Global genomics: representative research is key to unlocking the full potential of precision medicine

“Genomic science should not work for only a fraction of humanity. My career has been dedicated to changing that.”

Segun Fatumo (left) is Professor and Chair of Genomic Diversity at Queen Mary University of London (UK) and the head of Non-Communicable Disease Genomics at the Medical Research Council in Uganda. His work sits at the intersection of genomics, data science and health equity, driven by a mission to make genomic discovery globally representative so that precision medicine works for all, not just a privileged few.

Segun trained in computational genetics and statistical genomics, and over the years, he has led large-scale genome-wide association studies (GWAS) and polygenic risk score (PRS) research across diverse populations. Much of his work has focused on understanding cardiometabolic disease, blood cell traits, kidney disease and, more recently, psychiatric genetics in African populations.

Beyond the science itself, Segun’s career has evolved into something larger, building data resources and biobanks that are helping to shape policy and strengthen research capacity so that genomics becomes truly global, rather than disproportionately Eurocentric.

In this interview, we spoke with Segun to learn about the high-throughput genomics and advanced computational analyses he and his team use to increase African genomic representation. Furthermore, Segun shares how he is strengthening genomic research capacity in Africa as well as influencing global genomics policy, encouraging a shift from simply including African data to empowering African scientists.

Please tell us about the diversity gap that’s present in genomic data and provide examples of how these gaps are affecting people.

Over 86% of participants in GWAS are of European ancestry, yet they represent less than 20% of the global population. Africa, which harbors the greatest human genetic diversity on Earth, remains dramatically underrepresented with only ~1% representation in genomics.

This imbalance has real clinical consequences. One of the most powerful examples is PCSK9, a gene now central to cholesterol-lowering therapies. Loss-of-function variants in PCSK9 were first identified in individuals of African ancestry who naturally had very low LDL cholesterol and reduced cardiovascular risk. That discovery directly led to the development of PCSK9 inhibitor drugs, which are now widely used to prevent heart disease worldwide in people of ALL ancestries not just African. In other words, insights from African genetic variation transformed global cardiovascular medicine.

Yet paradoxically, African populations remain underrepresented in the very genomic datasets used to refine cardiovascular risk prediction tools, including PRSs. PRSs developed in European populations often perform poorly in African populations. A test that predicts disease risk accurately in the UK may be unreliable in Uganda, Nigeria or South Africa. That means misclassification of risk, missed diagnoses and widening health disparities.

In pharmacogenomics, genetic variants influencing drug metabolism differ across populations. If drug development and dosing guidelines are based primarily on European data, we risk suboptimal treatment or adverse effects elsewhere. Even more fundamentally, by not studying African genomes adequately, we are missing novel biological insights. Africa’s genetic diversity offers unparalleled opportunities to refine causal variants, refine disease loci and discover new biology that benefits everyone. The diversity gap is both a scientific blind spot and a social justice issue.

What programs or studies are you conducting to bridge this gap?

My work focuses on four complementary pillars: global genomic diversity; genomic epidemiology and population health; capacity building and training; and building data resources and biobanks.

One major initiative involves large-scale genomic analyses using African cohorts, including KidneyGenAfrica – a partnership that is delivering research and training excellence in genomics of kidney disease in Africa. One component of this project leverages genomic datasets across Africa through genome-wide and rare variant studies, allowing for the identification of population-specific and shared genetic architecture across African populations.

We are also building large biobanking and multi-omics initiatives to ensure long-term infrastructure. These include pan-African partnerships that integrate genomics with proteomics and metabolomics, ensuring that Africa is part of the next phase of precision medicine. Importantly, we are not simply ‘including’ African samples in external projects. We are strengthening African-led science by ensuring leadership, authorship and intellectual ownership remain local. We strongly believe that bridging the gap is not just about extracting more data. It is about giving opportunity.

What lab techniques and computational tools do you and your team use to collect and analyze this genomic data?

Our work spans high-throughput genomics and advanced computational analysis. On the laboratory side, we use whole-genome sequencing, whole-exome sequencing and high-density genotyping arrays optimized for African variation. We integrate these with multi-omics platforms, including proteomics and metabolomics, to move beyond single-layer genomic analysis.

Computationally, our team works extensively with GWAS, rare variant burden testing, fine-mapping and causal inference, PRS development and Mendelian randomization.

We rely heavily on programming languages such as R, Perl and Python-based pipelines, scalable cloud computing infrastructure and reproducible workflows. Because African genomes are more diverse and have lower linkage disequilibrium compared to European populations, our statistical models must be carefully adapted. Methods developed in homogeneous populations cannot simply be applied unchanged. In many ways, working in African genomics pushes methodological innovation forward.

What role do you play in shaping global genomics policy?

Equity does not happen accidentally; we believe it must be designed into systems. I contribute to and lead global discussions on genomic diversity, equitable data sharing and inclusive research design through international collaborations, advisory boards and partnerships across Africa, Europe and North America.

Community engagement frameworks begin with trust. In many African settings, historical exploitation has created understandable skepticism toward biomedical research. Therefore, engagement must be bidirectional. Communities are not merely participants, they are stakeholders.

Our ethical guidelines involve transparent consent processes, clear data governance structures, fair benefit-sharing mechanisms, and capacity development embedded into every grant. Equity-centered policies ensure that data generated in Africa supports African scientists, institutions and healthcare systems. This includes local leadership in projects, training components in grants and long-term infrastructure investment. We believe that global genomics policy must move from inclusion to empowerment.

How are you strengthening genomic research capacity in Africa, including training initiatives for early career scientists?

Capacity building is central to everything I do. We are training early career scientists in statistical genetics, bioinformatics, data science and grant writing through workshops, exchange programs and structured mentorship. Many of our initiatives include annual training academies and hands-on computational courses using real genomic datasets.

In our KidneyGenAfrica grant funded by MRC, we have funding to train up to 120 early career African researchers, and up to ten of these researchers will be supported for research exchange up to 6 months with our collaborators in the USA, Europe and UK. Once they return to their countries in Africa, we then provide seed funding to start a project at their institution.

In our training, we emphasize independent analytical skills, reproducible research practices, leadership development and international collaboration. A key priority is ensuring that young African scientists lead analyses, publish first-author papers and compete successfully for independent funding. I believe that sustainable impact will not come from external experts flying in briefly. It will come from a critical mass of highly trained African genomic scientists who are shaping global research agendas themselves.

How do you envision diverse and comprehensive genomic datasets changing how we approach research and develop healthcare strategies?

When genomic datasets become truly diverse, three transformative shifts will occur. First, biological discovery will accelerate. Africa’s genetic diversity improves fine-mapping resolution and enhances our ability to pinpoint causal variants. This benefits global science.

Second, predictive tools such as PRSs will become more equitable and clinically reliable across populations. Precision medicine cannot be precise if it excludes most of the world.

Third, healthcare strategies will move from reactive to preventive models tailored to population-specific risk architecture. Drug development pipelines will become more inclusive, and public health strategies will better reflect global realities.

Ultimately, diversity in genomics is the key to unlocking the full potential of precision medicine. It is to the benefit of all populations if genomic studies are diversified to include Africans and other underrepresented populations. Giving the right treatment to the right person at the right time will lead to better outcomes for patients. This is precision medicine.

The interviewee has not disclosed any competing interests.

The opinions expressed in this interview are those of the interviewees and do not necessarily reflect the views of BioTechniques or Taylor & Francis Group.