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Multicenter Study
. 2020 Mar 17;117(11):5997-6002.
doi: 10.1073/pnas.1919976117. Epub 2020 Mar 4.

Assessing thyroid cancer risk using polygenic risk scores

Affiliations
Multicenter Study

Assessing thyroid cancer risk using polygenic risk scores

Sandya Liyanarachchi et al. Proc Natl Acad Sci U S A. .

Abstract

Genome-wide association studies (GWASs) have identified at least 10 single-nucleotide polymorphisms (SNPs) associated with papillary thyroid cancer (PTC) risk. Most of these SNPs are common variants with small to moderate effect sizes. Here we assessed the combined genetic effects of these variants on PTC risk by using summarized GWAS results to build polygenic risk score (PRS) models in three PTC study groups from Ohio (1,544 patients and 1,593 controls), Iceland (723 patients and 129,556 controls), and the United Kingdom (534 patients and 407,945 controls). A PRS based on the 10 established PTC SNPs showed a stronger predictive power compared with the clinical factors model, with a minimum increase of area under the receiver-operating curve of 5.4 percentage points (P ≤ 1.0 × 10-9). Adding an extended PRS based on 592,475 common variants did not significantly improve the prediction power compared with the 10-SNP model, suggesting that most of the remaining undiscovered genetic risk in thyroid cancer is due to rare, moderate- to high-penetrance variants rather than to common low-penetrance variants. Based on the 10-SNP PRS, individuals in the top decile group of PRSs have a close to sevenfold greater risk (95% CI, 5.4-8.8) compared with the bottom decile group. In conclusion, PRSs based on a small number of common germline variants emphasize the importance of heritable low-penetrance markers in PTC.

Keywords: GWAS; polygenic risk score; risk prediction; thyroid cancer.

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Conflict of interest statement

Competing interest statement: J.G., E.F., V.T., G.T., and K.S. are employees of deCODE/Amgen. The other authors have no conflicts of interest to declare.

Figures

Fig. 1.
Fig. 1.
ROC curves assessing the discriminative power of the PRS models for the Ohio (A), Iceland (B), and UKB (C) study groups. The CF model includes year of birth, gender, ancestry, and familiality for all groups except the UKB group, for which no information was available about family history of thyroid cancer.
Fig. 2.
Fig. 2.
OR estimates for 10-SNP PRS deciles of thyroid cancer status obtained from the meta-analysis results from the Ohio, Iceland, and the UKB study groups, using the bottom 10-SNP PRS decile (0 to 10%) as the reference group (shown as a horizontal solid line).

References

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