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A proteomics approach to identify COPD-related changes in lung fibroblasts

  • Nicolaas J. Bekker (First author)
  • , Alienke van Pijkeren
  • , Justina C. Wolters
  • , Alejandro Sánchez Brotons
  • , Victor Guryev
  • , Roy R. Woldhuis
  • , Rainer Bischoff
  • , Wynand Alkema
  • , Peter Horvatovich
  • , Johannes L.L. van Nijnatten
  • , Maarten van den Berge
  • , Wim Timens
  • , Corry-Anke Brandsma
    • Rijksuniversiteit Groningen, Universitair Medisch Centrum Groningen, Afdeling Pathologie en Medische Biologie
    • University of Groningen, University Medical Center Groningen, GRIAC Research Institute
    • University of Groningen, Department of Analytical Biochemistry
    • Rijksuniversiteit Groningen, Universitair Medisch Centrum Groningen, Afdeling Kindergeneeskunde
    • Rijksuniversiteit Groningen, Universitair Medisch Centrum Groningen, Europees onderzoeksinstituut voor onderzoek naar de biologie van veroudering
    • Rijksuniversiteit Groningen, Universitair Medisch Centrum Groningen, Afdeling voor Longziekten en Tuberculose
    • University of Technology Sydney, Respiratory Bioinformatics and Molecular Biology

    Onderzoeksoutput: Article › Academic › peer review

    Samenvatting

    Background: Lung fibroblasts are implicated in abnormal tissue repair in chronic obstructive pulmonary disease (COPD). The exact mechanisms are unknown and comprehensive analysis comparing COPD- and control fibroblasts is lacking. Aim: To gain insight in the role of lung fibroblasts in COPD pathology using unbiased proteomic and transcriptomic analysis. Methods: Protein and RNA was isolated from cultured parenchymal lung fibroblasts of 17 stage IV COPD patients and 16 non-COPD controls. Proteins were analyzed using LC-MS/MS and RNA through RNA sequencing. Differential protein and gene expression in COPD was assessed via linear regression, followed by pathway enrichment, correlation analysis and immunohistological staining in lung tissue. Proteomic and transcriptomic data was compared to investigate the overlap and correlation between both levels of data. Results: We identified 40 differentially expressed (DE) proteins and zero DE genes between COPD and control fibroblasts. The most significant DE proteins were HNRNPA2B1 and FHL1. Thirteen of the 40 proteins were previously associated with COPD, including FHL1 and GSTP1. Six of the 40 proteins were related to telomere maintenance pathways, and were positively correlated with the senescence marker LMNB1. No significant correlation between gene and protein expression was observed for the 40 proteins. Conclusions: The 40 DE proteins in COPD fibroblasts include previously described COPD proteins (FHL1, GSTP1) and new COPD research targets like HNRNPA2B1. Lack of overlap and correlation between gene and protein data supports the use of unbiased proteomics analysis and indicates that different types of information are generated with both methods.
    Originele taal-2English
    Pagina's (van-tot)L521-L535
    TijdschriftAmerican Journal of Physiology - Lung Cellular and Molecular Physiology
    Volume324
    Nummer van het tijdschrift4
    DOI's
    StatusPublished - 1 apr. 2023

    Keywords

    • datawetenschap
    • proteomica
    • gezond oud worden

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