Unraveling Genetic Ties: Leveraging Relatedness in Precision Medicine with WES

In the realm of precision medicine, large-scale sequencing projects are progressively becoming a cornerstone for understanding the genetic underpinnings of diseases. A recent article titled "Profiling and Leveraging Relatedness in a Precision Medicine Cohort of 92,455 Exomes," authored by Jeffrey Staples and colleagues, delves into the significant role of cryptic relatedness within these cohorts. The study, conducted on the first 92,455 exomes from the DiscovEHR cohort, highlights the pivotal findings and methodologies employed to harness relatedness in genetic research.

The Significance of Relatedness in Large Genetic Studies
Relatedness, or the genetic connection between individuals, is a common but often overlooked component in large genetic studies. In the DiscovEHR study, about 66,000 close relationships (first- and second-degree) were identified, involving over half of the study participants. This extensive relatedness can influence genetic analysis and interpretation, making it a critical factor to consider in research design.

Methodological Innovations
The study introduced a custom simulation framework called SimProgeny to model and understand the patterns of relatedness within the cohort. This tool is instrumental in predicting the impact of relatedness as the cohort scales up, projecting that over 70% of participants will have close genetic ties as the cohort expands to 250,000 individuals. These relationships are vital for reconstructing family pedigrees, which can significantly enhance the phasing accuracy of genetic mutations and the identification of novel de novo mutations.

Applications of Relatedness in Genetic Analyses
The relatedness data facilitated several applications: Improved Phasing Accuracy: By reconstructing pedigrees, researchers were able to phase over 20,947 rare, deleterious compound heterozygous mutations with greater precision.
Identification of De Novo Mutations: The study identified 3,415 de novo mutations across approximately 1,783 genes, critical for understanding sporadic genetic diseases.
Segregation Analysis: Known and suspected disease-causing mutations were analyzed through these pedigrees, providing insights into genetic diseases like familial hypercholesterolemia.

Implications for Precision Medicine
The findings underscore the importance of recognizing and leveraging familial ties within genetic studies. This approach not only improves the accuracy of genetic analyses but also allows for a deeper understanding of hereditary diseases. The methodologies developed, like the SimProgeny simulation framework, pave the way for more robust research designs that can accommodate the complexities of large-scale genetic data.

Conclusion
The DiscovEHR study exemplifies how embracing the intrinsic relatedness within a cohort can transform genetic research, turning potential analytical challenges into opportunities for discovery. As genetic databases continue to grow, the strategies developed in this study will be crucial for unlocking the full potential of genetic information in precision medicine, providing a roadmap for future studies to follow.

Reference:
Staples, J., Maxwell, E. K., Gosalia, N., Gonzaga-Jauregui, C., Snyder, C., Hawes, A., ... & Reid, J. G. (2018). Profiling and leveraging relatedness in a precision medicine cohort of 92,455 exomes. The American Journal of Human Genetics, 102(5), 874-889.