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.

项目总结/摘要 帕金森氏病（PD）是美国增长最快的神经系统疾病之一。的人数 到2030年，PD预计将增加到1200多万，经济负担将超过790亿美元。 2037.发病机制的进展与症状严重程度的加剧并行，这是基础 需要住院治疗。如果环境暴露加剧了PD症状，则应在第二天（急性效应）或第三天（急性效应）， 多年（慢性效应）的较高暴露应该会导致更高的住院率。有证据表明： 1)空气污染可能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障碍或药物使用导致的PD风险;以及3）访问 到绿色空间可以防止PD恶化。虽然很少有研究调查这种联系， 空气污染、温度和绿色度与PD之间的关系，导致PD的特定PM2.5组分 未知，天气参数对PD的影响知之甚少，并且缺乏证据 如何识别PD不良结局风险最高的个体。到目前为止，没有研究估计 同时暴露于空气污染，天气和绿色与PD恶化之间的联系， 使用严格的统计方法进行混杂调整的全国代表性人群。我们的目标是 开展全国性研究，以确定导致帕金森病的多种可改变的环境因素 恶化和PD脆弱性增加。具体而言，在目标1中，我们将进行国家研究， 1a）PM2.5、NO2、臭氧、PM2.5组分的慢性效应，1b）绿色，1c）同时多重 暴露及其相互作用：a）首次PD住院的发生率和B）再次住院， 加速疾病严重程度的替代物。在目标2中，我们将评估2a）PM2.5、NO2、臭氧， 2b）绿色，2c）平均每日温度和热指数，3c）PD同时多次暴露 住院治疗在主要分析的目标1和2中，我们将使用Medicare A部分（住院患者） 然后，我们将使用与B相关的A部分进行敏感性分析 （门诊）和D（药物使用）声称增加了识别PD病例的严格性。在目标3中，我们将开发 并应用机器学习方法和现有方法来识别风险增加的亚群。在Aim中 4、为了确保透明度和可重复性，我们将开发同行评审、开源和计算 高效的软件，以便其他研究人员可以实施我们的方法。总之，这项研究的结果将 提供关于同时环境暴露与PD恶化之间联系的证据， 尽可能高的科学严谨性，并将确定多种可改变的风险和保护因素，导致 PD的脆弱性增加。该项目的完成将为制定可行的政策奠定基础 (e.g.,确保严格的PM2.5空气污染标准，实施防热策略，通知城市 计划），以帮助减缓PD疾病负担，提高数百万美国人的生活质量。