Biomedical subjects

Glenys Thomson

Publications and source records attributed to Glenys Thomson.

6 recordsLinked to original sources

PubMed2003

An integrated haplotype map of the human major histocompatibility complex.

Numerous studies have clearly indicated a role for the major histocompatibility complex (MHC) in susceptibility to autoimmune diseases. Such studies have focused on the genetic variation of a small number of classical human-leukocyte-antigen (HLA) genes in the region. Although these genes represent good candidates, given their immunological roles, linkage disequilibrium (LD) surrounding these genes has made it difficult to rule out neighboring genes, many with immune function, as influencing disease susceptibility. It is likely that a comprehensive analysis of the patterns of LD and variation, by using a high-density map of single-nucleotide polymorphisms (SNPs), would enable a greater understanding of the nature of the observed associations, as well as lead to the identification of causal variation. We present herein an initial analysis of this region, using 201 SNPs, nine classical HLA loci, two TAP genes, and 18 microsatellites. This analysis suggests that LD and variation in the MHC, aside from the classical HLA loci, are essentially no different from those in the rest of the genome. Furthermore, these data show that multi-SNP haplotypes will likely be a valuable means for refining association signals in this region.

Chromosome Mapping↗

PubMed2003

PyPop: a software framework for population genomics: analyzing large-scale multi-locus genotype data.

Software to analyze multi-locus genotype data for entire populations is useful for estimating haplotype frequencies, deviation from Hardy-Weinberg equilibrium and patterns of linkage disequilibrium. These statistical results are important to both those interested in human genome variation and disease predisposition as well as evolutionary genetics. As part of the 13th International Histocompatibility and Immunogenetics Working Group (IHWG), we have developed a software framework (PyPop). The primary novelty of this package is that it allows integration of statistics across large numbers of data-sets by heavily utilizing the XML file format and the R statistical package to view graphical output, while retaining the ability to inter-operate with existing software. Largely developed to address human population data, it can, however, be used for population based data for any organism. We tested our software on the data from the 13th IHWG which involved data sets from at least 50 laboratories each of up to 1000 individuals with 9 MHC loci (both class I and class II) and found that it scales to large numbers of data sets well.

Computational Biology↗

PubMed2002

An immunogenetic and molecular basis for differences in outcomes of invasive group A streptococcal infections.

The role of host genetic factors in conferring predisposition or protection in infectious diseases has become evident. Infection with group A streptococci causes a wide spectrum of disease ranging from pharyngitis to streptococcal toxic shock syndrome. The release of inflammatory cytokines triggered by streptococcal superantigens has a pivotal role in invasive streptococcal disease. However, individuals infected with the same strain can develop very different manifestations. We report here that the immunogenetics of the host influence the outcome of invasive streptococcal infection, and demonstrate the underlying mechanism for these genetic associations. Specific human leukocyte antigen class II haplotypes conferred strong protection from severe systemic disease, whereas others increased the risk of severe disease. Patients with the DRB1*1501/DQB1*0602 haplotype mounted significantly reduced responses and were less likely to develop severe systemic disease (P < 0.0001). We propose that human leukocyte antigen class II allelic variation contributes to differences in severity of invasive streptococcal infections through their ability to regulate cytokine responses triggered by streptococcal superantigens.

Fasciitis, Necrotizing↗

PubMed2002

Haplotype frequency estimation in patient populations: the effect of departures from Hardy-Weinberg proportions and collapsing over a locus in the HLA region.

Haplotype analyses are an important area in the study of the genetic components of human disease. Associations between markers and disease loci that are not evident with a single marker locus may be identified in multi-locus marker analyses using estimated haplotype frequencies (HFs). Procedures that make use of the expectation-maximization (EM) algorithm to estimate HFs from unphased genotype data are in common use in genetic studies. The EM algorithm uses these unphased genotype frequencies along with the assumption of Hardy-Weinberg proportions (HWP) to converge on HF estimates. In this paper, we assess the accuracy of EM estimates of HFs in patients with type I diabetes for whom the true haplotypes are known, but the data are analyzed ignoring family information to allow comparison between estimated and true frequencies. The data consist of six HLA loci with high levels of polymorphism and a range of departures from HWP and linkage equilibrium. While the overall accuracy of the EM estimates is good, there can be large over- and underestimates of particular HFs, even for common haplotypes, especially when the loci involved deviate significantly from HWP. Estimating HFs for three or more loci and then collapsing over loci so as to generate two locus haplotypes can improve the accuracy of the estimation. The collapsing procedure is most beneficial when one of the loci in the two-locus haplotype of interest deviates significantly from HWP and the locus collapsed over is in linkage disequilibrium with the other loci.

Algorithms↗

PubMed2002

The HLA class I A locus affects susceptibility to type 1 diabetes.

Human leukocyte antigen A (HLA-A) genotypes were determined for samples from 283 multiplex, Caucasian, type 1 diabetes families from the Human Biological Data Interchange (HBDI) using an immobilized probe assay. Distribution of HLA-A alleles transmitted to patients was significantly different from that in affected family-based controls (AFBAC) (p = 0.004). Transmission disequilibrium test (TDT) analysis revealed differential transmission of several HLA-A alleles from parents to affected offspring. HLA class II DRB1 and DQB1 loci were also typed, allowing assignment of HLA-A alleles to haplotypes and calculation of linkage disequilibrium values. Some of the apparent effects of HLA-A alleles on type 1 diabetes susceptibility were attributable to linkage disequilibrium with DR and DQ alleles, although others were not. The differences in frequencies between patients and controls of alleles A*0101, A*2402, and A*3002 could not be explained by linkage disequilibrium alone. Our results suggest an important role for class I antigens in modulating susceptibility to type 1 diabetes.

Alleles↗

PubMed2002

Clinical usefulness of genetic information for predicting radiographic damage in rheumatoid arthritis.

OBJECTIVE: To determine whether knowledge of genetic information aids the prediction of radiographic damage for patients with rheumatoid arthritis (RA) in whom extensive sociodemographic, family history, clinical, and immunologic information is available. METHODS: Subjects included 146 Caucasian women who were participants in a community based longitudinal study of RA. Our primary outcome measure was the severity of erosive disease. Nongenetic covariates included age at RA onset, disease duration, family history of RA, education level, family income, baseline values of function, painful and swollen joint groups and pain rating, and rheumatoid factor positivity. All women were genotyped for the HLA-DRB1 shared epitope (SE) and the tumor necrosis factor a (TNFa) microsatellite. Likelihood ratio tests (LRT) were performed to evaluate the usefulness of genetic information for predicting radiographic damage in RA, after adjusting for nongenetic covariates. Receiver operating characteristic (ROC) curves displaying the sensitivity and specificity of combinations of nongenetic and genetic information were derived, and the areas under the curves (AUC) were compared. RESULTS: Genetic information contributed significantly to the prediction of radiographic damage in RA even after adjusting for all nongenetic covariates (p value for LRT = 0.0019). The odds ratio describing the risk of severe erosive disease among individuals who had inherited both the SE and TNFa allele 11 (TNFa11) was 7.6 compared to individuals who were SE and TNFa11 negative. Analysis of ROC curves confirmed the usefulness of genetic information. CONCLUSION: Genetic information is useful for predicting radiographic damage in RA even for patients in whom extensive sociodemographic, family history, clinical, and immunologic information is available.

Adult↗