The Spanish Polygenic Score reference distribution: a resource for personalized medicine
Here we present the Polygenic Score (PGS) distributions for 3124 common diseases and quantitative traits observed in the Spanish population. To achieve so, the genomes and exomes of 2190 unrelated individuals of Spanish ancestry were used. The analysis covered a wide range of diseases and traits, in...
| Autores: | , , , , , , , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Recursos: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/179165 |
| Acesso em linha: | https://hdl.handle.net/11441/179165 https://doi.org/10.1038/s41431-025-01850-9 |
| Access Level: | acceso abierto |
| Palavra-chave: | Genetic predisposition to disease Genome informatics Genome-wide association studies Predictive markers Risk factors |
| Resumo: | Here we present the Polygenic Score (PGS) distributions for 3124 common diseases and quantitative traits observed in the Spanish population. To achieve so, the genomes and exomes of 2190 unrelated individuals of Spanish ancestry were used. The analysis covered a wide range of diseases and traits, including both complex disorders, such as various types of cancer, and disorders associated with the digestive, cardiovascular, neuronal, and immune systems, as well as quantitative traits like hematological and anthropometric measurements. The resulting PGS distributions provide valuable insights into the genetic architecture of the Spanish population, offering a comprehensive framework for investigating disease susceptibility and potential risk factors in this specific population. The study has also explored potential relationships between diseases and traits based on PGS pairwise correlations, revealing significant correlations that warrant further investigation. These findings have contributed to increase our understanding of the genetic basis of human traits and have implications for personalized medicine and public health interventions in the Spanish population. In addition, for the sake of reproducibility, we provide a data processing pipeline, enabling the computation of PGS for external genomes and exomes. The pipeline, accessible on GitHub, supports parallel tasks on various computing platforms and contributes to the standardization of PGS comparisons globally. Lastly, a user-friendly web interface facilitates the exploration of PGS reference distributions, featuring a detailed table, distribution plots, and filtering options. This interface enhances accessibility for researchers and clinicians, fostering informed decision-making based on population-specific PGS distributions. |
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