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A network model of genomic hormone interactions underlying dementia and its translational validation through serendipitous off-target effect.

Younesi E, Hofmann-Apitius M - J Transl Med (2013)

Bottom Line: This model was evaluated for its biological and clinical relevance through pathway recovery test, evidence-based analysis, and biomarker-guided analysis.Translational validation of the model was performed using the proposed novel mechanism discovery approach based on 'serendipitous off-target effects'.Amongst these pathways, estrogen signaling pathway takes the major part in the model and insulin signaling pathway is analyzed for its association to learning and memory functions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing-SCAI, Schloss Birlinghoven, Sankt Augustin 53754, Germany. erfan.younesi@scai.fraunhofer.de

ABSTRACT

Background: While the majority of studies have focused on the association between sex hormones and dementia, emerging evidence supports the role of other hormone signals in increasing dementia risk. However, due to the lack of an integrated view on mechanistic interactions of hormone signaling pathways associated with dementia, molecular mechanisms through which hormones contribute to the increased risk of dementia has remained unclear and capacity of translating hormone signals to potential therapeutic and diagnostic applications in relation to dementia has been undervalued.

Methods: Using an integrative knowledge- and data-driven approach, a global hormone interaction network in the context of dementia was constructed, which was further filtered down to a model of convergent hormone signaling pathways. This model was evaluated for its biological and clinical relevance through pathway recovery test, evidence-based analysis, and biomarker-guided analysis. Translational validation of the model was performed using the proposed novel mechanism discovery approach based on 'serendipitous off-target effects'.

Results: Our results reveal the existence of a well-connected hormone interaction network underlying dementia. Seven hormone signaling pathways converge at the core of the hormone interaction network, which are shown to be mechanistically linked to the risk of dementia. Amongst these pathways, estrogen signaling pathway takes the major part in the model and insulin signaling pathway is analyzed for its association to learning and memory functions. Validation of the model through serendipitous off-target effects suggests that hormone signaling pathways substantially contribute to the pathogenesis of dementia.

Conclusions: The integrated network model of hormone interactions underlying dementia may serve as an initial translational platform for identifying potential therapeutic targets and candidate biomarkers for dementia-spectrum disorders such as Alzheimer's disease.

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Schematic representation of the methodology used for construction and analysis of dementia-related hormonal network.
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Figure 1: Schematic representation of the methodology used for construction and analysis of dementia-related hormonal network.

Mentions: FigureĀ 1 summarizes the overall strategy used for this study. It demonstrates a top-down integrative (knowledge- and data-driven) approach to modeling hormone protein interaction network.


A network model of genomic hormone interactions underlying dementia and its translational validation through serendipitous off-target effect.

Younesi E, Hofmann-Apitius M - J Transl Med (2013)

Schematic representation of the methodology used for construction and analysis of dementia-related hormonal network.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3733613&req=5

Figure 1: Schematic representation of the methodology used for construction and analysis of dementia-related hormonal network.
Mentions: FigureĀ 1 summarizes the overall strategy used for this study. It demonstrates a top-down integrative (knowledge- and data-driven) approach to modeling hormone protein interaction network.

Bottom Line: This model was evaluated for its biological and clinical relevance through pathway recovery test, evidence-based analysis, and biomarker-guided analysis.Translational validation of the model was performed using the proposed novel mechanism discovery approach based on 'serendipitous off-target effects'.Amongst these pathways, estrogen signaling pathway takes the major part in the model and insulin signaling pathway is analyzed for its association to learning and memory functions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing-SCAI, Schloss Birlinghoven, Sankt Augustin 53754, Germany. erfan.younesi@scai.fraunhofer.de

ABSTRACT

Background: While the majority of studies have focused on the association between sex hormones and dementia, emerging evidence supports the role of other hormone signals in increasing dementia risk. However, due to the lack of an integrated view on mechanistic interactions of hormone signaling pathways associated with dementia, molecular mechanisms through which hormones contribute to the increased risk of dementia has remained unclear and capacity of translating hormone signals to potential therapeutic and diagnostic applications in relation to dementia has been undervalued.

Methods: Using an integrative knowledge- and data-driven approach, a global hormone interaction network in the context of dementia was constructed, which was further filtered down to a model of convergent hormone signaling pathways. This model was evaluated for its biological and clinical relevance through pathway recovery test, evidence-based analysis, and biomarker-guided analysis. Translational validation of the model was performed using the proposed novel mechanism discovery approach based on 'serendipitous off-target effects'.

Results: Our results reveal the existence of a well-connected hormone interaction network underlying dementia. Seven hormone signaling pathways converge at the core of the hormone interaction network, which are shown to be mechanistically linked to the risk of dementia. Amongst these pathways, estrogen signaling pathway takes the major part in the model and insulin signaling pathway is analyzed for its association to learning and memory functions. Validation of the model through serendipitous off-target effects suggests that hormone signaling pathways substantially contribute to the pathogenesis of dementia.

Conclusions: The integrated network model of hormone interactions underlying dementia may serve as an initial translational platform for identifying potential therapeutic targets and candidate biomarkers for dementia-spectrum disorders such as Alzheimer's disease.

Show MeSH
Related in: MedlinePlus