Novel putative drugs and key initiating genes for neurodegenerative disease determined using network-based genetic integrative analysis.

Autor: Mortezaei Z; Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran., Cazier JB; Centre for Computational Biology, Haworth Building, University of Birmingham, Birmingham, UK., Mehrabi AA; Department of Biometry and Plant Genetics, University of Ilam, Ilam, Iran., Cheng C; Department of Biomedical Data Sciences, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire., Masoudi-Nejad A; Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Jazyk: angličtina
Zdroj: Journal of cellular biochemistry [J Cell Biochem] 2019 Apr; Vol. 120 (4), pp. 5459-5471. Date of Electronic Publication: 2018 Oct 09.
DOI: 10.1002/jcb.27825
Abstrakt: Understanding the genetic causes of neurodegenerative disease (ND) can be useful for their prevention and treatment. Among the genetic variations responsible for ND, heritable germline variants have been discovered in genome-wide association studies (GWAS), and nonheritable somatic mutations have been discovered in sequencing projects. Distinguishing the important initiating genes in ND and comparing the importance of heritable and nonheritable genetic variants for treating ND are important challenges. In this study, we analysed GWAS results, somatic mutations and drug targets of ND from large databanks by performing directed network-based analysis considering a randomised network hypothesis testing procedure. A disease-associated biological network was created in the context of the functional interactome, and the nonrandom topological characteristics of directed-edge classes were interpreted. Hierarchical network analysis indicated that drug targets tend to lie upstream of somatic mutations and germline variants. Furthermore, using directed path length information and biological explanations, we provide information on the most important genes in these created node classes and their associated drugs. Finally, we identified nine germline variants overlapping with drug targets for ND, seven somatic mutations close to drug targets from the hierarchical network analysis and six crucial genes in controlling other genes from the network analysis. Based on these findings, some drugs have been proposed for treating ND via drug repurposing. Our results provide new insights into the therapeutic actionability of GWAS results and somatic mutations for ND. The interesting properties of each node class and the existing relationships between them can broaden our knowledge of ND.
(© 2018 Wiley Periodicals, Inc.)
Databáze: MEDLINE
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