{"doi":"10.3389/fimmu.2025.1642923","title":"A two-transcript classifier model of host genes for discrimination of bacterial from viral infection in ulcerative colitis with opportunistic infections: a discovery and validation study","abstract":"<h4>Aims</h4>We aimed to develop and validate a classifier model to discriminate bacterial from viral infection in ulcerative colitis with opportunistic infections (UC-OI) by evaluating potential transcript signature in peripheral blood.<h4>Methods</h4>The study comprised UC patients with bacterial or viral infection or without opportunistic infections. We screened for differentially expressed genes associated with bacterial or viral infections (<i>IFI44L</i>, <i>PI3</i> and <i>ITGB2</i>) and compared the expression levels of the genes in different infection subgroups. Subsequently, UC patients were randomly assigned (1:1) to either the discovery or validation groups. We developed a binary logistic regression model integrating the expression of candidate genes using discovery group and evaluated its discriminatory performance in validation group.<h4>Results</h4>The expression levels of candidate genes differed significantly among infection subgroups. The <i>IFI44L</i> and <i>PI3</i> combination was the most discriminatory and was used to construct the model. The two-transcript classifier model had an AUC of 0.867 (95% CI 0.794-0.941) to discriminate bacterial and viral infections in the validation group. Its performance was better than that of PCT, CRP and ESR and was less affected by pathogen type.<h4>Conclusions</h4><i>IFI44L</i> and <i>PI3</i> transcript levels are robust classifiers to discriminate bacterial from viral infection in UC-OI, and measuring its levels appears to be predictive infection progression and treatment outcome in UC patients over time.","journal":"Frontiers in Immunology","year":2025,"id":1212,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0552,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-09-19","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":15743,"name":"Nannan Xu","orcid":null,"position":1,"is_corresponding":false},{"id":15744,"name":"Ahemala Duishanbai","orcid":null,"position":2,"is_corresponding":false},{"id":15745,"name":"Gang Huang","orcid":"0009-0008-3315-0634","position":3,"is_corresponding":false},{"id":13180,"name":"Jing Zhang","orcid":"0000-0002-5970-0509","position":4,"is_corresponding":false},{"id":15746,"name":"Guanwei Bi","orcid":null,"position":5,"is_corresponding":false},{"id":15747,"name":"Manyu Li","orcid":"0000-0002-8679-1346","position":6,"is_corresponding":false},{"id":15748,"name":"Gang Wang","orcid":"0000-0001-7264-2457","position":7,"is_corresponding":false},{"id":15749,"name":"Yanbo Yu","orcid":"0000-0003-2995-3270","position":8,"is_corresponding":false},{"id":15750,"name":"Nan-Nan Xu","orcid":null,"position":9,"is_corresponding":false},{"id":15751,"name":"Guorong Bi","orcid":null,"position":10,"is_corresponding":false},{"id":15742,"name":"Huipeng Zhang","orcid":"0009-0002-5328-2489","position":0,"is_corresponding":true}],"reference_count":31,"raw_metadata":null,"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}