Guare Lindsay A, Das Jagyashila, Caruth Lannawill, Setia-Verma Shefali
Department of Pathology and Laboratory Medicine, University of Pennsylvania Philadelphia, PA 19104, USA,
Pac Symp Biocomput. 2025;30:296-313. doi: 10.1142/9789819807024_0022.
Women's health conditions are influenced by both genetic and environmental factors. Understanding these factors individually and their interactions is crucial for implementing preventative, personalized medicine. However, since genetics and environmental exposures, particularly social determinants of health (SDoH), are correlated with race and ancestry, risk models without careful consideration of these measures can exacerbate health disparities. We focused on seven women's health disorders in the All of Us Research Program: breast cancer, cervical cancer, endometriosis, ovarian cancer, preeclampsia, uterine cancer, and uterine fibroids. We computed polygenic risk scores (PRSs) from publicly available weights and tested the effect of the PRSs on their respective phenotypes as well as any effects of genetic risk on age at diagnosis. We next tested the effects of environmental risk factors (BMI, lifestyle measures, and SDoH) on age at diagnosis. Finally, we examined the impact of environmental exposures in modulating genetic risk by stratified logistic regressions for different tertiles of the environment variables, comparing the effect size of the PRS. Of the twelve sets of weights for the seven conditions, nine were significantly and positively associated with their respective phenotypes. None of the PRSs was associated with different ages at diagnoses in the time-to-event analyses. The highest environmental risk group tended to be diagnosed earlier than the low and medium-risk groups. For example, the cases of breast cancer, ovarian cancer, uterine cancer, and uterine fibroids in highest BMI tertile were diagnosed significantly earlier than the low and medium BMI groups, respectively). PRS regression coefficients were often the largest in the highest environment risk groups, showing increased susceptibility to genetic risk. This study's strengths include the diversity of the All of Us study cohort, the consideration of SDoH themes, and the examination of key risk factors and their interrelationships. These elements collectively underscore the importance of integrating genetic and environmental data to develop more precise risk models, enhance personalized medicine, and ultimately reduce health disparities.
女性健康状况受到遗传和环境因素的双重影响。分别了解这些因素及其相互作用对于实施预防性的个性化医疗至关重要。然而，由于遗传因素和环境暴露，特别是健康的社会决定因素（SDoH），与种族和血统相关，未经仔细考量这些因素的风险模型可能会加剧健康差距。我们聚焦于“我们所有人”研究项目中的七种女性健康疾病：乳腺癌、宫颈癌、子宫内膜异位症、卵巢癌、先兆子痫、子宫癌和子宫肌瘤。我们根据公开可得的权重计算了多基因风险评分（PRSs），并测试了PRSs对各自表型的影响以及遗传风险对诊断年龄的任何影响。接下来，我们测试了环境风险因素（体重指数、生活方式指标和SDoH）对诊断年龄的影响。最后，我们通过对环境变量的不同三分位数进行分层逻辑回归，比较PRS的效应大小，研究环境暴露对调节遗传风险的影响。在这七种疾病的十二组权重中，有九组与各自的表型显著正相关。在事件发生时间分析中，没有一个PRS与不同的诊断年龄相关。环境风险最高的组往往比低风险和中等风险组更早被诊断。例如，体重指数最高三分位数组的乳腺癌、卵巢癌、子宫癌和子宫肌瘤病例分别比低体重指数和中等体重指数组显著更早被诊断。PRS回归系数在环境风险最高的组中通常最大，表明对遗传风险的易感性增加。本研究的优势包括“我们所有人”研究队列的多样性、对SDoH主题的考量以及对关键风险因素及其相互关系的研究。这些因素共同强调了整合遗传和环境数据以开发更精确的风险模型、加强个性化医疗并最终减少健康差距的重要性。
