Journal of Inflammation (Oct 2021)

TGF-β gene polimorphisms as risk factors for asthma control among clinic patients

  • Panek Michał,
  • Stawiski Konrad,
  • Kuna Piotr

DOI
https://doi.org/10.1186/s12950-021-00294-4
Journal volume & issue
Vol. 18, no. 1
pp. 1 – 12

Abstract

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Abstract Background TGF-β and its receptors play a crucial role in asthma pathogenesis, bronchial hyperreactivity, and bronchial remodeling. Expression of isoforms 1–3 of TGFβ cytokine is influenced by tagging polymorphisms in the TGFβ1, TGFβ2 and TGFβ3 gene, and these SNPs may be associated with the risk of asthma development and severity as well as with other diseases. Polymorphic forms of TGF-β1, TGF-β2 and TGF-β3 genes regulate the degree of bronchial inflammation, deterioration of lung functional parameters in spirometry and elevated level of total IgE. All this results in intensification of disease symptoms. According to current GINA 2020 guidelines, the Asthma Control Test (ACT™) should be applied to assess asthma symptoms. Methods An analysis of polymorphisms localized in TGF-β1, TGF-β2 and TGF-β3 genes was conducted on 652 DNA samples with an application of the MassARRAY® system using the mass spectrometry technique MALDI TOF MS. The degree of asthma control was evaluated with ACT™. Results The occurrence of the T / C genotype in rs8109627 (p = 0.0171) in the TGF-β1 gene is significantly associated with a higher ACT result (controlled asthma) in a multivariate linear regression analysis model after using backward stepwise selection of variables. In addition, in the linear model for prediction of ACT score we showed SNP rs8109627 (p = 0.0497) in the TGF-β1 gene (improvement of the disease control - controlled asthma) and rs2796822 (p = 0.0454) in the TGF-β2 gene (deterioration of the diseases control - uncontrolled asthma) significantly modify the degree of asthma control. Discussion We described clinical significance of two SNPs in two genes TGF-β1 and TGF-β2, as yet unknown. We proved that the use of both genotypes and MAC allows to create a moderately correct prognostic model which is about 70% efficient on the entire set of analyzed SNPs in TGF-β1, TGF-β2, and TGF-β3 genes.

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