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Li J, Zhang C, Wang JB, Chen SS, Zhang TP, Li S, Pan HF, Ye DQ. Relationship between the IL12B (rs3212227) gene polymorphism and susceptibility to multiple autoimmune diseases: A meta-analysis. Mod Rheumatol 2016; 26:749-56. [PMID: 26915668 DOI: 10.3109/14397595.2016.1157282] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
OBJECTIVES The purpose of this study was to evaluate whether a single-nucleotide polymorphism (SNP) IL12B 3(')UTR +1188A/C (rs3212227) confers susceptibility to several autoimmune diseases. METHODS A systematic literature search was conducted to identify relevant studies. Pooled odds ratio (OR) with 95% confidence interval (CI) was used to estimate the strength of association. RESULTS Twenty-five studies were included in the meta-analysis, which contained 9794 cases and 11,330 controls. Our result indicated that IL12B +1188A/C (rs3212227) polymorphism was associated with type-1 diabetes (T1D) in the dominant model (p = 0.008), and an increased risk was found in East Asians in the dominant model (p < 0.001). East Asians rheumatoid arthritis (RA) patients seemed to be at risk of allelic model (p = 0.011). As to Behcet's disease (BD), there was a risk in dominant model (p = 0.020) and positive associations of dominant model, allelic model in East Asians (p = 0.009; p < 0.001, respectively). But we failed to find any association between IL12B +1188A/C (rs3212227) polymorphism with Graves' disease (GD) and ankylosing spondylitis (AS). CONCLUSIONS The present study suggests that the IL12B +1188A/C (rs3212227) polymorphism might be associated with genetic susceptibility to autoimmune diseases, such as T1D, RA, BD, but not GD and AS.
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Affiliation(s)
- Jun Li
- a Department of Epidemiology and Biostatistics, School of Public Health , Anhui Medical University , Hefei , P.R. China and.,b Anhui Provincial Laboratory of Population Health & Major Disease Screening and Diagnosis , Anhui Medical University , Hefei , P.R. China
| | - Chao Zhang
- a Department of Epidemiology and Biostatistics, School of Public Health , Anhui Medical University , Hefei , P.R. China and.,b Anhui Provincial Laboratory of Population Health & Major Disease Screening and Diagnosis , Anhui Medical University , Hefei , P.R. China
| | - Jie-Bing Wang
- a Department of Epidemiology and Biostatistics, School of Public Health , Anhui Medical University , Hefei , P.R. China and.,b Anhui Provincial Laboratory of Population Health & Major Disease Screening and Diagnosis , Anhui Medical University , Hefei , P.R. China
| | - Shuang-Shuang Chen
- a Department of Epidemiology and Biostatistics, School of Public Health , Anhui Medical University , Hefei , P.R. China and.,b Anhui Provincial Laboratory of Population Health & Major Disease Screening and Diagnosis , Anhui Medical University , Hefei , P.R. China
| | - Tian-Ping Zhang
- a Department of Epidemiology and Biostatistics, School of Public Health , Anhui Medical University , Hefei , P.R. China and.,b Anhui Provincial Laboratory of Population Health & Major Disease Screening and Diagnosis , Anhui Medical University , Hefei , P.R. China
| | - Si Li
- a Department of Epidemiology and Biostatistics, School of Public Health , Anhui Medical University , Hefei , P.R. China and.,b Anhui Provincial Laboratory of Population Health & Major Disease Screening and Diagnosis , Anhui Medical University , Hefei , P.R. China
| | - Hai-Feng Pan
- a Department of Epidemiology and Biostatistics, School of Public Health , Anhui Medical University , Hefei , P.R. China and.,b Anhui Provincial Laboratory of Population Health & Major Disease Screening and Diagnosis , Anhui Medical University , Hefei , P.R. China
| | - Dong-Qing Ye
- a Department of Epidemiology and Biostatistics, School of Public Health , Anhui Medical University , Hefei , P.R. China and.,b Anhui Provincial Laboratory of Population Health & Major Disease Screening and Diagnosis , Anhui Medical University , Hefei , P.R. China
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Tang L, Wang L, Liao Q, Wang Q, Xu L, Bu S, Huang Y, Zhang C, Ye H, Xu X, Liu Q, Ye M, Mai Y, Duan S. Genetic associations with diabetes: meta-analyses of 10 candidate polymorphisms. PLoS One 2013; 8:e70301. [PMID: 23922971 PMCID: PMC3726433 DOI: 10.1371/journal.pone.0070301] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2013] [Accepted: 06/17/2013] [Indexed: 11/19/2022] Open
Abstract
Aims The goal of our study is to investigate the combined contribution of 10 genetic variants to diabetes susceptibility. Methods Bibliographic databases were searched from 1970 to Dec 2012 for studies that reported on genetic association study of diabetes. After a comprehensive filtering procedure, 10 candidate gene variants with informative genotype information were collected for the current meta-anlayses. Using the REVMAN software, odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to evaluate the combined contribution of the selected genetic variants to diabetes. Results A total of 37 articles among 37,033 cases and 54,716 controls were involved in the present meta-analyses of 10 genetic variants. Three variants were found to be significantly associated with type 1 diabetes (T1D): NLRP1 rs12150220 (OR = 0.71, 95% CI = 0.55–0.92, P = 0.01), IL2RA rs11594656 (OR = 0.86, 95% CI = 0.82–0.91, P<0.00001), and CLEC16A rs725613 (OR = 0.71, 95% CI = 0.55–0.92, P = 0.01). APOA5 −1131T/C polymorphism was shown to be significantly associated with of type 2 diabetes (T2D, OR = 1.27, 95% CI = 1.03–1.57, P = 0.03). No association with diabetes was showed in the meta-analyses of other six genetic variants, including SLC2A10 rs2335491, ATF6 rs2070150, KLF11 rs35927125, CASQ1 rs2275703, GNB3 C825T, and IL12B 1188A/C. Conclusion Our results demonstrated that IL2RA rs11594656 and CLEC16A rs725613 are protective factors of T1D, while NLRP1 rs12150220 and APOA5 −1131T/C are risky factors of T1D and T2D, respectively.
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Affiliation(s)
- Linlin Tang
- Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
- The Affiliated Hospital, Ningbo University, Ningbo, Zhejiang, China
| | - Lingyan Wang
- Bank of Blood Products, Ningbo No.2 Hospital, Ningbo, Zhejiang, China
| | - Qi Liao
- Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Qinwen Wang
- Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Leiting Xu
- Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Shizhong Bu
- Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Yi Huang
- Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Cheng Zhang
- Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Huadan Ye
- Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Xuting Xu
- Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Qiong Liu
- Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
| | - Meng Ye
- The Affiliated Hospital, Ningbo University, Ningbo, Zhejiang, China
- * E-mail: (SD); (YM); (MY)
| | - Yifeng Mai
- The Affiliated Hospital, Ningbo University, Ningbo, Zhejiang, China
- * E-mail: (SD); (YM); (MY)
| | - Shiwei Duan
- Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China
- * E-mail: (SD); (YM); (MY)
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van Wanrooij RLJ, Zwiers A, Kraal G, Bouma G. Genetic variations in interleukin-12 related genes in immune-mediated diseases. J Autoimmun 2012; 39:359-68. [PMID: 22819329 DOI: 10.1016/j.jaut.2012.06.002] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2012] [Revised: 06/13/2012] [Accepted: 06/24/2012] [Indexed: 12/20/2022]
Abstract
The interleukin-12 (IL-12) family comprises a group of heterodimeric cytokines and their respective receptors that play key roles in immune responses. A growing number of autoimmune diseases has been found to be associated with genetic variation in these genes. Based on their respective associations with the IL-12 genes, autoimmune diseases appear to cluster in two groups that either show strong associations with the Th1/Th17 pathway (as indicated by genetic association with IL12B and IL23R) or the Th1/IL-35 pathway as the consequence of their association with polymorphisms in the IL12A gene region. The genetic associations are described in relation to what is known of the functionality of these genes in the various diseases. Comparing association data for gene families in different diseases may lead to better insight in the function of the genes in the onset and course of the disease.
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Affiliation(s)
- R L J van Wanrooij
- Department of Gastroenterology and Hepatology, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, The Netherlands.
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Kaas A, Pfleger C, Kharagjitsingh AV, Schloot NC, Hansen L, Buschard K, Koeleman BPC, Roep BO, Mortensen HB, Alizadeh BZ. Association between age, IL-10, IFNγ, stimulated C-peptide and disease progression in children with newly diagnosed Type 1 diabetes. Diabet Med 2012; 29:734-41. [PMID: 22150609 DOI: 10.1111/j.1464-5491.2011.03544.x] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
AIMS The relation of disease progression and age, serum interleukin 10 (IL-10) and interferon gamma (IFNγ) and their genetic correlates were studied in paediatric patients with newly diagnosed Type 1 diabetes. METHODS Two hundred and twenty-seven patients from the Hvidoere Study Group were classified in four different progression groups as assessed by change in stimulated C-peptide from 1 to 6 months. CA repeat variants of the IL-10 and IFNγ gene were genotyped and serum levels of IL-10 and IFNγ were measured at 1, 6 and 12 months. RESULTS IL-10 decreased (P < 0.001) by 7.7% (1 month), 10.4% (6 months) and 8.6% (12 months) per year increase in age of child, while a twofold higher C-peptide concentration at 1 month (p = 0.06), 6 months (P = 0.0003) and 12 months (P = 0.02) was associated with 9.7%, 18.6% and 9.7% lower IL-10 levels, independent of each other. IL-10 concentrations did not associate with the disease progression groups. By contrast, IFNγ concentrations differed between the four progression groups at 6 and 12 months (P = 0.02 and P = 0.01, respectively); patients with rapid progressing disease had the highest levels at both time points. Distribution of IL-10 and IFNγ genotypes was equal among patients from the progression groups. CONCLUSION IL-10 serum levels associate inversely with age and C-peptide. As age and C-peptide also associate, a triangular association is proposed. Genetic influence on IL-10 production seems to be masked by distinct disease mechanisms. Increased serum IFNγ concentrations associate with rapid disease progression. Functional genetic variants do not associate with a single progression pattern group, implying that disease processes override genetically predisposed cytokine production.
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Affiliation(s)
- A Kaas
- Department of Paediatrics, Glostrup Hospital and University of Copenhagen, Denmark
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Morahan G, McKinnon E, Berry J, Browning B, Julier C, Pociot F, James I. Evaluation of IL12B as a candidate type I diabetes susceptibility gene using data from the Type I Diabetes Genetics Consortium. Genes Immun 2009; 10 Suppl 1:S64-8. [PMID: 19956104 PMCID: PMC2805152 DOI: 10.1038/gene.2009.94] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
As part of its efforts to identify genes affecting the risk of type I diabetes (T1D), the Type I Diabetes Genetics Consortium commissioned an extensive survey of variants associated with genes reported earlier to have an association with disease susceptibility. In this report, we present the analysis of a set of single-nucleotide polymorphisms (SNPs) within and flanking the IL12B gene, which encodes the p40 subunit of the cytokines interleukin (IL)-12 and IL-23. No SNP showed individually significant association in the population as a whole. Nevertheless, subjects stratified according to genotype at the earlier reported SNP in the IL12B 3'UTR, rs3212227, confirmed small, but significant, differences in age of disease onset with a relative hazard=0.88 (P=0.005). The protective effect of rs3212227 allele 2 was gender specific (P=0.004 overall and P=0.0003 when unaffected siblings were considered). Among females, the 2.2 genotype was more protective, with relative hazard=0.75. We conclude that while there was no major effect of IL12B polymorphisms on T1D susceptibility in the entire study group, they have an impact on a subset of at-risk individuals.
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Affiliation(s)
- G Morahan
- Centre for Diabetes Research, The Western Australian Institute for Medical Research, and Centre for Medical Research, University of Western Australia, 50 Murray Street, Perth, Western Australia 6000, Australia.
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Abstract
The evidence that there is clinical heterogeneity of type 1 diabetes is reviewed and the implications for genetic studies are discussed. In the past year, genome-wide linkage analysis of 1435 multiplex families was reported. Additionally, confirmed evidence for association of specific markers at two loci (PTPN22, OAS1) as well as failure to replicate three others (IL12B, SUMO4, PAX4) is discussed. Some common themes are identified and suggestions for improvements are made. We look forward to the results from genome-wide association studies.
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Affiliation(s)
- Andrew D Paterson
- Program in Genetics and Genomic Biology, The Hospital for Sick Children, Toronto Medical Discovery East Tower, Toronto, Ontario M5G 1L7, Canada.
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