Predicting phthalate bio-burden through medication and dietary supplement exposure

项目摘要/摘要 邻苯二甲酸酯在现代材料中普遍存在。美国国家健康和营养检查 调查(NHANES)显示，大多数美国成年人的尿液中存在可检测到的邻苯二甲酸酯代谢物水平。 这是令人不安的，因为邻苯二甲酸盐可以扰乱正常的内分泌信号，因此可能会推动 激素调节的结果包括乳腺癌、睾丸癌、前列腺癌、心脏代谢 疾病，男性和女性不孕不育，以及胎儿发育异常。尽管迫切需要流行病学研究 关于邻苯二甲酸盐对健康影响的研究，这样的研究很少。缺乏证据并不令人惊讶，因为很少有 流行病学研究收集尿液，这是测量邻苯二甲酸盐代谢物的唯一可靠媒介。 几种特定药物(如普萘洛尔、雷尼替丁和美沙拉明)包括使用邻苯二甲酸酯作为 用于延缓或延长胶囊中活性成分释放的辅料。这些药物的使用者有 邻苯二甲酸盐的负担比只接触背景知识的人高出50倍。药物使用者可以 因此有助于在邻苯二甲酸酯对健康影响的流行病学研究中确定高暴露人群 曝光。 我们将利用现有的资源，开发纵向邻苯二甲酸盐暴露的预测模型。 妇女健康倡议(WHI)的药物数据和尿邻苯二甲酸盐代谢物测量- 嵌套式乳腺癌病例对照研究(500例病例和1000例对照)。然后这些预测模型将被 应用于整个WHI队列，以乘以所有WHI参与者的邻苯二甲酸盐代谢物水平 (N&GT；160,000)。然后，我们将使用相乘的邻苯二甲酸盐数据来进行迄今为止最大规模的乳房研究 与邻苯二甲酸盐纵向接触有关的癌症风险。我们的模型和多重归因框架 可以扩展到具有药物数据的现有流行病学研究人群，以允许成本和时间- 对邻苯二甲酸盐暴露对健康影响的有效调查-无需注册和遵循新的 具有适当生物标本收集的队列。

PROJECT SUMMARY/ABSTRACT Phthalates are ubiquitous in modern materials. The U.S. National Health and Nutrition Examination Survey (NHANES) showed that most U.S. adults have detectable levels of phthalate metabolites in their urine. This is troubling because phthalates can disrupt normal endocrine signaling, and may therefore drive hormonally-mediated outcomes including breast cancer, testicular cancer, prostate cancer, cardiometabolic disorders, male and female infertility, and abnormal fetal development. Despite urgent need for epidemiologic studies of phthalate health effects, few such studies exist. This lack of evidence is unsurprising because few epidemiology studies collect urine, which is the only reliable medium for measuring phthalate metabolites. Several specific drugs (e.g., propranolol, ranitidine, and mesalamine) include products that use phthalates as excipients to delay or prolong release of active ingredients from capsules. Users of these medications have phthalate burdens up to 50-fold greater than individuals with only background exposure. Medication users may therefore help to define highly exposed groups in epidemiologic studies of the health effects of phthalate exposure. We will develop predictive models for longitudinal phthalate exposure by capitalizing on existing medication data and urinary phthalate metabolite measurements from a Women's Health Initiative (WHI)- nested breast cancer case-control study (500 cases and 1,000 controls). These predictive models will then be applied to the entire WHI cohort to multiply impute phthalate metabolite levels in all WHI participants (n>160,000). We will then use the multiply imputed phthalate data to conduct the largest-yet study of breast cancer risk as a function of longitudinal phthalate exposure. Our models and the multiple imputation framework may be extended to existing epidemiologic study populations with medication data to permit cost- and time- efficient investigation into the health effects of phthalate exposure—without having to enroll and follow new cohorts with appropriate biological specimen collection.