Konigsberg, I.R.* ; Borie, R.* ; Walts, A.D.* ; Cardwell, J.* ; Rojas, M.* ; Metzger, F. ; Hauck, S.M. ; Fingerlin, T.E.* ; Yang, I.V.* ; Schwartz, D.A.*
Molecular signatures of idiopathic pulmonary fibrosis.
Am. J. Respir. Cell Mol. Biol. 65, 430-441 (2021)
Molecular patterns and pathways in idiopathic pulmonary fibrosis (IPF) have been extensively investigated but few studies have assimilated multi-omic platforms to provide an integrative understanding of molecular patterns that are relevant in IPF. Herein, we combine coding and non-coding transcriptome, DNA methylome, and proteome 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 (LC-MS) proteomic data were collected on lung tissue from 24 IPF cases and 14 control subjects. Significant differential features were identified using linear models adjusting for age and sex, inflation and bias where appropriate. Data Integration Analysis for Biomarker discovery using a Latent component method for Omics studies (DIABLO) was used for integrative multi-omic analysis. We identified 4,643 differentially expressed transcripts aligning to 3,439 genes, 998 differentially abundant proteins, 2,500 differentially methylated regions (DMRs), and 1,269 differentially expressed lncRNAs that were significant after correcting for multiple tests (false discovery rate [FDR]<0.05). Unsupervised hierarchical clustering using 20 coding mRNA, protein, methylation, and lncRNA features with highest loadings on the top latent variable from the four datasets demonstrates perfect separation of IPF and control lungs. Our analysis confirmed previously validated molecules and pathways known to be dysregulated in disease, and implicated novel molecular features as potential drivers and modifiers of disease. For example, four proteins, 18 DMRs, and 10 lncRNAs were found to have strong correlations (|r|>0.8) with MMP7. Therefore, using a systems biology approach, we have identified novel molecular relationships in IPF.
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Methylome ; Multi-omics ; Proteome ; Systems Biology ; Transcriptome; Gene-expression Profiles; Dna Methylation; Muc5b Expression; Lung Fibrosis; T-cells; Risk; Hypermethylation; Fibroblasts; Inhibition; Activation
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1044-1549
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1535-4989
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Volume: 65,
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Pages: 430-441
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American Thoracic Society
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25 Broadway, 18 Fl, New York, Ny 10004 Usa
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European Respiratory Society Long Term Research Fellowship
University of Colorado Team Oriented Training across the Translational Sciences Spectrum program (National Center for Advancing Translational Sciences)
National Heart, Lung, and Blood Institute