title: Network analysis of neurodegenerative disease highlights a role of Toll-like receptor signaling.
abstract: Despite significant advances in the study of the molecular mechanisms altered in the development and progression of neurodegenerative diseases (NDs), the etiology is still enigmatic and the distinctions between diseases are not always entirely clear. We present an efficient computational method based on protein-protein interaction network (PPI) to model the functional network of NDs. The aim of this work is fourfold: (i) reconstruction of a PPI network relating to the NDs, (ii) construction of an association network between diseases based on proximity in the disease PPI network, (iii) quantification of disease associations, and (iv) inference of potential molecular mechanism involved in the diseases. The functional links of diseases not only showed overlap with the traditional classification in clinical settings, but also offered new insight into connections between diseases with limited clinical overlap. To gain an expanded view of the molecular mechanisms involved in NDs, both direct and indirect connector proteins were investigated. The method uncovered molecular relationships that are in common apparently distinct diseases and provided important insight into the molecular networks implicated in disease pathogenesis. In particular, the current analysis highlighted the Toll-like receptor signaling pathway as a potential candidate pathway to be targeted by therapy in neurodegeneration.
authors.affiliation: The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068 Rovereto, Italy.
authors.forename: Thanh-Phuong
authors.initials: TP
authors.lastname: Nguyen
authors.affiliation: The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068 Rovereto, Italy.
authors.forename: Laura
authors.identifier: 0000-0002-2122-851X
authors.initials: L
authors.lastname: Caberlotto
authors.affiliation: The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068 Rovereto, Italy ; Department of Mathematics, University of Trento, Via Sommarive, 14-38123 Povo, Italy.
authors.forename: Melissa J
authors.initials: MJ
authors.lastname: Morine
authors.affiliation: The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068 Rovereto, Italy ; Department of Mathematics, University of Trento, Via Sommarive, 14-38123 Povo, Italy.
authors.forename: Corrado
authors.identifier: 0000-0002-3261-6235
authors.initials: C
authors.lastname: Priami
mesh_terms: D019295:Computational Biology; D057225:Data Mining; D016208:Databases, Factual; D006801:Humans; D019636:Neurodegenerative Diseases / Q000503:physiopathology*; D060066:Protein Interaction Maps / Q000502:physiology*; D011506:Proteins / Q000032:analysis / Q000737:chemistry / Q000378:metabolism; D015398:Signal Transduction / Q000502:physiology*; D051193:Toll-Like Receptors / Q000378:metabolism / Q000502:physiology*
chemical_list: D011506:Proteins; D051193:Toll-Like Receptors