Next generation sequencing of HLA exonic amplicons with the 454 Life Sciences GS FLX System and Conexio AssignTM-ATF software provides high resolution, high throughput HLA genotyping for 8 class I and class II loci (Bentley et al., 20091, Holcomb et al., 20112). HLA typing of potential donors for Unrelated Bone Marrow Donor Registries requires using a subset of these loci at high sample throughput and low cost per sample. To maximize the throughput, we have incorporated the Fluidigm® Access ArrayTM system to simplify amplicon library preparation and allow the efficient introduction of MIDs (Multiplex Identifiers) or barcodes. For this application, a streamlined amplicon sequencing workflow employing many different Multiplex Identifiers (MIDs) enables multiplexed sequencing of a large number of samples, allowing researchers to meet these cost targets. The Fluidigm® 48 x 48 Access ArrayTM system and the “4 primer” approach provides an efficient way to achieve parallel semi-automated genomic PCRs with simultaneous incorporation of 48 different MIDs corresponding to 48 genomic DNA samples, and up to 48 different primer pairs, making possible 2,304 reactions in one amplification run. Minimal volumes (calculated to be about 45% less cost per run) of reagents are used in this micro- fluidics-based system. During genomic PCR, the outer set of primers containing the MIDs and the 454 adaptor sequences are incorporated into the amplicons generated by the inner set of HLA specific primers containing a complementary “universal” Fluidigm tag. Pools of the resulting amplicons are used for emulsion PCR and clonal sequencing on the 454 GS FLX System, as well as genotyping with Conexio AssignTM-ATF software. Using the Access Array system, we have successfully (100% concordance with known genotypes) genotyped 192 samples with 8 primer pairs (covering exons 2 and 3 in HLA-A, B, C and Exon 2 in DRB1, DRB3/4/5 and DQB1) using 96 MIDs per region in a single GS FLX run on a 2 region PicoTiterPlate™ (PTP) and 96 samples using 48 MIDs per region in a 4 region PTP. An average of 166 and 137 sequence reads per amplicon were recovered respectively. We have also genotyped, in a single run, 96 samples at high resolution (14 primer pairs covering exons 2, 3, and 4 of the class I loci and exons 2 of DRB1,3/4/5, DQA1, DQB1, DPB1, and exon 3 of DQB1) recovering an average of 175 sequence reads per amplicon at 100% concordance. The system reduces the overall time for the entire process (192 samples) from 8 days for manual processing to about 4 days with 1 FTE.

OBJECTIVE To determine the relative risk associated with DPA1 and DPB1 alleles and haplotypes in type 1 diabetes. RESEARCH DESIGN AND METHODS The frequency of DPA1 and DPB1 alleles and haplotypes in type 1 diabetic patients was compared to the family based control frequency in 1,771 families directly and conditional on HLA (B)-DRB1-DQA1-DQB1 linkage disequilibrium. A relative predispositional analysis (RPA) was performed in the presence or absence of the primary HLA DR-DQ associations and the contribution of DP haplotype to individual DR-DQ haplotype risks examined. RESULTS Eight DPA1 and thirty-eight DPB1 alleles forming seventy-four DPA1-DPB1 haplotypes were observed; nineteen DPB1 alleles were associated with multiple DPA1 alleles. Following both analyses, type 1 diabetes susceptibility was significantly associated with DPB1*0301 (DPA1*0103-DPB1*0301) and protection with DPB1*0402 (DPA1*0103-DPB1*0402) and DPA1*0103-DPB1*0101 but not DPA1*0201-DPB1*0101. In addition, DPB1*0202 (DPA1*0103-DPB1*0202) and DPB1*0201 (DPA1*0103-DPB1*0201) were significantly associated with susceptibility in the presence of the high risk and protective DR-DQ haplotypes. Three associations (DPB1*0301, *0402, and *0202) remained statistically significant when only the extended HLA-A1-B8-DR3 haplotype was considered, suggesting that DPB1 alone may delineate the risk associated with this otherwise conserved haplotype. CONCLUSIONS HLA DP allelic and haplotypic diversity contributes significantly to the risk for type 1 diabetes; DPB1*0301 (DPA1*0103-DPB1*0301) is associated with susceptibility and DPB1*0402 (DPA1*0103-DPB1*0402) and DPA1*0103-DPB1*0101 with protection. Additional evidence is presented for the susceptibility association of DPB1*0202 (DPA1*0103-DPB1*0202) and for a contributory role of individual amino acids and DPA1 or a gene in linkage disequilibrium in DR3-DPB1*0101 positive haplotypes.

Background Although human leukocyte antigen (HLA) DQ and DR loci appear to confer the strongest genetic risk for type 1 diabetes, more detailed information is required for other loci within the HLA region to understand causality and stratify additional risk factors. The Type 1 Diabetes Genetics Consortium (T1DGC) study design included high-resolution genotyping of HLA-A, B, C, DRB1, DQ, and DP loci in all affected sibling pair and trio families, and cases and controls, recruited from four networks worldwide, for analysis with clinical phenotypes and immunological markers.Purpose In this article, we present the operational strategy of training, classification, reporting, and quality control of HLA genotyping in four laboratories on three continents over nearly 5 years.Methods Methods to standardize HLA genotyping at eight loci included: central training and initial certification testing; the use of uniform reagents, protocols, instrumentation, and software versions; an automated data transfer; and the use of standardized nomenclature and allele databases. We implemented a rigorous and consistent quality control process, reinforced by repeated workshops, yearly meetings, and telephone conferences.Results A total of 15,246 samples have been HLA genotyped at eight loci to four-digit resolution; an additional 6797 samples have been HLA genotyped at two loci. The genotyping repeat rate decreased significantly over time, with an estimated unresolved Mendelian inconsistency rate of 0.21%. Annual quality control exercises tested 2192 genotypes (4384 alleles) and achieved 99.82% intra-laboratory and 99.68% inter-laboratory concordances.Limitations The chosen genotyping platform was unable to distinguish many allele combinations, which would require further multiple stepwise testing to resolve. For these combinations, a standard allele assignment was agreed upon, allowing further analysis if required.Conclusions High-resolution HLA genotyping can be performed in multiple laboratories using standard equipment, reagents, protocols, software, and communication to produce consistent and reproducible data with minimal systematic error. Many of the strategies used in this study are generally applicable to other large multi-center studies. Clinical Trials 2010; 7: S75-S87. http://ctj.sagepub.com.

OBJECTIVE To determine the relative risk associated with DPA1 and DPB1 alleles and haplotypes in type 1 diabetes. RESEARCH DESIGN AND METHODS The frequency of DPA1 and DPB1 alleles and haplotypes in type 1 diabetic patients was compared to the family based control frequency in 1,771 families directly and conditional on HLA (B)-DRB1-DQA1-DQB1 linkage disequilibrium. A relative predispositional analysis (RPA) was performed in the presence or absence of the primary HLA DR-DQ associations and the contribution of DP haplotype to individual DR-DQ haplotype risks examined. RESULTS Eight DPA1 and thirty-eight DPB1 alleles forming seventy-four DPA1-DPB1 haplotypes were observed; nineteen DPB1 alleles were associated with multiple DPA1 alleles. Following both analyses, type 1 diabetes susceptibility was significantly associated with DPB1*0301 (DPA1*0103-DPB1*0301) and protection with DPB1*0402 (DPA1*0103-DPB1*0402) and DPA1*0103-DPB1*0101 but not DPA1*0201-DPB1*0101. In addition, DPB1*0202 (DPA1*0103-DPB1*0202) and DPB1*0201 (DPA1*0103-DPB1*0201) were significantly associated with susceptibility in the presence of the high risk and protective DR-DQ haplotypes. Three associations (DPB1*0301, *0402, and *0202) remained statistically significant when only the extended HLA-A1-B8-DR3 haplotype was considered, suggesting that DPB1 alone may delineate the risk associated with this otherwise conserved haplotype. CONCLUSIONS HLA DP allelic and haplotypic diversity contributes significantly to the risk for type 1 diabetes; DPB1*0301 (DPA1*0103-DPB1*0301) is associated with susceptibility and DPB1*0402 (DPA1*0103-DPB1*0402) and DPA1*0103-DPB1*0101 with protection. Additional evidence is presented for the susceptibility association of DPB1*0202 (DPA1*0103-DPB1*0202) and for a contributory role of individual amino acids and DPA1 or a gene in linkage disequilibrium in DR3-DPB1*0101 positive haplotypes.

OBJECTIVE—The Type 1 Diabetes Genetics Consortium has collected type 1 diabetic families worldwide for genetic analysis. The major genetic determinants of type 1 diabetes are alleles at the HLA-DRB1 and DQB1 loci, with both susceptible and protective DR-DQ haplotypes present in all human populations. The aim of this study is to estimate the risk conferred by specific DR-DQ haplotypes and genotypes.RESEARCH DESIGN AND METHODS:—Six hundred and seven Caucasian families and 38 Asian families were typed at high resolution for the DRB1, DQA1, and DQB1 loci. The association analysis was performed by comparing the frequency of DR-DQ haplotypes among the chromosomes transmitted to an affected child with the frequency of chromosomes not transmitted to any affected child.RESULTS—A number of susceptible, neutral, and protective DR-DQ haplotypes have been identified, and a statistically significant hierarchy of type 1 diabetes risk has been established. The most susceptible haplotypes are the DRB1*0301-DQA1*0501-DQB1*0201 (odds ratio [OR] 3.64) and the DRB1*0405-DQA1*0301-DQB1*0302, DRB1*0401-DQA1*0301-DQB*0302, and DRB1*0402-DQA1*0301-DQB1*0302 haplotypes (ORs 11.37, 8.39, and 3.63), followed by the DRB1*0404-DQA1*0301-DQB1*0302 (OR 1.59) and the DRB1*0801-DQB1*0401-DQB1*0402 (OR 1.25) haplotypes. The most protective haplotypes are DRB1*1501-DQA1*0102-DQB1*0602 (OR 0.03), DRB1*1401-DQA1*0101-DQB1*0503 (OR 0.02), and DRB1*0701-DQA1*0201-DQB1*0303 (OR 0.02).CONCLUSIONS—Specific combinations of alleles at the DRB1, DQA1, and DQB1 loci determine the extent of haplotypic risk. The comparison of closely related DR-DQ haplotype pairs with different type 1 diabetes risks allowed identification of specific amino acid positions critical in determining disease susceptibility. These data also indicate that the risk associated with specific HLA haplotypes can be influenced by the genotype context and that the trans-complementing heterodimer encoded by DQA1*0501 and DQB1*0302 confers very high risk.