ArticleScientific reports2016
Identification of disease comorbidity through hidden molecular mechanisms.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- LLM-Enhanced Multimodal Framework for Drug-Drug Interaction Prediction.Biomedicines · 2025Article
- A mode of action protein based approach that characterizes the relationships among most major diseases.Scientific reports · 2025Article
- Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond.BMC bioinformatics · 2024Article
- Optimized network based natural language processing approach to reveal disease comorbidities in COVID-19.Scientific reports · 2024Article
- Genomic characterisation of the overlap of endometriosis with 76 comorbidities identifies pleiotropic and causal mechanisms underlying disease risk.Human genetics · 2023Article
- DapBCH: a disease association prediction model Based on Cross-species and Heterogeneous graph embedding.Frontiers in genetics · 2023Article
- Exploring novel disease-disease associations based on multi-view fusion network.Computational and structural biotechnology journal · 2023Article
- PHEVIR: an artificial intelligence algorithm that predicts the molecular role of pathogens in complex human diseases.Scientific reports · 2022Article
- Data-driven comorbidity analysis of 100 common disorders reveals patient subgroups with differing mortality risks and laboratory correlates.Scientific reports · 2022Article
- LeMeDISCO is a computational method for large-scale prediction & molecular interpretation of disease comorbidity.Communications biology · 2022Article
- Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data.Psychiatry investigation · 2022Article
- Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics.Results and problems in cell differentiation · 2022Article
- Prediction of severe adverse events, modes of action and drug treatments for COVID-19's complications.Scientific reports · 2021Article
- Shared Molecular Mechanisms of Hypertrophic Cardiomyopathy and Its Clinical Presentations: Automated Molecular Mechanisms Extraction Approach.Life (Basel, Switzerland) · 2021Article
- Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis.Clinical and experimental pediatrics · 2021Article
- Decoding information on COVID-19: Ontological approach towards design possible therapeutics.Informatics in medicine unlocked · 2021Review
- Development and Validation of a Risk Stratification Model Using Disease Severity Hierarchy for Mortality or Major Cardiovascular Event.JAMA network open · 2020Article
- Comorbidity of asthma and hypertension may be mediated by shared genetic dysregulation and drug side effects.Scientific reports · 2019Article
- The Alzheimer's comorbidity phenome: mining from a large patient database and phenome-driven genetics prediction.JAMIA open · 2019Article
- Navigating the disease landscape: knowledge representations for contextualizing molecular signatures.Briefings in bioinformatics · 2019Review
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4 authors.
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Abstract
Despite multiple diseases co-occur, their underlying common molecular mechanisms remain elusive. Identification of comorbid diseases by considering the interactions between molecular components is a key to understand the underlying disease mechanisms. Here, we developed a novel approach utilizing both common disease-causing genes and underlying molecular pathways to identify comorbid diseases. Our approach enables the analysis of common pathologies shared by comorbid diseases through molecular interaction networks. We found that the integration of direct genetic sharing and indirect high-level molecular associations revealed significantly strong consistency with known comorbid diseases. In addition, neoplasm-related diseases showed high comorbidity patterns within themselves as well as with other diseases, indicating severe complications. This study demonstrated that molecular pathway information could be used to discover disease comorbidity and hidden biological mechanism to understand pathogenesis and provide new insight on disease pathology.
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