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. 2016 Mar 9:9:12.
doi: 10.1186/s12920-016-0173-x.

Efficient and biologically relevant consensus strategy for Parkinson's disease gene prioritization

Maykel Cruz-Monteagudo  1   2 , Fernanda Borges  3 , Cesar Paz-Y-Miño  4 , M Natália D S Cordeiro  5 , Irene Rebelo  6 , Yunierkis Perez-Castillo  7   8 , Aliuska Morales Helguera  9 , Aminael Sánchez-Rodríguez  10 , Eduardo Tejera  11
Affiliations

Efficient and biologically relevant consensus strategy for Parkinson's disease gene prioritization

Maykel Cruz-Monteagudo et al. BMC Med Genomics. .

Abstract

Background: The systemic information enclosed in microarray data encodes relevant clues to overcome the poorly understood combination of genetic and environmental factors in Parkinson's disease (PD), which represents the major obstacle to understand its pathogenesis and to develop disease-modifying therapeutics. While several gene prioritization approaches have been proposed, none dominate over the rest. Instead, hybrid approaches seem to outperform individual approaches.

Methods: A consensus strategy is proposed for PD related gene prioritization from mRNA microarray data based on the combination of three independent prioritization approaches: Limma, machine learning, and weighted gene co-expression networks.

Results: The consensus strategy outperformed the individual approaches in terms of statistical significance, overall enrichment and early recognition ability. In addition to a significant biological relevance, the set of 50 genes prioritized exhibited an excellent early recognition ability (6 of the top 10 genes are directly associated with PD). 40 % of the prioritized genes were previously associated with PD including well-known PD related genes such as SLC18A2, TH or DRD2. Eight genes (CCNH, DLK1, PCDH8, SLIT1, DLD, PBX1, INSM1, and BMI1) were found to be significantly associated to biological process affected in PD, representing potentially novel PD biomarkers or therapeutic targets. Additionally, several metrics of standard use in chemoinformatics are proposed to evaluate the early recognition ability of gene prioritization tools.

Conclusions: The proposed consensus strategy represents an efficient and biologically relevant approach for gene prioritization tasks providing a valuable decision-making tool for the study of PD pathogenesis and the development of disease-modifying PD therapeutics.

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Figures

Fig. 1
Fig. 1
a Box plot of the differential average expression of genes across PD and healthy control samples (logPD-logHC) for genes conforming the nine PD WGCN modules. b Line plots of logPD-logHC for all the 8477 genes used to construct the global PD WGCN (center), 1437 genes in the predominantly underexpressed PD WGCN module PD_02 (left), and 494 genes in the predominantly overexpressed PD WGCN module PD_07 (right)
Fig. 2
Fig. 2
Representative common and unique biological process covered by modules PD_02 and PD_07
Fig. 3
Fig. 3
Accumulation curves of the four prioritization strategies considered. Overall enrichment represented by the accumulation curve for the full set of 8477 background genes for the respective prioritization strategies (a). Zoom of the top 20 %/1 % fraction of the ordered list providing information on the early recognition ability of the respective prioritization strategies (b/c)
Fig. 4
Fig. 4
Functional interaction network of the final set of 50 genes prioritized with the consensus strategy and 100 additional interacting genes. Each gene node was labeled in order to differentiate those genes in the 50 genes prioritized with the consensus strategy from the 100 additional interacting genes (labeled in gray). Genes with direct, indirect and no literature evidences of association with PD among the 50 genes prioritized with the consensus strategy were labeled in red, yellow and blue, respectively. Those genes among the 100 additional interacting genes included in the KEGG PD pathway were labeled in green
Fig. 5
Fig. 5
Functional interaction network comprising gene sets prioritized by Limma and ML, respectively. The genes prioritized by ML/Limma only are represented by yellow/green nodes, while those genes prioritized by both approaches (ML and Limma) are represented by blue nodes. Genes in the KEGG Dopaminergic Synapse Pathway/KEGG Parkinson’s Disease Pathway are represented by olive/red nodes, while those genes included in both pathways (Dopaminergic Synapse and Parkinson’s Disease) are represented by orange nodes
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