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

Frontiers in Medicine

article

Jessica Germaine Shull¹  Lurdes Planas-Cerezales¹  Carla Lara Compte¹  Rosario Perona²  Maria Molina-Molina¹ 

[1] Interstitial Lung Disease ,(ILD) Multidisciplinary Unit, Hospital Universitari Bellvitge, Instituto de Investigación Biomédica de Bellvitge ,(IDIBELL), Universitat de Barcelona, Hospitalet de Llobregat, L'Hospitalet de Llobregat;Instituto de Investigaciones Biomedicas Consejo Superior de Investigaciones Científicas/Universidad Autónoma de Madrid;Centro Investigación Biomédica en Red de Enfermedades Raras, Instituto de Salud Carlos III;Centro Investigación Biomédica en Red de Enfermedades Respiratorias, Instituto de Salud Carlos III

关键词: pulmonary fibrosis;    pollution;    telomeres;    big data;    impact PM2.5;   

DOI  :  10.3389/fmed.2022.871898

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

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.

【 授权许可】

CC BY