To explain it simply: polygenic testing utilizes information from genome-wide association studies (GWAS) to identify variants associated with a condition of interest. This information is formatted into a dataset by separating important signals from 'noise' and then used to select disease-associated variants that meet pre-specified thresholds for risk association. This variant information is then combined to create a cumulative result called a Polygenic Score (PGS), which is validated using an independent dataset of individuals. Once validated, an algorithm is created that utilizes this information to create individual risk scores for new patients. The resulting reports represent the risk for an individual to develop a condition compared to an others in the population that are at average risk.
GenomicMD’s utilizes 2 types of polygenic testing for our LGRA reports: PGS (which is more broad) and a subset of PGS called GRS (or Genetic Risk Scores - which are more personalized to the individual patient). Please see the chart below for a breakdown of the difference between these 2 testing methods.
| PGS vs GRS Comparison | |
| PGS | GRS |
| Thousands to millions of SNPs | Tens to hundreds of SNPs |
| SNPs with both moderate and modest effects on disease risk | SNPs with mainly moderate effects on disease risk |
| Pan Ancestry | Ancestry Specific (when data is available) |
| Broad applicability | More accurate and personalized |
| Results categorized as 'increased' or 'average' risk as compared to the general population's risk of developing a condition | Results reported as a numerical score (relative risk) that estimates personal risk of developing a condition over a predefined lifespan |
* For additional information about the methods and limitations of GenomicMD's Lifetime Genomics Risk Assessment please see the answer to this question.