Cargando…

Revealing the pathogenic changes of PAH based on multiomics characteristics

BACKGROUND: Pulmonary artery hypertension (PAH), which is characterized by an increase in pulmonary circulation blood pressure, is a fatal disease, and its pathogenesis remains unclear. METHODS: In this study, RNA sequencing (RNA-seq), tandem mass tags (TMT) and reduced representation bisulfite sequ...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Li, Chen, Shaokun, Zeng, Xixi, Lin, Dacen, Li, Yumei, Gui, Longxin, Lin, Mo-jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6647123/
https://www.ncbi.nlm.nih.gov/pubmed/31331330
http://dx.doi.org/10.1186/s12967-019-1981-5
_version_ 1783437660653617152
author Zhang, Li
Chen, Shaokun
Zeng, Xixi
Lin, Dacen
Li, Yumei
Gui, Longxin
Lin, Mo-jun
author_facet Zhang, Li
Chen, Shaokun
Zeng, Xixi
Lin, Dacen
Li, Yumei
Gui, Longxin
Lin, Mo-jun
author_sort Zhang, Li
collection PubMed
description BACKGROUND: Pulmonary artery hypertension (PAH), which is characterized by an increase in pulmonary circulation blood pressure, is a fatal disease, and its pathogenesis remains unclear. METHODS: In this study, RNA sequencing (RNA-seq), tandem mass tags (TMT) and reduced representation bisulfite sequencing (RRBS) were performed to detect the levels of mRNA, protein, and DNA methylation in pulmonary arteries (PAs), respectively. To screen the possible pathways and proteins related to PAH, pathway enrichment analysis and protein–protein interaction (PPI) network analysis were performed. For selected genes, differential expression levels were confirmed at both the transcriptional and translational levels by real-time PCR and Western blot analyses, respectively. RESULTS: A total of 362 differentially expressed genes (|Fold-change| > 1.5 and p < 0.05), 811 differentially expressed proteins (|Fold-change| > 1.2 and p < 0.05) and 76,562 differentially methylated regions (1000 bp slide windows, 500 bp overlap, p < 0.05, and |Fold-change| > 1.2) were identified when the PAH group (n = 15) was compared with the control group (n = 15). Through an integrated analysis of the characteristics of the three omic analyses, a multiomics table was constructed. Additionally, pathway enrichment analysis showed that the differentially expressed proteins were significantly enriched in five Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathways and ten Gene Ontology (GO) terms for the PAH group compared with the control group. Moreover, protein–protein interaction (PPI) networks were constructed to identify hub genes. Finally, according to the genes identified in the PPI and the protein expression fold-change, nine key genes and their associated proteins were verified by real-time PCR and Western blot analyses, including Col4a1, Itga5, Col2a1, Gstt1, Gstm3, Thbd, Mgst2, Kng1 and Fgg. CONCLUSIONS: This study conducted multiomic characteristic profiling to identify genes that contribute to the hypoxia-induced PAH model, identifying new avenues for basic PAH research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-019-1981-5) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6647123
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-66471232019-07-31 Revealing the pathogenic changes of PAH based on multiomics characteristics Zhang, Li Chen, Shaokun Zeng, Xixi Lin, Dacen Li, Yumei Gui, Longxin Lin, Mo-jun J Transl Med Research BACKGROUND: Pulmonary artery hypertension (PAH), which is characterized by an increase in pulmonary circulation blood pressure, is a fatal disease, and its pathogenesis remains unclear. METHODS: In this study, RNA sequencing (RNA-seq), tandem mass tags (TMT) and reduced representation bisulfite sequencing (RRBS) were performed to detect the levels of mRNA, protein, and DNA methylation in pulmonary arteries (PAs), respectively. To screen the possible pathways and proteins related to PAH, pathway enrichment analysis and protein–protein interaction (PPI) network analysis were performed. For selected genes, differential expression levels were confirmed at both the transcriptional and translational levels by real-time PCR and Western blot analyses, respectively. RESULTS: A total of 362 differentially expressed genes (|Fold-change| > 1.5 and p < 0.05), 811 differentially expressed proteins (|Fold-change| > 1.2 and p < 0.05) and 76,562 differentially methylated regions (1000 bp slide windows, 500 bp overlap, p < 0.05, and |Fold-change| > 1.2) were identified when the PAH group (n = 15) was compared with the control group (n = 15). Through an integrated analysis of the characteristics of the three omic analyses, a multiomics table was constructed. Additionally, pathway enrichment analysis showed that the differentially expressed proteins were significantly enriched in five Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathways and ten Gene Ontology (GO) terms for the PAH group compared with the control group. Moreover, protein–protein interaction (PPI) networks were constructed to identify hub genes. Finally, according to the genes identified in the PPI and the protein expression fold-change, nine key genes and their associated proteins were verified by real-time PCR and Western blot analyses, including Col4a1, Itga5, Col2a1, Gstt1, Gstm3, Thbd, Mgst2, Kng1 and Fgg. CONCLUSIONS: This study conducted multiomic characteristic profiling to identify genes that contribute to the hypoxia-induced PAH model, identifying new avenues for basic PAH research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-019-1981-5) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-22 /pmc/articles/PMC6647123/ /pubmed/31331330 http://dx.doi.org/10.1186/s12967-019-1981-5 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zhang, Li
Chen, Shaokun
Zeng, Xixi
Lin, Dacen
Li, Yumei
Gui, Longxin
Lin, Mo-jun
Revealing the pathogenic changes of PAH based on multiomics characteristics
title Revealing the pathogenic changes of PAH based on multiomics characteristics
title_full Revealing the pathogenic changes of PAH based on multiomics characteristics
title_fullStr Revealing the pathogenic changes of PAH based on multiomics characteristics
title_full_unstemmed Revealing the pathogenic changes of PAH based on multiomics characteristics
title_short Revealing the pathogenic changes of PAH based on multiomics characteristics
title_sort revealing the pathogenic changes of pah based on multiomics characteristics
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6647123/
https://www.ncbi.nlm.nih.gov/pubmed/31331330
http://dx.doi.org/10.1186/s12967-019-1981-5
work_keys_str_mv AT zhangli revealingthepathogenicchangesofpahbasedonmultiomicscharacteristics
AT chenshaokun revealingthepathogenicchangesofpahbasedonmultiomicscharacteristics
AT zengxixi revealingthepathogenicchangesofpahbasedonmultiomicscharacteristics
AT lindacen revealingthepathogenicchangesofpahbasedonmultiomicscharacteristics
AT liyumei revealingthepathogenicchangesofpahbasedonmultiomicscharacteristics
AT guilongxin revealingthepathogenicchangesofpahbasedonmultiomicscharacteristics
AT linmojun revealingthepathogenicchangesofpahbasedonmultiomicscharacteristics