18 research outputs found

    HLA Class I and Genetic Susceptibility to Type 1 Diabetes: Results From the Type 1 Diabetes Genetics Consortium

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    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 x 10(-11)) and B*3906 (10.31; P = 4 X 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 H. Other class I type 1 diabetes associations appear to be specific to individual class H 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 H alleles, are associated with type 1 diabetes. Diabetes 59:2972-2979, 201

    HLA DPA1, DPB1 Alleles and Haplotypes Contribute to the Risk Associated With Type 1 Diabetes: Analysis of the Type 1 Diabetes Genetics Consortium Families

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    OBJECTIVE-To determine the relative risk associated with DPA1 and DPB1 alleles and haplotypes in type I diabetes. RESEARCH DESIGN AND METHODS-The frequency of DPA1 and DPB1 alleles and haplotypes in type I diabetic patients was compared to the family based control frequency in 1,771 families directly and conditional on FILA (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 DPAI 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 I 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 I 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 Diabetes 59:2055-2062, 201

    HLA genotyping in the international Type 1 Diabetes Genetics Consortium

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    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

    Cholangiocyte organoids can repair bile ducts after transplantation in the human liver.

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    Organoid technology holds great promise for regenerative medicine but has not yet been applied to humans. We address this challenge using cholangiocyte organoids in the context of cholangiopathies, which represent a key reason for liver transplantation. Using single-cell RNA sequencing, we show that primary human cholangiocytes display transcriptional diversity that is lost in organoid culture. However, cholangiocyte organoids remain plastic and resume their in vivo signatures when transplanted back in the biliary tree. We then utilize a model of cell engraftment in human livers undergoing ex vivo normothermic perfusion to demonstrate that this property allows extrahepatic organoids to repair human intrahepatic ducts after transplantation. Our results provide proof of principle that cholangiocyte organoids can be used to repair human biliary epithelium

    Interaction between maternal killer immunoglobulin-like receptors and offspring HLAs and susceptibility of childhood ALL

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    Acute lymphoblastic leukemia (ALL) in children is associated with a distinct neonatal cytokine profile. The basis of this neonatal immune phenotype is unknown but potentially related to maternal-fetal immune receptor interactions. We conducted a case-control study of 226 case child-mother pairs and 404 control child-mother pairs to evaluate the role of interaction between HLA genotypes in the offspring and maternal killer immunoglobulin-like receptor (KIR) genotypes in the etiology of childhood ALL, while considering potential mediation by neonatal cytokines and the immune-modulating enzyme arginase-II (ARG-II). We observed different associations between offspring HLA-maternal KIR activating profiles and the risk of ALL in different predicted genetic ancestry groups. For instance, in Latino subjects who experience the highest risk of childhood leukemia, activating profiles were significantly associated with a lower risk of childhood ALL (odds ratio [OR] = 0.59; 95% confidence interval [CI], 0.49-0.71) and a higher level of ARG-II at birth (coefficient = 0.13; 95% CI, 0.04-0.22). HLA-KIR activating profiles were also associated with a lower risk of ALL in non-Latino Asians (OR = 0.63; 95% CI, 0.38-1.01), although they had a lower tumor necrosis factor-α level (coefficient = -0.27; 95% CI, -0.49 to -0.06). Among non-Latino White subjects, no significant association was observed between offspring HLA-maternal KIR interaction and ALL risk or cytokine levels. The current study reports the association between offspring HLA-maternal KIR interaction and the development of childhood ALL with variation by predicted genetic ancestry. We also observed some associations between activating profiles and immune factors related to cytokine control; however, cytokines did not demonstrate causal mediation of the activating profiles on ALL risk

    Automated Platform for the Plasmid Construction Process

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    There is a growing need for applications capable of handling large synthesis biology experiments. At the core of synthetic biology is the process of cloning and manipulating DNA as plasmids. Here, we report the development of an application named DNAda capable of writing automation instructions for any given DNA construct design generated by the J5 DNA assembly program. We also describe the automation pipeline and several useful features. The pipeline is particularly useful for the construction of combinatorial DNA assemblies. Furthermore, we demonstrate the platform by constructing a library of polyketide synthase parts, which includes 120 plasmids ranging in size from 7 to 14 kb from 4 to 7 DNA fragments.</p
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