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.
Highlights
Multiple Sclerosis (MS) is a neurodegenerative disease of the central nervous system (CNS) and is one of the most common CNS diseases in young adults affecting more than 2.5 million people worldwide [1]
The most recent MS Genome-wide association studies (GWAS) conducted by the International MS Genetics Consortium analysed the genomes of 9,722 MS patients against 17,376 healthy controls confirming 24 of the previously identified susceptibility loci and discovering an additional 29 novel susceptibility loci [11]
The 94 MS susceptibility genes interacted with a total of 897 first degree interactors, whereas the 21 MS severity and 19 IFN-ß response genes interacted with 457 and 138 first degree interactors, respectively
Summary
Multiple Sclerosis (MS) is a neurodegenerative disease of the central nervous system (CNS) and is one of the most common CNS diseases in young adults affecting more than 2.5 million people worldwide [1]. Genome-wide association studies (GWAS) have been successful in identifying genetic variations associated with disease susceptibility [2,3,4,5,6,7,8,9,10,11]. The most recent MS GWAS conducted by the International MS Genetics Consortium analysed the genomes of 9,722 MS patients against 17,376 healthy controls confirming 24 of the previously identified susceptibility loci and discovering an additional 29 novel susceptibility loci [11]. In GWAS studies, stringent statistical significance levels are applied in order to control for false positive associations. Such stringent statistical significance levels mean that true associations of modest effects may be discarded [12]. Baranzini and colleagues [13] have utilised GWAS data to explore susceptibility pathways relating to MS, while Menon and Farina [14] have attempted to identify shared susceptibility pathways with other autoimmune diseases
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