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Hospital for Children and Adolescents (S.M., H.K.A., M.K.), University of Helsinki, FIN-00029 Helsinki, Finland; Department of Pediatrics (K.S., P.K.), University of Oulu, FIN-90014 Oulu, Finland; Department of Virology and Turku Immunology Centre (H.R., J.I.), University of Turku, FIN-20520 Turku, Finland; and Department of Pediatrics (M.K.), Tampere University Hospital, FIN-33521 Tampere, Finland
Address all correspondence and requests for reprints to: Mikael Knip, M.D., Hospital for Children and Adolescents, University of Helsinki, P.O. Box 281, 00029 HUCH, Finland. E-mail: mikael.knip{at}hus.fi.
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Abstract |
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Introduction |
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The incidence of type 1 diabetes in Finland has been reported to be the highest in the world, followed by Sardinia (7), and has increased from 12 per 100,000 in 1953 (8) to 50 in 1998 (Reunanen, A., unpublished information). Similar increases in incidence have been observed in most European countries, according to a recent survey (9). This together with the fact that most cases are sporadic emphasizes the contribution of exogenous factors to the pathogenesis of type 1 diabetes.
The role of autoantibodies and genetic susceptibility in the prediction of progression to type 1 diabetes has been extensively investigated. Their combined contribution to the risk of type 1 diabetes is, however, a poorly explored area. We set out to study the association between HLA-defined genetic disease susceptibility and the stage of preclinical type 1 diabetes, and to ascertain whether genetic predisposition affects the natural course of preclinical type 1 diabetes in initially nondiabetic siblings of affected children. We were also interested in assessing the impact of genetic susceptibility on the risk of progression to clinical type 1 diabetes and whether it affects the kinetics of this process.
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Subjects and Methods |
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The study population was derived from the nationwide Childhood Diabetes in Finland (DiMe) study. From September 1986 to April 1989, children with newly diagnosed type 1 diabetes under the age of 15 yr and their families were invited to join the study, the aim of which was to evaluate the genetic, immunological, and environmental factors leading to the development of type 1 diabetes (7). The follow-up was prospective, and observation of the siblings was initiated shortly after the proband was diagnosed as having type 1 diabetes. Informed consent was obtained from the study participants and/or their parents. The study design was approved by the ethical committees of all participating hospitals. Blood samples were taken at intervals of 3–6 months during the first 2 yr and at 6- to 12-month intervals during the following 2 yr. Siblings with only one sample available were excluded from this analysis. If the sibling was found to test negative for islet cell antibodies (ICA) and insulin autoantibodies (IAA) on all occasions over the first 4 yr, antibody surveillance was discontinued. Siblings positive for ICA and/or IAA on at least one occasion over the initial 4 yr were subsequently observed at intervals of 12 months or less, and were invited for sequential iv glucose tolerance tests (IVGTTs) at intervals of 6–12 months starting from the time when antibodies were first detected. All of the siblings were observed for progression to type 1 diabetes up to the end of 1997. Observation of the siblings who progressed to clinical disease ended at diagnosis, which was based on clinical symptoms and an increased random blood glucose concentration (>10 mmol/liter) or elevated fasting (>6.7 mmol/liter) or random blood glucose on two occasions in the absence of symptoms (10).
The 801 index cases of the DiMe study had a mean age of 8.4 yr (range, 0.8–14.9 yr). Genetic data were available for 701 siblings, the mean age being 9.9 yr (range, 0.8–19.7 yr), covered by the classification based on autoantibodies (see Data handling and statistical analyses) and for 659 included in the classification based on the combination of autoantibodies and first-phase insulin response (FPIR). Their mean age was 9.9 yr (range, 0.8–19.7 yr). The mean age of the 83 cases who underwent at least one IVGTT was 9.7 yr (range, 2.1–18.9 yr) at the time of diagnosis of the index case and 11.2 yr (range, 3.2–20.0 yr) at the time of the first IVGTT.
Methods
Disease-associated autoantibodies. The presence of ICA was determined by a standard immunofluorescence assay performed on sections of frozen human pancreas from a blood group O donor (11). Fluorescein-conjugated antihuman IgG (Sigma, St. Louis, MO) was used to detect ICA. End-point dilution titers were identified, and the results were expressed in Juvenile Diabetes Foundation (JDF) units relative to an international reference standard (12). The detection limit was 2.5 JDF units. The sensitivity of the ICA assay was 100%, and the specificity was 98% in the most recent international standardization round (13).
IAA were analyzed by a modification of the liquid phase RIA described by Palmer et al. (14). The samples were treated with acid charcoal to remove insulin before the assay. A total of 80 µl of serum was incubated for 20 h with mono125I(TyrA14)-human insulin (Novo Research Institute, Bagsvaerd, Denmark), and the free and bound insulin fractions were separated using polyethylene glycol. The results were expressed in nU/ml, where 1 nU/ml corresponds to a specific binding of 0.01%. The interassay coefficient of variation was less than 8%. If the specific insulin binding was equal to or exceeded the 99th percentile in 105 nondiabetic subjects (55 nU/ml) the individual was considered IAA positive. The sensitivity of the IAA assay was 78%, and the specificity was 100% in the proficiency testing program.
An immunoprecipitation radioligand assay was used to detect glutamic acid decarboxylase antibodies (GADA; Refs. 15 and 16). The results were expressed in relative units (RU), representing the specific binding as a percentage of that obtained with a positive standard serum. The limit for GADA positivity was set at the 99th percentile in a series of 372 healthy control subjects (6.6 RU). The disease sensitivity of this assay was 79%, and the specificity was 97%, based on the 1995 Multiple Autoantibody Workshop (17).
A radiobinding assay was used to analyze IA-2 antibodies (IA-2A) (18). The results were expressed in RU based on a standard curve constructed from the dilution of a pool of strongly positive samples and a pool of negative samples. A standard curve was run for each plate. A subject was considered IA-2A positive if the serum antibody levels were equal to or exceeded 0.43 RU, which represents the 99th percentile in 374 healthy Finnish children and adolescents. The disease sensitivity of this assay was 62%, and the specificity was 97% based on 140 samples included in the 1995 Multiple Autoantibody Workshop (17).
IVGTTs. The siblings participating in an IVGTT were given a glucose dose of 0.5 g/kg in 3 min (±15 sec) after overnight fasting for 10–16 h. Blood samples were taken before the glucose infusion and at 1, 3, 6, 10, 20, 30, 40, 50, and 60 min thereafter. Serum insulin concentrations were measured radioimmunologically (19). The glucose oxidase method was used to measure the blood glucose levels (20). The sum of the insulin concentrations at 1 and 3 min was defined as the FPIR to glucose. To evaluate the degree of glucose tolerance, the glucose disappearance rate (Kg) was assessed and expressed as the percentage decrease in blood glucose per minute. FPIR levels below 45 mU/liter, which represents the third percentile of FPIR values in healthy control subjects (21) after adjustment for the insulin assay used based on serum exchange of insulin samples between Oulu and Boston, and Kg values under 1.30%/min were considered to be abnormal.
Genetics. HLA-A, -B, -C, and -DR typing was performed by conventional HLA serology as described by Tuomilehto-Wolf et al. (22). All of the HLA-A, -B, -C, and -DR specificities recognized by the Nomenclature Committee of the World Health Organization in 1984 were included in the test panel (23).
HLA-DQB1 typing was performed by a previously described method based on time-resolved fluorescence (24). We used four sequence-specific oligonucleotide probes to identify the following DQB1 alleles known to be associated with either susceptibility to or protection from type 1 diabetes in the Finnish population: DQB1*0302, DQB1*02, DQB1*0602 or *0603, and DQB1*0301 (25). The genotype classification was simplified to high risk (DQB1*02/0302), moderate risk (DQB1*0302/x, where x stands for 0302 or a nondefined allele), low risk (DQB1*0301/0302, DQB1*02/0301, DQB1*02/x, DQB1*0302/0602–3, where x stands for 02 or a nondefined allele), and decreased risk (DQB1*x/x, DQB1*0301/x, DQB1*02/0602–3, DQB1*0301/0602–3, where x stands for a nondefined allele) groups.
Data handling and statistical analyses. The siblings were classified into four stages of preclinical type 1 diabetes (no prediabetes, early, advanced, or late prediabetes) according to two sets of criteria. The first set was based on the number of antibodies detectable in each sample available. In most of the 701 siblings, the first sample was obtained within 3 wk after the diagnosis of type 1 diabetes in the index case. The first stage comprised the siblings who tested negative for all the antibodies analyzed (ICA, IAA, GADA, IA-2A), i.e. those with no prediabetes. Siblings who tested positive for only one of the antibody specificities were regarded as having early prediabetes, those with two antibody specificities detectable as having advanced prediabetes, and those testing positive for at least three of the four antibodies as having late prediabetes.
The second set of criteria was based on a combination of autoantibodies and FPIR. The siblings with no antibodies were still considered to have no prediabetes, those with one antibody specificity detectable but a normal FPIR to have early prediabetes, those with two or more antibodies but the FPIR still normal to have advanced prediabetes, and those with an abnormal FPIR and at least one antibody specificity to have late prediabetes. Antibody-positive siblings with no available data on FPIR were excluded from this classification, leaving 659 of the 701 siblings for the analyses.
The siblings were also classified as progressors, regressors, or stable cases, depending on the dynamics of the prediabetic process, by comparing the initial prediabetic stage with the stage based on the last sample available, which was obtained after an average observation period of 3.4 yr (range, 0.01–9.8 yr).
Cross-tabulation and 
2 statistics were used to analyze the distributions, except for comparisons that included numbers less than five, when the Fischer’s exact method was used. The parametric one-way ANOVA was used to compare normally distributed variables between groups, the nonparametric Kruskall-Wallis ANOVA being used when analyzing variables with a skewed distribution. The t test was used for comparisons between two groups in the case of normally distributed variables, and the Mann-Whitney U test in the case of variables with skewed distributions. The 95% confidence intervals (CI) were calculated by the exact method. Multiple regression analyses were performed with progression to type 1 diabetes or progression of the prediabetic process as dependent variables and with the number of detectable autoantibodies in the first sample, initial levels of ICA, IAA, GADA and IA-2A as well as HLA-DR- or DQB1-conferred genetic risk as independent variables.
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Results |
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There was a strong association between the HLA-conferred genetic risk and the severity of preclinical type 1 diabetes. Among the HLA-identical siblings, 10% had late prediabetes initially, whereas only 3% of the haploidentical and 2% of the nonidentical siblings (Table 1
) were at that stage. When using the criteria based on a combination of autoantibodies and FPIR, 4% of the HLA-identical siblings had late prediabetes, whereas the corresponding proportion among the HLA haploidentical siblings was 1%, and among nonidentical siblings was 0.6% (Table 2).
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). According to the second set of criteria, the difference was less obvious, although the HLA DR3 and/or DR4 alleles were still associated with an increased frequency of preclinical type 1 diabetes (Table 2). The risk of developing late prediabetes was also assessed in relation to the DQB1 genotype. When comparing siblings with high-, moderate-, and low-risk genotypes to siblings with DQB1 genotypes conferring decreased risk, it was again evident that strong genetic susceptibility is associated with an increased risk of developing signs of late prediabetes (Table 1). This was also true when using the second set of criteria (Table 2). Genetic modification of the disease risk associated with various stages of preclinical type 1 diabetes based on autoantibody criteria
The OR for presenting with any sign of prediabetes was 1.9 (CI, 1.2–3.1) for HLA-identical siblings relative to haploidentical or nonidentical siblings. HLA-identical siblings had an OR of 4.1 (CI, 2.0–8.5) of presenting with late prediabetes when compared with the haploidentical or nonidentical siblings. The HLA-identical siblings with late prediabetes (n = 18) had an OR of 775 (Table 3) for clinical diabetes in comparison to the haploidentical or nonidentical siblings without any signs of prediabetes (n = 468). Siblings who were heterozygous for DR 3/4 had an OR of 5 (CI, 2.3–10.9) of presenting with any stage of prediabetes and an OR of 25 (CI, 5.3–118) of presenting with late prediabetes when compared with the siblings carrying the non-DR3/non-DR4 combination. The DR3/4-heterozygous siblings with late prediabetes initially (n = 10) had an OR of 1809 (Table 3) for clinical diabetes compared with the siblings having non-DR3/non-DR4 phenotypes and no initial signs of prediabetes (n = 201). Similar results were also obtained when comparing the DQB1 genotypes, in that siblings with the high-risk DQB1 genotype had an OR of 90.5 (CI, 11.7–703) for presenting with any signs of prediabetes and an OR of 43.0 (CI, 5.3–348) for presenting with late prediabetes compared with siblings carrying genotypes conferring decreased risk. The OR of progression to overt type 1 diabetes was 1773 (Table 3) in the siblings with the high-risk genotype and late prediabetes (n = 9) relative to the siblings with genotypes associated with decreased genetic predisposition and without signs of ß-cell autoimmunity.
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HLA-identical siblings had an OR of 2.2 (CI, 1.2–4.1) of presenting with any signs of prediabetes compared with haploidentical or nonidentical siblings. The OR for presenting with late prediabetes was 4.4 (CI, 1.4–14.1) in the former group relative to the latter. The HLA-identical siblings with late prediabetes (n = 7) had an OR of 930 (Table 4) of clinical type 1 diabetes relative to the haploidentical or nonidentical siblings with no signs of prediabetes (n = 468). DR3/4-heterozygous siblings had an OR of 7.6 (CI, 2.7–21.1) of presenting with any signs of prediabetes and an OR of 23 (CI, 2.7–205) of presenting with late prediabetes relative to the non-DR3/non-DR4 phenotypes. The OR of progression to type 1 diabetes was 804 (Table 4) among the DR3/4-heterozygous siblings with late prediabetes (n = 5) compared with the siblings with non-DR3/non-DR4 phenotypes and no initial signs of prediabetes. Similar risks were observed when looking at DQB1 genotypes. Siblings carrying the high-risk DQ genotype had an OR of 5.7 (CI, 2.3–14.4) of presenting with any signs of ß-cell autoimmunity and an OR of 18 (CI, 2.0–169) of manifesting late prediabetes relative to siblings with genotypes conferring decreased risk. The OR of progression to overt type 1 diabetes was 591 (Table 4) for siblings with the high-risk genotype and late prediabetes relative to those with genotypes conferring decreased risk and with no initial signs of prediabetes. Among the siblings with late prediabetes, all with the high-risk DQ genotype (9/9; 100%) progressed to clinical diabetes, whereas 12 of the remaining 21 siblings (57%; P < 0.05) presented with clinical disease.
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When assessing whether genetic diabetes susceptibility is related to the natural course of preclinical type 1 diabetes, we observed that the higher the genetic risk, the more likely it was that the sibling would progress from a milder stage to a more severe one. This held true for the degree of HLA identity, because about 17% of the HLA-identical siblings progressed in terms of the classification based on the number of autoantibodies detectable, whereas less than 8% of nonidentical ones did so. About 30% of the siblings who were positive for DR3 and DR4 progressed, whereas only 11% of those carrying the non-DR3/non-DR4 combination did so (Table 5). Close to 30% of the siblings with the DQB1 high-risk genotype progressed in their prediabetic stage, whereas about 7% progressed out of those with DQB1 genotypes conferring decreased risk. In contrast, a sibling with low or decreased genetic disease susceptibility was more likely to remain stable in terms of the prediabetic stage. The regression rate was not significantly increased among those with decreased HLA-conferred disease predisposition. It was possible to explain 25–28% of the variation in the progression of the prediabetic process (P < 0.001) by a multiple regression model including the number and levels of autoantibodies in the initial sample and genetic risk (DR- or DQB1-conferred risk) as independent variables. DR-defined risk contributed significantly to the model (Table 6; P = 0.002), whereas the contribution of the DQB1 risk genotypes remained nonsignificant (P = 0.095).
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). About 21% of the siblings who were positive for DR3 and DR4 progressed, whereas only 2% of those carrying the non-DR3/non-DR4 combination did so. Close to 22% of the siblings with the DQB1 high-risk genotype progressed in their prediabetic stage; whereas about 3% progressed out of those with DQB1 genotypes conferring decreased risk. It also held true that a sibling with decreased genetic disease susceptibility was more likely to regress or remain stable in terms of the prediabetic stage (Table 7).
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A multiple regression analysis showed that it was possible to explain 48–50% of the variation in progression to overt type 1 diabetes by a model including initial number and levels of autoantibodies and HLA-conferred genetic risk as independent variables (Table 6). The DR-defined risk contributed significantly to the predictive model, and the same held true for DQB1-conferred risk (P < 0.001) if the former was substituted with the latter.
Siblings with late prediabetes according to the first classification who carried the DQB1*0302/x genotype had a significantly shorter time to diagnosis (1.2 vs. 4.3 yr; P = 0.01) than those who were heterozygous for DQB1*02/0302 (Fig. 1), but no other differences in time to diagnosis were observed between the siblings with an increased HLA-defined genetic risk and those with decreased genetic susceptibility.
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Discussion |
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In general, autoantibodies alone are more sensitive for the prediction of future diabetes in siblings than are antibodies combined with genetic susceptibility (26). In the general population in Finland, the OR of developing type 1 diabetes is 11 among subjects with the DQ high-risk genotype as compared with low risk persons, whereas the OR is 3.5 in siblings of affected children relative to siblings with decreased genetic susceptibility (25). In our study, late prediabetes, i.e. positivity for at least three diabetes-associated autoantibodies, gave an OR as high as 775 when combined with HLA identity, 1809 when combined with DR3/4 heterozygosity, and 1773 when combined with the DQB1*02/0302 genotype as compared with siblings having decreased HLA-defined disease susceptibility and no signs of prediabetes. The combination of late prediabetes with genetic risk markers similarly resulted in high relative risks according to the second set of criteria for prediabetes. Some of these risk ratios were higher than the OR of 258 associated with late prediabetes defined by autoantibodies alone or the OR of 1111 conferred by the stage of late prediabetes based on the combination of autoantibodies and FPIR. The OR integrating the genetic risk markers were not significantly higher than those based on autoantibodies alone or autoantibodies in combination with FPIR, however. On the other hand, all siblings with strong DQ-conferred risk and late prediabetes went on to clinical disease, whereas less than 60% of the other siblings with late prediabetes initially presented with type 1 diabetes.
There was a significantly larger proportion of siblings with late prediabetes among those with strong genetic disease susceptibility than among those with decreased susceptibility, whereas there was a larger proportion of siblings with no signs of prediabetes among those with genotypes conferring decreased risk. These observations suggest that strong HLA-conferred disease susceptibility predisposes the individual to more advanced stages of prediabetes, whereas siblings with low-risk genotypes are more likely to carry signs of early or no prediabetes. This indicates that genetic susceptibility has an impact on the likelihood of an autoimmune process being triggered. In addition, high-risk genotypes are more likely to be associated with a nonreversible immunological process, represented by advanced or late prediabetes. According to the multiple regression analyses, HLA-conferred risk has an impact independent of the autoantibody status on both progression in early prediabetes and on the development of clinical type 1 diabetes, although the relative importance of genetic susceptibility seems to be more modest than that of autoantibodies.
We also aimed to investigate whether any genetic markers predict accelerated or retarded progression to clinical type 1 diabetes. Although the DR3/DQB1*02 haplotype has been reported to be associated with a slowly progressive prediabetic process (27), we observed almost no relationship between time to diagnosis and the risk genotype. Accordingly, HLA-defined disease susceptibility did not provide any clear-cut explanation for the conspicuous interindividual variation in time to diagnosis. When looking only at the siblings with late prediabetes, we observed a shorter time to diagnosis among those with the DQB1*0302/x genotype as compared with those who were heterozygous for DQB1*02/0302. This suggests that the DQB1*0302 allele is linked to a particularly aggressive autoimmune process.
The genetic predisposition is also predictive of progression or regression from the initial prediabetic stage. The stronger the genetic risk, the more likely it is that a sibling will progress in terms of prediabetic stage. Conversely, the lower the genetic risk the more likely it is that the sibling will not progress in his/her prediabetic stage. This indicates not only that siblings with strong susceptibility genotypes have a higher risk of developing autoantibodies but also that their prediabetic autoimmune process more often represents a nonreversible process. The opposite was observed for siblings with genotypes conferring low or decreased diabetes susceptibility, in whom the emergence of autoantibodies is infrequent, and if a prediabetic process is initiated it is more likely to be nonprogressive.
It became evident in the course of this work that the classification according to autoantibodies and FPIR combined with markers of genetic disease susceptibility surprisingly conferred a lower risk of progression from the initial stage and of developing clinical signs of late prediabetes and finally signs of type 1 diabetes than did the classification based on autoantibodies only. This is in contrast with our earlier observations (28) and seems to suggest that HLA-defined disease susceptibility is not per se associated with a decrease in insulin secretory capacity.
In conclusion, siblings who would be suitable for possible future intervention can be identified most efficiently by reference to autoantibodies, either alone or in combination with FPIR. Genetic susceptibility adds to the risk assessment based on diabetes-associated autoantibodies when attempting to predict progression to clinical type 1 diabetes. Increased HLA-defined disease susceptibility is associated with a more frequent emergence of autoantibodies and an irreversible prediabetic process in siblings of children with type 1 diabetes.
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Acknowledgments |
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The Childhood Diabetes in Finland (DiMe) Study Group comprises the following members: principal investigators, H. K. Åkerblom and J. Tuomilehto; coordinators, R. Lounamaa and L. Toivanen; data management, E. Virtala and J. Pitkäniemi; local investigators, A. Fagerlund, M. Flittner, B. Gustafsson, C. Häggqvist, A. Hakulinen, L. Herva, P. Hiltunen, T. Huhtamäki, N.-P. Huttunen, T. Huupponen, M. Hyttinen, T. Joki, R. Jokisalo, M.-L. Käär, S. Kallio, E. A. Kaprio, U. Kaski, M. Knip, L. Laine, J. Lappalainen, J. Mäenpää, A.-L. Mäkelä, K. Niemi, A. Niiranen, A. Nuuja, P. Ojajärvi, T. Otonkoski, K. Pihlajamäki, S. Pöntynen, J. Rajantie, J. Sankala, J. Schumacher, M. Sillanpää, M.-R. Ståhlberg, C.-H. Stråhlman, T. Uotila, M. Väre, P. Varimo, and G. Wetterstrand; special investigators, A. Aro, H. Hurme, M. Hiltunen, H. Hyöty, J. Ilonen, J. Karjalainen, M. Knip, P. Leinikki, A. Miettinen, T. Petäys, H. Reijonen, A. Reunanen, L. Räsänen, T. Saukkonen, E. Savilahti, E. Tuomilehto-Wolf, P. Vähäsalo, and S. M. Virtanen.
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Footnotes |
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Abbreviations: CI, Confidence interval(s); DiMe, Childhood Diabetes in Finland Study; FPIR, first-phase insulin response; GADA, antibodies to the 65 kDa isoform of glutamic acid decarboxylase; HLA, human leukocyte antigen; IA-2A, antibodies to the IA-2 protein; IAA, insulin autoantibodies; ICA, islet cell antibodies; IVGTT, iv glucose tolerance test; OR, odds ratio(s); RU, relative units.
Received April 25, 2002.
Accepted March 11, 2003.
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| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Endocrinology | Endocrine Reviews | J. Clin. End. & Metab. |
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