The goal of the proposed work is to further develop and integrate our software for the analysis, collection, exchange and storage (ACES) of all current and future immunogenomic data. The Human Leukocyte Antigen (HLA) region on human chromosome 6p21 is the most medically important region of the human genome. In the most successful application of precision medicine to date, matching of HLA genotypes is required for bone marrow and solid organ transplantation. HLA molecules have functional interactions with Killer cell Immunoglobulin-like Receptor (KIR) molecules, also recognized to play critical roles in transplantation and disease. The extensive genetic variation of these immunogenomic loci in human populations also makes them model systems in health disparities research. However, because these immunogenomic data have been generated using a wide variety of methods and under different nomenclature systems, cross-study data compatibility has remained an important and debilitating limitation to the field. Recognizing the need to consolidate the data and standardize data analysis in such a broad field, we have developed our Push Immunogenomics to the Next Generation (PING) data-generation system, Toolkit for Immunogenomic Data Exchange and Storage (TIDES) data-management platform, and our Bridging ImmunoGenomic Data-Analysis Workflow Gaps (BIGDAWG) data-analysis pipeline for highly polymorphic genomic data. When coupled with our Genotype List Service, Histoimmunogenetic Markup Language and Minimum Information for Reporting Immunogenomic NGS Genotyping reporting data-exchange standard, our ACES systems will represent a significant advance toward the goal of completely integrated exchange and storage of immunogenomic data. To extend our work of the prior period, we will (1) further develop the TIDES platform as the hub that integrates these systems, services and standards, centralize consensus sequence as the primary data type in immunogenomic research and clinical practice, and develop a service for gene feature enumeration (GFE) that describes HLA and KIR polymorphism by acknowledging underlying gene structure. To facilitate analysis of these data for research and clinical applications, we will (2) extend our BIGDAWG pipeline to handle new data input formats, incorporate new analyses, and export new data formats. BIGDAWG will be adapted as TIDES' primary analysis partner, and will directly, seamlessly accept TIDES outputs. Our tools are designed to maximize the ongoing utility of immunogenomic data for clinical and basic research science. As leaders in the immunogenomics field, we are uniquely suited to address the critical unmet need for standardized, robust ACES of immunogenomic data. The capacity of the systems described here to take these complex, highly polymorphic and medically important data along a complete pipeline from data generation through high-level statistical analysis will be a significant milestone toward the goal of ?bench to bedside? precision medicine.
The Human Leukocyte Antigen (HLA) and killer cell immunoglobulin-like receptor (KIR) genes display extremely high levels of variation compared to the rest of the human genome, and are central for understanding the genetic basis of disease and improving human health. The unified system of specialized software tools that we are building will standardize the analysis, collection, exchange and storage (ACES) of all current and future forms of data for the HLA and KIR genes, making these immunogenomic data easier to use for medical research, as well as for improving patient therapies.
|Ahmadov, Gunduz Ahmad; Govender, Denira; Atkinson, Mark Alvin et al. (2018) Epidemiology of childhood-onset type 1 diabetes in Azerbaijan: Incidence, clinical features, biochemistry, and HLA-DRB1 status. Diabetes Res Clin Pract 144:252-259|
|Misra, Maneesh K; Damotte, Vincent; Hollenbach, Jill A (2018) The immunogenetics of neurological disease. Immunology 153:399-414|
|Chang, Chia-Jung; Osoegawa, Kazutoyo; Milius, Robert P et al. (2018) Collection and storage of HLA NGS genotyping data for the 17th International HLA and Immunogenetics Workshop. Hum Immunol 79:77-86|
|Mack, Steven J; Udell, Julia; Cohen, Franziska et al. (2018) Correction: High resolution HLA analysis reveals independent class I haplotypes and amino-acid motifs protective for multiple sclerosis. Genes Immun :|
|Amorim, Leonardo M; Santos, Tiago H S; Hollenbach, Jill A et al. (2018) Cost-effective and fast KIR gene-content genotyping by multiplex melting curve analysis. HLA 92:384-391|
|Mack, Steven J; Udell, Julia; Cohen, Franziska et al. (2018) High resolution HLA analysis reveals independent class I haplotypes and amino-acid motifs protective for multiple sclerosis. Genes Immun :|
|Moore, Eugene; Grifoni, Alba; Weiskopf, Daniela et al. (2018) Sequence-based HLA-A, B, C, DP, DQ, and DR typing of 496 adults from San Diego, California, USA. Hum Immunol 79:821-822|
|Misra, Maneesh K; Damotte, Vincent; Hollenbach, Jill A (2018) Structure-based selection of human metabolite binding P4 pocket of DRB1*15:01 and DRB1*15:03, with implications for multiple sclerosis. Genes Immun :|
|Pappas, D J; Lizee, A; Paunic, V et al. (2018) Significant variation between SNP-based HLA imputations in diverse populations: the last mile is the hardest. Pharmacogenomics J 18:367-376|
|Grifoni, Alba; Weiskopf, Daniela; Lindestam Arlehamn, Cecilia S et al. (2018) Sequence-based HLA-A, B, C, DP, DQ, and DR typing of 714 adults from Colombo, Sri Lanka. Hum Immunol 79:87-88|
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