Posted By: HGG Advances
Each month, the editors of Human Genetics and Genomics Advances interview an early-career researcher who has published work in the journal. This month, we check in with Oliver Pain, PhD, to discuss his paper “Leveraging Global Genetics Resources to Enhance Polygenic Prediction Across Ancestrally Diverse Populations.”
HGGA: What motivated you to start working on this project?
OP: Despite significant advances in our understanding of the genetic basis of complex traits and diseases — and the potential of polygenic scores (PGS) to guide personalized medicine — these tools are still only beginning to enter clinical use. A major limitation is their reduced predictive performance in populations that are underrepresented in genetic research, which raises concerns around equity and applicability.
Several methods have been developed to improve PGS performance across diverse ancestries by leveraging data from multiple populations; however, until now, there has been limited clarity on which approaches perform best across different scenarios. Many of these methods also require advanced skills in statistical genetics and programming, which creates barriers to their wider use.
I had previously developed GenoPred, a pipeline that makes it easier to calculate and apply PGS across ancestries using a standardized and interpretable framework. This project built on that work by systematically evaluating “multi-source” PGS methods — which combine GWAS data from different populations — and integrating these approaches into GenoPred. Our goal was to make it straightforward for others to robustly apply the best-performing methods and maximize predictive accuracy in ancestrally diverse populations.
HGGA: What about this paper/project most excites you?
OP: I’m especially excited by the potential for this work to directly support more equitable and accurate genetic prediction in diverse populations — something that is crucial for the ethical and effective translation of polygenic scores into research and clinical settings. It has also been rewarding to transform a methodological comparison into a practical tool that others can use immediately.
HGGA: What do you hope the impact of this work will be for the human genetics community?
OP: I hope this research lowers the barrier for others to implement polygenic scores in diverse cohorts by providing a transparent, robust, and easy-to-use pipeline. By integrating multi-ancestry methods into a unified tool, I aim to support the broader use of polygenic scores in underrepresented populations and help move the field closer to real-world clinical translation — in a way that is more equitable and accessible.
HGGA: What are some of the biggest challenges you’ve faced as a young scientist?
OP: One of the most challenging aspects of being an early-career researcher is the diversity of skills the role demands. Beyond designing and conducting research, there’s a growing need to develop software tools, communicate findings clearly to broad audiences, collaborate across disciplines, mentor students, and navigate the funding landscape.
I’ve embraced this variety as an opportunity to grow, and I’ve been fortunate to work with excellent mentors who’ve supported me along the way. As I look to the next stage of my career, I’m focused on building capacity through team leadership — I’m currently applying for a mid-career fellowship to support this goal and expand the impact of the research directions I’ve initiated.
HGGA: And for fun, what is one of the most fascinating things in genetics you’ve learned about in the past year or so?
OP: One fascinating insight I’ve come across recently is that causal variants for complex traits appear to be highly shared across global populations. For a long time, there has been concern that findings from European-centric genome-wide association studies wouldn’t translate to other ancestries. However, research using local ancestry inference has indicated strong cross-population correlation in causal effects — suggesting that, if we can identify the true causal variants, genetic discoveries could be more universally applicable than previously anticipated. Of course, this finding may vary across different environmental contexts, but it’s a hopeful finding for global health equity in genetics.
Oliver Pain, PhD, is a Sir Henry Wellcome Postdoctoral Research Fellow at the Maurice Wohl Clinical Neuroscience Institute at King’s College London.