Harnessing PM2.5 Exposure Data to Predict Progression of Fibrotic Interstitial Lung Diseases Based on Telomere Length

Abstract

Cross-analysis of clinical and pollution factors could help calculate the risk of fibrotic interstitial lung disease (ILD) development and progression. The intent of this study is to build a body of knowledge around early detection and diagnosis of lung disease, harnessing new data sets generated for other purposes. We cross-referenced exposure levels to particulate matter 2.5 (PM2.5) with telomere length of a cohort of 280 patients with fibrotic ILD to weigh impact and associations. There was no linear correlation between PM2.5 and telomere length in our data sets, as the value of the correlation coefficient was 0.08. This exploratory study offers additional insights into methodologies for investigating the development and prognosis of pulmonary fibrosis.