Winters Jessica L G, Piekos Jacqueline A, Hellwege Jacklyn N, Dikilitas Ozan, Kullo Iftikhar J, Schaid Daniel J, Edwards Todd L, Velez Edwards Digna R
Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37203, USA.
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Pac Symp Biocomput. 2025;30:268-280. doi: 10.1142/9789819807024_0020.
Uterine leiomyomata, or fibroids, are common gynecological tumors causing pelvic and menstrual symptoms that can negatively affect quality of life and child-bearing desires. As fibroids grow, symptoms can intensify and lead to invasive treatments that are less likely to preserve fertility. Identifying individuals at highest risk for fibroids can aid in access to earlier diagnoses. Polygenic risk scores (PRS) quantify genetic risk to identify those at highest risk for disease. Utilizing the PRS software PRS-CSx and publicly available genome-wide association study (GWAS) summary statistics from FinnGen and Biobank Japan, we constructed a multi-ancestry (META) PRS for fibroids. We validated the META PRS in two cross-ancestry cohorts. In the cross-ancestry Electronic Medical Record and Genomics (eMERGE) Network cohort, the META PRS was significantly associated with fibroid status and exhibited 1.11 greater odds for fibroids per standard deviation increase in PRS (95% confidence interval [CI]: 1.05 - 1.17, p = 5.21x10-5). The META PRS was validated in two BioVU cohorts: one using ICD9/ICD10 codes and one requiring imaging confirmation of fibroid status. In the ICD cohort, a standard deviation increase in the META PRS increased the odds of fibroids by 1.23 (95% CI: 1.15 - 1.32, p = 9.68x10-9), while in the imaging cohort, the odds increased by 1.26 (95% CI: 1.18 - 1.35, p = 2.40x10-11). We subsequently constructed single ancestry PRS for FinnGen (European ancestry [EUR]) and Biobank Japan (East Asian ancestry [EAS]) using PRS-CS and discovered a nominally significant association in the eMERGE cohort within fibroids and EAS PRS but not EUR PRS (95% CI: 1.09 - 1.20, p = 1.64x10-7). These findings highlight the strong predictive power of multi-ancestry PRS over single ancestry PRS. This study underscores the necessity of diverse population inclusion in genetic research to ensure precision medicine benefits all individuals equitably.
子宫平滑肌瘤，即纤维瘤，是常见的妇科肿瘤，会引起盆腔和月经症状，对生活质量和生育愿望产生负面影响。随着纤维瘤的生长，症状可能会加剧，并导致侵入性治疗，而这种治疗不太可能保留生育能力。识别纤维瘤风险最高的个体有助于更早地进行诊断。多基因风险评分（PRS）可量化遗传风险，以识别疾病风险最高的个体。利用PRS软件PRS-CSx以及来自芬兰基因库（FinnGen）和日本生物银行（Biobank Japan）的公开全基因组关联研究（GWAS）汇总统计数据，我们构建了一个针对纤维瘤的多血统（META）PRS。我们在两个跨血统队列中验证了META PRS。在跨血统电子病历与基因组学（eMERGE）网络队列中，META PRS与纤维瘤状态显著相关，PRS每增加一个标准差，患纤维瘤的几率就会增加1.11倍（95%置信区间[CI]：1.05 - 1.17，p = 5.21×10⁻⁵）。META PRS在两个BioVU队列中得到验证：一个使用国际疾病分类第九版/第十版（ICD9/ICD10）编码，另一个需要通过影像学确认纤维瘤状态。在ICD队列中，META PRS增加一个标准差会使患纤维瘤的几率增加1.23倍（95% CI：1.15 - 1.32，p = 9.68×10⁻⁹），而在影像学队列中，几率增加1.26倍（95% CI：1.18 - 1.35，p = 2.40×10⁻¹¹）。随后，我们使用PRS-CS为芬兰基因库（欧洲血统[EUR]）和日本生物银行（东亚血统[EAS]）构建了单血统PRS，并在eMERGE队列中发现纤维瘤与EAS PRS之间存在名义上的显著关联，但与EUR PRS不存在关联（95% CI：1.09 - 1.20，p = 1.64×10⁻⁷）。这些发现突出了多血统PRS相对于单血统PRS的强大预测能力。这项研究强调了在基因研究中纳入多样化人群的必要性，以确保精准医学公平地惠及所有个体。
