Statistical Resolution of Ambiguous HLA Typing Data

High-resolution HLA typing plays a central role in many areas of immunology, such as in identifying immunogenetic risk factors for disease, in studying how the genomes of pathogens evolve in response to immune selection pressures, and also in vaccine design, where identification of HLA-restricted epitopes may be used to guide the selection of vaccine immunogens. Perhaps one of the most immediate applications is in direct medical decisions concerning the matching of stem cell transplant donors to unrelated recipients. However, high-resolution HLA typing is frequently unavailable due to its high cost or the inability to re-type historical data. In this paper, we introduce and evaluate a method for statistical, in silico refinement of ambiguous and/or low-resolution HLA data. Our method, which requires an independent, high-resolution training data set drawn from the same population as the data to be refined, uses linkage disequilibrium in HLA haplotypes as well as four-digit allele frequency data to probabilistically refine HLA typings. Central to our approach is the use of haplotype inference. We introduce new methodology to this area, improving upon the Expectation-Maximization (EM)-based approaches currently used within the HLA community. Our improvements are achieved by using a parsimonious parameterization for haplotype distributions and by smoothing the maximum likelihood (ML) solution. These improvements make it possible to scale the refinement to a larger number of alleles and loci in a more computationally efficient and stable manner. We also show how to augment our method in order to incorporate ethnicity information (as HLA allele distributions vary widely according to race/ethnicity as well as geographic area), and demonstrate the potential utility of this experimentally. A tool based on our approach is freely available for research purposes at http://microsoft.com/science

Co-Operative Additive Effects between HLA Alleles in Control of HIV-1

Background: HLA class I genotype is a major determinant of the outcome of HIV infection, and the impact of certain alleles on HIV disease outcome is well studied. Recent studies have demonstrated that certain HLA class I alleles that are in linkage disequilibrium, such as HLA-A*74 and HLA-B*57, appear to function co-operatively to result in greater immune control of HIV than mediated by either single allele alone. We here investigate the extent to which HLA alleles - irrespective of linkage disequilibrium - function co-operatively. Methodology/Principal Findings: We here refined a computational approach to the analysis of >2000 subjects infected with C-clade HIV first to discern the individual effect of each allele on disease control, and second to identify pairs of alleles that mediate ‘co-operative additive’ effects, either to improve disease suppression or to contribute to immunological failure. We identified six pairs of HLA class I alleles that have a co-operative additive effect in mediating HIV disease control and four hazardous pairs of alleles that, occurring together, are predictive of worse disease outcomes (q<0.05 in each case). We developed a novel ‘sharing score’ to quantify the breadth of CD8+ T cell responses made by pairs of HLA alleles across the HIV proteome, and used this to demonstrate that successful viraemic suppression correlates with breadth of unique CD8+ T cell responses (p = 0.03). Conclusions/Significance: These results identify co-operative effects between HLA Class I alleles in the control of HIV-1 in an extended Southern African cohort, and underline complementarity and breadth of the CD8+ T cell targeting as one potential mechanism for this effect

Early evolution of HLA-associated escape mutations in variable Gag proteins predicts CD4+ decline in HIV-1 subtype C infected women.

CAPRISA, 2017.Abstract available in pdf

Clear and independent associations of several HLA-DRB1 alleles with differential antibody responses to hepatitis B vaccination in youth

To confirm and refine associations of human leukocyte antigen (HLA) genotypes with variable antibody (Ab) responses to hepatitis B vaccination, we have analyzed 255 HIV-1 seropositive (HIV+) youth and 80 HIV-1 seronegatives (HIV−) enrolled into prospective studies. In univariate analyses that focused on HLA-DRB1, -DQA1, and -DQB1 alleles and haplotypes, the DRB1*03 allele group and DRB1*0701 were negatively associated with the responder phenotype (serum Ab concentration ≥ 10 mIU/mL) (P = 0.026 and 0.043, respectively). Collectively, DRB1*03 and DRB1*0701 were found in 42 (53.8%) out of 78 non-responders (serum Ab <10 mIU/mL), 65 (40.6%) out of 160 medium responders (serum Ab 10–1,000 mIU/mL), and 27 (27.8%) out of 97 high responders (serum Ab >1,000 mIU/mL) (P < 0.001 for trend). Meanwhile, DRB1*08 was positively associated with the responder phenotype (P = 0.010), mostly due to DRB1*0804 (P = 0.008). These immunogenetic relationships were all independent of non-genetic factors, including HIV-1 infection status and immunodeficiency. Alternative analyses confined to HIV+ youth or Hispanic youth led to similar findings. In contrast, analyses of more than 80 non-coding, single nucleotide polymorphisms within and beyond the three HLA class II genes revealed no clear associations. Overall, several HLA-DRB1 alleles were major predictors of differential Ab responses to hepatitis B vaccination in youth, suggesting that T-helper cell-dependent pathways mediated through HLA class II antigen presentation are critical to effective immune response to recombinant vaccines

Phylogenetic Dependency Networks: Inferring Patterns of CTL Escape and Codon Covariation in HIV-1 Gag

HIV avoids elimination by cytotoxic T-lymphocytes (CTLs) through the evolution of escape mutations. Although there is mounting evidence that these escape pathways are broadly consistent among individuals with similar human leukocyte antigen (HLA) class I alleles, previous population-based studies have been limited by the inability to simultaneously account for HIV codon covariation, linkage disequilibrium among HLA alleles, and the confounding effects of HIV phylogeny when attempting to identify HLA-associated viral evolution. We have developed a statistical model of evolution, called a phylogenetic dependency network, that accounts for these three sources of confounding and identifies the primary sources of selection pressure acting on each HIV codon. Using synthetic data, we demonstrate the utility of this approach for identifying sites of HLA-mediated selection pressure and codon evolution as well as the deleterious effects of failing to account for all three sources of confounding. We then apply our approach to a large, clinically-derived dataset of Gag p17 and p24 sequences from a multicenter cohort of 1144 HIV-infected individuals from British Columbia, Canada (predominantly HIV-1 clade B) and Durban, South Africa (predominantly HIV-1 clade C). The resulting phylogenetic dependency network is dense, containing 149 associations between HLA alleles and HIV codons and 1386 associations among HIV codons. These associations include the complete reconstruction of several recently defined escape and compensatory mutation pathways and agree with emerging data on patterns of epitope targeting. The phylogenetic dependency network adds to the growing body of literature suggesting that sites of escape, order of escape, and compensatory mutations are largely consistent even across different clades, although we also identify several differences between clades. As recent case studies have demonstrated, understanding both the complexity and the consistency of immune escape has important implications for CTL-based vaccine design. Phylogenetic dependency networks represent a major step toward systematically expanding our understanding of CTL escape to diverse populations and whole viral genes

Impact of Pre-adapted HIV Transmission

Human Leukocyte Antigen class I (HLA) restricted CD8+ T lymphocyte (CTL) responses are critical to HIV-1 control. Although HIV can evade these responses, the longer-term impact of viral escape mutants remains unclear, since these variants can also reduce intrinsic viral fitness. To address this question, we here develop a metric to determine the degree of HIV adaptation to an HLA profile. We demonstrate that transmission of viruses pre-adapted to the HLA molecules expressed in the recipient is associated with impaired immunogenicity, elevated viral load and accelerated CD4 decline. Furthermore, the extent of pre-adaptation among circulating viruses explains much of the variation in outcomes attributed to expression of certain HLA alleles. Thus, viral pre-adaptation exploits “holes” in the immune response. Accounting for these holes may be critical for vaccine strategies seeking to elicit functional responses from viral variants, and to HIV cure strategies requiring broad CTL responses to achieve successful eradication of HIV reservoirs

The effect of immunogenetic variability on human health: bioinformatics investigations from different perspectives

The high level of diversity exhibited by genes coding for molecules involved in the immune system are critically involved with several aspects of human health. The ability of the immune system to recognize foreign pathogens or abnormal cells, while tolerating itself is achieved through a balance of various components and receptors in the immune system. Individual genotypes of immune genes such as HLA and KIR fine-tune this balance. Variability in those genes lead to diversity in the response to foreign molecules, and can also lead to intolerance to self-molecules in the form of autoimmune responses. Several past studies have found HLA and KIR polymorphisms to be associated with susceptibility or protection to a range of diseases and hypersensitivity to drugs. HLA has also a major role in transplantation, where transplanted tissues need to be as similar as possible to avoid rejection. The work described in this thesis contributes towards the knowledge of immunogenetic implications in associations with diseases, transplantation and adverse reactions to drugs using different bioinformatics approaches. First, it provides bioinformatics resources for a better understanding of the impact of immunogenetic diversity on human health in the form of two public databases, alongside with insights obtained through the analysis of their contents. The KIR and Disease Database (KDDB), described in Chapter 2, stores disease associations with KIR genes expressed in natural killer cells. The data within KDDB has been analysed to uncover trends within studies, in terms of the sets of KIR genes associated with susceptibility to, or protection from, auto-immune diseases, infectious diseases, pregnancy complications and cancer. The HLA Epitope Frequency Database (EpFreq-DB), described in Chapter 3, stores population frequencies of HLA epitopes, which are structural units on the surface of HLA molecules that have been increasingly associated with improvements in transplantation matching. An analysis has been performed to demonstrate global differences in the carriage of particular epitopes, and the potential functional consequences of using epitope mapping, instead of the more traditional allele matching for transplantation scenarios. Lastly, it investigates the molecular mechanisms underlying the association HLA polymorphisms with severe hypersensitivity caused by the anti- retroviral drug nevirapine, using molecular docking approaches. Developments described in this thesis contribute to better understanding of the influence of immune variability in human health and provides necessary knowledge to advances in personalized medicine

The development of a database and bioinformatics applications for the investigation of immune genes

The extensive allelic variability observed in several genes related to the immune response and its significance in transplantation, disease association studies and diversity in human populations has led the scientific community to analyse these variants among individuals. This thesis is focussed on the development of a database and software applications for the investigation of several immune genes and the frequencies of their corresponding alleles in worldwide human populations. The approach presented in this thesis includes the design of a relational database, a web interface, the design of models for data exchange and the development of online searching mechanisms for the analysis of allele, haplotype and genotype frequencies. At present, the database contains data from more than 1000 populations covering more than four million unrelated individuals. The repertory of datasets available in the database encompasses different polymorphic regions such as Human Leukocyte Antigens (HLA), Killer-cell Immunoglobulin-like Receptors (KIR), Major histocompatibility complex Class I chain-related (MIC) genes and a number of cytokine gene polymorphisms. The work presented in this document has been shown to be a valuable resource for the medical and scientific societies. Acting as a primary source for the consultation of immune gene frequencies in worldwide populations, the database has been widely used in a variety of contexts by scientists, including histocompatibility, immunology, epidemiology, pharmacogenetics and population genetics among many others. In the last year (August 2010 to August 2011), the website was accessed by 15,784 distinct users from 2,758 cities in 136 countries and has been cited in 168 peer-reviewed publications demonstrating its wide international use