Identification of Shared Genes and Pathways: A Comparative Study of Multiple Sclerosis Susceptibility, Severity and Response to Interferon Beta Treatment

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.近年来，全基因组关联研究（Genome-Wide Association Studies, GWAS）已成功鉴定出多个与多发性硬化（Multiple Sclerosis, MS）易感性、疾病严重程度或干扰素-β（Interferon-beta, IFN-β）应答相关的基因位点。然而，受限于此类研究的固有特性，这些基因位点的功能相关性尚未完全阐明。本研究采用基于系统生物学（systems biology）的方法，探究与多发性硬化相关性状的遗传互作组（genetic interactomes）。本研究提出如下假设：与这三种多发性硬化相关表型（phenotypes）相关的基因与通路可通过协同互作，影响已观测到的疾病异质性与不可预测的临床结局。我们构建了各性状对应的独立遗传互作组并进行比较分析，随后基于互作因子的出现频率对共有的互作因子进行优先级排序。随后开展通路富集分析（pathway enrichment analyses），以甄别共有的功能通路。本研究鉴定出ABL1、GRB2、INPP5D、KIF1B、PIK3R1、PLCG1、PRKCD、SRC、TUBA1A及TUBA4A等具有生物学相关性的基因，上述基因均为三种多发性硬化表型所共有。我们观察到，多发性硬化易感性与疾病严重程度之间共享的一级互作因子（first degree interactors）数量最多（p = 1.34×10⁻⁷⁹）；优先级排序分析显示，UBC是该表型对中最为显著的一级互作因子。如预期一致，两两比较结果表明，多发性硬化易感性与严重程度的互作组共享的通路数量最多。信号分子与互作、信号转导类别的通路为三种表型间共享最多的功能通路。最后，FYN是多发性硬化药物-基因网络（drug-gene network）中最常见的一级互作因子。通过应用基于系统生物学的研究策略，可从大型全基因组关联研究数据中提取更多具有生物学意义的信息。本研究的互作组分析结果与现有文献报道互为补充，同时还揭示了若干有待进一步实验验证的新型互作关系。总体而言，本研究阐明了采用基于系统生物学的方法，解析大型全基因组关联研究中鉴定出的基因位点生物学意义的潜力。