Journal of Immunology Research (Jan 2023)

Serum TGF-β1 and CD14 Predicts Response to Anti-TNF-α Therapy in IBD

  • Stepan Coufal,
  • Miloslav Kverka,
  • Jakub Kreisinger,
  • Tomas Thon,
  • Filip Rob,
  • Martin Kolar,
  • Zuzana Reiss,
  • Dagmar Schierova,
  • Klara Kostovcikova,
  • Radka Roubalova,
  • Lukas Bajer,
  • Zuzana Jackova,
  • Martin Mihula,
  • Pavel Drastich,
  • Jana Tresnak Hercogova,
  • Michaela Novakova,
  • Martin Vasatko,
  • Milan Lukas,
  • Helena Tlaskalova-Hogenova,
  • Zuzana Jiraskova Zakostelska

DOI
https://doi.org/10.1155/2023/1535484
Journal volume & issue
Vol. 2023

Abstract

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Background. Tumor necrosis factor-alpha (TNF-α) agonists revolutionized therapeutic algorithms in inflammatory bowel disease (IBD) management. However, approximately every third IBD patient does not respond to this therapy in the long term, which delays efficient control of the intestinal inflammation. Methods. We analyzed the power of serum biomarkers to predict the failure of anti-TNF-α. We collected serum of 38 IBD patients at therapy prescription and 38 weeks later and analyzed them with relation to therapy response (no-, partial-, and full response). We used enzyme-linked immunosorbent assay to quantify 16 biomarkers related to gut barrier (intestinal fatty acid-binding protein, liver fatty acid-binding protein, trefoil factor 3, and interleukin (IL)-33), microbial translocation, immune system regulation (TNF-α, CD14, lipopolysaccharide-binding protein, mannan-binding lectin, IL-18, transforming growth factor-β1 (TGF-β1), osteoprotegerin (OPG), insulin-like growth factor 2 (IGF-2), endocrine-gland-derived vascular endothelial growth factor), and matrix metalloproteinase system (MMP-9, MMP-14, and tissue inhibitors of metalloproteinase-1). Results. We found that future full-responders have different biomarker profiles than non-responders, while partial-responders cannot be distinguished from either group. When future non-responders were compared to responders, their baseline contained significantly more TGF-β1, less CD14, and increased level of MMP-9, and concentration of these factors could predict non-responders with high accuracy (AUC = 0.938). Interestingly, during the 38 weeks, levels of MMP-9 decreased in all patients, irrespective of the outcome, while OPG, IGF-2, and TGF-β1 were higher in non-responders compared to full-responders both at the beginning and the end of the treatment. Conclusions. The TGF-β1 and CD14 can distinguish non-responders from responders. The changes in biomarker dynamics during the therapy suggest that growth factors (such as OPG, IGF-2, and TGF-β) are not markedly influenced by the treatment and that anti-TNF-α therapy decreases MMP-9 without influencing the treatment outcome.