GWAS and polygenic scores
A genome-wide association study (GWAS) compares many people to find variants that occur more often with a trait. Most common diseases are polygenic: thousands of variants each add a tiny effect. A polygenic score sums these weighted effects into one number, a relative risk, not a diagnosis.
What a GWAS does
A GWAS compares the genome of many affected people with that of many unaffected and tests position by position whether a variant is more frequent in one group. The result is shown by the Manhattan plot: each dot is a variant, the height is the statistical strength. Towers that rise above a threshold mark regions linked to the trait.
From effect to score
Individually these variants usually explain only tiny risk differences. Their power lies in the sum. A polygenic score adds up a person's risk alleles, each with its weight from the study. The result is a number that places the person on a distribution, for instance in the upper or lower range compared with others.
Limits
A polygenic score is a relative risk, not a statement about a single life. Many studies come predominantly from cohorts of European ancestry, so the values fit other backgrounds less well. Lifestyle and environment shift the actual risk strongly. Genome presents such scores as orientation, explicitly not as a diagnosis.
What Genome measures. From hundreds of thousands of genotypes Genome can compute polygenic scores. They place you on a distribution, they do not predict an outcome.
Related topics
Sources
- 1Visscher et al., 2017 10 years of GWAS discovery: biology, function, and translation. American Journal of Human Genetics 101:5–22. doi.org/10.1016/j.ajhg.2017.06.005
- 2Torkamani et al., 2018 The personal and clinical utility of polygenic risk scores. Nature Reviews Genetics 19:581–590. doi.org/10.1038/s41576-018-0018-x