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Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is characterized by the accumulation of extracellular matrix in the pulmonary interstitium and progressive functional decline. We hypothesized that integration of multi-omics data would identify clinically meaningful molecular endotypes of IPF. METHODS...

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Autores principales: Ruan, Peifeng, Todd, Jamie L, Zhao, Hongyu, Liu, Yi, Vinisko, Richard, Soellner, Julia F., Schmid, Ramona, Kaner, Robert J., Luckhardt, Tracy R., Neely, Megan L., Noth, Imre, Porteous, Mary, Raj, Rishi, Safdar, Zeenat, Strek, Mary E, Hesslinger, Christian, Palmer, Scott M., Leonard, Thomas B., Salisbury, Margaret L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10283254/
https://www.ncbi.nlm.nih.gov/pubmed/37344825
http://dx.doi.org/10.1186/s12931-023-02435-0
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author Ruan, Peifeng
Todd, Jamie L
Zhao, Hongyu
Liu, Yi
Vinisko, Richard
Soellner, Julia F.
Schmid, Ramona
Kaner, Robert J.
Luckhardt, Tracy R.
Neely, Megan L.
Noth, Imre
Porteous, Mary
Raj, Rishi
Safdar, Zeenat
Strek, Mary E
Hesslinger, Christian
Palmer, Scott M.
Leonard, Thomas B.
Salisbury, Margaret L.
author_facet Ruan, Peifeng
Todd, Jamie L
Zhao, Hongyu
Liu, Yi
Vinisko, Richard
Soellner, Julia F.
Schmid, Ramona
Kaner, Robert J.
Luckhardt, Tracy R.
Neely, Megan L.
Noth, Imre
Porteous, Mary
Raj, Rishi
Safdar, Zeenat
Strek, Mary E
Hesslinger, Christian
Palmer, Scott M.
Leonard, Thomas B.
Salisbury, Margaret L.
author_sort Ruan, Peifeng
collection PubMed
description BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is characterized by the accumulation of extracellular matrix in the pulmonary interstitium and progressive functional decline. We hypothesized that integration of multi-omics data would identify clinically meaningful molecular endotypes of IPF. METHODS: The IPF-PRO Registry is a prospective registry of patients with IPF. Proteomic and transcriptomic (including total RNA [toRNA] and microRNA [miRNA]) analyses were performed using blood collected at enrollment. Molecular data were integrated using Similarity Network Fusion, followed by unsupervised spectral clustering to identify molecular subtypes. Cox proportional hazards models tested the relationship between these subtypes and progression-free and transplant-free survival. The molecular subtypes were compared to risk groups based on a previously described 52-gene (toRNA expression) signature. Biological characteristics of the molecular subtypes were evaluated via linear regression differential expression and canonical pathways (Ingenuity Pathway Analysis [IPA]) over-representation analyses. RESULTS: Among 232 subjects, two molecular subtypes were identified. Subtype 1 (n = 105, 45.3%) and Subtype 2 (n = 127, 54.7%) had similar distributions of age (70.1 +/- 8.1 vs. 69.3 +/- 7.6 years; p = 0.31) and sex (79.1% vs. 70.1% males, p = 0.16). Subtype 1 had more severe disease based on composite physiologic index (CPI) (55.8 vs. 51.2; p = 0.002). After adjusting for CPI and antifibrotic treatment at enrollment, subtype 1 experienced shorter progression-free survival (HR 1.79, 95% CI 1.28,2.56; p = 0.0008) and similar transplant-free survival (HR 1.30, 95% CI 0.87,1.96; p = 0.20) as subtype 2. There was little agreement in the distribution of subjects to the molecular subtypes and the risk groups based on 52-gene signature (kappa = 0.04, 95% CI= -0.08, 0.17), and the 52-gene signature risk groups were associated with differences in transplant-free but not progression-free survival. Based on heatmaps and differential expression analyses, proteins and miRNAs (but not toRNA) contributed to classification of subjects to the molecular subtypes. The IPA showed enrichment in pulmonary fibrosis-relevant pathways, including mTOR, VEGF, PDGF, and B-cell receptor signaling. CONCLUSIONS: Integration of transcriptomic and proteomic data from blood enabled identification of clinically meaningful molecular endotypes of IPF. If validated, these endotypes could facilitate identification of individuals likely to experience disease progression and enrichment of clinical trials. TRIAL REGISTRATION: NCT01915511 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12931-023-02435-0.
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spelling pubmed-102832542023-06-22 Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression Ruan, Peifeng Todd, Jamie L Zhao, Hongyu Liu, Yi Vinisko, Richard Soellner, Julia F. Schmid, Ramona Kaner, Robert J. Luckhardt, Tracy R. Neely, Megan L. Noth, Imre Porteous, Mary Raj, Rishi Safdar, Zeenat Strek, Mary E Hesslinger, Christian Palmer, Scott M. Leonard, Thomas B. Salisbury, Margaret L. Respir Res Research BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is characterized by the accumulation of extracellular matrix in the pulmonary interstitium and progressive functional decline. We hypothesized that integration of multi-omics data would identify clinically meaningful molecular endotypes of IPF. METHODS: The IPF-PRO Registry is a prospective registry of patients with IPF. Proteomic and transcriptomic (including total RNA [toRNA] and microRNA [miRNA]) analyses were performed using blood collected at enrollment. Molecular data were integrated using Similarity Network Fusion, followed by unsupervised spectral clustering to identify molecular subtypes. Cox proportional hazards models tested the relationship between these subtypes and progression-free and transplant-free survival. The molecular subtypes were compared to risk groups based on a previously described 52-gene (toRNA expression) signature. Biological characteristics of the molecular subtypes were evaluated via linear regression differential expression and canonical pathways (Ingenuity Pathway Analysis [IPA]) over-representation analyses. RESULTS: Among 232 subjects, two molecular subtypes were identified. Subtype 1 (n = 105, 45.3%) and Subtype 2 (n = 127, 54.7%) had similar distributions of age (70.1 +/- 8.1 vs. 69.3 +/- 7.6 years; p = 0.31) and sex (79.1% vs. 70.1% males, p = 0.16). Subtype 1 had more severe disease based on composite physiologic index (CPI) (55.8 vs. 51.2; p = 0.002). After adjusting for CPI and antifibrotic treatment at enrollment, subtype 1 experienced shorter progression-free survival (HR 1.79, 95% CI 1.28,2.56; p = 0.0008) and similar transplant-free survival (HR 1.30, 95% CI 0.87,1.96; p = 0.20) as subtype 2. There was little agreement in the distribution of subjects to the molecular subtypes and the risk groups based on 52-gene signature (kappa = 0.04, 95% CI= -0.08, 0.17), and the 52-gene signature risk groups were associated with differences in transplant-free but not progression-free survival. Based on heatmaps and differential expression analyses, proteins and miRNAs (but not toRNA) contributed to classification of subjects to the molecular subtypes. The IPA showed enrichment in pulmonary fibrosis-relevant pathways, including mTOR, VEGF, PDGF, and B-cell receptor signaling. CONCLUSIONS: Integration of transcriptomic and proteomic data from blood enabled identification of clinically meaningful molecular endotypes of IPF. If validated, these endotypes could facilitate identification of individuals likely to experience disease progression and enrichment of clinical trials. TRIAL REGISTRATION: NCT01915511 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12931-023-02435-0. BioMed Central 2023-05-31 2023 /pmc/articles/PMC10283254/ /pubmed/37344825 http://dx.doi.org/10.1186/s12931-023-02435-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ruan, Peifeng
Todd, Jamie L
Zhao, Hongyu
Liu, Yi
Vinisko, Richard
Soellner, Julia F.
Schmid, Ramona
Kaner, Robert J.
Luckhardt, Tracy R.
Neely, Megan L.
Noth, Imre
Porteous, Mary
Raj, Rishi
Safdar, Zeenat
Strek, Mary E
Hesslinger, Christian
Palmer, Scott M.
Leonard, Thomas B.
Salisbury, Margaret L.
Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression
title Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression
title_full Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression
title_fullStr Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression
title_full_unstemmed Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression
title_short Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression
title_sort integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10283254/
https://www.ncbi.nlm.nih.gov/pubmed/37344825
http://dx.doi.org/10.1186/s12931-023-02435-0
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