Oral Insulin Delay of Stage 3 Type 1 Diabetes Revisited in HLA DR4-DQ8 Participants in the TrialNet Oral Insulin Prevention Trial (TN07).

OBJECTIVE: To explore if oral insulin could delay onset of stage 3 type 1 diabetes (T1D) among patients with stage 1/2 who carry HLA DR4-DQ8 and/or have elevated levels of IA-2 autoantibodies (IA-2As). RESEARCH AND METHODS: Next-generation targeted sequencing technology was used to genotype eight HLA class II genes (DQA1, DQB1, DRB1, DRB3, DRB4, DRB5, DPA1, and DPB1) in 546 participants in the TrialNet oral insulin preventative trial (TN07). Baseline levels of autoantibodies against insulin (IAA), GAD65 (GADA), and IA-2A were determined prior to treatment assignment. Available clinical and demographic covariables from TN07 were used in this post hoc analysis with the Cox regression model to quantify the preventive efficacy of oral insulin. RESULTS: Oral insulin reduced the frequency of T1D onset among participants with elevated IA-2A levels (HR 0.62; P = 0.012) but had no preventive effect among those with low IA-2A levels (HR 1.03; P = 0.91). High IA-2A levels were positively associated with the HLA DR4-DQ8 haplotype (OR 1.63; P = 6.37 × 10-6) and negatively associated with the HLA DR7-containing DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02 extended haplotype (OR 0.49; P = 0.037). Among DR4-DQ8 carriers, oral insulin delayed the progression toward stage 3 T1D onset (HR 0.59; P = 0.027), especially if participants also had high IA-2A level (HR 0.50; P = 0.028). CONCLUSIONS: These results suggest the presence of a T1D endotype characterized by HLA DR4-DQ8 and/or elevated IA-2A levels; for those patients with stage 1/2 disease with such an endotype, oral insulin delays the clinical T1D onset.

HLA Class II (DR, DQ, DP) Genes Were Separately Associated With the Progression From Seroconversion to Onset of Type 1 Diabetes Among Participants in Two Diabetes Prevention Trials (DPT-1 and TN07).

OBJECTIVE: To explore associations of HLA class II genes (HLAII) with the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: Next-generation targeted sequencing was used to genotype eight HLAII genes (DQA1, DQB1, DRB1, DRB3, DRB4, DRB5, DPA1, DPB1) in 1,216 participants from the Diabetes Prevention Trial-1 and Randomized Diabetes Prevention Trial with Oral Insulin sponsored by TrialNet. By the linkage disequilibrium, DQA1 and DQB1 are haplotyped to form DQ haplotypes; DP and DR haplotypes are similarly constructed. Together with available clinical covariables, we applied the Cox regression model to assess HLAII immunogenic associations with the disease progression. RESULTS: First, the current investigation updated the previously reported genetic associations of DQA1*03:01-DQB1*03:02 (hazard ratio [HR] = 1.25, P = 3.50*10-3) and DQA1*03:03-DQB1*03:01 (HR = 0.56, P = 1.16*10-3), and also uncovered a risk association with DQA1*05:01-DQB1*02:01 (HR = 1.19, P = 0.041). Second, after adjusting for DQ, DPA1*02:01-DPB1*11:01 and DPA1*01:03-DPB1*03:01 were found to have opposite associations with progression (HR = 1.98 and 0.70, P = 0.021 and 6.16*10-3, respectively). Third, DRB1*03:01-DRB3*01:01 and DRB1*03:01-DRB3*02:02, sharing the DRB1*03:01, had opposite associations (HR = 0.73 and 1.44, P = 0.04 and 0.019, respectively), indicating a role of DRB3. Meanwhile, DRB1*12:01-DRB3*02:02 and DRB1*01:03 alone were found to associate with progression (HR = 2.6 and 2.32, P = 0.018 and 0.039, respectively). Fourth, through enumerating all heterodimers, it was found that both DQ and DP could exhibit associations with disease progression. CONCLUSIONS: These results suggest that HLAII polymorphisms influence progression from islet autoimmunity to T1D among at-risk subjects with islet autoantibodies.

Association of HLA-DQ Heterodimer Residues -18ß and ß57 With Progression From Islet Autoimmunity to Diabetes in the Diabetes Prevention Trial-Type 1.

OBJECTIVE: The purpose was to test the hypothesis that the HLA-DQαß heterodimer structure is related to the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: Next-generation targeted sequencing was used to genotype HLA-DQA1-B1 class II genes in 670 subjects in the Diabetes Prevention Trial-Type 1 (DPT-1). Coding sequences were translated into DQ α- and ß-chain amino acid residues and used in hierarchically organized haplotype (HOH) association analysis to identify motifs associated with diabetes onset. RESULTS: The opposite diabetes risks were confirmed for HLA DQA1*03:01-B1*03:02 (hazard ratio [HR] 1.36; P = 2.01 ∗ 10-3) and DQA1*03:03-B1*03:01 (HR 0.62; P = 0.037). The HOH analysis uncovered residue -18ß in the signal peptide and ß57 in the ß-chain to form six motifs. DQ*VA was associated with faster (HR 1.49; P = 6.36 ∗ 10-4) and DQ*AD with slower (HR 0.64; P = 0.020) progression to diabetes onset. VA/VA, representing DQA1*03:01-B1*03:02 (DQ8/8), had a greater HR of 1.98 (P = 2.80 ∗ 10-3). The DQ*VA motif was associated with both islet cell antibodies (P = 0.023) and insulin autoantibodies (IAAs) (P = 3.34 ∗ 10-3), while the DQ*AD motif was associated with a decreased IAA frequency (P = 0.015). Subjects with DQ*VA and DQ*AD experienced, respectively, increasing and decreasing trends of HbA1c levels throughout the follow-up. CONCLUSIONS: HLA-DQ structural motifs appear to modulate progression from islet autoimmunity to diabetes among at-risk relatives with islet autoantibodies. Residue -18ß within the signal peptide may be related to levels of protein synthesis and ß57 to stability of the peptide-DQab trimolecular complex.

The KAG motif of HLA-DRB1 (ß71, ß74, ß86) predicts seroconversion and development of type 1 diabetes.

BACKGROUND: HLA-DR4, a common antigen of HLA-DRB1, has multiple subtypes that are strongly associated with risk of type 1 diabetes (T1D); however, some are risk neutral or resistant. The pathobiological mechanism of HLA-DR4 subtypes remains to be elucidated. METHODS: We used a population-based case-control study of T1D (962 patients and 636 controls) to decipher genetic associations of HLA-DR4 subtypes and specific residues with susceptibility to T1D. Using a birth cohort of 7865 children with periodically measured islet autoantibodies (GADA, IAA or IA-2A), we proposed to validate discovered genetic associations with a totally different study design and time-to-seroconversions prior to clinical onset of T1D. A novel analytic strategy hierarchically organized the HLA-DRB1 alleles by sequence similarity and identified critical amino acid residues by minimizing local genomic architecture and higher-order interactions. FINDINGS: Three amino acid residues of HLA-DRB1 (ß71, ß74, ß86) were found to be predictive of T1D risk in the population-based study. The "KAG" motif, corresponding to HLA-DRB1×04:01, was most strongly associated with T1D risk ([O]dds [R]atio=3.64, p = 3.19 × 10-64). Three less frequent motifs ("EAV", OR = 2.55, p = 0.025; "RAG", OR = 1.93, p = 0.043; and "RAV", OR = 1.56, p = 0.003) were associated with T1D risk, while two motifs ("REG" and "REV") were equally protective (OR = 0.11, p = 4.23 × 10-4). In an independent birth cohort of HLA-DR3 and HLA-DR4 subjects, those having the "KAG" motif had increased risk for time-to-seroconversion (Hazard Ratio = 1.74, p = 6.51 × 10-14) after adjusting potential confounders. INTERPRETATIONS: DNA sequence variation in HLA-DRB1 at positions ß71, ß74, and ß86 are non-conservative (ß74 A→E, ß71 E vs K vs R and ß86 G vs V). They result in substantial differences in peptide antigen anchor pocket preferences at p1, p4 and potentially neighboring regions such as pocket p7. Differential peptide antigen binding is likely to be affected. These sequence substitutions may account for most of the HLA-DR4 contribution to T1D risk as illustrated in two HLA-peptide model complexes of the T1D autoantigens preproinsulin and GAD65. FUNDING: National Institute of Diabetes and Digestive and Kidney Diseases and the Swedish Child Diabetes Foundation and the Swedish Research Council.

Nine residues in HLA-DQ molecules determine with susceptibility and resistance to type 1 diabetes among young children in Sweden.

HLA-DQ molecules account over 50% genetic risk of type 1 diabetes (T1D), but little is known about associated residues. Through next generation targeted sequencing technology and deep learning of DQ residue sequences, the aim was to uncover critical residues and their motifs associated with T1D. Our analysis uncovered (αa1, α44, α157, α196) and (ß9, ß30, ß57, ß70, ß135) on the HLA-DQ molecule. Their motifs captured all known susceptibility and resistant T1D associations. Three motifs, "DCAA-YSARD" (OR = 2.10, p = 1.96*10-20), "DQAA-YYARD" (OR = 3.34, 2.69*10-72) and "DQDA-YYARD" (OR = 3.71, 1.53*10-6) corresponding to DQ2.5 and DQ8.1 (the latter two motifs) associated with susceptibility. Ten motifs were significantly associated with resistance to T1D. Collectively, homozygous DQ risk motifs accounted for 43% of DQ-T1D risk, while homozygous DQ resistant motifs accounted for 25% protection to DQ-T1D risk. Of the identified nine residues five were within or near anchoring pockets of the antigenic peptide (α44, ß9, ß30, ß57 and ß70), one was the N-terminal of the alpha chain (αa1), one in the CD4-binding region (ß135), one in the putative cognate TCR-induced αß homodimerization process (α157), and one in the intra-membrane domain of the alpha chain (α196). Finding these critical residues should allow investigations of fundamental properties of host immunity that underlie tolerance to self and organ-specific autoimmunity.

Next-Generation HLA Sequence Analysis Uncovers Seven HLA-DQ Amino Acid Residues and Six Motifs Resistant to Childhood Type 1 Diabetes.

HLA-DQA1 and -DQB1 genes have significant and potentially causal associations with autoimmune type 1 diabetes (T1D). To follow up on the earlier analysis on high-risk HLA-DQ2.5 and DQ8.1, the current analysis uncovers seven residues (αa1, α157, α196, ß9, ß30, ß57, and ß70) that are resistant to T1D among subjects with DQ4-, 5-, 6-, and 7-resistant DQ haplotypes. These 7 residues form 13 common motifs: 6 motifs are significantly resistant, 6 motifs have modest or no associations (P values >0.05), and 1 motif has 7 copies observed among control subjects only. The motifs "DAAFYDG," "DAAYHDG," and "DAAYYDR" have significant resistance to T1D (odds ratios [ORs] 0.03, 0.25, and 0.18; P = 6.11 × 10-24, 3.54 × 10-15, and 1.03 × 10-21, respectively). Remarkably, a change of a single residue from the motif "DAAYHDG" to "DAAYHSG" (D to S at ß57) alters the resistance potential, from resistant motif (OR 0.15; P = 3.54 × 10-15) to a neutral motif (P = 0.183), the change of which was significant (Fisher P value = 0.0065). The extended set of linked residues associated with T1D resistance and unique to each cluster of HLA-DQ haplotypes represents facets of all known features and functions of these molecules: antigenic peptide binding, peptide-MHC class II complex stability, ß167-169 RGD loop, T-cell receptor binding, formation of homodimer of α-ß heterodimers, and cholesterol binding in the cell membrane rafts. Identification of these residues is a novel understanding of resistant DQ associations with T1D. Our analyses endow potential molecular approaches to identify immunological mechanisms that control disease susceptibility or resistance to provide novel targets for immunotherapeutic strategies.

Motifs of Three HLA-DQ Amino Acid Residues (α44, ß57, ß135) Capture Full Association With the Risk of Type 1 Diabetes in DQ2 and DQ8 Children.

HLA-DQA1 and -DQB1 are strongly associated with type 1 diabetes (T1D), and DQ8.1 and DQ2.5 are major risk haplotypes. Next-generation targeted sequencing of HLA-DQA1 and -DQB1 in Swedish newly diagnosed 1- to 18 year-old patients (n = 962) and control subjects (n = 636) was used to construct abbreviated DQ haplotypes, converted into amino acid (AA) residues, and assessed for their associations with T1D. A hierarchically organized haplotype (HOH) association analysis allowed 45 unique DQ haplotypes to be categorized into seven clusters. The DQ8/9 cluster included two DQ8.1 risk and the DQ9 resistant haplotypes, and the DQ2 cluster included the DQ2.5 risk and DQ2.2 resistant haplotypes. Within each cluster, HOH found residues α44Q (odds ratio [OR] 3.29, P = 2.38 * 10-85) and ß57A (OR 3.44, P = 3.80 * 10-84) to be associated with T1D in the DQ8/9 cluster representing all ten residues (α22, α23, α44, α49, α51, α53, α54, α73, α184, ß57) due to complete linkage disequilibrium (LD) of α44 with eight such residues. Within the DQ2 cluster and due to LD, HOH analysis found α44C and ß135D to share the risk for T1D (OR 2.10, P = 1.96 * 10-20). The motif "QAD" of α44, ß57, and ß135 captured the T1D risk association of DQ8.1 (OR 3.44, P = 3.80 * 10-84), and the corresponding motif "CAD" captured the risk association of DQ2.5 (OR 2.10, P = 1.96 * 10-20). Two risk associations were related to GAD65 autoantibody (GADA) and IA-2 autoantibody (IA-2A) but in opposite directions. CAD was positively associated with GADA (OR 1.56, P = 6.35 * 10-8) but negatively with IA-2A (OR 0.59, P = 6.55 * 10-11). QAD was negatively associated with GADA (OR 0.88; P = 3.70 * 10-3) but positively with IA-2A (OR 1.64; P = 2.40 * 10-14), despite a single difference at α44. The residues are found in and around anchor pockets 1 and 9, as potential T-cell receptor contacts, in the areas for CD4 binding and putative homodimer formation. The identification of three HLA-DQ AAs (α44, ß57, ß135) conferring T1D risk should sharpen functional and translational studies.

A modified flow cytometry method for objective estimation of human CD4+ regulatory T cells (CD4+ Tregs) in peripheral blood, via CD4/CD25/CD45RO/FoxP3 labeling.

BACKGROUND: Several methods exist for flow-cytometric estimation of human peripheral blood CD4+ T regulatory cells (CD4+ Tregs). METHODS: We report our experience with the estimation of human CD4+ Tregs via three different characterizations using flow cytometry (CD25high FoxP3+ , CD25high CD127low/- FoxP3+ , and CD4+ CD25high/int CD45ROFoxP3+ ) in normal subjects. We have used these methods on the control populations from two studies (32 and 36 subjects, respectively), the latter two methods retrospectively on the subjects of the first study. The six CD4+ T cell fractions obtained by the third method were differentially colored to ascertain the distribution of these cell fractions in the CD25/FoxP3, CD45RO/FoxP3, and CD25/CD127 dot plots from CD4/CD25/CD45RO/FoxP3 and CD4/CD25/CD45RO/CD127 panels. RESULTS: Each approach gives significantly different estimates of Tregs (expressed as percentage of CD4+ T cells), with the second almost invariably yielding higher percentages than the other two. Only the third approach can distinguish among effector and naïve Tregs and FoxP3+ non-Tregs. Analysis of CD25/CD127 dot plots reveals that Treg delineation via the widely used definition of CD4+ CD25high CD127low/- cells unavoidably yields a mixture of nearly all effector and most of naïve Tregs, as well as FoxP3+ non-Tregs plus other cells. Delineation of effector/naïve Tregs and FoxP3+ non-Tregs is possible via CD45RO/CD25 dot plots but not by CD45RO/FoxP3 counterparts (as done previously) because of overlapping FoxP3 intensities among Tregs and non-Tregs. CONCLUSION: Our comparison shows that CD4/CD25/CD45RO/FoxP3 panels are an objective means of estimating effector and naïve Tregs via colored dot plots, aiding thus in Treg delineation in health and detecting aberrations in disease.

Eleven Amino Acids of HLA-DRB1 and Fifteen Amino Acids of HLA-DRB3, 4, and 5 Include Potentially Causal Residues Responsible for the Risk of Childhood Type 1 Diabetes.

Next-generation targeted sequencing of HLA-DRB1 and HLA-DRB3, -DRB4, and -DRB5 (abbreviated as DRB345) provides high resolution of functional variant positions to investigate their associations with type 1 diabetes risk and with autoantibodies against insulin (IAA), GAD65 (GADA), IA-2 (IA-2A), and ZnT8 (ZnT8A). To overcome exceptional DR sequence complexity as a result of high polymorphisms and extended linkage disequilibrium among the DR loci, we applied a novel recursive organizer (ROR) to discover disease-associated amino acid residues. ROR distills disease-associated DR sequences and identifies 11 residues of DRB1, sequences of which retain all significant associations observed by DR genes. Furthermore, all 11 residues locate under/adjoining the peptide-binding groove of DRB1, suggesting a plausible functional mechanism through peptide binding. The 15 residues of DRB345, located respectively in the ß49-55 homodimerization patch and on the face of the molecule shown to interact with and bind to the accessory molecule CD4, retain their significant disease associations. Further ROR analysis of DR associations with autoantibodies finds that DRB1 residues significantly associated with ZnT8A and DRB345 residues with GADA. The strongest association is between four residues (ß14, ß25, ß71, and ß73) and IA-2A, in which the sequence ERKA confers a risk association (odds ratio 2.15, P = 10-18), and another sequence, ERKG, confers a protective association (odds ratio 0.59, P = 10-11), despite a difference of only one amino acid. Because motifs of identified residues capture potentially causal DR associations with type 1 diabetes, this list of residuals is expected to include corresponding causal residues in this study population.

DRB4*01:01 Has a Distinct Motif and Presents a Proinsulin Epitope That Is Recognized in Subjects with Type 1 Diabetes.

DRB4*01:01 (DRB4) is a secondary HLA-DR product that is part of the high-risk DR4/DQ8 haplotype that is associated with type 1 diabetes (T1D). DRB4 shares considerable homology with HLA-DR4 alleles that predispose to autoimmunity, including DRB1*04:01 and DRB1*04:04. However, the DRB4 protein sequence includes distinct residues that would be expected to alter the characteristics of its binding pockets. To identify high-affinity peptides that are recognized in the context of DRB4, we used an HLA class II tetramer-based approach to identify epitopes within multiple viral Ags. We applied a similar approach to identify antigenic sequences within glutamic acid decarboxylase 65 and pre-proinsulin that are recognized in the context of DRB4. Seven sequences were immunogenic, eliciting high-affinity T cell responses in DRB4+ subjects. DRB1*04:01-restricted responses toward many of these peptides have been previously described, but responses to a novel pre-proinsulin 9-28 peptide were commonly observed in subjects with T1D. Furthermore, T cells that recognized this peptide in the context of DRB4 were present at significantly higher frequencies in patients with T1D than in healthy controls, implicating this as a disease-relevant specificity that may contribute to the breakdown of ß cell tolerance in genetically susceptible individuals. We then deduced a DRB4 motif and confirmed its key features through structural modeling. This modeling suggested that the core epitope within the pre-proinsulin 9-28 peptide has a somewhat unusual binding motif, with tryptophan in the fourth binding pocket of DRB4, perhaps influencing the availability of this complex for T cell selection.

Zinc transporter 8 autoantibodies and their association with SLC30A8 and HLA-DQ genes differ between immigrant and Swedish patients with newly diagnosed type 1 diabetes in the Better Diabetes Diagnosis study.

We examined whether zinc transporter 8 autoantibodies (ZnT8A; arginine ZnT8-RA, tryptophan ZnT8-WA, and glutamine ZnT8-QA variants) differed between immigrant and Swedish patients due to different polymorphisms of SLC30A8, HLA-DQ, or both. Newly diagnosed autoimmune (≥1 islet autoantibody) type 1 diabetic patients (n = 2,964, <18 years, 55% male) were ascertained in the Better Diabetes Diagnosis study. Two subgroups were identified: Swedes (n = 2,160, 73%) and immigrants (non-Swedes; n = 212, 7%). Non-Swedes had less frequent ZnT8-WA (38%) than Swedes (50%), consistent with a lower frequency in the non-Swedes (37%) of SLC30A8 CT+TT (RW+WW) genotypes than in the Swedes (54%). ZnT8-RA (57 and 58%, respectively) did not differ despite a higher frequency of CC (RR) genotypes in non-Swedes (63%) than Swedes (46%). We tested whether this inconsistency was due to HLA-DQ as 2/X (2/2; 2/y; y is anything but 2 or 8), which was a major genotype in non-Swedes (40%) compared with Swedes (14%). In the non-Swedes only, 2/X (2/2; 2/y) was negatively associated with ZnT8-WA and ZnT8-QA but not ZnT8-RA. Molecular simulation showed nonbinding of the relevant ZnT8-R peptide to DQ2, explaining in part a possible lack of tolerance to ZnT8-R. At diagnosis in non-Swedes, the presence of ZnT8-RA rather than ZnT8-WA was likely due to effects of HLA-DQ2 and the SLC30A8 CC (RR) genotypes.

The spectrum of HLA-DQ and HLA-DR alleles, 2006: a listing correlating sequence and structure with function.

The list of alleles in the HLA-DRB, HLA-DQA, and HLA-DQB gene loci has grown enormously since the last listing in this journal 8 years ago. Crystal structure determination of several human and mouse HLA class II alleles, representative of two gene loci in each species, enables a direct comparison of ortholog and paralog loci. A new numbering system is suggested, extending earlier suggestions by [Fremont et al. in Immunity 8:305-317, (1998)], which will bring in line all the structural features of various gene loci, regardless of animal species. This system allows for structural equivalence of residues from different gene loci. The listing also highlights all amino acid residues participating in the various functions of these molecules, from antigenic peptide binding to homodimer formation, CD4 binding, membrane anchoring, and cytoplasmic signal transduction, indicative of the variety of functions of these molecules. It is remarkable that despite the enormous number of unique alleles listed thus far (DQA = 22, DQB = 54, DRA = 2, and DRB = 409), there is invariance at many specific positions in man, but slightly less so in mouse or rat, despite their much lower number of alleles at each gene locus in the latter two species. Certain key polymorphisms (from substitutions to an eight-residue insertion in the cytoplasmic tail of certain DQB alleles) that have thus far gone unnoticed are highly suggestive of differences or diversities in function and thus call for further investigation into the properties of these specific alleles. This listing is amenable to supplementation by future additions of new alleles and the highlighting of new functions to be discovered, providing thus a unifying platform of reference in all animal species for the MHC class II allelic counterparts, aiding research in the field and furthering our understanding of the functions of these molecules.

The actin loci in the genus Drosophila: establishment of chromosomal homologies among five nearctic species of the Drosophila obscura group by in situ hybridization.

The actin genes of five nearctic species of the Drosophila obscura group were mapped by in situ hybridization, using the 5C actin gene of D. melanogaster as a probe. In all species but D. azteca eight actin loci were observed variously dispersed over all five (A- E) chromosomal elements. In D. azteca ten actin hybridization sites were found; four of which most probably originated by duplications or by transposition events. Although the five nearctic species differ from all other Drosophila species of the D. obscura group so far studied in the number of loci as well as in the chromosomal distribution and location of the actin loci, the uniformity of the main pattern with six actin loci throughout the genus Drosophila reinforces the hypothesis that the chromosomal elements have maintained their essential identities during the course of evolution. Our findings are in accordance with the conclusion that the nearctic D. obscura species have differentiated from a common ancestor of the palearctic species and that they belong to two distinct subgroups, the pseudoobscura and the affinis subgroups.