肺纤维化
医学
纤维化
寻常性间质性肺炎
肺
病理
癌症研究
间质性肺病
内科学
作者
Iain R. Konigsberg,Raphael Borie,Avram D Walts,Jonathan Cardwell,Mauricio Rojas,Fabian Metzger,Stefanie M. Hauck,Tasha E. Fingerlin,Ivana V. Yang,David A. Schwartz
标识
DOI:10.1165/rcmb.2020-0546oc
摘要
Molecular patterns and pathways in idiopathic pulmonary fibrosis (IPF) have been extensively investigated, but few studies have assimilated multiomic platforms to provide an integrative understanding of molecular patterns that are relevant in IPF. Herein, we combine the coding and noncoding transcriptomes, DNA methylomes, and proteomes from IPF and healthy lung tissue to identify molecules and pathways associated with this disease. RNA sequencing, Illumina MethylationEPIC array, and liquid chromatography-mass spectrometry proteomic data were collected on lung tissue from 24 subjects with IPF and 14 control subjects. Significant differential features were identified by using linear models adjusting for age and sex, inflation, and bias when appropriate. Data Integration Analysis for Biomarker Discovery Using a Latent Component Method for Omics Studies was used for integrative multiomic analysis. We identified 4,643 differentially expressed transcripts aligning to 3,439 genes, 998 differentially abundant proteins, 2,500 differentially methylated regions, and 1,269 differentially expressed long noncoding RNAs (lncRNAs) that were significant after correcting for multiple tests (false discovery rate 0.8) with MMP7 (matrix metalloproteinase 7). Therefore, by using a system biology approach, we have identified novel molecular relationships in IPF.
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