Rapid, Loop-Mediated Isothermal Amplification Detection of Celiac Disease Risk Alleles.

Human leukocyte antigen (HLA) genotyping has become a useful investigation in the diagnostic work-up of celiac disease (CD), with utility in risk stratification and screening. However, broad application of this technology has been hindered by the cost and time burden of conventional laboratory-based assays. We have developed and validated CD-loop-mediated isothermal amplification (CD-LAMP), a LAMP assay, which enables rapid identification of the signature CD risk genotypes, HLA-DQ2.5, HLA-DQ8, HLA-DQ2.2, and HLA-DQA1*05. Sample-to-answer is achieved in approximately 65 minutes without DNA purification, thermal cycling, or specialized analytical equipment. CD-LAMP genotyping of samples was 100% concordant with accredited pathology genotyping on a panel of 40 blood and 20 saliva samples. In a panel of 100 purified DNA samples, genotyping of the high-risk DQ2.5 genotype was 100% concordant with accredited pathology genotyping, with slightly reduced sensitivity for the DQ8 genotype (97.1%) and reduced specificity for the DQ8 (93.9%) and DQ2.2 (95.1%) genotypes. CD-LAMP results are easily visualized and instrument free through the addition of a DNA intercalating dye after amplification. Combined with point-of-care antibody testing, CD-LAMP may enable immediate, confident CD diagnosis at a low cost in the clinical setting.

Receiver operating characteristic analysis of HLA, CTLA4, and insulin genotypes for type 1 diabetes.

OBJECTIVE: This study assessed the ability to distinguish between type 1 diabetes-affected individuals and their unaffected relatives using HLA and single nucleotide polymorphism (SNP) genotypes. RESEARCH DESIGN AND METHODS: Eight models, ranging from only the high-risk DR3/DR4 genotype to all significantly associated HLA genotypes and two SNPs mapping to the cytotoxic T-cell-associated antigen-4 gene (CTLA4) and insulin (INS) genes, were fitted to high-resolution class I and class II HLA genotyping data for patients from the Type 1 Diabetes Genetics Consortium collection. Pairs of affected individuals and their unaffected siblings were divided into a "discovery" (n = 1,015 pairs) and a "validation" set (n = 318 pairs). The discriminating performance of various combinations of genetic information was estimated using receiver operating characteristic (ROC) curve analysis. RESULTS: The use of only the presence or absence of the high-risk DR3/DR4 genotype achieved very modest discriminating ability, yielding an area under the curve (AUC) of 0.62 in the discovery set and 0.59 in the validation set. The full model-which included HLA information from the class II loci DPB1, DRB1, and DQB1; selected alleles from HLA class I loci A and B; and SNPs from the CTLA4 and INS genes-increased the AUC to 0.74 in the discovery set and to 0.71 in the validation set. A cost-effective alternative is proposed, using genotype information equivalent to typing four SNPs (DR3, DR4-DQB1*03:02, CTLA-4, and INS), which achieved an AUC of 0.72 in the discovery set and 0.69 in the validation set. CONCLUSIONS: Genotyping data sufficient to tag DR3, DR4-DQB1*03:02, CTLA4, and INS were shown to distinguish between subjects with type 1 diabetes and their unaffected siblings adequately to achieve clinically utility to identify children in multiplex families to be considered for early intervention.

Definition of high-risk type 1 diabetes HLA-DR and HLA-DQ types using only three single nucleotide polymorphisms.

Evaluating risk of developing type 1 diabetes (T1D) depends on determining an individual's HLA type, especially of the HLA DRB1 and DQB1 alleles. Individuals positive for HLA-DRB1*03 (DR3) or HLA-DRB1*04 (DR4) with DQB1*03:02 (DQ8) have the highest risk of developing T1D. Currently, HLA typing methods are relatively expensive and time consuming. We sought to determine the minimum number of single nucleotide polymorphisms (SNPs) that could rapidly define the HLA-DR types relevant to T1D, namely, DR3/4, DR3/3, DR4/4, DR3/X, DR4/X, and DRX/X (where X is neither DR3 nor DR4), and could distinguish the highest-risk DR4 type (DR4-DQ8) as well as the non-T1D-associated DR4-DQB1*03:01 type. We analyzed 19,035 SNPs of 10,579 subjects (7,405 from a discovery set and 3,174 from a validation set) from the Type 1 Diabetes Genetics Consortium and developed a novel machine learning method to select as few as three SNPs that could define the HLA-DR and HLA-DQ types accurately. The overall accuracy was 99.3%, area under curve was 0.997, true-positive rates were >0.99, and false-positive rates were <0.001. We confirmed the reliability of these SNPs by 10-fold cross-validation. Our approach predicts HLA-DR/DQ types relevant to T1D more accurately than existing methods and is rapid and cost-effective.

Methods for diagnostic HLA typing in disease association and drug hypersensitivity.

This chapter describes the application of diagnostic HLA typing for disease association and five methods used for specific HLA genotypes. The methods utilise a combination of polymerase chain reaction (PCR) amplification to detect sequence polymorphism by the presence or absence of amplification, nucleotide sequencing of the PCR product, and hybridisation of the PCR product with labelled probes. The probes are specific for sequence polymorphism associated with the genotype and are attached to either a Micro Bead or a Solid Phase. In addition, the detection of single nucleotide polymorphism(s) which "tag" for the genotype using a real-time PCR is described.

A polymorphism in the HLA-DPB1 gene is associated with susceptibility to multiple sclerosis.

We conducted an association study across the human leukocyte antigen (HLA) complex to identify loci associated with multiple sclerosis (MS). Comparing 1927 SNPs in 1618 MS cases and 3413 controls of European ancestry, we identified seven SNPs that were independently associated with MS conditional on the others (each P ≤ 4 x 10(-6)). All associations were significant in an independent replication cohort of 2212 cases and 2251 controls (P ≤ 0.001) and were highly significant in the combined dataset (P ≤ 6 x 10(-8)). The associated SNPs included proxies for HLA-DRB1*15:01 and HLA-DRB1*03:01, and SNPs in moderate linkage disequilibrium (LD) with HLA-A*02:01, HLA-DRB1*04:01 and HLA-DRB1*13:03. We also found a strong association with rs9277535 in the class II gene HLA-DPB1 (discovery set P = 9 x 10(-9), replication set P = 7 x 10(-4), combined P = 2 x 10(-10)). HLA-DPB1 is located centromeric of the more commonly typed class II genes HLA-DRB1, -DQA1 and -DQB1. It is separated from these genes by a recombination hotspot, and the association is not affected by conditioning on genotypes at DRB1, DQA1 and DQB1. Hence rs9277535 represents an independent MS-susceptibility locus of genome-wide significance. It is correlated with the HLA-DPB1*03:01 allele, which has been implicated previously in MS in smaller studies. Further genotyping in large datasets is required to confirm and resolve this association.

HLA class I and genetic susceptibility to type 1 diabetes: results from the Type 1 Diabetes Genetics Consortium.

OBJECTIVE: We report here genotyping data and type 1 diabetes association analyses for HLA class I loci (A, B, and C) on 1,753 multiplex pedigrees from the Type 1 Diabetes Genetics Consortium (T1DGC), a large international collaborative study. RESEARCH DESIGN AND METHODS: Complete eight-locus HLA genotyping data were generated. Expected patient class I (HLA-A, -B, and -C) allele frequencies were calculated, based on linkage disequilibrium (LD) patterns with observed HLA class II DRB1-DQA1-DQB1 haplotype frequencies. Expected frequencies were compared to observed allele frequencies in patients. RESULTS: Significant type 1 diabetes associations were observed at all class I HLA loci. After accounting for LD with HLA class II, the most significantly type 1 diabetes-associated alleles were B*5701 (odds ratio 0.19; P = 4 × 10(-11)) and B*3906 (10.31; P = 4 × 10(-10)). Other significantly type 1 diabetes-associated alleles included A*2402, A*0201, B*1801, and C*0501 (predisposing) and A*1101, A*3201, A*6601, B*0702, B*4403, B*3502, C*1601, and C*0401 (protective). Some alleles, notably B*3906, appear to modulate the risk of all DRB1-DQA1-DQB1 haplotypes on which they reside, suggesting a class I effect that is independent of class II. Other class I type 1 diabetes associations appear to be specific to individual class II haplotypes. Some apparent associations (e.g., C*1601) could be attributed to strong LD to another class I susceptibility locus (B*4403). CONCLUSIONS: These data indicate that HLA class I alleles, in addition to and independently from HLA class II alleles, are associated with type 1 diabetes.

HLA genotyping in the international Type 1 Diabetes Genetics Consortium.

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.

Collection and processing of whole blood for transformation of peripheral blood mononuclear cells and extraction of DNA: the Type 1 Diabetes Genetics Consortium.

BACKGROUND: and PURPOSE: To yield large amounts of DNA for many genotype analyses and to provide a renewable source of DNA, the Type 1 Diabetes Genetics Consortium (T1DGC) harvested DNA and peripheral blood mononuclear cells (PBMCs) from individuals with type 1 diabetes and their family members in several regions of the world. METHODS: DNA repositories were established in Asia-Pacific, Europe, North America, and the United Kingdom. To address region-specific needs, different methods and sample processing techniques were used among the laboratories to extract and to quantify DNA and to establish Epstein-Barr virus transformed cell lines. RESULTS: More than 98% of the samples of PBMCs were successfully transformed. Approximately 20-25 microg of DNA were extracted per mL of whole blood. Extraction of DNA from the cell pack ranged from 92 to 165 microg per cell pack. In addition, the extracted DNA from whole blood or transformed cells was successfully utilized in each regional human leukocyte antigen genotyping laboratory and by several additional laboratories performing consortium-wide genotyping projects. LIMITATIONS: Although the isolation of PBMCs was consistent among sites, the measurement of DNA was difficult to harmonize. CONCLUSIONS: DNA repositories can be established in different regions of the world and produce similar amounts of high-quality DNA for a variety of high-throughput genotyping techniques. Furthermore, even with the distances and time necessary for transportation, highly efficient transformation of PBMCs is possible. For future studies/trials involving several laboratories in different locations, the T1DGC experience includes examples of protocols that may be applicable. In summary, T1DGC has developed protocols that would be of interest to any scientific organization attempting to overcome the logistical problems associated with studies/trials spanning multiple research facilities, located in different regions of the world.

HLA DPA1, DPB1 alleles and haplotypes contribute to the risk associated with type 1 diabetes: analysis of the type 1 diabetes genetics consortium families.

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.

Differential dynamics of donor DC and non-DC peripheral blood mononuclear cell microchimerism in lung transplantation.

Donor cell microchimerism induces tolerance in animal models and may increase graft survival in man. Since dendritic cells (DC) are critical for induction of both tolerance and alloreactivity we developed a method to quantitate microchimerism in donor DC and non-DC in peripheral blood mononuclear cells (PBMC) after lung transplantation. Longitudinal analysis of donor cell microchimerism in eleven sex mismatched lung transplant recipients (LTR) up to 12 months post-transplant used Y chromosome based real-time PCR on sorted cells. Total DC or a proportion of DC subsets in PBMC did not change but there were heterogeneous and dynamic changes in microchimerism in DC and non-DC. Analysis of changes in DC using a mixed model analysis showed significantly less reduction in DC compared to non-DC over time (0.49, p=0.001). Preferential DC persistence compared to non-DC may indicate tolerance induction but future studies are required to determine if DC microchimerism after transplantation affects clinical outcomes.

The rising incidence of type 1 diabetes is accounted for by cases with lower-risk human leukocyte antigen genotypes.

OBJECTIVE: The rising incidence of type 1 diabetes has been attributed to environment, implying a lesser role for genetic susceptibility. However, the rise could be accounted for by either more cases with classic high-risk genes or by cases with other risk genes. Separately, for any degree of genetic susceptibility, age at presentation may decrease in a permissive environment. To examine these possibilities, human leukocyte antigen (HLA) class II DRB1 genes known to confer risk for type 1 diabetes were analyzed in relation to year of birth and age at diagnosis over the last five decades. RESEARCH DESIGN AND METHODS: Caucasoid subjects (n = 462) diagnosed with type 1 diabetes before age 18 between 1950 and 2005 were DRB1 genotyped. RESULTS: Mean +/- SD age at diagnosis, 8.5 +/- 4.5 years, did not differ across decades. Recent diagnosis was associated with a lower proportion but unchanged incidence of the highest-risk DRB1 genotype DR3,4 (2000-2005, 28% vs. 1950-1969, 79%; P < 0.0001) and a higher proportion of lower-risk genotypes DR4,X and DR3,X (2000-2005, 48% vs. 1950-1969, 20%; P = 0.0002). The frequency of the DRX,X genotype was low (