HLA autoimmune risk alleles restrict the hypervariable region of T cell receptors

Ishigaki, Kazuyoshi; Lagattuta, Kaitlyn A.; Luo, Yang; James, Eddie A.; Buckner, Jane H.; Raychaudhuri, Soumya

doi:10.1038/s41588-022-01032-z

Cited by 49 publications

(32 citation statements)

References 51 publications

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“…Our group recently showed that the amino acid frequencies at complementarity-determining region 3 (CDR3) of the T cell receptor (TCR) are highly influenced by the HLA alleles and amino acids, possibly through thymic selection 6 . This type of analysis is an extension of the analyses we described in the previous sections.…”

Section: Multi-trait Analysismentioning

confidence: 99%

“…As spurious associations again arise when the frequencies of the tested alleles are relatively low 6 , we recommend performing permutation analyses to confirm the calibration of the test statistics.…”

Section: Multi-trait Analysismentioning

confidence: 99%

“…We assess the significance of the improvement in model fit between Full model and Reduced model with the multivariate analysis of variance (MANOVA) test for quantitative traits. As spurious associations again arise when the frequencies of the tested alleles are relatively low 6 , we recommend performing permutation analyses to confirm the calibration of the test statistics.…”

Section: Introductionmentioning

confidence: 99%

“…MHC-disease risk is modulated by several underlying mechanisms. For example, in rheumatoid arthritis, polymorphisms in the amino acid sequence of HLA-DRB1 change the capability of presenting autoantigens 5 or increase the autoreactive T cells during thymic selection 6 . In another example, the HLA-C*06:02 allele is associated with psoriasis, probably due to increased CD8+ T-cell mediated inflammatory reactions 7 .…”

Section: Main Introductionmentioning

confidence: 99%

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A statistical genetics guide to identifying HLA alleles driving complex disease

Sakaue

Gurajala

Curtis

et al. 2022

Preprint

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The human leukocyte antigen (HLA) locus is associated with more human complex diseases than any other locus. In many diseases it explains more heritability than all other known loci combined. Investigators have now demonstrated the accuracy of in silico HLA imputation methods. These approaches enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and infectious diseases, such as HIV infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine-mapping. Here, we present comprehensive statistical genetics guide to impute HLA alleles from genotype data. We provide detailed protocols, including standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids including a web-based Michigan Imputation Server. We updated the HLA imputation reference panel representing global populations (African, East Asian, European and Latino) available at the Michigan Imputation Server (n = 20,349) and achived high imputation accuracy (mean dosage correlation r = 0.981). We finally offer best practice recommendations to conduct association tests in order to define the alleles, amino acids, and haplotypes affecting human traits. This protocol will be broadly applicable to the large-scale genotyping data and contribute to defining the role of HLA in human diseases across global populations.

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Section: Multi-trait Analysismentioning

confidence: 99%

Section: Multi-trait Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Main Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A statistical genetics guide to identifying HLA alleles driving complex disease

Sakaue

Gurajala

Curtis

et al. 2022

Preprint

Self Cite

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“…DQ8 has a primary role in disease initiation through presentation of peptide epitopes to the autoreactive CD4 + T-cell receptors (TCR) from the N-terminal region of the insulin B chain, including residues 9-23 and 9-25 (B:9-23; B:9-25; Methods) [1][2][3][4][5][6][7] . It is already established that TCR repertoire differences from the thymus, mediated in part through variable a and b complementarity-determining region (CDR3) 3 regions and their interactions with peptide epitopes and amino acids in the peptidebinding cleft of HLA class II molecules, are determined by HLA class II genotype [21][22][23][24][25][26][27] .…”

Section: Mainmentioning

confidence: 99%

Autoimmune interactions between the HLA-DQβ1₅₇polymorphism, T cell receptors, and microbial mimics of insulin in type 1 diabetes

Garćıa

Paterou

Doherty

et al. 2022

Preprint

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Type 1 diabetes (T1D) is caused by a T-cell-mediated destruction of insulin-secreting pancreatic islet β cells. The T1D-predisposing human leukocyte antigen (HLA) class II molecule, DQ8, binds and presents insulin B chain peptides in the thymus producing autoreactive CD4+ T cells1–12. Here, we show that this process is driven by negatively-charged T cell receptor (TCR) complementarity-determining region 3β (CDR3β) sequences interacting with alanine at position 57 of the DQ8 β chain. Since T1D aetiology is linked to gut microbiota dysbiosis13–18, we hypothesized that the commensal proteome contains mimics of the primary insulin B:9-23 epitope that control TCR selection and tolerance. We identified a large set of bacterial proteins with significant similarity to insulin B:9-25, particularly from the transketolase (TKT) superfamily. We isolated a CD4+ TCR with a negatively-charged CDR3β from the pancreas of a DQ8-positive patient that was cross-reactive with one of these TKT peptides and insulin B:9-23. The T1D-protective molecule, DQ6, with the negatively-charged aspartic acid (D) at DQβ57(12,19), showed strong TKT mimotope binding, supporting a role for TKT-specific regulatory T cells in resistance to T1D. We propose that in a DQ8+DQ6− child with a proinflammatory dysbiotic gut microbiota, cross-reactive TKT-insulin B chain peptide T effector cells escape from the thymus and initiate T1D. TKT is a strong candidate because it is highly upregulated during weaning, a key period in T1D aetiology, and hence a prominent target for an autoimmune-prone immune system. Inhibiting gut dysbiosis and improving immune tolerance to TKT and other mimotopes, especially before and during weaning, could be a route to primary prevention of T1D and other common diseases.

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Human MHC Class II and Invariant Chain Knock‐in Mice Mimic Rheumatoid Arthritis with Allele Restriction in Immune Response and Arthritis Association

Romero‐Castillo,

Li,

et al. 2024

Advanced Science

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Transgenic mice expressing human major histocompatibility complex class II (MHCII) risk alleles are widely used in autoimmune disease research, but limitations arise due to non‐physiologic expression. To address this, physiologically relevant mouse models are established via knock‐in technology to explore the role of MHCII in diseases like rheumatoid arthritis. The gene sequences encoding the ectodomains are replaced with the human DRB1*04:01 and 04:02 alleles, DRA, and CD74 (invariant chain) in C57BL/6N mice. The collagen type II (Col2a1) gene is modified to mimic human COL2. Importantly, DRB1*04:01 knock‐in mice display physiologic expression of human MHCII also on thymic epithelial cells, in contrast to DRB1*04:01 transgenic mice. Humanization of the invariant chain enhances MHCII expression on thymic epithelial cells, increases mature B cell numbers in spleen, and improves antigen presentation. To validate its functionality, the collagen‐induced arthritis (CIA) model is used, where DRB1*04:01 expression led to a higher susceptibility to arthritis, as compared with mice expressing DRB1*04:02. In addition, the humanized T cell epitope on COL2 allows autoreactive T cell‐mediated arthritis development. In conclusion, the humanized knock‐in mouse faithfully expresses MHCII, confirming the DRB1*04:01 alleles role in rheumatoid arthritis and being also useful for studying MHCII‐associated diseases.

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HLA autoimmune risk alleles restrict the hypervariable region of T cell receptors

Cited by 49 publications

References 51 publications

A statistical genetics guide to identifying HLA alleles driving complex disease

A statistical genetics guide to identifying HLA alleles driving complex disease

Autoimmune interactions between the HLA-DQβ1₅₇polymorphism, T cell receptors, and microbial mimics of insulin in type 1 diabetes

Human MHC Class II and Invariant Chain Knock‐in Mice Mimic Rheumatoid Arthritis with Allele Restriction in Immune Response and Arthritis Association

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HLA autoimmune risk alleles restrict the hypervariable region of T cell receptors

Cited by 49 publications

References 51 publications

A statistical genetics guide to identifying HLA alleles driving complex disease

A statistical genetics guide to identifying HLA alleles driving complex disease

Autoimmune interactions between the HLA-DQβ157polymorphism, T cell receptors, and microbial mimics of insulin in type 1 diabetes

Human MHC Class II and Invariant Chain Knock‐in Mice Mimic Rheumatoid Arthritis with Allele Restriction in Immune Response and Arthritis Association

Contact Info

Product

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Autoimmune interactions between the HLA-DQβ1₅₇polymorphism, T cell receptors, and microbial mimics of insulin in type 1 diabetes