A polygenic risk score (PRS) is a sophisticated genetic tool that provides an estimate of an individual’s inherited susceptibility to developing common, complex diseases. This single-value metric is calculated by analyzing the cumulative effect of hundreds to millions of small genetic variations across the entire genome. The score acts as a measure of an individual’s genetic liability, helping to stratify people based on their inherited predisposition for a particular health condition. The PRS has emerged as a promising technology in the field of personalized medicine and proactive healthcare.
What is a Polygenic Risk Score?
The concept of a polygenic risk score stems from understanding the genetic basis of traits and diseases. Genetic disorders fall along a spectrum, ranging from monogenic to polygenic conditions. Monogenic disorders, such as Cystic Fibrosis or Huntington’s disease, are rare and result from a mutation in a single gene. Conversely, polygenic traits and diseases, like height or Type 2 Diabetes, are influenced by the combined effect of multiple genes, often interacting with environmental factors.
Polygenic risk scores specifically address these complex traits by aggregating the effects of numerous tiny genetic differences. These differences are typically Single Nucleotide Polymorphisms (SNPs), which are variations in a single base pair of DNA. While any single SNP has an almost negligible impact on disease risk, the PRS effectively sums the overall effect of thousands of these common variants. The score thus represents the total burden of small-effect genetic variants an individual carries for a specific condition.
The Process of Score Calculation
The foundation for calculating a polygenic risk score lies in the massive datasets generated by Genome-Wide Association Studies (GWAS). A GWAS involves scanning the genomes of large populations to identify SNPs that are statistically associated with a particular disease or trait. This process identifies which genetic variants occur more frequently in individuals with the condition compared to those without it.
To construct the PRS, each identified SNP is assigned a statistical weight based on its effect size, as determined in the GWAS. The score is calculated for an individual by examining their DNA and summing the number of risk-increasing alleles they possess for each relevant SNP. Each allele count is multiplied by its unique statistical weight before being added up to create the final, single-value score.
Current Health Applications
Polygenic risk scores are finding growing utility in stratifying individuals for common complex diseases, providing insights that may complement traditional risk factors. These scores are used for conditions like Coronary Artery Disease, Type 2 Diabetes, certain Cancers, and neuropsychiatric disorders such as schizophrenia. The primary application is in identifying individuals who fall into the “high-risk tail” of the population distribution.
For instance, a high PRS for Coronary Artery Disease could identify a person with few traditional risk factors, like high cholesterol or obesity, but whose genetic makeup still confers a significantly elevated lifetime risk. This early identification allows healthcare providers to recommend intensified, personalized screening protocols, such as more frequent mammograms for a high breast cancer PRS, or earlier, more aggressive preventative interventions like lifestyle changes or medication. Integrating the PRS with established clinical models can enhance the precision of risk prediction, enabling more proactive and targeted care strategies.
Interpreting the Result and Context
A polygenic risk score is a measure of inherited predisposition and should not be confused with a diagnosis. The result is typically presented as a measure of relative risk, indicating how much more or less likely an individual is to develop a condition compared to the average person in the study population. For example, a high score might suggest an individual is three times more likely to develop a disease than someone with an average score.
The predictive power of a PRS is significantly modified by non-genetic factors, including lifestyle, diet, and environment. A high genetic risk does not negate the benefits of healthy habits, and a low score is not a shield against disease if an individual engages in high-risk behaviors. The score reflects a genetic starting point that is fixed at conception, but the eventual onset of a condition often requires an interaction with environmental influences.
A limitation involves the generalizability of PRS across diverse populations. The vast majority of the GWAS data used to calculate these scores has been derived from populations of European ancestry. This ancestral bias means that a PRS calculated for one population may have reduced accuracy and predictive power when applied to individuals from different ancestral backgrounds, potentially exacerbating health disparities.