Browsing by Subject "HLA"

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    Analysis Of Human Leukocyte Antigen (HLA) Immunogenetic Data For Hematopoietic Stem Cell Transplantation And Disease Association
    (2014-12) Gragert, Loren
    The Major Histocompatibility Complex (MHC) of chromosome 6 is the most polymorphic region of the human genome, and is also under very strong selection pressure, resulting in genetic divergence of immune gene variants between human populations. The human leukocyte antigen (HLA) genes located in the MHC region play a central role in the immune system as HLA proteins distinguish self from non-self through antigenic peptide presentation to T-cells. Hematopoietic stem cell transplantation (HSCT) is a curative therapy for many patients with hematologic diseases, but successful transplant requires a high degree of HLA matching between donor and recipient. Unfortunately, HLA-matched donors are not available for all patients. HLA diversity is vast as millions of unique HLA genotypes have been observed worldwide, many of which have high privacy to specific human populations. In response to this HLA-matching challenge, large registries of unrelated donors have been constructed worldwide to provide HLA-matched HSCT to patients. Even with large registries, minority and admixed race/ethnic groups in the United States have lower likelihood than European-Americans of finding an HLA match. Legacy high-throughput HLA typing methods give high levels of typing ambiguity at recruitment, resulting in a lack of initial confirmation that a suitable match exists. Current population genetics techniques fall short in addressing the unique challenges of stem cell registry analytics, resulting in a difficult search process for some patients. This thesis describes new techniques developed to analyze immunogenetics data with direct operational application in the registry setting. Advancement in computational techniques in population genetics to better handle HLA typing ambiguity has improved calculation of HLA haplotype frequencies, prediction of allele-level HLA typing for subjects with typing ambiguity in registry matching algorithms, and projection of HLA match likelihoods as registries expand. These advances have had direct operational impact for National Marrow Donor Program (NMDP) through more rapid identification of suitably-matched donors and optimized allocation of resources in order to serve more patients, especially in underserved minority groups. These computational techniques have also enabled more detailed evaluation of immunogenetic associations with disease, which may lead to new avenues for treatment for cancer and autoimmune diseases.
  • Thumbnail Image
    Item
    Bioinformatics Tools for Improving Matching for Hematopoietic Stem Cell Transplantation
    (2017-08) Halagan, Michael
    Hematopoietic Stem Cell Transplantation (HSCT) is a curative therapy for multiple malignant and non-malignant blood disorders. Multiple opportunities exist for facilitating and improving the accuracy of matching potential donors with patients in need of HSCT. The global donor pool does not adequately represent many regions of the world; therefore, donor searches would benefit from the haplotype analysis and modeling of underserved populations. Utilizing sequence data in matching algorithms also has potential to improve HSCT for patients in need. We developed the Gene Feature Enumeration (GFE) ecosystem to supplement the current HLA nomenclature by retaining all sequence data, hence enhancing matching precision. To improve the global donor pool, we performed a haplotype frequency analysis and registry modeling on the Ezer Mizion registry in Israel. Combining all these bioinformatics tools provides invaluable resources for unrelated donor registries to help serve HSCT patients worldwide.
  • Thumbnail Image
    Item
    Computational Methods for Sequencing and Interpreting Killer-cell Immunoglobulin-like Receptors (KIRs) at Multiple Resolutions
    (2021-01) Roe, David
    The era of personalized genetic medicine has arrived. It is now routine to sequence an individual’s DNA, either whole genome sequences (WGS) or targeted, as part of a patient’s medical plan. One of the exceptions is an ~200 kilobase region in chromosome 19 containing the killer-cell immunoglobulin-like receptors (KIR). These genes encode proteins that influence the actions of natural killer (NK) cells based on whether or not they bind with peptide-bound human leukocyte antigen receptors. This is evolutionary important to fight pathogens and mediate pregnancy. Modern medicine has correlated low-resolution KIR with many diseases and treatments, although the findings are often relatively vague and sometimes contradictory due to low resolution interpretation and/or small cohort sizes. Whether for personal medicine or population studies, the current best practices for KIR genotyping are to determine the presence/absence (PA) or copy number variation (CNV) of each gene using oligo- or primer-based polymerase chain reaction.The goal of our research is to advance DNA sequencing and interpretation of human KIR haplotypes. To that end, we have created algorithms and workflows to enhance interpretations of KIR at resolutions from PA genotyping via short-read WGS to full-haplotype assembly from long-read targeted or whole-genome sequences. First, we developed the first workflow to efficiently and accurately capture, sequence, assemble, and annotate full KIR haplotype sequences. As part of this workflow, we designed small sequences to capture the DNA fragments. Next, we use the alignment pattern of those short sequences across finished KIR haplotypes to define and annotate haplotype structures. The results show, for the first time, that the KIR region is composed of 9 genes in 14 loci. Next, we annotated all 68 reported human haplotypes, aligned them at the structural level, and then refined the alignment down the base level, providing the first KIR haplotype multiple sequence alignment. These efforts have led to this region being the best annotated and most diverse in the human genome reference. We next leveraged the MSA to discover PA markers and leveraged them in the first KIR WGS genotyping application. It was evaluated independently and reported to be at least 97% accurate. These discoveries and inventions are the culmination of several computational methods we have developed that interpret KIR under different typing resolutions. This multi-resolution aspect is crucial to overall understanding; it improves resolution at any given level by leveraging references and/or markers from other resolutions. From low-resolution genotyping from any kind of DNA sequence to the first efficient full-haplotype assembly method, these results advance interpretation of this important genetic region to the personal and population levels.
  • Thumbnail Image
    Item
    Diabetes In Somali Children In Minneapolis and St.Paul, Minnesota
    (2015-09) Sunni, Muna
    Minnesota is home to the largest population of Somalis in the United States (US). The 2011 United States Census Bureau estimates that there are more than 32,000 individuals of Somali origin [1, 2], and many believe there is a significant underestimation of this number. Somalis originate from a distinct geographic region in East Africa, and have obvious similarities in physical features suggesting relative genetic homogeneity. In contrast, most African Americans descend from various areas in Africa, and have experienced significant intermingling amongst themselves and with other populations rendering this population less homogeneous. Thus, not surprisingly, diabetes may differ between Somalis and other African Americans. Type 1 diabetes (T1D) is an autoimmune disease of heterogeneous etiology [3-5]. Carrying specific human leukocyte antigen (HLA) alleles determines an individual’s genetic risk for developing T1D. It has been established that these alleles may differ between populations [3, 6]. This dissertation describes some of the clinical characteristics, diabetes autoantibody and HLA allele profiles, and explores cultural beliefs related to diabetes in Somali children with T1D who live in the Twin Cities, Minnesota. These studies have led to two papers, which have been submitted for peer-reviewed publication. My primary project, describes the immune and genetic basis of T1D in a group of Somali children in the Twin Cities, Minnesota by determining human leukocyte antigen (HLA) alleles and diabetes autoantibodies. Twenty-seven Somali children ≤19 years treated for T1D at the University of Minnesota and Children’s Hospitals and Clinics of Minnesota from January 1st, 2012 to January 31st, 2014, participated. Venous blood samples for HLA alleles, and diabetes autoantibodies (GAD65, islet antibodies, insulin antibodies and ZnT8) were obtained. In these 27 children, the most common HLA phenotype was DR3. Strikingly, 92% of subjects carried this phenotype (allele frequency 63%). Another common genotype was DR13 (27%, allele frequency 14%). There was a relatively low frequency of DR4 (15%, allele frequency 8%). This genetic pattern is very different from that of Caucasians or African Americans. All 27 participants had positive elevation of at least one diabetes autoantibody confirming that this is autoimmune diabetes. GAD65 antibodies were found in 56% of subjects, IA-2 in 33%, and ZnT8 in 22%. HASH(0x7f87dd84a058) My second project was a cross-sectional study that describes cultural beliefs related to diabetes in Minnesota Somali children with T1D, and compares their diabetes control to that of non-Somali children with T1D. Demographic and clinical data were collected by history and from medical records of Somali children ≤19 years with T1D followed at the University of Minnesota Children’s Hospital and Children’s Hospitals and Clinics of Minnesota. A survey was administered to parents of all participants and to children aged ≥12 years. Twenty-five Somali children participated, with 24 parent-child pairs (2 siblings). In general, diabetes was well accepted. Seventy-one percent of parents indicated the child was “the same as before” other than having to do diabetes cares. Families were coping well, and the child was not treated differently than siblings. Performance of routine medical cares was described as the hardest part about having diabetes, but this was not related to conflicts with traditional culture or religion. One notable exception was difficulty performing carbohydrate counting on Somali foods. Our education materials were not helpful when it came to the traditional Somali diet. Respondents were appreciative of the education provided by the diabetes team. Less than 10% used herbal supplements in addition to insulin. Mean HbA1c in Somali children was higher than the overall pediatric clinic average, 9.5±1.6% vs 8.8±1.6 (p =0.01). The difference was largely due to adolescent patients. These two studies suggest that autoantibody and HLA profiles of Somali children with diabetes are consistent with autoimmune T1D, and that their HLA profile is unique compared to African Americans with T1D. The data also highlight that the majority of Somali families cope well with diabetes, and that glycemic control in adolescents is worse than that of non-Somali peers. Findings from this study beg the question of whether differences in diabetes between Somali children and their non-Somali peers is merely a result of these differences in HLA alleles, or whether other factors influence glycemic control in this population. Data from this study will be used to target diabetes education and to provide culture-specific educational resources to improve the experience of living with this chronic condition.
  • Thumbnail Image
    Item
    Innate Immunogenetics Of Keratinocyte Carcinomas
    (2014-12) Vineretsky, Karin
    Keratinocyte carcinomas (KC) which include basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) of the skin represent the most common malignancies in the world. UVR is the major risk factor associated with KC, and contributes to skin cancer carcinogenesis both as a mutagen and an immune suppressing agent. Exposures to arsenic, immunosupressive medications, beta-HPV, and individual susceptibility risk factors including genetic variability have also been implicated in KC development. Previous research was largely focused on the role of adaptive immunity in KC, while the role of innate immunity has not been fully investigated. Recent studies, including those on the action of Imiquimod, point to the centrality of innate immunity in KC pathogenesis. Natural killer (NK) cells of the innate immune system are the first line of defense against transformed and infected cells. NK cell killing capacity is determined by multiple inhibitory and activating cell surface receptors, including broad cellular-stress sensing natural killer group 2 member D (NKG2D) receptors, and highly diverse in gene content, copy number, and allelic polymorphisms killer-cell immunoglobulin-like receptors (KIR) that recognize self-human leukocyte antigen class I (HLA-I) ligands. Inter-individual variability of the KIR locus, and its interaction with cognate HLA-I, has been increasingly implicated in various disease settings including cancer. Genetic variability of NKG2D receptor activity has also been described in epithelial cancers. Given that NK cell function is influenced by these two classes of receptors, we hypothesized that genetic variability at these loci impacts innate immunity and BCC and SCC risk. Using a large population-based case-control study, a three part investigation was conducted. First investigation examined whether two genetic variants related to high natural cytotoxic activity of the NKG2D receptor decrease risk of KC and are modified by susceptibility and exposure factors including: sex, skin type, number of severe sunburns, glucocorticoids, and arsenic. This revealed differential effects of NKG2D genotype on KC risk by sex and skin type. The second study, determined whether KIR gene content alone and in combination with HLA-I ligands was associated with KC risk. The results suggested interactions of the activating KIR and HLA-I ligands may be implicated in control of BCC and to a lesser degree of SCC. The third study investigated the combined effects of KIR and NKG2D. NKG2D activity was assigned based on the number of alleles with high cytotoxic activity, and activating KIR were grouped based on the presence of 2DS1, 3DS1 and 2DS5 that were previously associated with reduced KC risk. The results showed reduced KC risk with the highest activating profile (containing 3 activating KIR and 2 or more NKG2D high activity alleles). Taken together, the results suggest a greater involvement of the innate immune response in the etiology of BCC, and to a lesser extent of SCC. In the context of SCC, these data suggest increased inflammation may deregulate the innate immune response.