长期空气污染暴露与特发性肺纤维化的严重程度:来自 IPF-PRO 登记处的数据。

Coralynn Sack, Daniel M Wojdyla, Maeve G MacMurdo, Amanda Gassett, Joel D Kaufman, Ganesh Raghu, Carrie A Redlich, Peide Li, Amy L Olson, Thomas B Leonard, Jamie L Todd, Megan L Neely, Laurie D Snyder, Mridu Gulati
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引用次数: 0

摘要

理由:虽然暴露于空气污染是导致不良肺部结果的已知风险因素,但其对特发性肺纤维化(IPF)患者的影响却不甚了解:虽然暴露于空气污染是导致肺部不良后果的已知风险因素,但其对特发性肺纤维化(IPF)患者的影响却不甚了解:调查长期暴露于空气污染对特发性肺纤维化患者疾病严重程度和进展的影响,并确定基因组因素(如 MUC5B 启动子多态性或端粒长度)是否会改变这些关联:我们在IPF-PRO登记处进行了入组时和随访一年后的分析,IPF-PRO登记处是一个前瞻性观察登记处,2014年6月至2018年10月期间在美国46个地点登记了IPF患者。利用经过验证的国家时空模型估算了参与者居住地址在注册日期之前的五年平均污染暴露量(PM2.5、二氧化氮、臭氧)。多变量回归模型估算了入组时污染暴露与生理测量(FVC、DLCO、休息时补充氧气的使用)和生活质量测量(圣乔治呼吸问卷[SGRQ]、EuroQoL、咳嗽和痰液评估问卷)之间的关系。Cox 比例危险模型估计了污染物与入组后一年内死亡、肺移植或 FVC 预测百分比绝对值下降 >10% 的复合结果之间的关系。模型对个体水平和空间混杂因素进行了调整,包括疾病发病的替代因素。评估了基因-环境与 MUC5B 和端粒长度的相互作用:在835名参与者中,94%为非西班牙裔白人,76%为男性,平均(标清)年龄为70(7.7)岁。在完全调整分析中,PM2.5暴露量越高,生活质量越差,每2微克/立方米PM2.5的SGRQ活动评分(3.48[95%置信区间(CI)0.64, 6.32])和EuroQoL评分(-0.04[95%CI -0.06, -0.01])越高,入学时FVC预测百分比和DLCO预测百分比越低。臭氧暴露量每相差十亿分之三,入学时的预测肺活量百分比就会增加 1.57% [95% CI 0.15, 2.98],尽管在多污染物模型中这一影响有所减弱。二氧化氮与入组指标之间、污染暴露与一年结果之间均无关联,也无证据表明基因与环境之间存在相互作用:结论:在IPF-PRO注册中,长期暴露于PM2.5与注册时生活质量和肺功能下降有关,但与短期疾病进展或死亡率无关。没有证据表明基因组因素与污染的相互作用会改变影响。O3暴露与较高的FVC之间存在意想不到的关系,其原因尚不清楚。
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Long-Term Air Pollution Exposure and Severity of Idiopathic Pulmonary Fibrosis: Data from the IPF-PRO Registry.

Rationale: While exposure to air pollution is a known risk factor for adverse pulmonary outcomes, its impact in individuals with idiopathic pulmonary fibrosis (IPF) is less well understood.

Objective: To investigate the effects of long-term exposure to air pollution on disease severity and progression in patients with IPF and to determine whether genomic factors, such as MUC5B promoter polymorphism or telomere length, modify these associations.

Methods: We performed analyses at enrollment and after one year of follow-up in the IPF-PRO Registry, a prospective observational registry that enrolled individuals with IPF at 46 US sites from June 2014 to October 2018. Five-year average pollution exposures (PM2.5, NO2, O3) prior to enrollment date were estimated at participants' residential addresses with validated national spatio-temporal models. Multivariable regression models estimated associations between pollution exposure and physiologic measurements (FVC, DLCO, supplemental oxygen use at rest) and quality of life measurements (St. George's Respiratory Questionnaire [SGRQ], EuroQoL, Cough and Sputum Assessment Questionnaire) at enrollment. Cox proportional hazard models estimated associations between pollutants and a composite outcome of death, lung transplant, or >10% absolute decline in FVC % predicted in the year after enrollment. Models were adjusted for individual-level and spatial confounders, including proxies for disease onset. Gene-environment interactions with MUC5B and telomere length were assessed.

Results: Of 835 participants, 94% were non-Hispanic Whites, 76% were male, mean (SD) age was 70 (7.7) years. In fully adjusted analyses, higher PM2.5 exposure was associated with worse quality of life per SGRQ activity score (3.48 [95% confidence interval (CI) 0.64, 6.32] per 2µg/m3 PM2.5) and EuroQoL scores (-0.04 [95%CI -0.06, -0.01] per 2µg/m3 PM2.5), and lower FVC % predicted and lower DLCO% predicted at enrollment. Each 3 parts per billion difference in O3 exposure was associated with a 1.57% [95% CI 0.15, 2.98] higher FVC % predicted at enrollment, although this effect was attenuated in multi-pollutant models. There was no association between NO2 and enrollment measures, between pollution exposure and one-year outcomes, or evidence for gene-environment interactions.

Conclusion: In the IPF-PRO Registry, long-term exposure to PM2.5 was associated with worse quality of life and lung function at enrollment, but not with short-term disease progression or mortality. There was no evidence of effect modification by interaction of genomic factors with pollution. The reason for the unexpected relationship between O3 exposure and higher FVC is unclear.

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