163 research outputs found

    Diversity and structure of human T-Cell receptor Ī²-chain variable region genes

    Get PDF
    The nucleotide sequences of 27 T-cell receptor Ī² cDNA clones isolated from a human peripheral lymphocyte library were determined and compared to five additional published sequences. These cDNA clones represent 22 distinct T-cell receptor Ī²-chain variable region (VĪ²) gene segment sequences, which fall into 15 different VĪ² gene subfamilies, each containing six or fewer members. From this analysis, we estimate that the repertoire of expressed human VĪ² genes is <59, apparently much smaller than the immunoglobulin heavy chain and light chain variable region (VH and VL) repertoires. Variability plots comparing these human VĪ² regions with each other and with published mouse VĪ² regions provide evidence for only four hypervariable regions homologous to those seen in comparisons of immunoglobulin V regions. Somatic hypermutation appears to be used infrequently, if at all, in these VĪ² genes

    Imputing Amino Acid Polymorphisms in Human Leukocyte Antigens

    Get PDF
    DNA sequence variation within human leukocyte antigen (HLA) genes mediate susceptibility to a wide range of human diseases. The complex genetic structure of the major histocompatibility complex (MHC) makes it difficult, however, to collect genotyping data in large cohorts. Long-range linkage disequilibrium between HLA loci and SNP markers across the major histocompatibility complex (MHC) region offers an alternative approach through imputation to interrogate HLA variation in existing GWAS data sets. Here we describe a computational strategy, SNP2HLA, to impute classical alleles and amino acid polymorphisms at class I (HLA-A, -B, -C) and class II (-DPA1, -DPB1, -DQA1, -DQB1, and -DRB1) loci. To characterize performance of SNP2HLA, we constructed two European ancestry reference panels, one based on data collected in HapMap-CEPH pedigrees (90 individuals) and another based on data collected by the Type 1 Diabetes Genetics Consortium (T1DGC, 5,225 individuals). We imputed HLA alleles in an independent data set from the British 1958 Birth Cohort (N = 918) with gold standard four-digit HLA types and SNPs genotyped using the Affymetrix GeneChip 500 K and Illumina Immunochip microarrays. We demonstrate that the sample size of the reference panel, rather than SNP density of the genotyping platform, is critical to achieve high imputation accuracy. Using the larger T1DGC reference panel, the average accuracy at four-digit resolution is 94.7% using the low-density Affymetrix GeneChip 500 K, and 96.7% using the high-density Illumina Immunochip. For amino acid polymorphisms within HLA genes, we achieve 98.6% and 99.3% accuracy using the Affymetrix GeneChip 500 K and Illumina Immunochip, respectively. Finally, we demonstrate how imputation and association testing at amino acid resolution can facilitate fine-mapping of primary MHC association signals, giving a specific example from type 1 diabetes

    A method for gene-based pathway analysis using genomewide association study summary statistics reveals nine new type 1 diabetes associations.

    Get PDF
    Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed (P=9.85Ɨ10-11) with 12 of the 22 SNPs showing P<0.05. Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, P=7.86Ɨ10-9), NRP1 (rs722988, 4.88Ɨ10-8), BAD (rs694739, 2.37Ɨ10-7), CTSB (rs1296023, 2.79Ɨ10-7), FYN (rs11964650, P=5.60Ɨ10-7), UBE2G1 (rs9906760, 5.08Ɨ10-7), MAP3K14 (rs17759555, 9.67Ɨ10-7), ITGB1 (rs1557150, 1.93Ɨ10-6), and IL7R (rs1445898, 2.76Ɨ10-6). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available.This is the final version. It was first published by Wiley at http://onlinelibrary.wiley.com/doi/10.1002/gepi.21853/abstract

    Genome-Wide Association Study of Cryptosporidiosis in Infants Implicates PRKCA.

    Get PDF
    Diarrhea is a major cause of both morbidity and mortality worldwide, especially among young children. Cryptosporidiosis is a leading cause of diarrhea in children, particularly in South Asia and sub-Saharan Africa, where it is responsible for over 200,000 deaths per year. Beyond the initial clinical presentation of diarrhea, it is associated with long-term sequelae such as malnutrition and neurocognitive developmental deficits. Risk factors include poverty and overcrowding, and yet not all children with these risk factors and exposure are infected, nor do all infected children develop symptomatic disease. One potential risk factor to explain these differences is their human genome. To identify genetic variants associated with symptomatic cryptosporidiosis, we conducted a genome-wide association study (GWAS) examining 6.5 million single nucleotide polymorphisms (SNPs) in 873 children from three independent cohorts in Dhaka, Bangladesh, namely, the Dhaka Birth Cohort (DBC), the Performance of Rotavirus and Oral Polio Vaccines in Developing Countries (PROVIDE) study, and the Cryptosporidiosis Birth Cohort (CBC). Associations were estimated separately for each cohort under an additive model, adjusting for length-for-age Z-score at 12ā€‰months of age, the first two principal components to account for population substructure, and genotyping batch. The strongest meta-analytic association was with rs58296998 (Pā€‰=ā€‰3.73ā€‰Ć—ā€‰10-8), an intronic SNP and expression quantitative trait locus (eQTL) of protein kinase C alpha (PRKCA). Each additional risk allele conferred 2.4 times the odds of Cryptosporidium-associated diarrhea in the first year of life. This genetic association suggests a role for protein kinase C alpha in pediatric cryptosporidiosis and warrants further investigation.IMPORTANCE Globally, diarrhea remains one of the major causes of pediatric morbidity and mortality. The initial symptoms of diarrhea can often lead to long-term consequences for the health of young children, such as malnutrition and neurocognitive developmental deficits. Despite many children having similar exposures to infectious causes of diarrhea, not all develop symptomatic disease, indicating a possible role for human genetic variation. Here, we conducted a genetic study of susceptibility to symptomatic disease associated with Cryptosporidium infection (a leading cause of diarrhea) in three independent cohorts of infants from Dhaka, Bangladesh. We identified a genetic variant within protein kinase C alpha (PRKCA) associated with higher risk of cryptosporidiosis in the first year of life. These results indicate a role for human genetics in susceptibility to cryptosporidiosis and warrant further research to elucidate the mechanism

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

    Get PDF
    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

    Hormone receptor status of a first primary breast cancer predicts contralateral breast cancer risk in the WECARE study population

    Get PDF
    Abstract Background Previous population-based studies have described first primary breast cancer tumor characteristics and their association with contralateral breast cancer (CBC) risk. However, information on influential covariates such as treatment, family history of breast cancer, and BRCA1/2 mutation carrier status was not available. In a large, population-based, case-control study, we evaluated whether tumor characteristics of the first primary breast cancer are associated with risk of developing second primary asynchronous CBC, overall and in subgroups of interest, including among BRCA1/2 mutation non-carriers, women who are not treated with tamoxifen, and women without a breast cancer family history. Methods The Womenā€™s Environmental Cancer and Radiation Epidemiology Study is a population-based case-control study of 1521 CBC cases and 2212 individually-matched controls with unilateral breast cancer. Detailed information about breast cancer risk factors, treatment for and characteristics of first tumors, including estrogen receptor (ER) and progesterone receptor (PR) status, was obtained by telephone interview and medical record abstraction. Multivariable risk ratios (RRs) and 95% confidence intervals (CIs) were estimated in conditional logistic regression models, adjusting for demographics, treatment, and personal medical and family history. A subset of women was screened for BRCA1/2 mutations. Results Lobular histology of the first tumor was associated with a 30% increase in CBC risk (95% CI 1.0ā€“1.6). Compared to women with ER+/PR+ first tumors, those with ER-/PR- tumors had increased risk of CBC (RRā€‰=ā€‰1.4, 95% CI 1.1ā€“1.7). Notably, women with ER-/PR- first tumors were more likely to develop CBC with the ER-/PR- phenotype (RRā€‰=ā€‰5.4, 95% CI 3.0ā€“9.5), and risk remained elevated in multiple subgroups: BRCA1/2 mutation non-carriers, women younger than 45Ā years of age, women without a breast cancer family history, and women who were not treated with tamoxifen. Conclusions Having a hormone receptor negative first primary breast cancer is associated with increased risk of CBC. Women with ER-/PR- primary tumors were more likely to develop ER-/PR- CBC, even after excluding BRCA1/2 mutation carriers. Hormone receptor status, which is routinely evaluated in breast tumors, may be used clinically to determine treatment protocols and identify patients who may benefit from increased surveillance for CBC
    • ā€¦
    corecore