DiseaseCIO: a multi-omics atlas for characterizing clinical intervention outcomes across diverse diseases
- 1School of Life Science and Technology, Faculty of Life Sciences and Medicine, Harbin Institute of Technology , Harbin 150001 ,
- 2College of Pathology, Qiqihar Medical University , Qiqihar 161042 ,
- 3Department of Neurology, The Second Affiliated Hospital of Harbin Medical University , Harbin 150001 ,
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.
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BibTeX
@article{zhai2026diseasecio,
title = {{DiseaseCIO: a multi-omics atlas for characterizing clinical intervention outcomes across diverse diseases}},
author = {Ruiyang Zhai and Te Ma and Mu Su and Hongli Wang and Ji Li and Jie Xing and Xianhe Huang and Peishen Yu and Junyao Qiu and Ting Liu and Xingjun Xiao and Yu Li and Yue Gu and Yan Zhang},
journal = {Nucleic Acids Research},
year = {2026},
month = oct,
doi = {10.1093/nar/gkag1044},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1044/9005084},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - DiseaseCIO: a multi-omics atlas for characterizing clinical intervention outcomes across diverse diseases
AU - Ruiyang Zhai
AU - Te Ma
AU - Mu Su
AU - Hongli Wang
AU - Ji Li
AU - Jie Xing
AU - Xianhe Huang
AU - Peishen Yu
AU - Junyao Qiu
AU - Ting Liu
AU - Xingjun Xiao
AU - Yu Li
AU - Yue Gu
AU - Yan Zhang
PY - 2026
DA - 2026/10/30
JO - Nucleic Acids Research
DO - 10.1093/nar/gkag1044
UR - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1044/9005084
AB - 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.
SN - 0305-1048
SN - 1362-4962
ER -