Characterizing the link between multiple environmental exposures and Parkinsons disease exacerbation

描述多种环境暴露与帕金森病恶化之间的联系

• 批准号: 10707226
• 负责人: Danielle Braun
• 金额: $ 61.02万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-20 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10707226
• 关键词: Acceleration; Acute; Admission activity; Adverse effects; Age; Air Pollution; American; Carbon Black; Caring; Censuses; Central Nervous System; Cessation of life; Chronic; Climate; Communities; Complex; Computer software; Data; Data Science; Disease; Disease Outcome; Economic Burden; Ensure; Environmental Exposure; Environmental Health; Environmental Risk Factor; Etiology; Exposure to; Foundations; Genetic; Goals; Green space; Hospitalization; Incidence; Individual; Inpatients; Intervention; Knowledge; Link; Medical; Medicare; Medicare Part A; Medicare claim; Methods; Modeling; Nitrates; Nitrogen Dioxide; Outcome; Outpatients; Oxidative Stress; Ozone; Parkinson Disease; Pathogenesis; Peer Review; Persons; Pharmaceutical Preparations; Policies; Population; Poverty; Predisposition; Prevention strategy; Quality of life; Race; Reproducibility; Reproducibility of Results; Research; Research Personnel; Risk; Risk Factors; Role; Severities; Severity of illness; Socioeconomic Status; Statistical Data Interpretation; Statistical Methods; Subgroup; Sulfate; Symptoms; Temperature; Visit; Weather; burden of illness; climate change; comorbidity; fine particles; high risk; hospital readmission; hospitalization rates; improved; indexing; machine learning algorithm; machine learning method; modifiable risk; nervous system disorder; neuroinflammation; novel; open source; protective factors; response; sex; spatiotemporal; study population; urban planning

Project Summary/Abstract Parkinson's disease (PD) is one of the fastest growing neurological disorders in the US. The number of people with PD is projected to increase to over 12 million by 2030, with an economic burden surpassing $79 billion by 2037. The progression of pathogenesis is paralleled by an exacerbation in symptom severity, which underlies the need for hospitalization. If environmental exposures exacerbate PD symptoms, then days (acute effects) or years (chronic effects) of higher exposure should result in higher rates of hospitalizations. There is evidence that: 1) air pollution might negatively impact the central nervous system via oxidative stress and neuroinflammation; 2) temperature might increase the risk of PD due to thermoregulatory disorders or medication use; and 3) access to green spaces might protect against PD exacerbation. While few studies have examined the association between air pollution, temperature, and greenness and PD, the specific PM2.5 components contributing to PD are unknown, the effects of weather parameters on PD are poorly understood, and there is a lack of evidence on how to identify individuals who are at highest risk for adverse PD outcomes. To date, no study has estimated the link between simultaneous exposure to air pollution, weather, and greenness and PD exacerbation in a nationally representative population using rigorous statistical methods for confounding adjustment. Our goal is to conduct national studies to identify the multiple modifiable environmental factors that contribute to PD exacerbation and increased PD vulnerability. Specifically, in Aim 1 we will conduct national studies to estimate the chronic effects of 1a) PM2.5, NO2, ozone, PM2.5 components, 1b) greenness, 1c) simultaneous multiple exposures and their interactions on: a) incidence of first PD hospitalization and b) re-hospitalizations, as surrogate for accelerated disease severity. In Aim 2 we will estimate the acute effects of 2a) PM2.5, NO2, ozone, 2b) greenness, 2c) mean daily temperature and heat index, 3c) simultaneous multiple exposures on PD hospitalizations. In both Aims 1 and 2 in main analysis we will use Medicare Part A (inpatient hospitalizations) for the full study period (2000-2020), and we will then conduct sensitivity analyses using Part A linked to B (outpatient) and D (medication use) claims to increase rigor in identifying PD cases. In Aim 3 we will develop and apply machine learning methods and existing methods to identify subpopulations at increased risk. In Aim 4, to ensure transparency and reproducibility, we will develop peer-reviewed, open-source, and computationally efficient software so other investigators may implement our methods. In summary, findings of this study will provide evidence on the link between simultaneous environmental exposures and PD exacerbation with the highest possible scientific rigor, and will identify multiple modifiable risk and protective factors that lead to increased vulnerability in PD. Completion of this project will provide the foundation to inform actionable policy (e.g., ensure stringent air pollution standards for PM2.5, implement heat prevention strategies, inform urban planning) to help slow the PD disease burden and improve the quality of life for millions of Americans.

项目摘要/摘要 帕金森氏病（PD）是美国增长最快的神经系统疾病之一。人数 预计到2030年，PD预计将增加到超过1200万，经济负担超过790亿美元 2037年。发病机理的进展与症状严重程度的加剧相似，这是基础的 需要住院。如果环境暴露会加剧PD症状，则几天（急性影响）或 较高暴露的年（慢性影响）应导致更高的住院率。有证据表明： 1）空气污染可能会通过氧化应激和神经炎症对中枢神经系统产生负面影响； 2）温度可能会增加由于体温调节疾病或使用药物治疗而引起的PD风险； 3）访问 绿色空间可能可以防止PD加剧。虽然很少研究协会 在空气污染，温度和绿色和PD之间，有助于PD的特定PM2.5成分 尚不清楚，天气参数对PD的影响知之甚少，并且缺乏证据 关于如何识别患有不良PD结果风险最高的个人。迄今为止，尚无研究估计 同时暴露于空气污染，天气，绿色和PD加剧之间的联系 使用严格的统计方法来混淆调整的国家代表性人群。我们的目标是 进行国家研究以确定有助于PD的多种可修改环境因素 加剧并增加了PD脆弱性。具体而言，在AIM 1中，我们将进行国家研究以估计 1A）PM2.5，NO2，臭氧，PM2.5组件的慢性效应，1B）绿色，1C）同时多次 暴露及其相互作用：a）第一次PD住院和b）重新住院的发生率， 替代加速疾病的严重程度。在AIM 2中，我们将估计2A）PM2.5，NO2，臭氧的急性效应， 2b）绿色，2C）平均每日温度和热量指数，3C）同时在PD上进行多次暴露 住院。在AIM 1和2中，在主要分析中，我们将使用Medicare A部分（住院住院） 在整个研究期（2000-2020）中，我们将使用与B链接的A部分进行灵敏度分析 （门诊）和D（药物使用）要求在识别PD病例中增加严格性。在目标3中，我们将发展 并应用机器学习方法和现有方法，以识别风险增加的亚群。目标 4，为了确保透明度和可重复性，我们将在同行评审，开源和计算上开发 有效的软件，因此其他研究人员可以实施我们的方法。总而言之，这项研究的结果将 提供有关同时环境暴露与PD加剧之间联系的证据 可能的科学严谨性最高，并将确定多种可修改的风险和保护性因素 PD的脆弱性增加。该项目的完成将为可行的政策提供基础 （例如，确保PM2.5的严格空气污染标准，实施预防热策略，通知城市 计划）帮助减缓PD疾病负担并改善数百万美国人的生活质量。