Large-scale association analysis of TNF/LTA gene region polymorphisms in type 2 diabetes
© Boraska et al; licensee BioMed Central Ltd. 2010
Received: 27 November 2009
Accepted: 6 May 2010
Published: 6 May 2010
The TNF/LTA locus has been a long-standing T2D candidate gene. Several studies have examined association of TNF/LTA SNPs with T2D but the majority have been small-scale and produced no convincing evidence of association. The purpose of this study is to examine T2D association of tag SNPs in the TNF/LTA region capturing the majority of common variation in a large-scale sample set of UK/Irish origin.
This study comprised a case-control (1520 cases and 2570 control samples) and a family-based component (423 parent-offspring trios). Eleven tag SNPs (rs928815, rs909253, rs746868, rs1041981 (T60N), rs1800750, rs1800629 (G-308A), rs361525 (G-238A), rs3093662, rs3093664, rs3093665, and rs3093668) were selected across the TNF/LTA locus and genotyped using a fluorescence-based competitive allele specific assay. Quality control of the obtained genotypes was performed prior to single- and multi-point association analyses under the additive model.
We did not find any consistent SNP associations with T2D in the case-control or family-based datasets.
The present study, designed to analyse a set of tag SNPs specifically selected to capture the majority of common variation in the TNF/LTA gene region, found no robust evidence for association with T2D. To investigate the presence of smaller effects of TNF/LTA gene variation with T2D, a large-scale meta-analysis will be required.
Type 2 diabetes (T2D) is a complex disease influenced by environmental and genetic factors. Genetic association studies have thus far identified at least 20 replicating T2D susceptibility loci of modest to small effect, which together explain less than 10% of the genetic component of disease [1, 2]. Several genome-wide association scans (GWAS) have been carried out for T2D [3–10]. These have used a variety of genotyping platforms with different SNP content, typically capturing over 80% of common variation in European-descent populations. Although this extent of coverage, in combination with imputation approaches , reduces the need for candidate gene studies, in-depth investigation of variation at loci of interest can conceivably prove useful in characterising them further.
The TNF/LTA locus has been a long-standing T2D candidate gene. T2D and obesity have been hypothesised to have an inflammatory basis [12, 13]. Insulin resistance is associated with increased plasma levels of proinflammatory cytokines such as TNF and IL6, and with interactions between TNF and NFkappaB that lead to an increase of oxidative stress [14–16].
The genes coding for TNF and LTA reside in the class III MHC region on chromosome 6p21.3. TNF and LTA are members of the TNF ligand superfamily, bind the same TNF receptors and mediate similar pleiotropic effects [17, 18]. Of the multiple SNPs in the TNF/LTA gene region, the rs361525 (G-238A) and rs1800629 (G-308A) TNF promoter variants, and the rs1041981 (T60N) LTA variant have been the most frequently studied in T2D. The majority of studies of TNF/LTA SNPs have been small-scale, with some notable exceptions , and have produced no convincing evidence for association with the disease [19–27].
The Wellcome Trust Case Control Consortium (WTCCC) T2D GWAS examined 17 directly typed and imputed SNPs from the TNF/LTA gene region and detected no association with T2D in 2000 cases and 3000 controls from the UK [6, 28]. In addition, a GWAS meta-analysis for T2D carried out by the DIAGRAM consortium, which examined the same 17 directly genotyped and imputed SNPs in the TNF/LTA region in samples from three sources (Diabetes Genetics Initiative (DGI), Finland-United States Investigation of NIDDM Genetics (FUSION) and WTCCC) also found no association between TNF/LTA SNPs and T2D . However, the WTCCC genotyping platform (Affymetrix 500k) and HapMap-based imputation do not provide exhaustive coverage of common variation in this gene region. To increase coverage, we carried out a genetic association study of the TNF/LTA loci in a total of 5359 samples from the UK by typing additional SNPs, selected on the basis of sequence data to better capture variation in the region.
Clinical characteristics of T2D cases
Average Age At Study (years)
Average AODc (years)
Average BMI (kg/m2)
SNP Selection and Genotyping
Characteristics of 11 TNF/LTA tag SNPs.
dbSNP rs number
Position on chr. 6a
dbSNP CEU MAFc
252G > A
Thr26Asn;T60N; 804C > A
-376 G > A
5' of TNF
-308 G > A
5' of TNF
-238 G > A
5' of TNF
IVS1-122A > G; +851
TNF - 3'UTR
3' of TNF
Quality control (QC) of the obtained genotypes was performed prior to association analysis. The SNP genotyping success rates ranged from 93.3% to 98.6%. We evaluated the comparative rate of missing genotypes between cases and controls using Plink (version 1.00)  and excluded rs3093662 from the case-control association analysis due to low call rate. The tag SNPs were tested for deviation from Hardy-Weinberg equilibrium (HWE) in affected and healthy individuals separately using Stata v. 8 (Stata Corporation, College Station, TX, USA) and Plink (version 1.00) . No deviations from HWE were observed. Minor allele frequencies (MAFs) of controls in both studies were compared with the National Center for Biotechnology Information SNP database (NCBI dbSNP) MAFs for the CEU population and showed no significant differences. Testing of Mendelian inheritance using Plink and Haploview [36, 37] identified inconsistencies in one family, which was excluded from further analysis. After QC, 10 tag SNPs were taken forward to case-control association analyses and 11 tag SNPs were included in family-based association analysis.
Single-point case-control association analyses were carried out using Stata v. 8 (Stata Corporation, College Station, TX, USA). Multi-point case-control association analyses of fixed haplotype sizes (sliding windows of 2-10 SNPs shifting 1 SNP at a time) were performed using the expectation-maximisation algorithm-based approach implemented in Plink . Single-point and multi-point (sliding windows of 2-11 SNPs) family-based association analyses were carried out using implementations of the transmission disequilibrium test (TDT) in Plink . 10,000 permutations were run for each association analysis. r2 and D' measures of pairwise LD were calculated for all SNPs using Haploview . Power was calculated under the log-additive model for a range of effect-sizes (1.1<OR>2) at α = 0.05 using Quanto . All association analyses are unadjusted (e.g. for BMI, blood pressure and other environmental variables), as these data were not available to us. We did not investigate gene-environment interactions.
Case-control association analysis results for the 10 TNF/LTA tag SNPs
Transmission disequilibrium analysis of 11 TNF/LTA tag SNPs in T2D parent-offspring trios
95% CI f
The comparison of association results for T60N, G-308A and G-238A between the present study and the WTCCC T2D GWAS
rs3093668 (proxy for rs361525)
We investigated capture further on the basis of the 1000 genomes project data. Four of our 11 tag SNPs (rs909253, rs1800750, rs3093662 and rs3093665) were not found in the 1000G dataset and the remaining 7 tag SNPs capture 60.6% of common variation (overall 33 TNF/LTA SNPs in the 1000G dataset) on a multimarker tagging basis at an r2 threshold of ≥0.8. This is again an underestimate of the TNF/LTA common variation capture by our tag SNPs.
In this study of 11 tag SNPs, we find no consistent evidence for association between TNF/LTA region variation and T2D. The present study was designed to analyse a set of tag SNPs specifically selected to capture the majority of common variation in the TNF/LTA gene region based on proprietary sequence and genotype data [32, 33]. Although a proportion of the investigated variants had been examined as part of the WTCCC GWAS [5, 28], this study provides further capture of common variation across the region. However, the overall conclusion remains unchanged - there was no evidence of association with disease.
This is one of the largest studies to date, showing no association between TNF/LTA variation and T2D. A recent meta-analysis (2106 cases and 2920 controls) of the rs361525 (G-238A) variant did not detect a significant association with T2D . Similar meta-analyses of all reported association studies for the rs1800629 (G-308A) and rs1041981 (T60N) SNPs, which have been widely investigated with respect to T2D, may boost power to detect possible small effects at these loci.
T2D is a complex disease caused by complex interplay between environmental and genetic factors. A limitation of our study is that we have not been able to adjust for or investigate interaction of SNPs with BMI, age, gender, blood pressure, serum lipid levels etc. as these data were unavailable to us. In addition, even though our study examined the majority of common variation across the region, it is possible that causal, associated variants may have been missed.
The purpose of this study was to examine if genetic variation in the genes encoding inflammatory proteins TNF and LTA alter the risk of developing T2D. We tested a carefully selected set of haplotype tagging SNPs that capture the majority of common variation in the TNF/LTA gene region in case-control and parent-offspring samples and find no robust evidence for association. Large-scale meta-analyses will be required to investigate the presence of smaller effects at polymorphic sites in the TNF/LTA gene region.
central European population
genome wide association study
minor allele frequency
single nucleotide polymorphism
- tag SNP:
transmission disequilibrium test
tumor necrosis factor
type 2 diabetes mellitus.
The work was supported by the Diabetes UK RD04/0002809 and RD06/0003190 grants. We thank The British Scholarship Trust for support for the VB study visit to Oxford. This study makes use of data generated by the Wellcome Trust Case-Control Consortium. A full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 076113. This work was supported by the Wellcome Trust (WT088885/Z/09/Z). We acknowledge use of DNA from the British 1958 Birth Cohort collection, funded by the UK Medical Research Council grant G0000934 and Wellcome Trust grant 068545/Z/02.
- McCarthy MI, Zeggini E: Genome-wide association studies in type 2 diabetes. Current diabetes reports. 2009, 9 (2): 164-171. 10.1007/s11892-009-0027-4.View ArticlePubMedPubMed CentralGoogle Scholar
- Rung J, Cauchi S, Albrechtsen A, Shen L, Rocheleau G, Cavalcanti-Proenca C, Bacot F, Balkau B, Belisle A, Borch-Johnsen K, et al: Genetic variant near IRS1 is associated with type 2 diabetes, insulin resistance and hyperinsulinemia. Nature genetics. 2009, 41 (10): 1110-1115. 10.1038/ng.443.View ArticlePubMedGoogle Scholar
- Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PI, Chen H, Roix JJ, Kathiresan S, Hirschhorn JN, Daly MJ, et al: Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science (New York, NY). 2007, 316 (5829): 1331-1336.View ArticleGoogle Scholar
- Scott LJ, Mohlke KL, Bonnycastle LL, Willer CJ, Li Y, Duren WL, Erdos MR, Stringham HM, Chines PS, Jackson AU, et al: A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science (New York, NY). 2007, 316 (5829): 1341-1345.View ArticleGoogle Scholar
- Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007, 447 (7145): 661-678. 10.1038/nature05911.
- Zeggini E, Weedon MN, Lindgren CM, Frayling TM, Elliott KS, Lango H, Timpson NJ, Perry JR, Rayner NW, Freathy RM, et al: Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science (New York, NY). 2007, 316 (5829): 1336-1341.View ArticleGoogle Scholar
- Sladek R, Rocheleau G, Rung J, Dina C, Shen L, Serre D, Boutin P, Vincent D, Belisle A, Hadjadj S, et al: A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature. 2007, 445 (7130): 881-885. 10.1038/nature05616.View ArticlePubMedGoogle Scholar
- Salonen JT, Uimari P, Aalto JM, Pirskanen M, Kaikkonen J, Todorova B, Hypponen J, Korhonen VP, Asikainen J, Devine C, et al: Type 2 diabetes whole-genome association study in four populations: the DiaGen consortium. American journal of human genetics. 2007, 81 (2): 338-345. 10.1086/520599.View ArticlePubMedPubMed CentralGoogle Scholar
- Steinthorsdottir V, Thorleifsson G, Reynisdottir I, Benediktsson R, Jonsdottir T, Walters GB, Styrkarsdottir U, Gretarsdottir S, Emilsson V, Ghosh S, et al: A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nature genetics. 2007, 39 (6): 770-775. 10.1038/ng2043.View ArticlePubMedGoogle Scholar
- Unoki H, Takahashi A, Kawaguchi T, Hara K, Horikoshi M, Andersen G, Ng DP, Holmkvist J, Borch-Johnsen K, Jorgensen T, et al: SNPs in KCNQ1 are associated with susceptibility to type 2 diabetes in East Asian and European populations. Nature genetics. 2008, 40 (9): 1098-1102. 10.1038/ng.208.View ArticlePubMedGoogle Scholar
- Marchini J, Howie B, Myers S, McVean G, Donnelly P: A new multipoint method for genome-wide association studies by imputation of genotypes. Nature genetics. 2007, 39 (7): 906-913. 10.1038/ng2088.View ArticlePubMedGoogle Scholar
- Dandona P, Aljada A, Bandyopadhyay A: Inflammation: the link between insulin resistance, obesity and diabetes. Trends in immunology. 2004, 25 (1): 4-7. 10.1016/j.it.2003.10.013.View ArticlePubMedGoogle Scholar
- Pickup JC, Crook MA: Is type II diabetes mellitus a disease of the innate immune system?. Diabetologia. 1998, 41 (10): 1241-1248. 10.1007/s001250051058.View ArticlePubMedGoogle Scholar
- Plomgaard P, Nielsen AR, Fischer CP, Mortensen OH, Broholm C, Penkowa M, Krogh-Madsen R, Erikstrup C, Lindegaard B, Petersen AM, et al: Associations between insulin resistance and TNF-alpha in plasma, skeletal muscle and adipose tissue in humans with and without type 2 diabetes. Diabetologia. 2007, 50 (12): 2562-2571. 10.1007/s00125-007-0834-6.View ArticlePubMedGoogle Scholar
- Hotamisligil GS, Shargill NS, Spiegelman BM: Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance. Science (New York, NY). 1993, 259 (5091): 87-91.View ArticleGoogle Scholar
- Yang J, Park Y, Zhang H, Xu X, Laine GA, Dellsperger KC, Zhang C: Feed-forward signaling of TNF-alpha and NF-kappaB via IKK-beta pathway contributes to insulin resistance and coronary arteriolar dysfunction in type 2 diabetic mice. American journal of physiology. 2009, 296 (6): H1850-1858.PubMedPubMed CentralGoogle Scholar
- Zeggini E, Groves CJ, Parkinson JR, Halford S, Owen KR, Frayling TM, Walker M, Hitman GA, Levy JC, O'Rahilly S, et al: Large-scale studies of the association between variation at the TNF/LTA locus and susceptibility to type 2 diabetes. Diabetologia. 2005, 48 (10): 2013-2017. 10.1007/s00125-005-1902-4.View ArticlePubMedGoogle Scholar
- Feugeas JP, Caillens H, Poirier JC, Charron D, Marcelli-Barge A, Wautier JL: Influence of metabolic and genetic factors on tumour necrosis factor-alpha and lymphotoxin-alpha production in insulin-dependent diabetes mellitus. Diabetes & metabolism. 1997, 23 (4): 295-301.Google Scholar
- Susa S, Daimon M, Sakabe J, Sato H, Oizumi T, Karasawa S, Wada K, Jimbu Y, Kameda W, Emi M, et al: A functional polymorphism of the TNF-alpha gene that is associated with type 2 DM. Biochemical and biophysical research communications. 2008, 369 (3): 943-947. 10.1016/j.bbrc.2008.02.121.View ArticlePubMedGoogle Scholar
- Nicaud V, Raoux S, Poirier O, Cambien F, O'Reilly DS, Tiret L: The TNF alpha/G-308A polymorphism influences insulin sensitivity in offspring of patients with coronary heart disease: the European Atherosclerosis Research Study II. Atherosclerosis. 2002, 161 (2): 317-325. 10.1016/S0021-9150(01)00648-7.View ArticlePubMedGoogle Scholar
- Li H, Groop L, Nilsson A, Weng J, Tuomi T: A combination of human leukocyte antigen DQB1*02 and the tumor necrosis factor alpha promoter G308A polymorphism predisposes to an insulin-deficient phenotype in patients with type 2 diabetes. The Journal of clinical endocrinology and metabolism. 2003, 88 (6): 2767-2774. 10.1210/jc.2002-020506.View ArticlePubMedGoogle Scholar
- Heijmans BT, Westendorp RG, Droog S, Kluft C, Knook DL, Slagboom PE: Association of the tumour necrosis factor alpha -308G/A polymorphism with the risk of diabetes in an elderly population-based cohort. Genes and immunity. 2002, 3 (4): 225-228. 10.1038/sj.gene.6363859.View ArticlePubMedGoogle Scholar
- Feng R, Li Y, Zhao D, Wang C, Niu Y, Sun C: Lack of association between TNF 238 G/A polymorphism and type 2 diabetes: a meta-analysis. Acta diabetologica. 2009, 46 (4): 339-343. 10.1007/s00592-009-0118-3.View ArticlePubMedGoogle Scholar
- Willer CJ, Bonnycastle LL, Conneely KN, Duren WL, Jackson AU, Scott LJ, Narisu N, Chines PS, Skol A, Stringham HM, et al: Screening of 134 single nucleotide polymorphisms (SNPs) previously associated with type 2 diabetes replicates association with 12 SNPs in nine genes. Diabetes. 2007, 56 (1): 256-264. 10.2337/db06-0461.View ArticlePubMedGoogle Scholar
- Ozaki K, Ohnishi Y, Iida A, Sekine A, Yamada R, Tsunoda T, Sato H, Sato H, Hori M, Nakamura Y, et al: Functional SNPs in the lymphotoxin-alpha gene that are associated with susceptibility to myocardial infarction. Nature genetics. 2002, 32 (4): 650-654. 10.1038/ng1047.View ArticlePubMedGoogle Scholar
- Hamid YH, Urhammer SA, Glumer C, Borch-Johnsen K, Jorgensen T, Hansen T, Pedersen O: The common T60N polymorphism of the lymphotoxin-alpha gene is associated with type 2 diabetes and other phenotypes of the metabolic syndrome. Diabetologia. 2005, 48 (3): 445-451. 10.1007/s00125-004-1659-1.View ArticlePubMedGoogle Scholar
- Yamada A, Ichihara S, Murase Y, Kato T, Izawa H, Nagata K, Murohara T, Yamada Y, Yokota M: Lack of association of polymorphisms of the lymphotoxin alpha gene with myocardial infarction in Japanese. Journal of molecular medicine (Berlin, Germany). 2004, 82 (7): 477-483.View ArticleGoogle Scholar
- Zeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T, de Bakker PI, Abecasis GR, Almgren P, Andersen G, et al: Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nature genetics. 2008, 40 (5): 638-645. 10.1038/ng.120.View ArticlePubMedPubMed CentralGoogle Scholar
- Power C, Elliott J: Cohort profile: 1958 British birth cohort (National Child Development Study). International journal of epidemiology. 2006, 35 (1): 34-41. 10.1093/ije/dyi183.View ArticlePubMedGoogle Scholar
- Frayling TM, Walker M, McCarthy MI, Evans JC, Allen LI, Lynn S, Ayres S, Millauer B, Turner C, Turner RC, et al: Parent-offspring trios: a resource to facilitate the identification of type 2 diabetes genes. Diabetes. 1999, 48 (12): 2475-2479. 10.2337/diabetes.48.12.2475.View ArticlePubMedGoogle Scholar
- Wiltshire S, Hattersley AT, Hitman GA, Walker M, Levy JC, Sampson M, O'Rahilly S, Frayling TM, Bell JI, Lathrop GM, et al: A genomewide scan for loci predisposing to type 2 diabetes in a U.K. population (the Diabetes UK Warren 2 Repository): analysis of 573 pedigrees provides independent replication of a susceptibility locus on chromosome 1q. American journal of human genetics. 2001, 69 (3): 553-569. 10.1086/323249.View ArticlePubMedPubMed CentralGoogle Scholar
- Hanchard N, Diakite M, Koch O, Keating B, Pinder M, Jallow M, Sisay-Joof F, Nijnik A, Wilson J, Udalova I, et al: Implications of inter-population linkage disequilibrium patterns on the approach to a disease association study in the human MHC class III. Immunogenetics. 2006, 58 (5-6): 465-470. 10.1007/s00251-006-0118-1.View ArticlePubMedGoogle Scholar
- Hanchard N, Rockett K, Udalova I, Wilson J, Keating B, Koch O, Nijnik A, Diakite M, Herbert M, Kwiatkowski D: An investigation of transmission ratio distortion in the central region of the human MHC. Genes and immunity. 2006, 7 (1): 51-58. 10.1038/sj.gene.6364277.View ArticlePubMedGoogle Scholar
- The International HapMap Project. Nature. 2003, 426 (6968): 789-796. 10.1038/nature02168.
- de Bakker PI, Yelensky R, Pe'er I, Gabriel SB, Daly MJ, Altshuler D: Efficiency and power in genetic association studies. Nature genetics. 2005, 37 (11): 1217-1223. 10.1038/ng1669.View ArticlePubMedGoogle Scholar
- Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, et al: PLINK: a tool set for whole-genome association and population-based linkage analyses. American journal of human genetics. 2007, 81 (3): 559-575. 10.1086/519795.View ArticlePubMedPubMed CentralGoogle Scholar
- Barrett JC, Fry B, Maller J, Daly MJ: Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics (Oxford, England). 2005, 21 (2): 263-265. 10.1093/bioinformatics/bth457.View ArticleGoogle Scholar
- Gauderman WJ: Candidate gene association analysis for a quantitative trait, using parent-offspring trios. Genetic epidemiology. 2003, 25 (4): 327-338. 10.1002/gepi.10262.View ArticlePubMedGoogle Scholar
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