AS, Taylor GA, Deretic V (2006) Human IRGM induces autophagy to eliminate intracellular mycobacteria. Science 313: 1438-1441. doi:https://doi.org/10.1126/science.1129577. PubMed: 16888103.
- 42. Collazo CM, Yap GS, Sempowski GD, Lusby KC, Tessarollo L et al. (2001) Inactivation of LRG-47 and IRG-47 reveals a family of interferon gamma-inducible genes with essential, pathogen-specific roles in resistance to infection. J Exp Med 194: 181-188. doi:https://doi.org/10.1084/jem.194.2.181. PubMed: 11457893.
- 43. Kühn R, Löhler J, Rennick D, Rajewsky K, Müller W (1993) Interleukin-10-deficient mice develop chronic enterocolitis. Cell 75: 263-274. doi:https://doi.org/10.1016/0092-8674(93)80068-P. PubMed: 8402911.
- 44. Qu X, Zou Z, Sun Q, Luby-Phelps K, Cheng P et al. (2007) Autophagy gene-dependent clearance of apoptotic cells during embryonic development. Cell 128: 931-946. doi:https://doi.org/10.1016/j.cell.2006.12.044. PubMed: 17350577.
- 45. Hugot JP, Chamaillard M, Zouali H, Lesage S, Cézard JP et al. (2001) Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn's disease. Nature 411: 599-603. doi:https://doi.org/10.1038/35079107. PubMed: 11385576.
- 46. Rigoli L, Romano C, Caruso RA, Lo Presti MA, Di Bella C et al. (2008) Clinical significance of NOD2/CARD15 and Toll-like receptor 4 gene single nucleotide polymorphisms in inflammatory bowel disease. World J Gastroenterol 14: 4454-4461. doi:https://doi.org/10.3748/wjg.14.4454. PubMed: 18680223.
- 47. Ng SC, Tsoi KK, Kamm MA, Xia B, Wu J et al. (2012) Genetics of inflammatory bowel disease in Asia: systematic review and meta-analysis. Inflamm Bowel Dis 18: 1164-1176. doi:https://doi.org/10.1002/ibd.21845. PubMed: 21887729.
- 48. Wang ZW, Ji F, Teng WJ, Yuan XG, Ye XM (2011) Risk factors and gene polymorphisms of inflammatory bowel disease in population of Zhejiang, China. World J Gastroenterol 17: 118-122. doi:https://doi.org/10.3748/wjg.v17.i1.118. PubMed: 21218092.
- 49. Yamazaki K, Takazoe M, Tanaka T, Kazumori T, Nakamura Y (2002) Absence of mutation in the NOD2/CARD15 gene among 483 Japanese patients with Crohn's disease. J Hum Genet 47: 469-472. doi:https://doi.org/10.1007/s100380200067. PubMed: 12202985.
- 50. Yazdanyar S, Weischer M, Nordestgaard BG (2009) Genotyping for NOD2 genetic variants and crohn disease: a metaanalysis. Clin Chem 55: 1950-1957. doi:https://doi.org/10.1373/clinchem.2009.127126. PubMed: 19713276.
- 51. Oostenbrug LE, Nolte IM, Oosterom E, van der Steege G, te Meerman GJ et al. (2006) CARD15 in inflammatory bowel disease and Crohn's disease phenotypes: an association study and pooled analysis. Dig Liver Dis 38: 834-845. doi:https://doi.org/10.1016/j.dld.2006.06.042. PubMed: 16920047.