Mosca Ettore, Bersanelli Matteo, Gnocchi Matteo, Moscatelli Marco, Castellani Gastone, Milanesi Luciano, Mezzelani Alessandra
Bioinformatics Group, Institute of Biomedical Technologies, National Research Council of Italy, Segrate, Italy.
Applied Physics Group, Department of Physics and Astronomy, University of Bologna, Bologna, Italy.
Front Genet. 2017 Sep 25;8:129. doi: 10.3389/fgene.2017.00129. eCollection 2017.
Autism spectrum disorder (ASD) is marked by a strong genetic heterogeneity, which is underlined by the low overlap between ASD risk gene lists proposed in different studies. In this context, molecular networks can be used to analyze the results of several genome-wide studies in order to underline those network regions harboring genetic variations associated with ASD, the so-called "disease modules." In this work, we used a recent network diffusion-based approach to jointly analyze multiple ASD risk gene lists. We defined genome-scale prioritizations of human genes in relation to ASD genes from multiple studies, found significantly connected gene modules associated with ASD and predicted genes functionally related to ASD risk genes. Most of them play a role in synapsis and neuronal development and function; many are related to syndromes that can be in comorbidity with ASD and the remaining are involved in epigenetics, cell cycle, cell adhesion and cancer.
自闭症谱系障碍(ASD)具有很强的遗传异质性,不同研究提出的ASD风险基因列表之间重叠率低就突出了这一点。在此背景下,分子网络可用于分析多项全基因组研究的结果,以突显那些含有与ASD相关的遗传变异的网络区域,即所谓的“疾病模块”。在这项工作中,我们使用了一种基于网络扩散的最新方法来联合分析多个ASD风险基因列表。我们定义了与多项研究中的ASD基因相关的人类基因的全基因组规模优先级,发现了与ASD显著相关的基因模块,并预测了与ASD风险基因功能相关的基因。其中大多数在突触形成、神经元发育和功能中发挥作用;许多与可能与ASD合并存在的综合征有关,其余的则涉及表观遗传学、细胞周期、细胞黏附和癌症。