Analyses of multiple single-nucleotide polymorphisms in the SUMO4/IDDM5 region in affected sib-pair families with type I diabetes

SUMO: From Bench to Bedside

Sentrin/small ubiquitin-like modifier (SUMO) is protein modification pathway that regulates multiple biological processes, including cell division, DNA replication/repair, signal transduction, and cellular metabolism. In this review, we will focus on recent advances in the mechanisms of disease pathogenesis, such as cancer, diabetes, seizure, and heart failure, which have been linked to the SUMO pathway. SUMO is conjugated to lysine residues in target proteins through an isopeptide linkage catalyzed by SUMO-specific activating (E1), conjugating (E2), and ligating (E3) enzymes. In steady state, the quantity of SUMO-modified substrates is usually a small fraction of unmodified substrates due to the deconjugation activity of the family Sentrin/SUMO-specific proteases (SENPs). In contrast to the complexity of the ubiquitination/deubiquitination machinery, the biochemistry of SUMOylation and de-SUMOylation is relatively modest. Specificity of the SUMO pathway is achieved through redox regulation, acetylation, phosphorylation, or other posttranslational protein modification of the SUMOylation and de-SUMOylation enzymes. There are three major SUMOs. SUMO-1 usually modifies a substrate as a monomer; however, SUMO-2/3 can form poly-SUMO chains. The monomeric SUMO-1 or poly-SUMO chains can interact with other proteins through SUMO-interactive motif (SIM). Thus SUMO modification provides a platform to enhance protein-protein interaction. The consequence of SUMOylation includes changes in cellular localization, protein activity, or protein stability. Furthermore, SUMO may join force with ubiquitin to degrade proteins through SUMO-targeted ubiquitin ligases (STUbL). After 20 yr of research, SUMO has been shown to play critical roles in most, if not all, biological pathways. Thus the SUMO enzymes could be targets for drug development to treat human diseases.

Association between the SUMO4 M55V (A163G) polymorphism and susceptibility to type 1 diabetes: a meta-analysis

OBJECTIVE

The aim of this study was to determine whether the SUMO4 M55V (A163G) polymorphism confers susceptibility to type 1 diabetes (T1D).

METHODS

A meta-analysis was conducted on the association between the SUMO4 M55V polymorphism and T1D using; (1) allelic contrast (G vs. A), and the (2) recessive (GG vs. GA+AA), (3) dominant (GG+GA vs. AA), and (4) additive models (GG vs. AA).

RESULTS

Thirteen separate studies were considered in the meta-analysis, which in total included 5915 patients and 6660 controls, and five European and eight Asian sample populations. Europeans had a higher prevalence of the G allele than Asians (50.4% vs. 30.2%). Meta-analysis of the SUMO4 M55V polymorphism showed an association between T1D and the SUMO4 G allele in all study subjects (OR=1.236, 95% CI=1.112-1.373, p=7.9×10(-6)), and stratification by ethnicity indicated a highly significant association between the SUMO4 G allele and T1D in Asians (OR=1.303, 95% CI=1.169-1.452, p=1.78×10(-7)) and a marginal association with T1D in Europeans (OR=1.177, 95% CI=1.000-1.386, p=0.050). Furthermore, significant associations were found between the SUMO4 M55V polymorphism and T1D and all study subjects, Europeans, and Asians using the dominant model (OR=1.239, 95% CI=1.144-1.342, p=1.4×10(-8); OR=1.156, 95% CI=1.051-1.271, p=0.003; OR=1.461, 95% CI=1.262-1.691, p=3.8×10(-8), respectively).

CONCLUSIONS

This meta-analysis indicates that the SUMO4 M55V polymorphism confers susceptibility to T1D in Asians and Europeans.

The Type I Diabetes Genetics Consortium 'Rapid Response' family-based candidate gene study: strategy, genes selection, and main outcome

Candidate gene studies have long been the principal method for identification of susceptibility genes for type I diabetes (T1D), resulting in the discovery of HLA, INS, PTPN22, CTLA4, and IL2RA. However, many of the initial studies that relied on this strategy were largely underpowered, because of the limitations in genomic information and genotyping technology, as well as the limited size of available cohorts. The Type I Diabetes Genetic Consortium (T1DGC) has established resources to re-evaluate earlier reported genes associated with T1D, using its collection of 2298 Caucasian affected sib-pair families (with 11 159 individuals). A total of 382 single-nucleotide polymorphisms (SNPs) located in 21 T1D candidate genes were selected for this study and genotyped in duplicate on two platforms, Illumina and Sequenom. The genes were chosen based on published literature as having been either 'confirmed' (replicated) or not (candidates). This study showed several important features of genetic association studies. First, it showed the major impact of small rates of genotyping errors on association statistics. Second, it confirmed associations at INS, PTPN22, IL2RA, IFIH1 (earlier confirmed genes), and CTLA4 (earlier confirmed, with distinct SNPs) loci. Third, it did not find evidence for an association with T1D at SUMO4, despite confirmed association in Asian populations, suggesting the potential for population-specific gene effects. Fourth, at PTPN22, there was evidence for a novel contribution to T1D risk, independent of the replicated effect of the R620W variant. Fifth, among the candidate genes selected for replication, the association of TCF7-P19T with T1D was newly replicated in this study. In summary, this study was able to replicate some genetic effects, reject others, and provide suggestions of association with several of the other candidate genes in stratified analyses (age at onset, HLA status, population of origin). These results have generated additional interesting functional hypotheses that will require further replication in independent cohorts.

Overview of the Type I Diabetes Genetics Consortium

The Type I Diabetes Genetics Consortium (T1DGC) is an international, multicenter research program with two primary goals. The first goal is to identify genomic regions and candidate genes whose variants modify an individual's risk of type I diabetes (T1D) and help explain the clustering of the disease in families. The second goal is to make research data available to the research community and to establish resources that can be used by, and that are fully accessible to, the research community. To facilitate the access to these resources, the T1DGC has developed a Consortium Agreement (http://www.t1dgc.org) that specifies the rights and responsibilities of investigators who participate in Consortium activities. The T1DGC has assembled a resource of affected sib-pair families, parent-child trios, and case-control collections with banks of DNA, serum, plasma, and EBV-transformed cell lines. In addition, both candidate gene and genome-wide (linkage and association) studies have been performed and displayed in T1DBase (http://www.t1dbase.org) for all researchers to use in their own investigations. In this supplement, a subset of the T1DGC collection has been used to investigate earlier published candidate genes for T1D, to confirm the results from a genome-wide association scan for T1D, and to determine associations with candidate genes for other autoimmune diseases or with type II diabetes that may be involved with beta-cell function.

Analysis of 19 genes for association with type I diabetes in the Type I Diabetes Genetics Consortium families

In recent years the pace of discovery of genetic associations with type I diabetes (T1D) has accelerated, with the total number of confirmed loci, including the major histocompatibility complex (MHC) region, reaching 43. However, much of the deciphering of the associations at these, and the established T1D loci, has yet to be performed in sufficient numbers of samples or with sufficient markers. Here, 257 single-nucleotide polymorphisms (SNPs) have been genotyped in 19 candidate genes (INS, PTPN22, IL2RA, CTLA4, IFIH1, SUMO4, VDR, PAX4, OAS1, IRS1, IL4, IL4R, IL13, IL12B, CEACAM21, CAPSL, Q7Z4c4(5Q), FOXP3, EFHB) in 2300 affected sib-pair families and tested for association with T1D as part of the Type I Diabetes Genetics Consortium's candidate gene study. The study had approximately 80% power at alpha=0.002 and a minor allele frequency of 0.2 to detect an effect with a relative risk (RR) of 1.20, which drops to just 40% power for a RR of 1.15. At the INS gene, rs689 (-23 HphI) was the most associated SNP (P=3.8 x 10(-31)), with the estimated RR=0.57 (95% confidence interval, 0.52-0.63). In addition, rs689 was associated with age-at-diagnosis of T1D (P=0.001), with homozygosity for the T1D protective T allele, delaying the onset of T1D by approximately 2 years in these families. At PTPN22, rs2476601 (R620W), in agreement with previous reports, was the most significantly associated SNP (P=6.9 x 10(-17)), with RR=1.55 (1.40-1.72). Evidence for association with T1D was observed for the IFIH1 SNP, rs1990760 (P=7.0 x 10(-4)), with RR=0.88 (0.82-0.95) and the CTLA4 SNP rs1427676 (P=0.0005), with RR=1.14 (1.06-1.23). In contrast, no convincing evidence of association was obtained for SUMO4, VDR, PAX4, OAS1, IRS1, IL4, IL4R, IL13, IL12B, CEACAM21 or CAPSL gene regions (http://www.T1DBase.org).