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A computational approach for the identification of key genes and biological pathways of chronic lung diseases: a systems biology approach
BACKGROUND: Chronic lung diseases are characterized by impaired lung function. Given that many diseases have shared clinical symptoms and pathogenesis, identifying shared pathogenesis can help the design of preventive and therapeutic strategies. This study aimed to evaluate the proteins and pathways...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329352/ https://www.ncbi.nlm.nih.gov/pubmed/37422662 http://dx.doi.org/10.1186/s12920-023-01596-7 |
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author | Rezaeeyan, Hadi Nobakht M. Gh, B. Fatemeh Arabfard, Masoud |
author_facet | Rezaeeyan, Hadi Nobakht M. Gh, B. Fatemeh Arabfard, Masoud |
author_sort | Rezaeeyan, Hadi |
collection | PubMed |
description | BACKGROUND: Chronic lung diseases are characterized by impaired lung function. Given that many diseases have shared clinical symptoms and pathogenesis, identifying shared pathogenesis can help the design of preventive and therapeutic strategies. This study aimed to evaluate the proteins and pathways of chronic obstructive pulmonary disease (COPD), asthma, idiopathic pulmonary fibrosis (IPF), and mustard lung disease (MLD). METHODS AND RESULTS: After collecting the data and determining the gene list of each disease, gene expression changes were examined in comparison to healthy individuals. Protein–protein interaction (PPI) and pathway enrichment analysis were used to evaluate genes and shared pathways of the four diseases. There were 22 shared genes, including ACTB, AHSG, ALB, APO, A1, APO C3, FTH1, GAPDH, GC, GSTP1, HP, HSPB1, IGKC, KRT10, KRT9, LCN1, PSMA2, RBP4, 100A8, S100A9, TF, and UBE2N. The major biological pathways in which these genes are involved are inflammatory pathways. Some of these genes activate different pathways in each disease, leading to the induction or inhibition of inflammation. CONCLUSION: Identification of the genes and shared pathways of diseases can contribute to identifying pathogenesis pathways and designing preventive and therapeutic strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01596-7. |
format | Online Article Text |
id | pubmed-10329352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103293522023-07-09 A computational approach for the identification of key genes and biological pathways of chronic lung diseases: a systems biology approach Rezaeeyan, Hadi Nobakht M. Gh, B. Fatemeh Arabfard, Masoud BMC Med Genomics Research BACKGROUND: Chronic lung diseases are characterized by impaired lung function. Given that many diseases have shared clinical symptoms and pathogenesis, identifying shared pathogenesis can help the design of preventive and therapeutic strategies. This study aimed to evaluate the proteins and pathways of chronic obstructive pulmonary disease (COPD), asthma, idiopathic pulmonary fibrosis (IPF), and mustard lung disease (MLD). METHODS AND RESULTS: After collecting the data and determining the gene list of each disease, gene expression changes were examined in comparison to healthy individuals. Protein–protein interaction (PPI) and pathway enrichment analysis were used to evaluate genes and shared pathways of the four diseases. There were 22 shared genes, including ACTB, AHSG, ALB, APO, A1, APO C3, FTH1, GAPDH, GC, GSTP1, HP, HSPB1, IGKC, KRT10, KRT9, LCN1, PSMA2, RBP4, 100A8, S100A9, TF, and UBE2N. The major biological pathways in which these genes are involved are inflammatory pathways. Some of these genes activate different pathways in each disease, leading to the induction or inhibition of inflammation. CONCLUSION: Identification of the genes and shared pathways of diseases can contribute to identifying pathogenesis pathways and designing preventive and therapeutic strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01596-7. BioMed Central 2023-07-08 /pmc/articles/PMC10329352/ /pubmed/37422662 http://dx.doi.org/10.1186/s12920-023-01596-7 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 Rezaeeyan, Hadi Nobakht M. Gh, B. Fatemeh Arabfard, Masoud A computational approach for the identification of key genes and biological pathways of chronic lung diseases: a systems biology approach |
title | A computational approach for the identification of key genes and biological pathways of chronic lung diseases: a systems biology approach |
title_full | A computational approach for the identification of key genes and biological pathways of chronic lung diseases: a systems biology approach |
title_fullStr | A computational approach for the identification of key genes and biological pathways of chronic lung diseases: a systems biology approach |
title_full_unstemmed | A computational approach for the identification of key genes and biological pathways of chronic lung diseases: a systems biology approach |
title_short | A computational approach for the identification of key genes and biological pathways of chronic lung diseases: a systems biology approach |
title_sort | computational approach for the identification of key genes and biological pathways of chronic lung diseases: a systems biology approach |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329352/ https://www.ncbi.nlm.nih.gov/pubmed/37422662 http://dx.doi.org/10.1186/s12920-023-01596-7 |
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