DiseaseCIO: a multi-omics atlas for characterizing clinical intervention outcomes across diverse diseases

Heterogeneity in clinical intervention outcomes across patients is a major barrier to precision medicine. The integration of multidimensional high-throughput omics can help reveal the molecular basis of differences in clinical interventions and provide insights into outcome prediction, prognostic stratification, regulatory patterns, and resistance mechanisms. We present DiseaseCIO (Disease Clinical Intervention Outcomes, http://db.edbc.org/DiseaseCIO/), a database that integrates microbiome, transcriptome, and epigenome data with human disease intervention outcomes. It is designed to characterize the molecular landscape associated with disease intervention outcomes at the individual patient level. DiseaseCIO encompasses 42 798 pretreatment samples from 94 disease states, covering 510 treatment regimens involving 377 pharmacological and non-pharmacological interventions. These samples comprise four types of specimens collected from eight sampling locations. Using the customized iMOD workflow for multi-omics data processing, we generated 20 categories of molecular features and identified >1.84 million candidate feature-outcome associations. DiseaseCIO also provides interactive tools for differential analysis, prognostic evaluation, cross-omics correlation analysis, and cross-cohort integrative analysis of multidimensional features as well as enrichment analysis and signature construction for user-submitted feature sets. DiseaseCIO provides a molecular-level resource for exploring intervention outcome heterogeneity across diseases and identifying candidate multi-omics biomarkers associated with treatment response and prognosis.

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Publication Details

Journal
Nucleic Acids Research
Published
2026-10-30
DOI
https://doi.org/10.1093/nar/gkag1044
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

DiseaseCIO: a multi-omics atlas for characterizing clinical intervention outcomes across diverse diseases

Junyao Qiu, Ruiyang Zhai, Xingjun Xiao, Ji Li et al.
Nucleic Acids Research
Bioinformatics and Genomic Networks
article

DiseaseCIO: a multi-omics atlas for characterizing clinical intervention outcomes across diverse diseases

Junyao Qiu, Ruiyang Zhai, Xingjun Xiao, Ji Li, Yan Zhang, Te Ma, Ting Liu, Peishen Yu, Mu Su, Hongli Wang, Jie Xing, Xianhe Huang, Yue Gu, Yu Li
article en

Abstract

Heterogeneity in clinical intervention outcomes across patients is a major barrier to precision medicine. The integration of multidimensional high-throughput omics can help reveal the molecular basis of differences in clinical interventions and provide insights into outcome prediction, prognostic stratification, regulatory patterns, and resistance mechanisms. We present DiseaseCIO (Disease Clinical Intervention Outcomes, http://db.edbc.org/DiseaseCIO/), a database that integrates microbiome, transcriptome, and epigenome data with human disease intervention outcomes. It is designed to characterize the molecular landscape associated with disease intervention outcomes at the individual patient level. DiseaseCIO encompasses 42 798 pretreatment samples from 94 disease states, covering 510 treatment regimens involving 377 pharmacological and non-pharmacological interventions. These samples comprise four types of specimens collected from eight sampling locations. Using the customized iMOD workflow for multi-omics data processing, we generated 20 categories of molecular features and identified >1.84 million candidate feature-outcome associations. DiseaseCIO also provides interactive tools for differential analysis, prognostic evaluation, cross-omics correlation analysis, and cross-cohort integrative analysis of multidimensional features as well as enrichment analysis and signature construction for user-submitted feature sets. DiseaseCIO provides a molecular-level resource for exploring intervention outcome heterogeneity across diseases and identifying candidate multi-omics biomarkers associated with treatment response and prognosis.

Nucleic Acids Research
Harbin Institute of Technology (CN), Second Affiliated Hospital of Harbin Medical University (CN), Qiqihar Medical University (CN)
Harbin Medical University, Health Commission of Heilongjiang Province, National Natural Science Foundation of China, Science and Technology Department, Heilongjiang Province, Bijzonder Onderzoeksfonds UGent
Good health and well-being
Openalex Percentile: Top 22%
Bioinformatics and Genomic Networks
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