利用基于端粒长度的PM2.5暴露数据预测纤维化间质性肺疾病的进展
Harnessing PM2.5 Exposure Data to Predict Progression of Fibrotic Interstitial Lung Diseases Based on Telomere Length.
作者信息
Shull Jessica Germaine, Planas-Cerezales Lurdes, Lara Compte Carla, Perona Rosario, Molina-Molina Maria
机构信息
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, Spain.
Instituto de Investigaciones Biomedicas Consejo Superior de Investigaciones Científicas/Universidad Autónoma de Madrid (CSIC/UAM), Madrid, Spain.
出版信息
Front Med (Lausanne). 2022 May 12;9:871898. doi: 10.3389/fmed.2022.871898. eCollection 2022.
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.
对临床因素和污染因素进行交叉分析有助于计算纤维化间质性肺病（ILD）发生和进展的风险。本研究的目的是利用为其他目的生成的新数据集，围绕肺部疾病的早期检测和诊断建立知识体系。我们将280例纤维化ILD患者队列的细颗粒物2.5（PM2.5）暴露水平与端粒长度进行交叉参照，以权衡其影响和关联。在我们的数据集中，PM2.5与端粒长度之间不存在线性相关性，因为相关系数的值为0.08。这项探索性研究为研究肺纤维化的发生和预后的方法提供了更多见解。
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