Topological data analysis identifies molecular phenotypes of idiopathic pulmonary fibrosis.

ABSTRACT:

Background

Idiopathic pulmonary fibrosis (IPF) is a debilitating, progressive disease with a median survival time of 3-5 years. Diagnosis remains challenging and disease progression varies greatly, suggesting the possibility of distinct subphenotypes.

Methods and results

We analysed publicly available peripheral blood mononuclear cell expression datasets for 219 IPF, 411 asthma, 362 tuberculosis, 151 healthy, 92 HIV and 83 other disease samples, totalling 1318 patients. We integrated the datasets and split them into train (n=871) and test (n=477) cohorts to investigate the utility of a machine learning model (support vector machine) for predicting IPF. A panel of 44 genes predicted IPF in a background of healthy, tuberculosis, HIV and asthma with an area under the curve of 0

SUBMITTER: Shapanis A 

PROVIDER: S-EPMC10314053 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature