{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T12:03:03Z","timestamp":1784203383094,"version":"3.55.0"},"reference-count":24,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T00:00:00Z","timestamp":1783555200000},"content-version":"vor","delay-in-days":189,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["92574106"],"award-info":[{"award-number":["92574106"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018542","name":"Sichuan Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2026NSFSC0495"],"award-info":[{"award-number":["2026NSFSC0495"]}],"id":[{"id":"10.13039\/501100018542","id-type":"DOI","asserted-by":"publisher"}]},{"name":"West China Hospital of Sichuan University","award":["ZYYC23007"],"award-info":[{"award-number":["ZYYC23007"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Decoding human immune responses to infectious diseases through transcriptomic analysis is crucial for understanding disease progression and guiding therapeutic development. The absence of a comprehensive database integrating infectious disease transcriptomes with immune-focused analyses limits such efforts. Here, we developed the GIDISdb (a Gene expression database for Infectious DISeases) to address this. Distinct from existing resources that focus on single pathogen types or lack standardized analytical workflows, GIDISdb uniquely integrates cross-disease transcriptomic data with an immune-centric analytical framework. GIDISdb integrates 3949 whole-blood RNA-seq samples from 51 projects across 15 types of bacterial, viral, and fungal infections (e.g. AIDS, COVID-19, and tuberculosis). By leveraging this extensive collection, GIDISdb enables detailed transcriptome analysis, including differential expression analysis and gene set enrichment analysis, for various diseases and their subgroups. Beyond traditional transcriptome analysis, it integrates immune-specific annotations from ImmPort, Reactome, and gene ontology, encompassing genes and pathways related to immune function, as well as estimated immune cell abundance. In a case study comparing latent tuberculosis (LTBI), active tuberculosis (TB), and healthy controls, LTBI showed upregulated microbial defense genes and downregulated inflammatory genes relative to controls, along with reduced IFN\u2013\u03b3 signaling compared to active TB. Immune-cell profiling revealed partially restored dendritic cells and expanded regulatory T cells, indicating a balanced immunoregulatory network. In summary, GIDISdb is a comprehensive, immune-centric platform for investigating gene expression in infection immunology, poised to accelerate the discovery of infection-specific immune mechanisms and biomarkers. The GIDISdb is accessible at https:\/\/guolab.wchscu.cn\/GIDISdb\/.<\/jats:p>","DOI":"10.1093\/database\/baag036","type":"journal-article","created":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T11:48:13Z","timestamp":1783597693000},"source":"Crossref","is-referenced-by-count":0,"title":["GIDISdb: a gene expression database for exploring human immune responses in infectious diseases"],"prefix":"10.1093","volume":"2026","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7947-2716","authenticated-orcid":false,"given":"Yu","family":"Liao","sequence":"first","affiliation":[{"name":"Department of Laboratory Medicine, West China Biomedical Big Data Center, West China Hospital, Sichuan University , Chengdu, 610041 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen-Lin","family":"Tan","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine, West China Biomedical Big Data Center, West China Hospital, Sichuan University , 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