Immunogenetics of HLA class II in Israeli patients with adult-onset type 1 diabetes mellitus.

The distribution of HLA class II alleles and genotypes in Israelis of different ethnic origin with adult-onset type 1 diabetes (T1D) was examined. The results were compared with published findings in healthy Israelis and childhood-onset T1D Israelis. An additional comparison was made between subgroups of patients with rapidly and slowly progressive adult-onset T1D (LADA). A DNA-based low-resolution analysis was performed for DRB1* and DQB1* alleles and a high-resolution analysis for DRB1*04 and DQB1*1 alleles. In all, 87% of the study group was positive for DRB1*03 or DRB1*04 compared with 36% of the healthy controls. The main alleles accounting for susceptibility to T1D were DRB1*0402, found in 77.9% of carriers of DRB1*04 and DQB1*0302, found in 74.6% of carriers of DQB1*03. The DQB1*0602 was not detected in any patient. The distribution was similar to that reported in Israeli children with T1D and significantly different from healthy Israelis. There was no significant difference in the distribution of HLA class II alleles between patients with rapidly progressive T1D or LADA. It may be concluded that the different ages of onset of T1D and its different forms of development in Israeli patients are apparently not caused by a different prevalence of HLA class II alleles.

Hematopoietic chimerism monitoring based on STRs: quantitative platform performance on sequential samples.

Hematopoietic stem cell transplantation (HSCT) creates a donor-recipient cellular chimerism in the patient, which is quantitatively assayed from peripheral blood based on STR-DNA. Since chimerism values often vary across a patient's samples, it is important to determine to what extent this variability reflects technical aspects of platform performance. This issue is systematically assessed in the current study for the first time. Using the SGM Plus multiplex PCR kit and ABI platform, the longitudinal performance of STR markers was quantitatively evaluated in two chimeric models with true values, and in patient samples (n >500 marker loci). Computation of percent chimerism for each marker, and mean (sample) percent chimerism, standard deviation, and coefficient of variance was performed by our ChimerTrack utility. In chimeric models with known values, individual markers exhibited an accuracy (observed/true) of 88-98%; replication precision was 92-100% true, with a mean error of 2%. Fragment size calling was greater than 99% accurate and precise. Patient results were comparable for markers, relaive to sample means. One source of technical variability in chimerism estimation was allelic differential amplification efficiency. The latter was influenced by signal amplitude, dye label, marker size, and allelic size interval. It can be concluded that long-term chimeric tracking is routinely feasible using this platform in conjunction with ChimerTrack software. Importantly, mean percent chimerism, for any sample, should closely approximate the true chimeric status, with a technical accuracy of 98%. Guidelines are presented for selecting an optimized marker profile.