An integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test case
Abstract In addition to the psychological depressive phenotype, major depressive disorder (MDD) patients are also associated with underlying immune dysregulation that correlates with metabolic syndrome prevalent in depressive patients. A robust integrative analysis of biological pathways underlying...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2021-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-89040-7 |
| _version_ | 1818400879979528192 |
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| author | Anup Mammen Oommen Stephen Cunningham Páraic S. O’Súilleabháin Brian M. Hughes Lokesh Joshi |
| author_facet | Anup Mammen Oommen Stephen Cunningham Páraic S. O’Súilleabháin Brian M. Hughes Lokesh Joshi |
| author_sort | Anup Mammen Oommen |
| collection | DOAJ |
| description | Abstract In addition to the psychological depressive phenotype, major depressive disorder (MDD) patients are also associated with underlying immune dysregulation that correlates with metabolic syndrome prevalent in depressive patients. A robust integrative analysis of biological pathways underlying the dysregulated neural connectivity and systemic inflammatory response will provide implications in the development of effective strategies for the diagnosis, management and the alleviation of associated comorbidities. In the current study, focusing on MDD, we explored an integrative network analysis methodology to analyze transcriptomic data combined with the meta-analysis of biomarker data available throughout public databases and published scientific peer-reviewed articles. Detailed gene set enrichment analysis and complex protein–protein, gene regulatory and biochemical pathway analysis has been undertaken to identify the functional significance and potential biomarker utility of differentially regulated genes, proteins and metabolite markers. This integrative analysis method provides insights into the molecular mechanisms along with key glycosylation dysregulation underlying altered neutrophil-platelet activation and dysregulated neuronal survival maintenance and synaptic functioning. Highlighting the significant gap that exists in the current literature, the network analysis framework proposed reduces the impact of data gaps and permits the identification of key molecular signatures underlying complex disorders with multiple etiologies such as within MDD and presents multiple treatment options to address their molecular dysfunction. |
| first_indexed | 2024-12-14T07:43:36Z |
| format | Article |
| id | doaj.art-7eae96b9cf37442c9578d13b6926dd7a |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-14T07:43:36Z |
| publishDate | 2021-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-7eae96b9cf37442c9578d13b6926dd7a2022-12-21T23:10:57ZengNature PortfolioScientific Reports2045-23222021-05-0111111410.1038/s41598-021-89040-7An integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test caseAnup Mammen Oommen0Stephen Cunningham1Páraic S. O’Súilleabháin2Brian M. Hughes3Lokesh Joshi4Advanced Glycoscience Research Cluster (AGRC), National University of Ireland GalwayAdvanced Glycoscience Research Cluster (AGRC), National University of Ireland GalwayDepartment of Psychology, University of LimerickSchool of Psychology, National University of Ireland GalwayAdvanced Glycoscience Research Cluster (AGRC), National University of Ireland GalwayAbstract In addition to the psychological depressive phenotype, major depressive disorder (MDD) patients are also associated with underlying immune dysregulation that correlates with metabolic syndrome prevalent in depressive patients. A robust integrative analysis of biological pathways underlying the dysregulated neural connectivity and systemic inflammatory response will provide implications in the development of effective strategies for the diagnosis, management and the alleviation of associated comorbidities. In the current study, focusing on MDD, we explored an integrative network analysis methodology to analyze transcriptomic data combined with the meta-analysis of biomarker data available throughout public databases and published scientific peer-reviewed articles. Detailed gene set enrichment analysis and complex protein–protein, gene regulatory and biochemical pathway analysis has been undertaken to identify the functional significance and potential biomarker utility of differentially regulated genes, proteins and metabolite markers. This integrative analysis method provides insights into the molecular mechanisms along with key glycosylation dysregulation underlying altered neutrophil-platelet activation and dysregulated neuronal survival maintenance and synaptic functioning. Highlighting the significant gap that exists in the current literature, the network analysis framework proposed reduces the impact of data gaps and permits the identification of key molecular signatures underlying complex disorders with multiple etiologies such as within MDD and presents multiple treatment options to address their molecular dysfunction.https://doi.org/10.1038/s41598-021-89040-7 |
| spellingShingle | Anup Mammen Oommen Stephen Cunningham Páraic S. O’Súilleabháin Brian M. Hughes Lokesh Joshi An integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test case Scientific Reports |
| title | An integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test case |
| title_full | An integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test case |
| title_fullStr | An integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test case |
| title_full_unstemmed | An integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test case |
| title_short | An integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test case |
| title_sort | integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test case |
| url | https://doi.org/10.1038/s41598-021-89040-7 |
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