An Interferon-Induced Helicase (IFIH1) Gene Polymorphism Associates With Different Rates of Progression From Autoimmunity to Type 1 Diabetes

The BABYDIAB study examined the natural history of islet autoimmunity in children of patients with type 1 diabetes (8). Families were eligible if one or both parents had type 1 diabetes. Recruitment began in 1989 and ended in 2000. Venous blood samples were obtained from children at study visits scheduled at age 9 months and 2, 5, 8, 11, 14, 17, and 20 years. Islet autoantibodies were measured in all collected samples. If children had a positive autoantibody result, visit frequencies and islet autoantibody measurements were subsequently performed at 6- to 12-month intervals. The study was coordinated centrally from Munich and conducted from this site by directly contacting the participating families and their family pediatrician. The BABYDIAB cohort contains 1,650 offspring followed from birth to last sample for a median of 8.8 years (range 0.75–20.1). The cumulative dropout rate was 20.9% by age 8 years. Written informed consent was provided by participating families. BABYDIAB was approved by the Bavarian ethical committee (Bayerische Landesärztekammer number 95357).

Families were asked to report the occurrence of symptoms of diabetes. In children with islet autoantibodies, a yearly oral glucose tolerance test was performed. Diabetes onset was defined according to American Diabetes Association criteria, which include unequivocal hyperglycemia with acute metabolic decompensation or the observation (on at least two occasions) of a 2-h plasma glucose >200 mg/dL after an oral glucose challenge, or a random blood glucose >200 mg/dL if accompanied by unequivocal symptoms. Since 1997, fasting blood glucose >126 mg/dL on two occasions was added to the diabetes diagnosis criteria.

Insulin autoantibodies (IAAs), GAD autoantibodies (GADAs), IA-2A autoantibodies (IA-2As), and ZnT8 autoantibodies (ZnT8As) were measured by radiobinding assays as previously described (8,9). The upper limits of normal were determined using QQ plots and corresponded to the 99th percentile of control children. Performances in the Diabetes Autoantibody Standardization Program are shown as laboratory 121 in published reports (10,11). Offspring were considered islet autoantibody positive when two consecutive samples collected after birth were positive.

Thyroid peroxidase antibodies (TPOAs) were measured by radiobinding assay according to the manufacturer’s instructions (CentAK anti-TPO; Medipan, Dahlewitz/Berlin, Germany) as previously described (12). Samples were TPOA positive if levels were >50 units/mL, as suggested by the manufacturer and confirmed using QQ plot analysis.

IgA antibodies to tissue transglutaminase autoantibodies (tTGAs) were measured by ELISA according to the manufacturer’s instructions (Eurospital, Trieste, Italy) and by radiobinding assay with [³⁵S]methionine-labeled in vitro transcribed/translated recombinant human tissue transglutaminase as previously described (13). Positive thresholds were determined using QQ plots and corresponded to the 95th percentile of control children without diabetes or celiac disease for the ELISA and the 99th percentile of control samples for the radiobinding assay. Samples were positive if they were above thresholds in both assays.

HLA-DRB1, HLA-DQA1, and HLA-DQB1 alleles were typed using PCR-amplified DNA and nonradioactive sequence-specific oligonucleotide probes as described previously (5). Classification into high-risk HLA genotypes was based on The Environmental Determinants of Diabetes in the Young (TEDDY) study inclusion genotypes for first-degree relatives (14): DR4-DQA1*030X-DQB1*0302^@/DR3-DQA1*0501-DQB1*0201; DR4-DQA1*030X-DQB1*0302^@/DR4-DQA1*030X-DQB1*0302^@; DR4-DQA1*030X-DQB1*0302^@/DR8- DQA1*0401-DQB1*0402, DR3-DQA1*0501-DQB1*0201/DR3-DQA1*0501-DQB1*0201; DR4-DQA1*030X-DQB1*0302^@/DR4-DQA1*030X-DQB1*020X; DR4-DQA1*030X-DQB1*0302^@/DR1-DQA1*0101-DQB1*0501; DR4-DQA1*030X-DQB1*0302^@/DR13-DQA1*0102-DQB1*0604, DR4-DQA1*030X-DQB1*0302/DR4-DQA1*030X-DQB1*0304, DR4-DQA1*030X-DQB1*0302^@/DR9-DQA1*030×-DQB1*0303; DR3-DQA1*0501-DQB1*0201/DR9-DQA1*030X-DQB1*0303, where ^@ includes DQB1*0302 and *0304.

Additional genes were selected from associations reported in 2007 (1). Tested were the originally described PTPN2 rs1893217and CD25 rs11594656 SNPs (1) and, to facilitate typing in the multiplex method, the proxy SNPs PTPN22 rs6679677, ERBB3 rs705704, KIAA0350 rs12935413, and IFIH1 rs2111485. SNP genotyping was performed with the MassARRAY system using iPLEX chemistry (Sequenom, San Diego, CA) as previously described (15). Reproducibility was assessed by duplicate genotyping in 16.3% of samples (discordance rate <0.5%). SNPs were tested for deviation from Hardy-Weinberg equilibrium by χ² or Fisher exact test. DNA samples for genotyping were available from 1,350 children.

The study design was a priori established to examine overall genotype association with diabetes and subsequently examine relationships to islet autoantibodies and progression to diabetes only in diabetes-associated genes. The probability of diabetes and autoantibodies was estimated by Kaplan-Meier analysis. Hazards ratios (HRs) were determined using Cox proportional hazards model (with and without adjustment for HLA risk genotype). Within islet autoantibody–positive children, Kaplan-Meier analysis was used to calculate the probability of progression to diabetes where follow-up time was calculated from the age when autoantibodies were first detected to the age of type 1 diabetes diagnosis, or last contact. Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS 18.0; SPSS, Chicago, IL).

IFIH1 SNP rs2111485 was associated with diabetes development in the BABYDIAB cohort (HR 2.08; 95% CI 1.16–3.74; P = 0.014; Table 1). The probability of type 1 diabetes was 5% (95% CI 3.2–6.8) by age 15 years for children with GG genotypes and 2% (95% CI 0.8–3.2) for children with GA or AA genotypes (P = 0.004; Fig. 1A). The association remained when adjusted for HLA genotypes (HR 1.98; 95% CI 1.01–3.56; P = 0.023; Table 1), and IFIH1 genotypes were able to stratify diabetes risk in children with high-risk HLA genotypes (Fig. 1B). No significant association with diabetes development could be observed for SNPs in the other five gene regions (Table 1).

To determine whether the association with diabetes observed in the cohort was at the stage of autoimmunity development or the progression to clinical diabetes, we examined IFIH1 associations with islet autoantibody development. No IFIH1-associated difference in the development of autoantibodies was observed (P = 0.80; Fig. 2A). Autoantibody appearance curves were similar between susceptible and protective IFIH1 genotypes for IAAs (P = 0.44), GADAs (P = 0.24), and ZnT8As (P = 0.20) and slightly, but not significantly, higher for susceptible genotypes for the later marker IA-2A (P = 0.06). Moreover, no significant difference between IFIH1 genotypes was found for the probability of developing autoantibodies to thyroid autoantigens and transglutaminase antigen (P = 0.55 and 0.66; Fig. 2F and G).

Among 137 islet autoantibody–positive children, 47 developed diabetes (median, 4.66 years after their first islet autoantibody–positive sample). In contrast to the lack of association with islet autoantibody development, a significant association of the IFIH1 GG genotype with progression from islet autoantibody positivity to diabetes was observed (31 vs. 11% within 5 years; P = 0.006; Fig. 3). This remained significant (HR 1.9; P = 0.05) after adjustment for islet autoantibody status of the child as single or multiple and HLA genotype.

Understanding the mode of action of genes influencing the development of type 1 diabetes requires knowledge as to whether genes influence the development of islet autoimmunity and/or progression from autoimmunity to diabetes. Here we have examined association in a cohort of genetically at-risk children who were followed from birth for both development of islet autoantibodies and diabetes. An association of the IFIH1 gene with diabetes development in this cohort allowed us to determine at what stage the gene is likely to influence diabetes development. Unlike HLA class II genes, which strongly influence the risk for developing islet autoantibodies (5–7), association of the IFIH1 gene was restricted to the progression to diabetes after development of islet autoimmunity. In view of the involvement of the IFIH1 gene in responses to virus infection (16,17), the findings are consistent with a role of infection in determining the progression to diabetes after islet autoimmunity has been initiated.

The findings are from a unique cohort characterized by a family history of type 1 diabetes, perspective follow-up from birth with relatively frequent testing for islet autoantibody development, monitoring for diabetes development, and testing and monitoring for the development of thyroid- and celiac disease–associated autoimmunity up to age 20 years. To minimize the number of comparisons, we chose association with diabetes as the outcome and selected genes that showed association both alone and together with HLA genotypes in a multiple Cox proportional hazards model. The disadvantage of this approach is that modest numbers developed diabetes, allowing us to identify only moderate to strong genetic associations. Thus, the findings from our study are not informative for SNPs in the five gene regions, where we found no association with type 1 diabetes. A potential caveat is that not all islet autoantibodies may be specific for type 1 diabetes (18). The findings were, however, significant for the IFIH1 SNP after adjustment for multiple islet autoantibodies, which is a specific characteristic of type 1 diabetes. Finally, because our study is in subjects with a type 1 diabetes family history, we cannot make conclusions for case subjects without a family history. Analyses in the Finnish Diabetes Prediction and Prevention (DIPP) study (6) and the multicenter TEDDY study (14) are informative in this respect.

The IFIH1 gene encodes helicase C domain 1, which mediates induction of the interferon response to viral RNA (16,17). The association of IFIH1 polymorphisms including rare variants with type 1 diabetes (19,20) has been noteworthy because of their link to the inflammatory response caused by infectious agents, including enteroviruses. Viral infection is hypothesized to cause islet autoimmunity and/or influence progression to diabetes (21–23). Data in humans are inconclusive, whereas data from the murine models lean toward effects at the progression stage (24). Our study provides unique insight into this debate. First, a common polymorphism of the IFIH1 gene had an odds ratio for diabetes development of around 2 in our cohort, potentially implying relatively strong effects in children with a type 1 diabetes family history. Second, we found no association with the initiation of autoimmunity, as defined by the development of islet autoantibodies, and the development of thyroid- or celiac disease–associated autoantibodies. Examining individual islet autoantibodies found no association with the development of IAAs or GADAs, which appear early in the disease process, and borderline association with IA-2As, which in our cohort appear later than IAAs or GADAs. Of interest, the development of all these autoantibodies is strongly influenced by the HLA class II genotype (5–7,10,11), whereas progression to diabetes after the appearance of islet autoantibodies is only minimally associated with HLA class II (6,25). In contrast, we observed a strong effect of the IFIH1 genotype on the rate of progression to disease from first islet autoantibody detection.

With respect to pathogenesis, our findings would be consistent, with infection playing a more prominent role in diabetes development after the onset of islet autoimmunity than during initiation of autoimmunity. The findings also have potential implications for type 1 diabetes prevention. They suggest that intervention in autoantibody-positive children to delay or prevent the onset of type 1 diabetes is possible and furthermore suggest that interference with host response to infection may be a means to achieve successful intervention.

This work was supported by grants from the Kompetenznetz Diabetes Mellitus (Competence Network for Diabetes Mellitus) and was funded by the Federal Ministry of Education and Research (FKZ 01GI0805-07), the Juvenile Diabetes Research Foundation (JDRF 1-2006-665), the German National Genome Research Network, and the Helmholtz Center Munich, German Research Center for Environmental Health. E.B. was supported by the Diabetes Prediction and Prevention Center for Regenerative Therapies Dresden, Cluster of Excellence (FZ 111).

No potential conflicts of interests relevant to this article were reported.

C.W. acquired and reviewed data, undertook statistical analysis and interpretation of the results, and drafted the manuscript. C.L. and K.A. prepared and kept the biobank samples used for genotyping (including the preparation of protocols for DNA preparation and storage), assisted in obtaining data, performed analysis, and critically reviewed the manuscript. H.G. performed the genotyping. T.I. established the genotyping and critically reviewed the manuscript for intellectual content. A.-G.Z. was the principal investigator, designed the BABYDIAB study and concept, was involved in the interpretation of the results and the writing of the manuscript, and critically reviewed the manuscript for intellectual content. E.B. designed the study analysis and the concept, performed the statistical analysis with C.W., was involved in the interpretation of the results, wrote the manuscript, and critically reviewed the manuscript for intellectual content.

The authors thank Annette Knopff, Marina Zwilling, Ulrike Mollenhauer, and Stephanie Krause (Forschergruppe Diabetes e.V. at Helmholtz Center Munich, Neuherberg, Germany) for data collection and expert technical assistance and Markus Walter (Schwabing City Hospital, Munich, Germany) for follow-up of children. The authors also thank all pediatricians and family doctors in Germany for their participation in the BABYDIAB study.