The Khayelitsha Comorbidity Cohort: Establishing a multimorbidity cohort with integrated clinical, genomic and epidemiological data in South Africa.

Khayelitsha 合并症队列：利用南非的综合临床、基因组和流行病学数据建立一个多病队列。

• 批准号: MC_PC_22007
• 负责人: Nicki Tiffin
• 金额: $ 25.37万
• 依托单位: University of Cape Town
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MC_PC_22007
• 关键词: Khayelitsha; Comorbidity; Cohort; Establishing; multimorbidity

In the Western Cape Province of South Africa, there is a large burden of diseases including infectious diseases HIV and TB as well as chronic diseases like hypertension, diabetes and kidney disease. Often patients have more than one condition at the same time. The Provincial Health Data Centre (PHDC) at the Department of Health collects ongoing patient information about their visits to health facilities, medicines received and laboratory tests done, in order to provide health care. Where patients consent, these health data can be used for research to better understand health conditions. Genes and DNA are unique to each individual and can affect whether they will get some diseases, how ill they will get with those illnesses, and how they respond to treatment. By understanding this relationship between DNA and diseases, individual patients will be able to receive better health care tailored to their own DNA sequence. Most of the research done on DNA and diseases until now has been done on Caucasian populations, and African patients have been poorly represented in research. This means that most health care is not optimised for Africans, even though African populations have rich genetic diversity which can provide many insights into the mechanisms of disease through biomedical research. In addition, research about genetic effects on disease have generally been conducted from the perspective of looking at a single disease and doing the analysis on who has the disease or not without taking into consideration other health conditions that the participant might also be experiencing. Recently, the H3Africa Bioinformatics Network (H3ABioNet) developed the H3Africa Illumina genotyping chip, a tool that is specifically optimised for measuring DNA variation in Africans, across the whole human genome. With the consent of research participants, health data from the PHDC can be combined with genetic data generated using the H3Africa genotyping chip, making it possible to research the relationship between DNA and different diseases in African individuals. In the first instance, this project aims to collect 700 DNA samples from consenting participants and link their DNA data to their health data from the PHDC. In this first stage it will be possible to research the more common diseases - hypertension, diabetes and kidney disease; but as the number of research participants increases in the future it will also become possible to research the less common illnesses. Updated health information will be received from the PHDC twice a year, to document all health outcomes as they occur in participants going forward. An additional benefit to this research is that it will use a participant-based approach rather than a disease-based view, researching the whole health profile of the participant instead of only looking at whether they have a single disease or not. By working in collaboration with the Department of Health, a system will be set up to return useful findings from the research so that they can be used to provide better tailored health care by the Department of Health for individuals as well as the whole population. The information will also help to inform health care in other African countries, and well as providing research insights that can help improve our understanding of disease processes across the world.

在南非的西开普省，有大量的疾病负担，包括传染病艾滋病毒和结核病以及高血压、糖尿病和肾病等慢性病。患者通常同时患有多种疾病。卫生部下属的省卫生数据中心不断收集病人的信息，包括他们到卫生设施就诊、得到的药物和进行的实验室检查，以便提供保健服务。在患者同意的情况下，这些健康数据可用于研究，以更好地了解健康状况。基因和DNA对每个人来说都是独一无二的，可以影响他们是否会患上某些疾病，他们会患上这些疾病，以及他们对治疗的反应。通过了解DNA与疾病之间的关系，个体患者将能够获得更好的医疗保健，以适应他们自己的DNA序列。到目前为止，大多数关于DNA和疾病的研究都是在高加索人群中进行的，非洲患者在研究中的代表性很低。这意味着大多数卫生保健并不是为非洲人优化的，尽管非洲人口具有丰富的遗传多样性，可以通过生物医学研究提供许多关于疾病机制的见解。此外，关于遗传对疾病的影响的研究通常是从单一疾病的角度进行的，并对谁患有这种疾病进行分析，而不考虑参与者可能也正在经历的其他健康状况。最近，H3 Africa生物信息学网络（H3 ABioNet）开发了H3 Africa Illumina基因分型芯片，这是一种专门优化用于测量非洲人整个人类基因组DNA变异的工具。在研究参与者的同意下，PHDC的健康数据可以与使用H3非洲基因分型芯片生成的遗传数据相结合，从而可以研究DNA与非洲个体不同疾病之间的关系。首先，该项目的目标是从同意的参与者那里收集700个DNA样本，并将他们的DNA数据与PHDC的健康数据联系起来。在这第一阶段，将有可能研究更常见的疾病-高血压、糖尿病和肾病;但随着未来研究参与者人数的增加，也将有可能研究不太常见的疾病。每年两次从PHDC收到更新的健康信息，以记录参与者未来发生的所有健康结果。这项研究的另一个好处是，它将使用基于参与者的方法，而不是基于疾病的观点，研究参与者的整个健康状况，而不是只看他们是否患有单一疾病。卫生署会与卫生署合作，设立一个系统，收集有用的研究结果，以便卫生署利用这些结果，为个人及全港市民提供更适切的医疗服务。这些信息还将有助于为其他非洲国家的医疗保健提供信息，并提供研究见解，有助于提高我们对世界各地疾病过程的理解。

项目成果

Multimorbidity research in Sub-Saharan Africa: Proceedings of an interdisciplinary workshop

撒哈拉以南非洲的多发病研究：跨学科研讨会论文集

• DOI: 10.12688/wellcomeopenres.18850.1
• 发表时间: 2023
• 期刊: Wellcome Open Research
• 作者: Banda G

Polygenic risk scores for disease risk prediction in Africa: current challenges and future directions.

• DOI: 10.1186/s13073-023-01245-9
• 发表时间: 2023-10-30
• 期刊: GENOME MEDICINE
• 影响因子: 12.3
• 作者: Fatumo, Segun;Sathan, Dassen;Samtal, Chaimae;Isewon, Itunuoluwa;Tamuhla, Tsaone;Soremekun, Chisom;Jafali, James;Panji, Sumir;Tiffin, Nicki;Fakim, Yasmina Jaufeerally
• 通讯作者: Fakim, Yasmina Jaufeerally

Routine health data describe adherence and persistence patterns for oral diabetes medication for a virtual cohort in the Khayelitsha sub-district of Cape Town, South Africa.

• DOI: 10.1371/journal.pgph.0002730
• 发表时间: 2023
• 期刊: PLOS global public health

Multiple modes of data sharing can facilitate secondary use of sensitive health data for research.

• DOI: 10.1136/bmjgh-2023-013092
• 发表时间: 2023-10
• 期刊: BMJ GLOBAL HEALTH
• 影响因子: 8.1
• 作者: Tamuhla, Tsaone;Lulamba, Eddie T.;Mutemaringa, Themba;Tiffin, Nicki
• 通讯作者: Tiffin, Nicki