Abstract
Disease–disease relationships (e.g., disease comorbidities) play crucial roles in pathobiological manifestations of diseases and personalized approaches to managing those conditions. In this study, we develop a network-based methodology, termed meta-path-based Disease Network (mpDisNet) capturing algorithm, to infer disease–disease relationships by assembling four biological networks: disease–miRNA, miRNA–gene, disease–gene, and the human protein–protein interactome. mpDisNet is a meta-path-based random walk to reconstruct the heterogeneous neighbors of a given node. mpDisNet uses a heterogeneous skip-gram model to solve the network representation of the nodes. We find that mpDisNet reveals high performance in inferring clinically reported disease–disease relationships, outperforming that of traditional gene/miRNA-overlap approaches. In addition, mpDisNet identifies network-based comorbidities for pulmonary diseases driven by underlying miRNA-mediated pathobiological pathways (i.e., hsa-let-7a- or hsa-let-7b-mediated airway epithelial apoptosis and pro-inflammatory cytokine pathways) as derived from the human interactome network analysis. The mpDisNet offers a powerful tool for network-based identification of disease–disease relationships with miRNA-mediated pathobiological pathways.
Highlights
The manifestation and clinical severity of human disease are affected by myriad factors, including genetic, epigenetic, lifestyle, and various environmental variables.[1]
We found that mpDisNet displayed a higher performance in inferring disease–disease relationships compared with tradimiRNA–gene miRNA
Understanding of disease–disease relationships is important for the diagnosis, prevention, and treatment of the human disease
Summary
The manifestation and clinical severity of human disease are affected by myriad factors, including genetic, epigenetic, lifestyle, and various environmental variables.[1]. We performed a multi-layer human interactome network analysis to inspect the miRNA-mediated pathobiological pathways for lung cancer-associated asthma via mpDisNet (Fig. 6). Potential miRNA-mediated disease pathways captured by mpDisNet offer candidate biomarkers in understanding of pathobiological mechanisms of lung cancer-associated asthma. These candidate network biomarkers identified by mpDisNet are warranted by experimental or clinical validation further. Genetic studies and in vitro observations have shown potential associations of CCND1 and CCND2 with asthma and COPD.[43,44,45] In addition, CASP3 was reported to play a functional role in airway epithelial apoptosis[46,47] and pro-inflammatory cytokines (FOXO4) may contribute to regulation of muscle atrophy and smooth muscle cell migration.[48,49] Altogether, miRNA-mediated airway epithelial apoptosis and pro-inflammatory cytokine pathways (hsa-let-7a and hsa-let7b) may offer potential mechanisms for the overlapping syndrome between asthma and COPD. We may improve mpDisNet by integrating more comprehensive biological networks, analyzing the relevant associations in tissue-specific networks in which the disease occurs, adopting more flexible
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
