Limits...
DEGAS: de novo discovery of dysregulated pathways in human diseases.

Ulitsky I, Krishnamurthy A, Karp RM, Shamir R - PLoS ONE (2010)

Bottom Line: Recent studies have found that only a small number of the genes in human disease-related pathways show consistent dysregulation in sick individuals.However, those studies found that some pathway genes are affected in most sick individuals, but genes can differ among individuals.We applied DEGAS to seven human diseases and obtained statistically significant results that appear to home in on compact pathways enriched with hallmarks of the diseases.

View Article: PubMed Central - PubMed

Affiliation: Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel. ulitsky@wi.mit.edu

ABSTRACT

Background: Molecular studies of the human disease transcriptome typically involve a search for genes whose expression is significantly dysregulated in sick individuals compared to healthy controls. Recent studies have found that only a small number of the genes in human disease-related pathways show consistent dysregulation in sick individuals. However, those studies found that some pathway genes are affected in most sick individuals, but genes can differ among individuals. While a pathway is usually defined as a set of genes known to share a specific function, pathway boundaries are frequently difficult to assign, and methods that rely on such definition cannot discover novel pathways. Protein interaction networks can potentially be used to overcome these problems.

Methodology/principal findings: We present DEGAS (DysrEgulated Gene set Analysis via Subnetworks), a method for identifying connected gene subnetworks significantly enriched for genes that are dysregulated in specimens of a disease. We applied DEGAS to seven human diseases and obtained statistically significant results that appear to home in on compact pathways enriched with hallmarks of the diseases. In Parkinson's disease, we provide novel evidence for involvement of mRNA splicing, cell proliferation, and the 14-3-3 complex in the disease progression. DEGAS is available as part of the MATISSE software package (http://acgt.cs.tau.ac.il/matisse).

Conclusions/significance: The subnetworks identified by DEGAS can provide a signature of the disease potentially useful for diagnosis, pinpoint possible pathways affected by the disease, and suggest targets for drug intervention.

Show MeSH

Related in: MedlinePlus

A DP of genes up-regulated in Parkinson's disease patients in the Moran et al. data.Nodes that appear also in the DP for k = 10 are in blue, the radius of each node is proportional to the number of patients in which it is dysregulated. Triangles are genes involved in mRNA splicing, diamonds are genes involved in cell proliferation.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2957424&req=5

pone-0013367-g005: A DP of genes up-regulated in Parkinson's disease patients in the Moran et al. data.Nodes that appear also in the DP for k = 10 are in blue, the radius of each node is proportional to the number of patients in which it is dysregulated. Triangles are genes involved in mRNA splicing, diamonds are genes involved in cell proliferation.

Mentions: We first focused on the PD expression dataset of Moran et al. [42], as it contained more samples than Lesnick et al. [43]. Using these expression profiles, we identified a 73-gene pathway as the most significantly up-regulated pathway in PD (MORAN-PD-UP, Figure 5). It was strikingly enriched with genes related to splicing– it contained 15 genes annotated with RNA splicing in GO “biological process” (p = 1.17·10−10, FDR<0.1). The module was identified for k = 30, but similar enrichments were seen in the pathways identified for k values between 25 and 10 (The core pathway dysregulated for k = 10 is highlighted in Figure 5). These results thus suggest a major up-regulation of the splicing machinery in PD. The literature contains several additional lines of evidence that splicing is affected in PD. Several studies found that the splicing of several of the key genes in PD, α-synuclein, parkin, synphilin-1, FOSB and RGS9, are affected in diseased individuals and in mouse models of the disease [54], [55], [56]. Furthermore, DJ-1, one of the genes mutated in genetic PD, has been implicated in splicing, through regulation of the splicing of tyrosine hydroxylase by the protein-associated splicing factor (PSF) [57]. Mitochondrial damage, a common phenomenon of several neurodegenerative diseases, including PD, Alzheimer's disease (AD) and Amyotrophic lateral sclerosis (ALS), was shown to affect alternative splicing in neural cells by increasing the relative abundance of shorter isoforms [58]. Finally, a recent study used three PD microarray datasets that were not used in our study [59], [60], [61] and identified the splicing factor SRRM2 as the only gene that was dysregulated in PD in all three datasets [62]. The latter study also identified hundreds of alternative splicing events in the blood of PD patients. However, we are not aware of any previous reports on a concerted up-regulation of parts of the splicing machinery in PD patients.


DEGAS: de novo discovery of dysregulated pathways in human diseases.

Ulitsky I, Krishnamurthy A, Karp RM, Shamir R - PLoS ONE (2010)

A DP of genes up-regulated in Parkinson's disease patients in the Moran et al. data.Nodes that appear also in the DP for k = 10 are in blue, the radius of each node is proportional to the number of patients in which it is dysregulated. Triangles are genes involved in mRNA splicing, diamonds are genes involved in cell proliferation.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2957424&req=5

pone-0013367-g005: A DP of genes up-regulated in Parkinson's disease patients in the Moran et al. data.Nodes that appear also in the DP for k = 10 are in blue, the radius of each node is proportional to the number of patients in which it is dysregulated. Triangles are genes involved in mRNA splicing, diamonds are genes involved in cell proliferation.
Mentions: We first focused on the PD expression dataset of Moran et al. [42], as it contained more samples than Lesnick et al. [43]. Using these expression profiles, we identified a 73-gene pathway as the most significantly up-regulated pathway in PD (MORAN-PD-UP, Figure 5). It was strikingly enriched with genes related to splicing– it contained 15 genes annotated with RNA splicing in GO “biological process” (p = 1.17·10−10, FDR<0.1). The module was identified for k = 30, but similar enrichments were seen in the pathways identified for k values between 25 and 10 (The core pathway dysregulated for k = 10 is highlighted in Figure 5). These results thus suggest a major up-regulation of the splicing machinery in PD. The literature contains several additional lines of evidence that splicing is affected in PD. Several studies found that the splicing of several of the key genes in PD, α-synuclein, parkin, synphilin-1, FOSB and RGS9, are affected in diseased individuals and in mouse models of the disease [54], [55], [56]. Furthermore, DJ-1, one of the genes mutated in genetic PD, has been implicated in splicing, through regulation of the splicing of tyrosine hydroxylase by the protein-associated splicing factor (PSF) [57]. Mitochondrial damage, a common phenomenon of several neurodegenerative diseases, including PD, Alzheimer's disease (AD) and Amyotrophic lateral sclerosis (ALS), was shown to affect alternative splicing in neural cells by increasing the relative abundance of shorter isoforms [58]. Finally, a recent study used three PD microarray datasets that were not used in our study [59], [60], [61] and identified the splicing factor SRRM2 as the only gene that was dysregulated in PD in all three datasets [62]. The latter study also identified hundreds of alternative splicing events in the blood of PD patients. However, we are not aware of any previous reports on a concerted up-regulation of parts of the splicing machinery in PD patients.

Bottom Line: Recent studies have found that only a small number of the genes in human disease-related pathways show consistent dysregulation in sick individuals.However, those studies found that some pathway genes are affected in most sick individuals, but genes can differ among individuals.We applied DEGAS to seven human diseases and obtained statistically significant results that appear to home in on compact pathways enriched with hallmarks of the diseases.

View Article: PubMed Central - PubMed

Affiliation: Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel. ulitsky@wi.mit.edu

ABSTRACT

Background: Molecular studies of the human disease transcriptome typically involve a search for genes whose expression is significantly dysregulated in sick individuals compared to healthy controls. Recent studies have found that only a small number of the genes in human disease-related pathways show consistent dysregulation in sick individuals. However, those studies found that some pathway genes are affected in most sick individuals, but genes can differ among individuals. While a pathway is usually defined as a set of genes known to share a specific function, pathway boundaries are frequently difficult to assign, and methods that rely on such definition cannot discover novel pathways. Protein interaction networks can potentially be used to overcome these problems.

Methodology/principal findings: We present DEGAS (DysrEgulated Gene set Analysis via Subnetworks), a method for identifying connected gene subnetworks significantly enriched for genes that are dysregulated in specimens of a disease. We applied DEGAS to seven human diseases and obtained statistically significant results that appear to home in on compact pathways enriched with hallmarks of the diseases. In Parkinson's disease, we provide novel evidence for involvement of mRNA splicing, cell proliferation, and the 14-3-3 complex in the disease progression. DEGAS is available as part of the MATISSE software package (http://acgt.cs.tau.ac.il/matisse).

Conclusions/significance: The subnetworks identified by DEGAS can provide a signature of the disease potentially useful for diagnosis, pinpoint possible pathways affected by the disease, and suggest targets for drug intervention.

Show MeSH
Related in: MedlinePlus