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Front. Physiol. | doi: 10.3389/fphys.2018.00154

Integrative Computational Network Analysis Reveals Site-Specific Mediators of Inflammation in Alzheimer’s Disease

Srikanth Ravichandran1,  Alessandro Michelucci2 and  Antonio del Sol1*
  • 1Computational Biology Group, Luxembourg Centre for System Biomedicine, Luxembourg
  • 2NORLUX Neuro-Oncology Laboratory, Luxembourg Institute of Health (LIH), Luxembourg

Alzheimer’s disease (AD) is a major neurodegenerative disease and is one of the most common cause of dementia in older adults. Among several factors, neuroinflammation is known to play a critical role in the pathogenesis of chronic neurodegenerative diseases. In particular, studies of brains affected by AD show a clear involvement of several inflammatory pathways. Furthermore, depending on the brain regions affected by the disease, the nature and the effect of inflammation can vary. Here, in order to shed more light on distinct and common features of inflammation in different brain regions affected by AD, we employed a computational approach to analyze gene expression data of six site-specific neuronal populations from AD patients. Our network based computational approach is driven by the concept that a sustained inflammatory environment could result in neurotoxicity leading to the disease. Thus, our method aims to infer intracellular signaling pathways/networks that are likely to be constantly activated or inhibited due to persistent inflammatory conditions. The computational analysis identified several inflammatory mediators, such as tumor necrosis factor alpha (TNF-a)-associated pathway, as key upstream receptors/ligands that are likely to transmit sustained inflammatory signals. Further, the analysis revealed that several inflammatory mediators were mainly region specific with few commonalities across different brain regions. Taken together, our results show that our integrative approach aids identification of inflammation-related signaling pathways that could be responsible for the onset or the progression of AD and can be applied to study other neurodegenerative diseases. Furthermore, such computational approaches can enable the translation of clinical omics data towards the development of novel therapeutic strategies for neurodegenerative diseases.

Keywords: Neuroinflammation, Integrative approach, computational modeling, signaling network, sustained inflammatory response

Received: 17 Oct 2017; Accepted: 14 Feb 2018.

Edited by:

Enrique Hernandez-Lemus, National Institute of Genomic Medicine, Mexico

Reviewed by:

Beth J. Allison, Hudson Institute of Medical Research, Australia
Jesús Espinal-Enríquez, National Institute of Genomic Medicine, Mexico  

Copyright: © 2018 Ravichandran, Michelucci and del Sol. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Antonio del Sol, DEL SOL., Luxembourg Centre for System Biomedicine, Computational Biology Group, Luxembourg, Luxembourg, antonio.delsol@uni.lu