Omni-ARMD: an integrated genomic and clinical knowledgebase bridging clinical phenotypes and molecular determinants of antimicrobial resistance

Antimicrobial resistance (AMR) is a major global health threat, yet its molecular determinants remain difficult to characterize in real-world settings, as genomic and clinical data are fragmented across resources. Existing databases typically separate gene-level mechanisms, curated genotype-phenotype associations, and large-scale clinical antimicrobial susceptibility testing (AST) data, limiting cross-scale interpretation. Here, we present Omni-ARMD, an open-access knowledgebase that integrates multi-source genomic and clinical data to systematically infer genotype-phenotype relationships in AMR. Omni-ARMD bridges large-scale clinical AST records and gene-level resistance evidence through a confidence-weighted log-odds enrichment framework, which quantifies genotype-phenotype associations at the organism-antimicrobial level and integrates these associations into aggregated cross-domain evidence representations. The current release includes over 12 million de-identified microbiology records from more than 1 million patients, harmonized to generate over 7.83 million standardized AST records. It also integrates over 0.36 million gene-phenotype associations, spanning 38 organisms, 52 antimicrobials, and 375 resistance genes. Omni-ARMD links over 5.16 million clinical records to genomic evidence, achieving a 65.86% match rate and a 2.61% coverage of organism-antimicrobial pairs. Omni-ARMD provides interactive modules for clinical investigation, genomic evidence analysis, mechanistic interpretation, and artificial intelligence-assisted exploration, enabling integrative and data-driven discovery in AMR. Omni-ARMD is freely available at www.omniarmd.cn.

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Publication Details

Journal
Nucleic Acids Research
Published
2026-10-27
DOI
https://doi.org/10.1093/nar/gkag1045
Primary Topic
Antibiotic Resistance in Bacteria
Type
article
Field-Weighted Citation Impact
0.00

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article

Omni-ARMD: an integrated genomic and clinical knowledgebase bridging clinical phenotypes and molecular determinants of antimicrobial resistance

Hai Tang, Shikang Zheng, Xiaoying Xie, Guo‐Bao Tian et al.
3 links
Nucleic Acids Research
Antibiotic Resistance in Bacteria
article

Omni-ARMD: an integrated genomic and clinical knowledgebase bridging clinical phenotypes and molecular determinants of antimicrobial resistance

Hai Tang, Shikang Zheng, Xiaoying Xie, Guo‐Bao Tian, Xin Ding, Weizhong Li, Runtian Yao, Lei Wang
article en

Abstract

Antimicrobial resistance (AMR) is a major global health threat, yet its molecular determinants remain difficult to characterize in real-world settings, as genomic and clinical data are fragmented across resources. Existing databases typically separate gene-level mechanisms, curated genotype-phenotype associations, and large-scale clinical antimicrobial susceptibility testing (AST) data, limiting cross-scale interpretation. Here, we present Omni-ARMD, an open-access knowledgebase that integrates multi-source genomic and clinical data to systematically infer genotype-phenotype relationships in AMR. Omni-ARMD bridges large-scale clinical AST records and gene-level resistance evidence through a confidence-weighted log-odds enrichment framework, which quantifies genotype-phenotype associations at the organism-antimicrobial level and integrates these associations into aggregated cross-domain evidence representations. The current release includes over 12 million de-identified microbiology records from more than 1 million patients, harmonized to generate over 7.83 million standardized AST records. It also integrates over 0.36 million gene-phenotype associations, spanning 38 organisms, 52 antimicrobials, and 375 resistance genes. Omni-ARMD links over 5.16 million clinical records to genomic evidence, achieving a 65.86% match rate and a 2.61% coverage of organism-antimicrobial pairs. Omni-ARMD provides interactive modules for clinical investigation, genomic evidence analysis, mechanistic interpretation, and artificial intelligence-assisted exploration, enabling integrative and data-driven discovery in AMR. Omni-ARMD is freely available at www.omniarmd.cn.

Nucleic Acids Research
Sun Yat-sen University (CN), The Seventh Affiliated Hospital of Sun Yat-sen University (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 22%
Antibiotic Resistance in Bacteria
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