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. 2022 Nov;141(11):1739-1748.
doi: 10.1007/s00439-022-02442-z. Epub 2022 Feb 28.

Uterine fibroid polygenic risk score (PRS) associates and predicts risk for uterine fibroid

Affiliations

Uterine fibroid polygenic risk score (PRS) associates and predicts risk for uterine fibroid

Jacqueline A Piekos et al. Hum Genet. 2022 Nov.

Abstract

Uterine fibroids (UF) are common pelvic tumors in women, heritable, and genome-wide association studies (GWAS) have identified ~ 30 loci associated with increased risk in UF. Using summary statistics from a previously published UF GWAS performed in a non-Hispanic European Ancestry (NHW) female subset from the Electronic Medical Records and Genomics (eMERGE) Network, we constructed a polygenic risk score (PRS) for UF. UF-PRS was developed using PRSice and optimized in the separate clinical population of BioVU. PRS was validated using parallel methods of 10-fold cross-validation logistic regression and phenome-wide association study (PheWAS) in a seperate subset of eMERGE NHW females (validation set), excluding samples used in GWAS. PRSice determined pt < 0.001 and after linkage disequilibrium pruning (r2 < 0.2), 4458 variants were in the PRS which was significant (pseudo-R2 = 0.0018, p = 0.041). 10-fold cross-validation logistic regression modeling of validation set revealed the model had an area under the curve (AUC) value of 0.60 (95% confidence interval [CI] 0.58-0.62) when plotted in a receiver operator curve (ROC). PheWAS identified six phecodes associated with the PRS with the most significant phenotypes being 218 'benign neoplasm of uterus' and 218.1 'uterine leiomyoma' (p = 1.94 × 10-23, OR 1.31 [95% CI 1.26-1.37] and p = 3.50 × 10-23, OR 1.32 [95% CI 1.26-1.37]). We have developed and validated the first PRS for UF. We find our PRS has predictive ability for UF and captures genetic architecture of increased risk for UF that can be used in further studies.

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Conflict of interest statement

STATEMENTS AND DECLARATIONS

Competing Interests

All authors have no relevant financial or non-financial interests to disclose.

Figures

Fig. 1.
Fig. 1.
Flow chart depicting methods used in this study. Pink boxes indicate usage of eMERGE Network and the blue box indicates usage of BioVU at various stages. The summary statistics from a previous uterine fibroid (UF) GWAS performed in eMERGE were taken as input for PRSice and PRSice performed the optimization of the polygenic risk score (PRS) in an independent BioVU sample. PRSice used the optimization set to determine the P-value threshold (PT) and linkage disequilibrium (LD) pruning to produce the best PRS possible. A PRS was then calculated for all samples in the validation set. The validation set is comprised of self-reported “non-Hispanic”, “white”, females from the eMERGE network and excludes samples used in the previous GWAS. 10-fold cross validation and phenome-wide association studies (PheWAS) were used as validation methods. Additionally, we performed supplemental discovery PheWAS in various gender and self-reported racial groups.
Fig. 2.
Fig. 2.
Density plot of the uterine fibroid (UF) polygenic risk score (PRS) calculated in the validation set. The validation set consisted of 18,605 self-reported “non-Hispanic white” (NHW) females whose case/control status was determined by phecode 218.1 ‘uterine leiomyoma’ according to phenome wide association study (PheWAS) case/control definitions. The cases had a mean PRS of 1,231.07 while controls had a mean PRS of 1,227.49. T-test revealed the means are significantly different (p = 4.09×10−15).
Fig. 3.
Fig. 3.
Receiver operator characteristic (ROC) curves of the various 10-fold cross validation logistic regression models produced using uterine fibroid (UF) status as the outcome and UF polygenic risk score (PRS) as the predictor in the validation set. The validation set consisted of 18,605 self-reported “non-Hispanic white” (NHW) females whose case/control status was determined by phecode 218.1 ‘uterine leiomyoma’ according to phenome wide association study (PheWAS) case/control definitions. With only the PRS as a predictor, the area under the curve (AUC) is 0.56. Adding 10 PCs, age, and BMI as covariates iteratively increases the area to 0.63. DeLong’s test for two correlated ROC curves found the AUC values of the models to be significantly different (p = 7.74×10−7).
Fig. 4
Fig. 4
A. Manhattan plot of PheWAS results for eMERGE non-Hispanic EA individuals (N=51,396). Model was adjusted for age, sex, BMI, and ten principal components. Most significantly associated phenotypes with the PRS are benign neoplasm of uterus (phecode 218) and uterine leiomyoma (phecode 218.1). Red line represents Bonferroni significance (2.7×10−5) and blue line represents suggested significance (2.7×10−4). (B) A zoomed in Manhattan plot of just genitourinary category phenotypes from the eMERGE non-Hispanic EA individuals adjusted for age, sex, BMI, and ten principal components PheWAS (N=51,396). Three of the four other significant phenotypes are in this category along with many phecodes sitting just below significance including ovarian cysts and endometriosis

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