Molecular network analysis of hormonal contraceptives side effects via database integration
Hormonal contraceptives (HCs) have been shown to be safe and effective when used correctly and consistently, however, as other classes of drugs, they are also associated with adverse health outcomes. In this study, we aim to explain the occurrence of common and unexpected HCs side effects (SEs) inte...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-01-01
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| Series: | Informatics in Medicine Unlocked |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352914823000059 |
| _version_ | 1797951507476250624 |
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| author | Manuela Petti Caterina Alfano Lorenzo Farina |
| author_facet | Manuela Petti Caterina Alfano Lorenzo Farina |
| author_sort | Manuela Petti |
| collection | DOAJ |
| description | Hormonal contraceptives (HCs) have been shown to be safe and effective when used correctly and consistently, however, as other classes of drugs, they are also associated with adverse health outcomes. In this study, we aim to explain the occurrence of common and unexpected HCs side effects (SEs) integrating drug-target, drug-SE and protein-protein interaction (PPI) public databases. We created a tripartite network that includes three types of vertices: SEs, drugs, and targets. The three layers are linked by means of the inter-layer associations drug-target and drug-SE, whereas only the target layer is characterized also by intra-layer links (PPIs). We exploited the drug-mediated association SE-target to identify the side effect modules defined as a network connected component composed of target proteins plus the proteins needed to connect them. We found that module proteins are associated with diseases/phenotypes and/or KEGG pathways related to the SEs. In particular, in many cases, targets are not enriched in SE features, whereas investigating their neighborhood (here defined as the proteins that allow the targets' connection) we found SE-related pathways. These results show that HCs action can perturb the targets’ neighborhood inducing unwanted reaction and that the proposed approach can help to understand how, and through which molecular mechanisms, side effects can occur. The approach is general in its nature: it can be applied to other drugs categories providing a support in identifying a subject-specific therapy that takes into account comorbidities and lifestyle to reduce or avoid the most undesired side effects. |
| first_indexed | 2024-04-10T22:31:43Z |
| format | Article |
| id | doaj.art-42c8bee03db840e89fcdf6fd3b5c8c99 |
| institution | Directory Open Access Journal |
| issn | 2352-9148 |
| language | English |
| last_indexed | 2024-04-10T22:31:43Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Informatics in Medicine Unlocked |
| spelling | doaj.art-42c8bee03db840e89fcdf6fd3b5c8c992023-01-17T04:07:24ZengElsevierInformatics in Medicine Unlocked2352-91482023-01-0136101163Molecular network analysis of hormonal contraceptives side effects via database integrationManuela Petti0Caterina Alfano1Lorenzo Farina2Department of Computer, Control and Management Engineering, Sapienza University of Rome, Via Ariosto, 25, 00185, Rome, Italy; Corresponding author.Department of Experimental Medicine, Sapienza University of Rome, Viale Regina Elena, 324, 00161, Rome, ItalyDepartment of Computer, Control and Management Engineering, Sapienza University of Rome, Via Ariosto, 25, 00185, Rome, ItalyHormonal contraceptives (HCs) have been shown to be safe and effective when used correctly and consistently, however, as other classes of drugs, they are also associated with adverse health outcomes. In this study, we aim to explain the occurrence of common and unexpected HCs side effects (SEs) integrating drug-target, drug-SE and protein-protein interaction (PPI) public databases. We created a tripartite network that includes three types of vertices: SEs, drugs, and targets. The three layers are linked by means of the inter-layer associations drug-target and drug-SE, whereas only the target layer is characterized also by intra-layer links (PPIs). We exploited the drug-mediated association SE-target to identify the side effect modules defined as a network connected component composed of target proteins plus the proteins needed to connect them. We found that module proteins are associated with diseases/phenotypes and/or KEGG pathways related to the SEs. In particular, in many cases, targets are not enriched in SE features, whereas investigating their neighborhood (here defined as the proteins that allow the targets' connection) we found SE-related pathways. These results show that HCs action can perturb the targets’ neighborhood inducing unwanted reaction and that the proposed approach can help to understand how, and through which molecular mechanisms, side effects can occur. The approach is general in its nature: it can be applied to other drugs categories providing a support in identifying a subject-specific therapy that takes into account comorbidities and lifestyle to reduce or avoid the most undesired side effects.http://www.sciencedirect.com/science/article/pii/S2352914823000059Hormonal contraceptivesMultipartite graphNetwork medicineSide effect modulePrecision medicine |
| spellingShingle | Manuela Petti Caterina Alfano Lorenzo Farina Molecular network analysis of hormonal contraceptives side effects via database integration Informatics in Medicine Unlocked Hormonal contraceptives Multipartite graph Network medicine Side effect module Precision medicine |
| title | Molecular network analysis of hormonal contraceptives side effects via database integration |
| title_full | Molecular network analysis of hormonal contraceptives side effects via database integration |
| title_fullStr | Molecular network analysis of hormonal contraceptives side effects via database integration |
| title_full_unstemmed | Molecular network analysis of hormonal contraceptives side effects via database integration |
| title_short | Molecular network analysis of hormonal contraceptives side effects via database integration |
| title_sort | molecular network analysis of hormonal contraceptives side effects via database integration |
| topic | Hormonal contraceptives Multipartite graph Network medicine Side effect module Precision medicine |
| url | http://www.sciencedirect.com/science/article/pii/S2352914823000059 |
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