Journal article
A systems biology approach to identify intelligence quotient score-related genomic regions, and pathways relevant to potential therapeutic treatments
Scientific Reports, Vol.4(4176), pp.1-7
2014
Abstract
Although the intelligence quotient (IQ) is the most popular intelligence test in the world, little is known about the underlying biological mechanisms that lead to the differences in human. To improve our understanding of cognitive processes and identify potential biomarkers, we conducted a comprehensive investigation of 158 IQ-related genes selected from the literature. A genomic distribution analysis demonstrated that IQ-related genes were enriched in seven regions of chromosome 7 and the X chromosome. In addition, these genes were enriched in target lists of seven transcription factors and sixteen microRNAs. Using a network-based approach, we further reconstructed an IQ-related pathway from known human pathway interaction data. Based on this reconstructed pathway, we incorporated enriched drugs and described the importance of dopamine and norepinephrine systems in IQ-related biological process. These findings not only reveal several testable genes and processes related to IQ scores, but also have potential therapeutic implications for IQ-related mental disorders.
Details
- Title
- A systems biology approach to identify intelligence quotient score-related genomic regions, and pathways relevant to potential therapeutic treatments
- Authors
- Min Zhao (Author) - Peking University, ChinaL Kong (Author) - Peking University, ChinaH Qu (Author) - Peking University, China
- Publication details
- Scientific Reports, Vol.4(4176), pp.1-7
- Publisher
- Nature Publishing Group
- Date published
- 2014
- DOI
- 10.1038/srep04176
- ISSN
- 2045-2322
- Copyright note
- Copyright © 2014 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0
- Organisation Unit
- School of Science and Engineering - Legacy; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 99449001502621
- Output Type
- Journal article
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