A Polygenic Risk Score (PRS) estimates an individual’s genetic predisposition to certain traits or diseases. It summarizes the collective influence of numerous genetic variations across a person’s genome. It provides a statistical estimate of genetic likelihood compared to a reference population.
Understanding the Genetic Building Blocks
Polygenic Risk Scores are built upon fundamental genetic data. They involve single nucleotide polymorphisms (SNPs), which are common variations in the DNA sequence where a single nucleotide base differs between individuals. While each SNP typically has a small individual effect, their combined influence is significant for complex traits and diseases.
Information about SNPs comes primarily from Genome-Wide Association Studies (GWAS). GWAS are large-scale research efforts that scan the genomes of many individuals to find SNPs statistically associated with a particular trait or disease. These studies provide “effect sizes” or “weights” for each SNP, quantifying its association with the trait.
Variations have varying impacts. These are captured by their effect sizes, crucial for accurately calculating a PRS.
The Calculation Process
PRS calculation begins with collecting genetic data. This involves genotyping, which identifies specific alleles (gene versions) at many relevant SNPs across an individual’s genome.
Each identified SNP is assigned a “weight.” These weights correspond to effect sizes from Genome-Wide Association Studies. This ensures SNPs with a stronger association contribute more significantly to the final score.
Weighted SNP contributions are summed to produce a raw Polygenic Risk Score. Raw scores are then standardized or compared against a reference population. This converts the raw score into a meaningful metric, such as a percentile, indicating an individual’s genetic predisposition within that population.
Interpreting Your Score
A PRS provides a measure of relative genetic predisposition, not an absolute risk or diagnosis. A higher score indicates increased genetic likelihood for a trait or disease compared to a reference population; a lower score suggests decreased likelihood.
Scores are presented as percentiles, illustrating an individual’s position within a population. For example, a 90th percentile score means an individual’s genetic risk is higher than 90% of the reference group.
A PRS indicates a predisposition, not a definite outcome. The score suggests genetic likelihood, but environmental factors, lifestyle choices, and other genes also play substantial roles in trait or disease development. Even individuals with a high PRS may not develop the condition, and those with a low PRS are not entirely protected.
Applications and Important Considerations
Polygenic Risk Scores are used in several areas. They identify individuals with higher genetic likelihood for common diseases like heart disease or type 2 diabetes. This supports targeted screening or preventative measures. PRS also predicts medication response, contributing to personalized medicine.
Important considerations and limitations exist for PRS. Population specificity is a significant factor; a PRS developed using data primarily from one population (e.g., European ancestry) may not be accurate for others due to genetic architecture differences. This highlights the need for more diverse genetic studies.
Genetic and environmental factor interaction is another consideration. PRS only accounts for genetic predisposition, while environmental and lifestyle elements significantly influence disease development.
PRS are a risk assessment tool, not a diagnostic test. They estimate genetic likelihood but do not confirm disease presence. Misinterpreting PRS as a diagnosis can lead to anxiety or inappropriate medical decisions. Ethical implications involve concerns about misinterpretation, psychological impact, and genetic discrimination. These necessitate careful communication and robust ethical frameworks as PRS integrate into healthcare.