The development and value assessment of an integrated cardiovascular disease risk score in an African setting
| dc.contributor.author | Kamp, Michelle | |
| dc.contributor.supervisor | Ramsay, Michѐle | |
| dc.contributor.supervisor | Lewis, Cathryn | |
| dc.contributor.supervisor | Pain, Oliver | |
| dc.date.accessioned | 2024-12-12T08:52:29Z | |
| dc.date.available | 2024-12-12T08:52:29Z | |
| dc.date.issued | 2024 | |
| dc.description | A Thesis submitted in fulfillment of the requirements for the degree of Doctor of Philosophy y 2024 to the Faculty of Health Sciences, School of Pathology, University of the Witwatersrand, Johannesburg, 2024 | |
| dc.description.abstract | Cardiovascular diseases (CVD) are a significant health threat in Africa and are a leading cause of mortality and morbidity in the region. Risk stratification is the preferred approach to disease prevention but is challenging to apply due to scarce data and current scores not being validated in African populations. CVD risk is influenced by genetic and environmental factors, with the latter mostly considered in risk calculators. Precision medicine (PM) aims to tailor medical diagnostics and therapeutics by leveraging the genetics, environment, and lifestyle of individual patients. Polygenic scores (PGS) can quantify an individual’s genetic burden for CVD and improve the predictive value of risk tools when included with conventional risk factors. PGS for European ancestry populations are reaching the point where they may be useful in clinical care. However, transferability of European-derived PGS to African populations is limited and may hamper application in clinical practice. The overarching aim of the study was to develop and evaluate an integrated CVD risk score incorporating both genetic and non-genetic factors for continental African populations. This comprised of developing ancestry-aligned PGS for various cardiometabolic traits, and then deriving, evaluating, and comparing the predictive utility of genetic, non-genetic, and integrated (genetic + non-genetic) CVD risk prediction models using elastic net regression with nested 10-fold cross validation. Furthermore, we aimed to contextualise the potential utility of such PM-based tools in Africa through an assessment of the current landscape of translational genomics on the continent and by gauging clinician’s perceptions on implementing the derived CVD-risk stratification tool in South Africa’s public health setting. This study demonstrated the potential of genetic information to enhance disease risk stratification among continental African populations. Results revealed PGS provide both independent and complementary information in predicting dyslipidaemia, hypertension, and obesity - integrated scores improved prediction by at least 2.5% compared to models consisting of non-genetic factors alone. The study also highlights the challenges limiting the advancement of PM in Africa – 1. the paucity of genetic and phenotypic data within continental African populations limits the development and validation of robust and clinically useful models. This challenge is exacerbated by Euro-centric genomic and computational tools and echoes the call for more inclusive methodological approaches. 2. Despite positive perceptions of PM, there is an urgent need to address complex structural and operational barriers, including insufficient funding, lack of political will, healthcare infrastructure deficits, and training and education gaps | |
| dc.description.sponsorship | The National Institute of Health (NIH) | |
| dc.description.sponsorship | MADIVA | |
| dc.description.sponsorship | National Research Foundation (NRF) | |
| dc.description.submitter | MM2024 | |
| dc.faculty | Faculty of Health Sciences | |
| dc.identifier | https://orcid.org/ 0000-0002-4334-6883 | |
| dc.identifier.citation | Kamp, Michelle. (2024). The development and value assessment of an integrated cardiovascular disease risk score in an African setting [PhD thesis, University of the Witwatersrand, Johannesburg]. WireDSpace. | |
| dc.identifier.uri | https://hdl.handle.net/10539/43298 | |
| dc.language.iso | en | |
| dc.publisher | University of the Witwatersrand, Johannesburg | |
| dc.rights | © 2024 University of the Witwatersrand, Johannesburg. All rights reserved. The copyright in this work vests in the University of the Witwatersrand, Johannesburg. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of University of the Witwatersrand, Johannesburg. | |
| dc.rights.holder | University of the Witwatersrand, Johannesburg | |
| dc.school | School of Pathology | |
| dc.subject | Cardiovascular diseases | |
| dc.subject | Risk stratification | |
| dc.subject | Polygenic scores | |
| dc.subject | Prediction modelling | |
| dc.subject | African populations | |
| dc.subject | UCTD | |
| dc.subject.other | SDG-3: Good health and well-being | |
| dc.title | The development and value assessment of an integrated cardiovascular disease risk score in an African setting | |
| dc.type | Thesis |