Microbiomics: The Next Pillar of Precision Medicine and Its Role in African Healthcare.

Limited access to technologies that support early monitoring of disease risk and a poor understanding of the geographically unique biological and environmental factors underlying disease, represent significant barriers to improved health outcomes and precision medicine efforts in low to middle income countries. These challenges are further compounded by the rich genetic diversity harboured within Southern Africa thus necessitating alternative strategies for the prediction of disease risk and clinical outcomes in regions where accessibility to personalized healthcare remains limited. The human microbiome refers to the community of microorganisms (bacteria, archaea, fungi and viruses) that co-inhabit the human body. Perturbation of the natural balance of the gut microbiome has been associated with a number of human pathologies, and the microbiome has recently emerged as a critical determinant of drug pharmacokinetics and immunomodulation. The human microbiome should therefore not be omitted from any comprehensive effort towards stratified healthcare and would provide an invaluable and orthogonal approach to existing precision medicine strategies. Recent studies have highlighted the overarching effect of geography on gut microbial diversity as it relates to human health. Health insights from international microbiome datasets are however not yet verified in context of the vast geographical diversity that exists throughout the African continent. In this commentary we discuss microbiome research in Africa and its role in future precision medicine initiatives across the African continent.

Gut microbiome profiling of a rural and urban South African cohort reveals biomarkers of a population in lifestyle transition.

BACKGROUND: Comparisons of traditional hunter-gatherers and pre-agricultural communities in Africa with urban and suburban Western North American and European cohorts have clearly shown that diet, lifestyle and environment are associated with gut microbiome composition. Yet, little is known about the gut microbiome composition of most communities in the very diverse African continent. South Africa comprises a richly diverse ethnolinguistic population that is experiencing an ongoing epidemiological transition and concurrent spike in the prevalence of obesity, largely attributed to a shift towards more Westernized diets and increasingly inactive lifestyle practices. To characterize the microbiome of African adults living in more mainstream lifestyle settings and investigate associations between the microbiome and obesity, we conducted a pilot study, designed collaboratively with community leaders, in two South African cohorts representative of urban and transitioning rural populations. As the rate of overweight and obesity is particularly high in women, we collected single time-point stool samples from 170 HIV-negative women (51 at Soweto; 119 at Bushbuckridge), performed 16S rRNA gene sequencing on these samples and compared the data to concurrently collected anthropometric data. RESULTS: We found the overall gut microbiome of our cohorts to be reflective of their ongoing epidemiological transition. Specifically, we find that geographical location was more important for sample clustering than lean/obese status and observed a relatively higher abundance of the Melainabacteria, Vampirovibrio, a predatory bacterium, in Bushbuckridge. Also, Prevotella, despite its generally high prevalence in the cohorts, showed an association with obesity. In comparisons with benchmarked datasets representative of non-Western populations, relatively higher abundance values were observed in our dataset for Barnesiella (log2fold change (FC) = 4.5), Alistipes (log2FC = 3.9), Bacteroides (log2FC = 4.2), Parabacteroides (log2FC = 3.1) and Treponema (log2FC = 1.6), with the exception of Prevotella (log2FC = - 4.7). CONCLUSIONS: Altogether, this work identifies putative microbial features associated with host health in a historically understudied community undergoing an epidemiological transition. Furthermore, we note the crucial role of community engagement to the success of a study in an African setting, the importance of more population-specific studies to inform targeted interventions as well as present a basic foundation for future research.

H3Africa AWI-Gen Collaborative Centre: a resource to study the interplay between genomic and environmental risk factors for cardiometabolic diseases in four sub-Saharan African countries.

Africa is experiencing a rapid increase in adult obesity and associated cardiometabolic diseases (CMDs). The H3Africa AWI-Gen Collaborative Centre was established to examine genomic and environmental factors that influence body composition, body fat distribution and CMD risk, with the aim to provide insights towards effective treatment and intervention strategies. It provides a research platform of over 10 500 participants, 40-60 years old, from Burkina Faso, Ghana, Kenya and South Africa. Following a process that involved community engagement, training of project staff and participant informed consent, participants were administered detailed questionnaires, anthropometric measurements were taken and biospecimens collected. This generated a wealth of demographic, health history, environmental, behavioural and biomarker data. The H3Africa SNP array will be used for genome-wide association studies. AWI-Gen is building capacity to perform large epidemiological, genomic and epigenomic studies across several African counties and strives to become a valuable resource for research collaborations in Africa.

The process of installing REDCap, a web based database supporting biomedical research: the first year.

BACKGROUND: Clinical and research data are essential for patient care, research and healthcare system planning. REDCapTM is a web-based tool for research data curatorship developed at Vanderbilt University in Nashville, USA. The Faculty of Health Sciences at the University of the Witwatersrand, Johannesburg South Africa identified the need for a cost effective data management instrument. REDCap was installed as per the user agreement with Vanderbilt University in August 2012. OBJECTIVES: In order to assist other institutions that may lack the in-house Information Technology capacity, this paper describes the installation and support of REDCap and incorporates an analysis of user uptake over the first year of use. METHODS: We reviewed the staffing requirements, costs of installation, process of installation and necessary infrastructure and end-user requests following the introduction of REDCap at Wits. The University Legal Office and Human Research Ethics Committee were consulted regarding the REDCap end-user agreement. Bi-monthly user meetings resulted in a training workshop in August 2013. We compared our REDCap software user numbers and records before and after the first training workshop. RESULTS: Human resources were recruited from existing staff. Installation costs were limited to servers and security certificates. The total costs to provide a functional REDCap platform was less than $9000. Eighty-one (81) users were registered in the first year. After the first training workshop the user numbers increased by 59 in one month and the total number of active users to 140 by the end of August 2013. Custom software applications for REDCap were created by collaboration between clinicians and software developers. CONCLUSION: REDCap was installed and maintained at limited cost. A small number of people with defined skills can support multiple REDCap users in two to four hours a week. End user training increased in the number of users, number of projects created and the number of projects moved to production.