Characterizing the link between multiple environmental exposures and Parkinsons disease exacerbation

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。人数之多 预计到2030年，PD将增加到1200万以上，经济负担到 2037年。发病机制的进展与症状严重程度的恶化是平行的，这是基础 住院的需要。如果环境暴露加剧了帕金森病的症状，那么天数(急性影响)或 多年(慢性影响)的较高暴露应导致较高的住院率。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而导致的帕金森病的风险；以及3)接触 绿色空间可能会预防帕金森病的恶化。虽然很少有研究研究这种联系 在空气污染、温度和绿度与PD之间，特定的PM2.5成分对PD有贡献 尚不清楚，天气参数对PD的影响知之甚少，缺乏证据 关于如何识别帕金森病不良后果风险最高的个人。到目前为止，还没有研究估计 同时暴露于空气污染、天气和绿化与帕金森病恶化之间的联系 全国代表性人口使用严格的统计方法进行混杂调整。我们的目标是 进行全国性研究，以确定导致帕金森病的多种可改变的环境因素 病情恶化，帕金森病易感性增加。具体地说，在目标1中，我们将进行全国性研究，以估计 1a)PM2.5、NO2、臭氧、PM2.5组分、1b)绿色、1c)同时倍数的慢性影响 暴露及其相互作用对：a)首次帕金森病住院和b)再次住院的发生率，如 作为加速疾病严重程度的替代品。在目标2中，我们将评估PM2.5、NO2、臭氧、 2b)绿度，2c)平均每日温度和热度指数，3c)同时多次暴露在PD上 住院治疗。在目标1和目标2的主要分析中，我们将使用医疗保险A部分(住院治疗) 在整个研究期间(2000-2020)，然后我们将使用链接到B的A部分进行敏感性分析 (门诊)和D(药物使用)声称在识别PD病例方面更加严格。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 4、为了确保透明度和可重复性，我们将开发同行评审、开放源代码和计算的 高效的软件，以便其他调查人员可以实现我们的方法。总而言之，这项研究的结果将 提供同时暴露在环境中与帕金森病恶化之间联系的证据 尽可能高的科学严谨性，并将确定导致以下问题的多个可修改风险和保护因素 帕金森病的脆弱性增加。该项目的完成将为制定可操作的政策提供基础 (例如，确保严格的PM2.5空气污染标准，实施防暑战略，通知城市 计划)帮助减缓帕金森氏症的负担，提高数百万美国人的生活质量。

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.