Polygenic Risk, Complex Traits & Population Genomics
Session Overview
The study of complex traits and common diseases requires a population-scale lens to understand the combined influence of countless genetic variants and environmental factors. This session delves into the methodologies and implications of polygenic risk, exploring how aggregated genetic information across the genome can quantify an individual’s predisposition to disease. We will examine the journey from large-scale genetic discovery in diverse populations to the development of predictive models, while rigorously addressing the critical challenges of equity, generalizability, and responsible translation into clinical and public health contexts.
Why This Session Matters Now
Polygenic risk scores (PRS) represent a powerful tool for risk stratification, but their development and application sit at a complex crossroads of statistical genetics, clinical medicine, and ethics. The validity and utility of these scores are inherently tied to the diversity and scale of the underlying genetic studies. This session addresses the pressing need to advance robust, equitable, and clinically meaningful frameworks for PRS, ensuring that the promise of population genomics translates into benefits for all individuals, regardless of ancestry, and is integrated into healthcare with appropriate caution and clarity.
Key Scientific and Clinical Themes
Polygenic risk score development and validation
Examining the statistical methods for constructing PRS, including clumping and thresholding, penalized regression, and Bayesian approaches, alongside rigorous standards for their technical and clinical validation.
Application to common complex diseases
Exploring the evidence for the predictive utility of PRS across a spectrum of conditions such as cardiovascular disease, diabetes, psychiatric disorders, and cancer, and discussing their potential roles in prevention and early intervention.
Genome-wide association studies and fine-mapping
Discussing the foundational role of large-scale GWAS in identifying genetic loci associated with traits and diseases, and the subsequent methods for fine-mapping causal variants and genes within associated regions.
Population-specific allele frequencies and ancestry considerations
Highlighting the profound impact of genetic ancestry on variant frequencies and linkage disequilibrium patterns, and the resulting limitations and biases when PRS derived from one population are applied to another.
Risk stratification models and clinical integration
Focusing on how PRS can be combined with traditional clinical risk factors and family history to improve risk prediction models, and evaluating pathways for their potential integration into clinical workflows.
Addressing ancestry bias and equity in genomics
Confronting the historical lack of diversity in genomic research and its consequences. This theme focuses on strategies to build more representative datasets, develop ancestry-aware algorithms, and promote equitable access to genomic advances.
Large-scale biobank studies and data resources
Showcasing the pivotal role of national and international biobanks with linked genetic and phenotypic data in powering discovery and validation research, and discussing best practices for leveraging these resources.
Nature of Research in This Field
Research in this domain is characterized by its massive scale and collaborative, consortium-driven nature. It heavily relies on biostatistics, computational biology, and epidemiology. The work involves multi-stage processes: initial discovery in large cohorts, methodological refinement for score construction, and validation in independent and diverse populations. A significant and growing component of the field is dedicated to ethical, legal, and social implications (ELSI) research, ensuring that scientific advances are matched by careful consideration of their societal impact. The trajectory is increasingly translational, with a focus on generating the evidence needed for clinical guideline development.
Who Should Attend
This session is designed for:
- Statistical geneticists, epidemiologists, and population geneticists.
- Clinicians and clinical researchers in preventive medicine and complex diseases.
- Bioethicists and health policy researchers.
- Data scientists and biostatisticians working with large genomic datasets.
- Professionals involved in the management and analysis of biobank resources.
- Clinical laboratory directors considering the implementation of PRS.
- Trainees and investigators interested in the intersection of genetics, medicine, and society.
Session Perspective
“Polygenic Risk, Complex Traits & Population Genomics” confronts a central reality of human genetics: for most health outcomes, inheritance is not dictated by single genes but shaped by the subtle, collective contribution of thousands. This session underscores that realizing the potential of this polygenic paradigm demands rigorous science, inclusive datasets, and thoughtful translation. By examining the entire pipeline from discovery to application, this forum provides a crucial space to navigate the scientific promise and the imperative for equity, shaping a future where polygenic risk assessment—if implemented—is both accurate for and accessible to all.
If your research aligns with this session, we invite you to submit an abstract for consideration.
