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Identification of shared genes and pathways: a comparative study of multiple sclerosis susceptibility, severity and response to interferon beta treatment.

Mahurkar S, Moldovan M, Suppiah V, O'Doherty C - PLoS ONE (2013)

Bottom Line: Pathways from signalling molecules and interaction, and signal transduction categories were found to be highest shared pathways between 3 phenotypes.By applying the systems biology based approach, additional significant information can be extracted from GWAS.Overall, this study illustrates the potential of using a systems biology based approach in an attempt to unravel the biological significance of gene loci identified in large GWAS.

View Article: PubMed Central - PubMed

Affiliation: School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, Australia.

ABSTRACT
Recent genome-wide association studies (GWAS) have successfully identified several gene loci associated with multiple sclerosis (MS) susceptibility, severity or interferon-beta (IFN-ß) response. However, due to the nature of these studies, the functional relevance of these loci is not yet fully understood. We have utilized a systems biology based approach to explore the genetic interactomes of these MS related traits. We hypothesised that genes and pathways associated with the 3 MS related phenotypes might interact collectively to influence the heterogeneity and unpredictable clinical outcomes observed. Individual genetic interactomes for each trait were constructed and compared, followed by prioritization of common interactors based on their frequencies. Pathway enrichment analyses were performed to highlight shared functional pathways. Biologically relevant genes ABL1, GRB2, INPP5D, KIF1B, PIK3R1, PLCG1, PRKCD, SRC, TUBA1A and TUBA4A were identified as common to all 3 MS phenotypes. We observed that the highest number of first degree interactors were shared between MS susceptibility and MS severity (p = 1.34×10(-79)) with UBC as the most prominent first degree interactor for this phenotype pair from the prioritisation analysis. As expected, pairwise comparisons showed that MS susceptibility and severity interactomes shared the highest number of pathways. Pathways from signalling molecules and interaction, and signal transduction categories were found to be highest shared pathways between 3 phenotypes. Finally, FYN was the most common first degree interactor in the MS drugs-gene network. By applying the systems biology based approach, additional significant information can be extracted from GWAS. Results of our interactome analyses are complementary to what is already known in the literature and also highlight some novel interactions which await further experimental validation. Overall, this study illustrates the potential of using a systems biology based approach in an attempt to unravel the biological significance of gene loci identified in large GWAS.

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Number of shared first degree interactors between each of the three GWAS phenotype categories.
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pone-0057655-g001: Number of shared first degree interactors between each of the three GWAS phenotype categories.

Mentions: To investigate the relationships between MS susceptibility, severity and IFN-ß response modifying genes we performed shared comparative interactome analysis between these 3 phenotype categories in a pairwise fashion using methodology similar to Menon and Farina [14] (see Table S3 for details). The statistical significance of the number of shared first degree interactors between any 2 categories was assessed using p-values from a hypergeometric test, which objectively reflect the probability of obtaining the observed or greater number of shared first degree interactors given the common pool of genes under the assumption of no underlying biological mechanism. The test is equivalent to the one-sided Fisher’s test applied to information arranged in a 2×2 contingency table [20] (Table S4). The key entry of the table quantifies the observed numbers of shared first degree interactors between each pair of phenotypes that can be obtained from Figure 1. The corresponding p-value is the probability of obtaining the observed or greater number of first degree interactors belonging to both phenotype 1 and phenotype 2 related sets of first degree interactors, under the hypothesis of no underlying biological mechanism. Following from this, smaller p-values correspond to stronger evidence against the hypothesis, thus pointing towards the presence of an underlying biological mechanism.


Identification of shared genes and pathways: a comparative study of multiple sclerosis susceptibility, severity and response to interferon beta treatment.

Mahurkar S, Moldovan M, Suppiah V, O'Doherty C - PLoS ONE (2013)

Number of shared first degree interactors between each of the three GWAS phenotype categories.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3585216&req=5

pone-0057655-g001: Number of shared first degree interactors between each of the three GWAS phenotype categories.
Mentions: To investigate the relationships between MS susceptibility, severity and IFN-ß response modifying genes we performed shared comparative interactome analysis between these 3 phenotype categories in a pairwise fashion using methodology similar to Menon and Farina [14] (see Table S3 for details). The statistical significance of the number of shared first degree interactors between any 2 categories was assessed using p-values from a hypergeometric test, which objectively reflect the probability of obtaining the observed or greater number of shared first degree interactors given the common pool of genes under the assumption of no underlying biological mechanism. The test is equivalent to the one-sided Fisher’s test applied to information arranged in a 2×2 contingency table [20] (Table S4). The key entry of the table quantifies the observed numbers of shared first degree interactors between each pair of phenotypes that can be obtained from Figure 1. The corresponding p-value is the probability of obtaining the observed or greater number of first degree interactors belonging to both phenotype 1 and phenotype 2 related sets of first degree interactors, under the hypothesis of no underlying biological mechanism. Following from this, smaller p-values correspond to stronger evidence against the hypothesis, thus pointing towards the presence of an underlying biological mechanism.

Bottom Line: Pathways from signalling molecules and interaction, and signal transduction categories were found to be highest shared pathways between 3 phenotypes.By applying the systems biology based approach, additional significant information can be extracted from GWAS.Overall, this study illustrates the potential of using a systems biology based approach in an attempt to unravel the biological significance of gene loci identified in large GWAS.

View Article: PubMed Central - PubMed

Affiliation: School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, Australia.

ABSTRACT
Recent genome-wide association studies (GWAS) have successfully identified several gene loci associated with multiple sclerosis (MS) susceptibility, severity or interferon-beta (IFN-ß) response. However, due to the nature of these studies, the functional relevance of these loci is not yet fully understood. We have utilized a systems biology based approach to explore the genetic interactomes of these MS related traits. We hypothesised that genes and pathways associated with the 3 MS related phenotypes might interact collectively to influence the heterogeneity and unpredictable clinical outcomes observed. Individual genetic interactomes for each trait were constructed and compared, followed by prioritization of common interactors based on their frequencies. Pathway enrichment analyses were performed to highlight shared functional pathways. Biologically relevant genes ABL1, GRB2, INPP5D, KIF1B, PIK3R1, PLCG1, PRKCD, SRC, TUBA1A and TUBA4A were identified as common to all 3 MS phenotypes. We observed that the highest number of first degree interactors were shared between MS susceptibility and MS severity (p = 1.34×10(-79)) with UBC as the most prominent first degree interactor for this phenotype pair from the prioritisation analysis. As expected, pairwise comparisons showed that MS susceptibility and severity interactomes shared the highest number of pathways. Pathways from signalling molecules and interaction, and signal transduction categories were found to be highest shared pathways between 3 phenotypes. Finally, FYN was the most common first degree interactor in the MS drugs-gene network. By applying the systems biology based approach, additional significant information can be extracted from GWAS. Results of our interactome analyses are complementary to what is already known in the literature and also highlight some novel interactions which await further experimental validation. Overall, this study illustrates the potential of using a systems biology based approach in an attempt to unravel the biological significance of gene loci identified in large GWAS.

Show MeSH
Related in: MedlinePlus