{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T10:31:02Z","timestamp":1784629862469,"version":"3.55.0"},"reference-count":50,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2022,2,2]],"date-time":"2022-02-02T00:00:00Z","timestamp":1643760000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Gastro and Hepatol"],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Aim<\/jats:title>\n                    <jats:p>Anti\u2010tumor necrosis factor\u2010\u03b1 (anti\u2010TNF\u2010\u03b1) agents have been used for inflammatory bowel disease; however, it has up to 30% nonresponse rate. Identifying molecular pathways and finding reliable diagnostic biomarkers for patient response to anti\u2010TNF\u2010\u03b1 treatment are needed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Publicly available transcriptomic data from inflammatory bowel disease patients receiving anti\u2010TNF\u2010\u03b1 therapy were systemically collected and integrated.\n                      <jats:italic>In silico<\/jats:italic>\n                      flow cytometry approaches and Metascape were applied to evaluate immune cell populations and to perform gene enrichment analysis, respectively. Genes identified within enrichment pathways validated in neutrophils were tracked in an anti\u2010TNF\u2010\u03b1\u2010treated animal model (with lipopolysaccharide\u2010induced inflammation). The receiver operating characteristic curve was applied to all genes to identify the best prediction biomarkers.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 449 samples were retrieved from control, baseline, and after primary anti\u2010TNF\u2010\u03b1 therapy or placebo. No statistically significant differences were observed between anti\u2010TNF\u2010\u03b1 treatment responders and nonresponders at baseline in immune microenvironment scores. Neutrophil, endothelial cell, and B\u2010cell populations were higher in baseline nonresponders, and chemotaxis pathways may contribute to the treatment resistance. Genes related to chemotaxis pathways were significantly upregulated in lipopolysaccharide\u2010induced neutrophils, but no statistically significant changes were observed in neutrophils treated with anti\u2010TNF\u2010\u03b1. Interleukin 13 receptor subunit alpha 2 (\n                      <jats:italic>IL13RA2<\/jats:italic>\n                      ) is the best predictor (receiver operating characteristic curve: 80.7%, 95% confidence interval: 73.8\u201387.5%), with a sensitivity of 68.13% and specificity of 84.93%, and significantly higher in nonresponders compared with responders (\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0&lt;\u00a00.0001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      Hyperactive neutrophil chemotaxis influences responses to anti\u2010TNF\u2010\u03b1 treatment, and\n                      <jats:italic>IL13RA2<\/jats:italic>\n                      is a potential biomarker to predict anti\u2010TNF\u2010\u03b1 treatment response.\n                    <\/jats:p>\n                  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