Abstract
Here, we argue that polygenic risk scores (PRSs) are different epistemic objects as compared to other biomarkers such as blood pressure or sodium level. While the latter two may be subject to variation, measured inaccurately or interpreted in various ways, blood flow has pressure and sodium is available in a concentration that can be quantified and visualised. In stark contrast, PRSs are calculated, compiled or constructed through the statistical assemblage of genetic variants. How researchers frame and name PRSs has consequences for how we interpret and value their results. We distinguish between the tangible and inferential understanding of PRS and the corresponding languages of measurement and computation, respectively. The conflation of these frames obscures important questions we need to ask: what PRS seeks to represent, whether current ways of ‘doing PRS’ are optimal and responsible, and upon what we base the credibility of PRS-based knowledge claims.
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Abbreviations
- GWAS:
-
Genome-wide association studies
- PRS(s):
-
Polygenic Risk Score(s)
- RCT:
-
Randomized clinical trial
- SNP:
-
Single nucleotide polymorphism
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We thank Lotte Thissen for providing valuable and constructive feedback on earlier versions of our manuscript.
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BP: Conceptualization, writing – original draft, writing – review & editing; ACJWJ: Conceptualization, writing – original draft, writing – review & editing (CRediT roles).
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Penders, B., Janssens, A.C.J.W. Do we measure or compute polygenic risk scores? Why language matters. Hum Genet 141, 1093–1097 (2022). https://doi.org/10.1007/s00439-021-02262-7
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DOI: https://doi.org/10.1007/s00439-021-02262-7