Evidence map›Paper›PMID 42353626›Full record

ArticleCurrent issues in molecular biology2026

FuDiCo: Gene Fusion-Initiated Path Propagation for Disease Comorbidity Prediction.

Ashwag Altayyar, Li Liao

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Article in Current issues in molecular biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Ashwag AltayyarDepartment of Computer and Information Sciences, University of Delaware, Newark, DE 19716, USA.ORCID 0000-0003-3517-4214
Li LiaoDepartment of Computer and Information Sciences, University of Delaware, Newark, DE 19716, USA.ORCID 0000-0002-1197-1879

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disease comorbidity-the co-occurrence of two or more diseases in the same individual-has gained growing attention due to its association with adverse clinical outcomes and increased treatment complexity. Recent subgraph-based approaches for disease comorbidity prediction model disease modules as subgraphs induced by disease-associated genes in the protein-protein interaction (PPI) network and learn disease representations from subgraph topology. However, these approaches are constrained by incomplete disease-gene annotations, which may obscure important molecular relationships between diseases. Accordingly, disease comorbidity may also be influenced by molecular events beyond annotated disease genes, such as gene fusion events that have emerged as important contributors to disease mechanisms. Motivated by the role of gene fusions in disease development, we introduce Gene Fusion-Initiated Path Propagation for Disease Comorbidity Prediction (FuDiCo), a framework that models comorbidity through influence propagation over the PPI network. FuDiCo represents fusion-associated genes as localized perturbation sources and learns how their influence propagates along interaction paths toward disease subgraphs, thereby capturing propagation patterns that link related diseases and contribute to their comorbidity. Experiments on a benchmark disease comorbidity dataset show that FuDiCo outperforms state-of-the-art methods, achieving statistically significant improvements. These results shed light on the importance of gene fusion events in understanding disease relationships.

Indexed as

disease comorbidity predictiongene fusiongraph analysisinfluence propagationprotein–protein interaction networksubgraph representation learning

Identifiers

PMID42353626
PMCPMC13298404

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.