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Comment
. 2018 Dec;14(12):723-724.
doi: 10.1038/s41581-018-0067-6.

Genome-wide polygenic risk predictors for kidney disease

Lili Liu  1 , Krzysztof Kiryluk  2
Affiliations
Comment

Genome-wide polygenic risk predictors for kidney disease

Lili Liu et al. Nat Rev Nephrol. 2018 Dec.

Abstract

A new study reports that genome-wide polygenic risk scores can identify individuals at risk of common complex diseases, such as coronary artery disease or type 2 diabetes, with comparable performance to that of monogenic mutation screens. These findings support the potential clinical utility of genome-wide association study (GWAS)-based risk stratification; however, several issues need to be addressed before this approach can be applied to kidney disease.

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Conflict of interest statement

Competing interests

The authors declare no competing interests.

Figures

Fig. 1 |
Fig. 1 |. Construction of a GPS.
A genome-wide polygenic risk score (GPS) is based on genome-wide association study (GWAS) summary statistics. The optimization step enables selection of the best method according to the genetic architecture of a disease under study. The validation step requires an external cohort and is critical to obtaining reliable metrics of performance. Clinical predictors of absolute risk will require incorporation of additional demographic, clinical or lifestyle factors into composite risk models. AUROC, area under receiver operating characteristic. SNP, single-nucleotide polymorphism.
See this image and copyright information in PMC

Comment on

References

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