An Exploratory Application of Multilayer Networks and Pathway Analysis in Pharmacogenomics

Marianna Milano; Giuseppe Agapito; Mario Cannataro

doi:10.3390/genes14101915

An Exploratory Application of Multilayer Networks and Pathway Analysis in Pharmacogenomics

Genes (Basel). 2023 Oct 7;14(10):1915. doi: 10.3390/genes14101915.

Authors

Marianna Milano^{1

2}, Giuseppe Agapito^{2

3}, Mario Cannataro^{2

4}

Affiliations

¹ Department of Experimental and Clinical Medicine, University Magna Græcia of Catanzaro, 88100 Catanzaro, Italy.
² Data Analytics Research Center, University Magna Græcia of Catanzaro, 88100 Catanzaro, Italy.
³ Department of Law, Economics and Social Sciences, University Magna Græcia of Catanzaro, 88100 Catanzaro, Italy.
⁴ Department of Medical and Surgical Sciences, University Magna Græcia of Catanzaro, 88100 Catanzaro, Italy.

Abstract

Over the years, network analysis has become a promising strategy for analysing complex system, i.e., systems composed of a large number of interacting elements. In particular, multilayer networks have emerged as a powerful framework for modelling and analysing complex systems with multiple types of interactions. Network analysis can be applied to pharmacogenomics to gain insights into the interactions between genes, drugs, and diseases. By integrating network analysis techniques with pharmacogenomic data, the goal consists of uncovering complex relationships and identifying key genes to use in pathway enrichment analysis to figure out biological pathways involved in drug response and adverse reactions. In this study, we modelled omics, disease, and drug data together through multilayer network representation. Then, we mined the multilayer network with a community detection algorithm to obtain the top communities. After that, we used the identified list of genes from the communities to perform pathway enrichment analysis (PEA) to figure out the biological function affected by the selected genes. The results show that the genes forming the top community have multiple roles through different pathways.

Keywords: community detection; multilayer networks; network analysis; pathway enrichment analysis; pharmacogenomics.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Gene Regulatory Networks*
Pharmacogenetics*

Grants and funding

This work was funded by Next Generation EU, Italian NRRP, Mission 4, Component 2, Investment 1.5, call for the creation and strengthening of ‘Innovation Ecosystems’, building ‘Territorial R&D Leaders’ (Directorial Decree n. 2021/3277), and project Tech4You—Technologies for climate change adaptation and quality of life improvement, n. ECS0000009. This work reflects only the authors’ views and opinions; neither the Ministry for University and Research nor the European Commission can be considered responsible for them.