Implementation of a genotyped African population cohort, with virtual follow-up: A feasibility study in the Western Cape Province, South Africa

Abstract

Background: There is limited knowledge regarding African genetic drivers of disease due to prohibitive costs of large-scale genomic research in Africa. Methods: We piloted a scalable virtual genotyped cohort in South Africa that was affordable in this resource-limited context, cost-effective, scalable virtual genotyped cohort in South Africa, with participant recruitment using a tiered informed consent model and DNA collection by buccal swab. Genotype data was generated using the H3Africa Illumina micro-array, and phenotype data was derived from routine health data of participants. We demonstrated feasibility of nested case control genome wide association studies using these data for phenotypes type 2 diabetes mellitus (T2DM) and severe COVID-19. Results: 2267346 variants were analysed in 459 participant samples, of which 229 (66.8%) are female. 78.6% of SNPs and 74% of samples passed quality control (QC). Principal component analysis showed extensive ancestry admixture in study participants. Of the 343 samples that passed QC, 93 participants had T2DM and 63 had severe COVID-19. For 1780 previously published COVID-19-associated variants, 3 SNPs in the pre-imputation data and 23 SNPS in the imputed data were significantly associated with severe COVID-19 cases compared to controls (p<0.05). For 2755 published T2DM associated variants, 69 SNPs in the pre-imputation data and 419 SNPs in the imputed data were significantly associated with T2DM cases when compared to controls (p<0.05). Conclusions: The results shown here are illustrative of what will be possible as the cohort expands in the future. Here we demonstrate the feasibility of this approach, recognising that the findings presented here are preliminary and require further validation once we have a sufficient sample size to improve statistical significance of findings. We implemented a genotyped population cohort with virtual follow up data in a resource-constrained African environment, demonstrating feasibility for scale up and novel health discoveries through nested case-control studies. Copyright: © 2025 Tamuhla T et al.

What are we researching? Our study focuses on understanding the genetic causes of diseases in African populations, where there is very little genetic data available. Even though it's cheaper now to gather genetic data, it's still expensive to collect large amounts of data needed to study these populations properly. What were the aims of the research? Create an African Genotyped Cohort: This means gathering genetic information from African participants using tools made specifically for African genetics. Use Strong Informed Consent: We wanted to make sure participants understood and agreed to the study, allowing us to grow the cohort over time. Use Existing Health Data: To make the process affordable, we used health data that was already being collected. What did we do? We made sure our consent process was clear and thorough. We collected DNA samples from consenting participants using cheek swabs and existing blood samples. We generated and checked the quality of the genetic data. We tested if we could study diseases like Type 2 Diabetes and severe COVID-19 with this approach. What did we find? In our pilot study, we genotyped 459 samples, with 74% being good quality. We analysed over 2 million genetic markers, with 78.6% passing quality checks. Our study shows that this approach works well in African populations and can analyse their genetic diversity. The next step is to expand the cohort for more comprehensive studies