- Short report
- Open Access
Disease association and inter-connectivity analysis of human brain specific co-expressed functional modules
© Oh et al. 2015
- Received: 3 August 2015
- Accepted: 4 December 2015
- Published: 16 December 2015
In the recent studies, it is suggested that the analysis of transcriptomic change of functional modules instead of individual genes would be more effective for system-wide identification of cellular functions. This could also provide a new possibility for the better understanding of difference between human and chimpanzee.
In this study, we analyzed to find molecular characteristics of human brain functions from the difference of transcriptome between human and chimpanzee’s brain using the functional module-centric co-expression analysis. We performed analysis of brain disease association and systems-level connectivity of species-specific co-expressed functional modules.
Throughout the analyses, we found human-specific functional modules and significant overlap between their genes in known brain disease genes, suggesting that human brain disorder could be mediated by the perturbation of modular activities emerged in human brain specialization. In addition, the human-specific modules having neurobiological functions exhibited higher networking than other functional modules. This finding suggests that the expression of neural functions are more connected than other functions, and the resulting high-order brain functions could be identified as a result of consolidated inter-modular gene activities. Our result also showed that the functional module based transcriptome analysis has a potential to expand molecular understanding of high-order complex functions like cognitive abilities and brain disorders.
- Co-expressed functional module
- Disease association
- Inter-connectivity analysis
To characterize the molecular bases associated with human’s remarkably advanced high-order brain functions and vulnerability to various brain disorders, a comparative analysis between human and chimpanzee brain transcriptome is considered as an important way . Until now, several previous studies compared the transcriptome data of human and chimpanzee brains. Despite some successes, little has been understood to account for unique features of human brain. In the previous study, we showed that a co-expression analysis of functional modules has shown increased sensitivity for identifying implication of more diverse genes and cellular functions that were previously undetected . Recent studies have shown the existence of inter-module co-expression networks in the human brain, suggesting that systems-level relationships might also uniquely constitute human brain specificity [3, 4]. However, the implication of functional modules and their network properties have not been investigated in depth to further extract functional meanings of each module and their interplay with respect to human brain specialization. In this study, we analysed to find molecular characteristics of human brain functions using the human-specific co-expressed functional modules (HS-COMODs) and the chimpanzee-specific co-expressed functional modules (CS-COMODs). Our new approach using integrated analysis of gene expression data should be an aid in molecular interpretation of other complex biological functions too.
Association of HS-COMODs and brain disorders
Systems-level characteristics of HS-COMODs
There are 25 neurobiological modules in total 248 non-overlapping HS-COMODs in human-specific functional module networks. In top 5 % (13 functional modules) HS-COMODs which have highest normalized connectivity, there are 5 neurobiological modules (one-sided Fisher’s exact test, P = 4.53E−03). In addition, average connectivity score of neurobiological modules is 0.308 compare to average connectivity of total functional modules and non-neurobiological module is 0.246 and 0.239, respectively. These results showed that the neurobiological modules had significantly higher normalized connectivity than did the other modules. In addition, the neurobiological modules had higher normalized connectivity than the rest, particularly in the ‘denser’ network (Fig. 2b). Our data suggests the central importance of the neurobiological modules, several of which are influential to the high-order brain functions such as learning or memory, and the prevalent functional cooperation of the neurobiological modules with a wide variety of functional modules in human brain.
Top 10 HS-COMODs showing highest connectivity to neurobiological modules
Negative regulation of protein modification process
Generation of precursor metabolites and energy
RNF5 hub protein network
Ubiquitin mediated proteolysis (KEGG)
Protein ubiquitination (UniPathway)
Protein modification by small protein conjugation
Energy derivation by oxidation of organic compounds
Proteasomal ubiquitin-dependent protein catabolic process
It is important to unravel the molecular mechanisms underlying the high-order human brain functions for the drug development for the cognition enhancement. Despite tremendous researches, only few drugs have been approved  and the efficacy of those drugs for both healthy people and patients with cognitive dysfunctions seems to be modest and even harmful in some ways . Recently it has been suggested that targeting multiple genes or complementary mechanisms by multiple drugs would be more desirable approach for the improved therapeutics [13, 14]. Moreover, it has been shown that evolutionarily emerging genes are likely to be the targets of successful drugs . In these regards, this study might provide insight to the drug development. To make it more plausible, it would be further necessary to elucidate the specificity of the transcription factors or the epigenetic regulators on those key functional modules.
We showed the significant overlap between the HS-COMODs and the brain disease modules, suggesting that the emergent functionalization of modular activities in human brain might be sensitive to the perturbations. In a system-level analysis into the HS-COMODs, it was shown that the functional modules show complex inter-module co-expression in human brain. Of particular note, the functional modules implicated to the neurobiological processes showed significantly higher connectivity than the others. From this point of view, neurobiological modules might have the potential contribution to cooperate with a wide variety of functional modules to drive cognitive functions at the systems level. Therefore, our findings showed that a systems approach adopted in the interpretation of transcriptomic change between human and chimpanzee brains has a potential to improve our molecular understanding of high-order complex functions like cognitive abilities and brain disorders.
Identification of brain disease modules
Disease categories used to compile brain disease modules
Cerebral palsy and other paralytic syndromes
Mental and behavioural disorders due to other psycho-active substance use
Mental and behavioural disorders due to use of alcohol
Mood (affective) disorders
Nerve, nerve root and plexus disorders
Neurotic, stress-related and somatoform disorders
Other congenital malformations of the nervous system
Other diseases of the nervous system
Schizophrenia, schizotypal and delusional disorders
Construction of co-expression network and characterization of inter-modular correlation
KO and TH designed and conducted the experiments and wrote the manuscript. KC helped preparation of data from public databases. GSY designed and supervised the experiments and wrote the manuscript. All authors discussed the results and implications and commented on the manuscript at all stages. All authors read and approved the final manuscript.
This work was supported by the Bio-Synergy Research Project (NRF-2012M3A9C4048759) of the Ministry of Science, ICT and Future Planning through the National Research Foundation, the KAIST Future Systems Healthcare Project from the Ministry of Science, ICT and Future Planning, and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2010-0028631).
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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