A comparison of three statistical models for IDDM associations with HLA

Non-HLA type 1 diabetes genes modulate disease risk together with HLA-DQ and islet autoantibodies

The possible interrelations between HLA-DQ, non-HLA single nucleotide polymorphisms (SNPs) and islet autoantibodies were investigated at clinical onset in 1-34 year old type 1 diabetes (T1D) patients (n=305) and controls (n=203). Among the non-HLA SNPs reported by the Type 1 Diabetes Genetics Consortium, 24% were supported in this Swedish replication set including that the increased risk of minor PTPN22 allele and high risk HLA was modified by GAD65 autoantibodies. The association between T1D and the minor AA+AC genotype in ERBB3 gene was stronger among IA-2 autoantibody-positive patients (comparison p=0.047). The association between T1D and the common insulin (AA) genotype was stronger among insulin autoantibody (IAA)-positive patients (comparison p=0.008). In contrast, the association between T1D and unidentified 26471 gene was stronger among IAA-negative (comparison p=0.049) and IA-2 autoantibody-negative (comparison p=0.052) patients. Finally, the association between IL2RA and T1D was stronger among IAA-positive than among IAA-negative patients (comparison p=0.028). These results suggest that the increased risk of T1D by non-HLA genes is often modified by both islet autoantibodies and HLA-DQ. The interactions between non-HLA genes, islet autoantibodies and HLA-DQ should be taken into account in T1D prediction studies as well as in prevention trials aimed at inducing immunological tolerance to islet autoantigens.

Temporal trends of HLA genotype frequencies of type 1 diabetes patients in Sweden from 1986 to 2005 suggest altered risk

The aim of this study was to compare the frequency of human leukocyte antigen (HLA) genotypes in 1-18-year-old patients with type 1 diabetes newly diagnosed in 1986-1987 (n = 430), 1996-2000 (n = 342) and in 2003-2005 (n = 171). We tested the hypothesis that the HLA DQ genotype distribution changes over time. Swedish type 1 diabetes patients and controls were typed for HLA using polymerase chain reaction amplification and allele specific probes for DQ A1* and B1* alleles. The most common type 1 diabetes HLA DQA1*-B1*genotype 0501-0201/0301-0302 was 36% (153/430) in 1986-1987 and 37% (127/342) in 1996-2000, but decreased to 19% (33/171) in 2003-2005 (P \ 0.0001). The 0501-0201/0501-0201 genotype increased from 1% in 1986-1987 to 7% in 1996-2000 (P = 0.0047) and to 5% in 2003-2005 (P > 0.05). This study in 1-18-year-old Swedish type 1 diabetes patients supports the notion that there is a temporal change in HLA risk.

Genetic and perinatal factors as risk for childhood type 1 diabetes

The mechanisms by which gestational infections, blood incompatibility, birth weight, mother's age and other prenatal or neonatal events increase the risk for type 1 diabetes are not understood. Studies so far have been retrospective, and there is a lack of population-based prospective studies. The possibility of identifying children at type 1 diabetes risk among first-degree relatives has resulted in prospective studies aimed at identifying postnatal events associated with the appearance of autoantibody markers for type 1 diabetes and a possible later onset of diabetes. However, the majority (85%) of new onset type 1 diabetes children do not have a first-degree relative with the disease. Population-based studies are therefore designed to prospectively analyse pregnant mothers and their offspring. One such study is DiPiS (Diabetes Prediction in Skåne), which is examining a total of about 10,000 pregnancies expected every year in the Skåne (Scania) region of Sweden that has 1.1 million inhabitants. Blood samples from all mothers in this region are obtained during pregnancy and at the time of delivery. Cord blood is analysed for HLA high-risk alleles and for autoantibodies against the 65 kD isoform of glutamic acid decarboxylase (GADA), the protein tyrosine phosphatase-related IA-2 antigen (IA-2A) and insulin (IAA) as a measure of prenatal autoimmune exposure. Identifying high-risk children by genetic, autoimmune and gestational risk factors followed by prospective analyses will make it possible to test the hypothesis that gestational events may trigger beta cell autoimmunity as a prerequisite for childhood type 1 diabetes.

Complex interaction between HLA DR and DQ in conferring risk for childhood type 1 diabetes

Type 1 (insulin-dependent) diabetes mellitus is associated with HLA DR and DQ factors, but the primary risk alleles are difficult to identify because recombination events are rare in the DQ-DR region. The risk of HLA genotypes for type 1 diabetes was therefore studied in more than 420 incident new onset, population-based type 1 diabetes children and 340 age, sex and geographically matched controls from Sweden. A stepwise approach was used to analyse risk by relative and absolute risks, stratification analysis and the predispositional allele test. The strongest relative and absolute risks were observed for DQB1*02-DQA1*0501/DQB1*0302-DQA1*0301 heterozygotes (AR 1/46, P < 0.001) or the simultaneous presence of both DRB1*03 and DQB1*0302 (AR 1/52, P < 0.001). Stratification analysis showed that DQB1*0302 was more frequent among DRB1*04 patients than DRB1*04 controls (P < 0.001), while DRB1*03 was more frequent among both DQA1*0501 (P < 0.001) and DQB1*02 (P < 0.001) patients than respective controls. The predispositional allele test indicated that DRB1*03 (P < 0.001) would be the predominant risk factor on the DRB1*03-DQA1*0501-DQB1*02 haplotype. In contrast, although DQB1*0302 (P < 0.001) would be the predominant risk factor on the DRB1*04-DQA1*0301-DQB1*0302 haplotype, the predispositional allele test also showed that DRB1*0401, but no other DRB1*04 subtype, had an additive risk to that of DQB1*0302 (P < 0.002). It is concluded that the association between type 1 diabetes and HLA is due to a complex interaction between DR and DQ since (1) DRB1*03 was more strongly associated with the disease than DQA1*0501-DQB1*02 and (2) DRB1*0401 had an additive effect to DQB1*0302. The data from this population-based investigation suggest an independent role of DR in the risk of developing type 1 diabetes, perhaps by providing diseases-promoting transcomplementation molecules.

A unified approach to the analysis of case-distribution (case-only) studies

A number of new study designs have appeared in which the exposure distribution of a case series is compared to an exposure distribution representing a complete theoretical population or distribution. These designs include the case-genotype study, the case-cross-over study, and the case-specular study. This paper describes a unified likelihood-based approach to the analysis of such studies, and discusses extensions of these methods when a control group is available. The approach clarifies certain assumptions implicit in the methods, and helps contrast these assumptions to those underlying ordinary case-control studies. There are several reasons to expect discrepancies between ordinary case-control estimates and case-distribution estimates; for example, case-distribution estimates can be more sensitive to exposure misclassification. Some discrepancies are illustrated in an application to case-specular data on wire codes and childhood cancer.