{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T16:15:18Z","timestamp":1762272918115,"version":"3.41.2"},"reference-count":26,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,6,14]],"date-time":"2022-06-14T00:00:00Z","timestamp":1655164800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010408","name":"Polpharma Scientific Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010408","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>TGF-\u03b2 and its receptors play a crucial role in asthma pathogenesis and bronchial remodeling in the course of the disease. TGF-\u03b21, TGF-\u03b22, and TGF-\u03b23 isoforms are responsible for chronic inflammation, bronchial hyperreactivity, myofibroblast activation, fibrosis, bronchial remodeling, and change the expression of approximately 1000 genes in asthma. TGF-\u03b2 SNPs are associated with the elevated plasma level of TGF-\u03b21, an increased level of total IgE, and an increased risk of remodeling of bronchi.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The analysis of selected TGF-\u03b21, TGF-\u03b22, TGF-\u03b23-related single-nucleotide polymorphisms (SNP) was conducted on 652 DNA samples with an application of the MassARRAY<jats:sup>\u00ae<\/jats:sup> 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\u2019s test.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Minor 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>Derived predictive models suggest the analysis of selected SNPs in TGF-\u03b2 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.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fimmu.2022.746360","type":"journal-article","created":{"date-parts":[[2022,6,14]],"date-time":"2022-06-14T14:41:07Z","timestamp":1655217667000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Cytokine TGF\u03b2 Gene Polymorphism in Asthma: TGF-Related SNP Analysis Enhances the Prediction of Disease Diagnosis (A Case-Control Study With Multivariable Data-Mining Model 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