Construction and Analysis of the Protein-Protein Interaction Networks Based on Gene Expression Profiles of Parkinson's Disease
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TLDR
This study represents a novel investigation of the PPI networks for PD, a complex disease, and 37 proteins identified can be considered as PD network biomarkers.Abstract:
Background
Parkinson's Disease (PD) is one of the most prevailing neurodegenerative diseases. Improving diagnoses and treatments of this disease is essential, as currently there exists no cure for this disease. Microarray and proteomics data have revealed abnormal expression of several genes and proteins responsible for PD. Nevertheless, few studies have been reported involving PD-specific protein-protein interactions.
Results
Microarray based gene expression data and protein-protein interaction (PPI) databases were combined to construct the PPI networks of differentially expressed (DE) genes in post mortem brain tissue samples of patients with Parkinson's disease. Samples were collected from the substantia nigra and the frontal cerebral cortex. From the microarray data, two sets of DE genes were selected by 2-tailed t-tests and Significance Analysis of Microarrays (SAM), run separately to construct two Query-Query PPI (QQPPI) networks. Several topological properties of these networks were studied. Nodes with High Connectivity (hubs) and High Betweenness Low Connectivity (bottlenecks) were identified to be the most significant nodes of the networks. Three and four-cliques were identified in the QQPPI networks. These cliques contain most of the topologically significant nodes of the networks which form core functional modules consisting of tightly knitted sub-networks. Hitherto unreported 37 PD disease markers were identified based on their topological significance in the networks. Of these 37 markers, eight were significantly involved in the core functional modules and showed significant change in co-expression levels. Four (ARRB2, STX1A, TFRC and MARCKS) out of the 37 markers were found to be associated with several neurotransmitters including dopamine.
Conclusion
This study represents a novel investigation of the PPI networks for PD, a complex disease. 37 proteins identified in our study can be considered as PD network biomarkers. These network biomarkers may provide as potential therapeutic targets for PD applications development.read more
Citations
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A review of genome-wide transcriptomics studies in Parkinson's disease.
Genevie Borrageiro,William Haylett,Soraya Seedat,Helena Kuivaniemi,Helena Kuivaniemi,Soraya Bardien +5 more
TL;DR: The concordance of several pathways such as mitochondrial function, protein degradation and inflammation, identified in both blood and brain tissues, suggests that the disease process is systemic and not restricted to neurological tissues.
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Disrupted iron homeostasis causes dopaminergic neurodegeneration in mice
Pavle Matak,Andrija Matak,Sarah Moustafa,Dipendra K. Aryal,Eric J. Benner,William C. Wetsel,Nancy C. Andrews +6 more
TL;DR: It is demonstrated that loss of transferrin receptor 1, but not loss of ferroportin, can cause neurodegeneration in a subset of dopaminergic neurons in mice, and proposed that neuronal iron deficiency may contribute to neurodegenersation in human disease.
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Midbrain dopamine neurons in Parkinson's disease exhibit a dysregulated miRNA and target-gene network.
Christine Briggs,Yulei Wang,Benjamin Kong,Tsung-Ung W. Woo,Lakshmanan K. Iyer,Kai C. Sonntag +5 more
TL;DR: This study provides evidence for a general association of miRNAs with the cellular function and identity of SN DA neurons, and with deregulated gene expression networks and signaling pathways related to PD pathogenesis that may be sex-specific.
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A computational framework for the prioritization of disease-gene candidates
TL;DR: This work proposes a computational pipeline for the prioritization of disease-gene candidates and revealed the prioritized genes are modulated in AD pathogenesis including: regulation of neurogenesis and generation of neurons.
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Identification of new key genes for type 1 diabetes through construction and analysis of protein–protein interaction networks based on blood and pancreatic islet transcriptomes
Nahid Safari-Alighiarloo,Mohammad Taghizadeh,Seyyed Mohammad Tabatabaei,Soodeh Shahsavari,Saeed Namaki,Soheila Khodakarim,Mostafa Rezaei-Tavirani +6 more
TL;DR: The aims of the study were to elucidate the underlying molecular mechanisms and identify key genes associated with T1D risk using a network biology approach.
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