Cytokine TGFβ Gene Polymorphism in Asthma: TGF-Related SNP Analysis Enhances the Prediction of Disease Diagnosis (A Case-Control Study With Multivariable Data-Mining Model Development)

Abstract

IntroductionTGF-β and its receptors play a crucial role in asthma pathogenesis and bronchial remodeling in the course of the disease. TGF-β1, TGF-β2, and TGF-β3 isoforms are responsible for chronic inflammation, bronchial hyperreactivity, myofibroblast activation, fibrosis, bronchial remodeling, and change the expression of approximately 1000 genes in asthma. TGF-β SNPs are associated with the elevated plasma level of TGF-β1, an increased level of total IgE, and an increased risk of remodeling of bronchi.MethodsThe analysis of selected TGF-β1, TGF-β2, TGF-β3-related single-nucleotide polymorphisms (SNP) was conducted on 652 DNA samples with an application of the MassARRAY® using the mass spectrometry (MALDI-TOF MS). Dataset was randomly split into training (80%) and validation sets (20%). For both asthma diagnosis and severity prediction, the C5.0 modelling with hyperparameter optimization was conducted on: clinical and SNP data (Clinical+TGF), only clinical (OnlyClinical) and minimum redundancy feature selection set (MRMR). Area under ROC (AUCROC) curves were compared using DeLong’s test.ResultsMinor allele carriers (MACs) in SNP rs2009112 [OR=1.85 (95%CI:1.11-3.1), p=0.016], rs2796821 [OR=1.72 (95%CI:1.1-2.69), p=0.017] and rs2796822 [OR=1.71 (95%CI:1.07-2.71), p=0.022] demonstrated an increased odds of severe asthma. Clinical+TGF model presented better diagnostic potential than OnlyClinical model in both training (p=0.0009) and validation (AUCROC=0.87 vs. 0.80,p=0.0052). At the same time, the MRMR model was not worse than the Clinical+TGF model (p=0.3607 on the training set, p=0.1590 on the validation set), while it was better in comparison with the Only Clinical model (p=0.0010 on the training set, p=0.0235 on validation set, AUCROC=0.85 vs. 0.87). On validation set Clinical+TGF model allowed for asthma diagnosis prediction with 88.4% sensitivity and 73.8% specificity.DiscussionDerived predictive models suggest the analysis of selected SNPs in TGF-β genes in combination with clinical factors could predict asthma diagnosis with high sensitivity and specificity, however, the benefit of SNP analysis in severity prediction was not shown.

Evaluation of TGF-β isoforms based on selected clinical parameters in asthmatic patients.

“…The transforming growth factor-β (TGF-β) has attracted the attention of researchers because of its pleiotropism and widespread occurrence in the body, including the airways. Despite single reports casting doubt on the role of TGF-β on airway remodeling processes, a vast majority of papers show a markedly increased expression of speci c TGF-β isoforms among asthmatic patients (8,11,(19)(20)(21)(22)(23). In our previous study, we proved that TGF-β1 and TGF-β2 isoform levels were statistically signi cantly higher among asthmatics compared to healthy volunteers.…”

Assessment of the effectiveness of the peptide inhibitor homologous to the transforming growth factor β cytokine blocking the TGFβRI/TGFβRII receptor complex—pilot study

“…The complex thus formed leads to the phosphorylation of the kinase domain of TGFβRI, which in turn results in the activation of the Smad pathway. [9][10][11] This is therefore a targeted pathway for research into Analyses of the functional role of selected TGF-β cytokine homologous molecules conducted so far as part of the pilot study have demonstrated that newly designed peptide inhibitors for the region I inhibit gene expression of Smad-dependent and Smad-independent pathways, which indicates that they are potent to block the TGFβRI/ TGFβRII receptor complex in vitro (Figures 7 and 8, Tables 2-5).…”

“…The complex thus created is responsible This process may also take place via non-Smad pathways, in which the Erk1/2, Jun N-terminal kinase (JNK) and p38 MAP kinase pathways, Src tyrosine kinase, phosphatidylinositol 3 0 -kinase, and Rho GTPases are also involved. [3][4][5][6][7][8][9] Hyperactivity of TGF-β-Smad pathway by specific TGFβRI/ TGFβRII receptors (two highly conserved single transmembrane receptors with intracellular serine/threonine kinase domains) leads to the development of chronic pathway inflammation and miofibroblast activation. Therefore, the inhibition of TGFβRI (also known as activin receptor-like kinase 5, Alk5) seems to be a good strategy for the treatment of many abovementioned disorders manifesting with fibrosis.…”

“…Therefore, the inhibition of TGFβRI (also known as activin receptor-like kinase 5, Alk5) seems to be a good strategy for the treatment of many abovementioned disorders manifesting with fibrosis. [9][10][11] To sum up, TGF-β is a pluripotent cytokine involved in a range of cellular functions including cell growth, proliferation, differentiation and death. The TGF-β-Smad signaling pathway is also muddled in the pathophysiology of many diseases including organ fibrosis, such as asthma or COVID-19 (Coronavirus disease), but also plays a significant role in the development of several cancers.…”

“…Activation of TGFβRI/TGFβRII through TGF‐β stimulates the signaling pathway via the formation of Smad complexes that are translocated to the nucleus where they act as transcription factors. This process may also take place via non‐Smad pathways, in which the Erk1/2, Jun N‐terminal kinase (JNK) and p38 MAP kinase pathways, Src tyrosine kinase, phosphatidylinositol 3′‐kinase, and Rho GTPases are also involved 3–9 …”