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Summary: Patients with high-risk human leukocyte antigen (HLA)-DR-DQ genotypes for type 1 diabetes (T1D) were compared with HLA-matched controls to evaluate T1D risk for other HLA loci, including HLA-A, -B, -Cw, and DPB1. Patients (n = 133) with high-risk genotypes (DR3/DR3, DR3/DR4, DR4/DR4) were selected from the Lazio (Rome) region of Italy. Screening of more than 9000 patients from the Lazio region and northern Italy yielded 162 controls with high-T1D-risk haplotypes. Although the overall distributions did not differ significantly, allele frequency differences were discovered between the controls from Lazio and controls from northern Italy for some alleles previously determined to affect T1D risk, such as A*3002, DPB1*0301, and DPB1*0402. Therefore, Lazio patient data were compared both with the Lazio subset of controls (n = 53) and with the entire group of controls for association analyses. Significant allele frequency differences between patients and DR-DQ-matched controls existed for specific alleles at all loci. Data for the DR3/DR3 subset of patients and controls demonstrated an increase of Cw*0702 in patients. Compared with controls, reduced patient frequencies were seen for several alleles, including A*0101, B*0801, and Cw*0701, all on the highly conserved, extended DR3 haplotype known as 8.1 in DR3/DR3, but not DR3/DR4, subgroup. DPB1*0101, often reported on 8.1 haplotypes, was also less frequent in DR3/DR3 patients than controls. Analysis of family-based data from the HBDI repository was consistent with the observed results from the Italian patients, indicating the presence of a T1D-protective locus at or near A*0101 and a second T1D-protective locus at or near DPB1*0101. These data indicate that T1D risk conferred by the 8.1 haplotype is genotype dependent. [Copyright &y& Elsevier]

Aims/hypothesis: The study aimed to assess, in multiple populations, the role of HLA alleles on early and late age at onset of type 1 diabetes., Methods: Stepwise linear regression models were used to determine which HLA class I and class II risk alleles to include. High-resolution genotyping data for patients from the Type 1 Diabetes Genetics Consortium (T1DGC) collection (n = 2,278) and four independent cohorts from Denmark, Sardinia and the USA (Human Biological Data Interchange [HBDI] and Joslin Diabetes Center) (n = 1,324) (total n = 3,602) were used to assess the role of HLA variation on age of onset and predict early onset (age ≤ 5 years) and late onset (age ≥ 15 years) of type 1 diabetes., Results: In addition to carriage of HLA class I alleles A*24:02, B*39:06, B*44:03 and B*18:01, HLA class II DRB1-DQB1 loci significantly contributed to age at onset, explaining 3.4% of its variance in the combined data. HLA genotypes, together with sex, were able to predict late onset in all cohorts studied, with AUC values ranging from 0.58 to 0.63. Similar AUC values (0.59-0.70) were obtained for early onset for most cohorts, except in the Sardinian study, in which none of the models tested had significant predictive power., Conclusions/interpretation: HLA associations with age of onset are consistent across most white populations and HLA information can predict some of the risk of early and late onset of type 1 diabetes. Considerable heterogeneity was observed between Sardinian and other populations, particularly with regard to early age of onset.

Mutational processes of simple sequence repeats (SSRs) in complex genomes are poorly understood. We examined these processes by introducing a two-phase mutation model. In this model, most mutations are single-step changes, but infrequent large jumps in repeat number also occur. We used computer simulations to determine expected values of statistics that reflect frequency distributions of allele size for the two-phase model and two alternatives, the one-step and geometric models. The theoretical expectations for each model were tested by comparison with observed values for 10 SSR loci genotyped in the Sardinian population, whose genetic and demographic histories have been previously reconstructed. The two-phase model provided the best fit to the data for most of these loci in this population. In the analysis we assumed that the loci were neutral and that this population had undergone rapid population growth. Recent observations made for unstable trinucleotide repeats support our suggestion that frequent small changes and rare large changes in repeat number represent two distinct classes of mutation at SSR loci. We genotyped the same 10 loci in Egyptian and sub-Saharan African samples to assess the utility of SSRs for studying the divergence of populations and found that estimates of interpopulation distances from SSRs were similar to those derived from analysis of mitochondrial DNA.