There is documented evidence of high genetic diversity amongst African populations, but there is limited data on human leukocyte antigen (HLA) diversity in these populations. HLA genes are highly polymorphic, and encode for proteins that are part of the host defence mechanism mediated through antigen presentation to immune system effector cells. The highly polymorphic nature of HLA genes facilitates the presentation of a wide range of antigenic peptides to the immune system leading to an immune response. With the high disease burden in Africa, it is important to fully understand HLA diversity in these populations, to establish HLA-disease associations, and potentially use this data for the informed design of population-specific vaccines against the many diseases, and to improve on donor-recipient matching. The aim of this thesis is to understand HLA diversity in South African populations to support transplantation programs, add knowledge on human diversity and build a potential future resource for disease association and population studies.
There is generally limited HLA data from southern African populations (Chapter 2) to support disease association studies, provide guidance in vaccine design and donor recruitment for transplantation programs. Despite being the only active bone marrow donor registry in Africa supporting transplantation programs, HLA diversity in volunteer bone marrow donors registered at the South African Bone Marrow Registry (SABMR) is largely undocumented. This study documents HLA -A, -B, -C, -DRB1 and -DQB1 allele and haplotype frequencies from a subset of 237 SABMR registered donors with the objective of highlighting HLA diversity in South Africans (Chapter 3). Additionally, mixed resolution HLA data from the National Health Laboratory Services (NHLS) and the South African National Blood Transfusion Service (SANBS) are reported (Chapter 4). A comparison of South African HLA data (NHLS and SANBS) with other global populations including sub Saharan Africans confirm the genetic diversity of South Africans. To counter the paucity of HLA data, in silico HLA imputation tools may be used to determine HLA alleles from existing whole genome sequencing (WGS) data. HLA imputation is an economically feasible typing option for resource limited settings. To support the feasibility of HLA imputation, this study describes high resolution (up to 8 digit typing) HLA alleles determined by in silico HLA imputation tools from 24 WGS of South African individuals (chapter 5). Generally, HLA diversity of South African populations is described in detail through literature meta-analysis, documentation of previously typed individuals (SANBS, NHLS and SABMR) and HLA imputation from existing next generation sequencing (NGS) data. Although results reported here are from a small subset of 237 SABMR registered donors (chapter 3), 24 WGS (chapter 5) and mixed resolution typing NHLS and SANBS data (chapter 4), allele and haplotype frequencies generated could be a useful resource for future anthropological and population genetics studies. Furthermore, these findings may better inform donor recruitment strategies for the SABMR, and disease association studies. Future study recommendations include development of an HLA diversity resource for African populations, a comparison of large SABMR dataset with other global registries, and using more robust assembly based computational tools to fully understand the HLA diversity in South Africans. / Thesis (PhD)--University of Pretoria, 2018. / South African Medical Research Council (SAMRC) in terms of the MRC’s Flagships Awards Project (SAMRC-RFA-UFSP-01-2013/STEM CELLS), the SAMRC Extramural Unit for stem cell Research and Therapy, the Institute for Cellular and Molecular Medicine of the University of Pretoria, and the National Research Foundation of South Africa. / Immunology / PhD Medical Immunology / Unrestricted
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/70238 |
| Date | January 2018 |
| Creators | Tshabalala, Mqondisi |
| Contributors | Pepper, Michael Sean, mtshabaz@gmail.com, Christoffels, Alan |
| Publisher | University of Pretoria |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Rights | © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
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