Department of Molecular Biology, Semmelweis University, Budapest, 1085, Hungary.
Mol Brain. 2024 Aug 9;17(1):55. doi: 10.1186/s13041-024-01127-0.
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social and communication difficulties, along with repetitive behaviors. While genetic factors play a significant role in ASD, the precise genetic landscape remains complex and not fully understood, particularly in non-syndromic cases. The study performed an in silico comparison of three genetic databases. ClinVar, SFARI Gene, and AutDB were utilized to identify relevant gene subset and genetic variations associated with non-syndromic ASD. Gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network analysis were conducted to elucidate the biological significance of the identified genes. The integrity of ASD-related gene subset and the distribution of their variations were statistically assessed. A subset of twenty overlapping genes potentially specific for non-syndromic ASD was identified. GSEA revealed enrichment of biological processes related to neuronal development and differentiation, synaptic function, and social skills, highlighting their importance in ASD pathogenesis. PPI network analysis demonstrated functional relationships among the identified genes. Analysis of genetic variations showed predominance of rare variants and database-specific distribution patterns. The results provide valuable insights into the genetic landscape of ASD and outline the genes and biological processes involved in the condition, while taking into account that the study relied exclusively on in silico analyses, which may be subject to biases inherent to database methodologies. Further research incorporating multi-omics data and experimental validation is warranted to enhance our understanding of non-syndromic ASD genetics and facilitate the development of targeted research, interventions and therapies.
自闭症谱系障碍 (ASD) 是一种神经发育障碍，其特征是社交和沟通困难，以及重复行为。虽然遗传因素在 ASD 中起着重要作用，但确切的遗传图谱仍然很复杂，尚未完全理解，尤其是在非综合征病例中。本研究对三个遗传数据库进行了计算机模拟比较。使用 ClinVar、SFARI Gene 和 AutDB 来识别与非综合征 ASD 相关的基因子集和遗传变异。进行了基因集富集分析 (GSEA) 和蛋白质-蛋白质相互作用 (PPI) 网络分析，以阐明鉴定基因的生物学意义。对 ASD 相关基因子集的完整性及其变异的分布进行了统计学评估。确定了一组二十个可能与非综合征 ASD 相关的重叠基因。GSEA 揭示了与神经元发育和分化、突触功能以及社交技能相关的生物学过程的富集，突出了它们在 ASD 发病机制中的重要性。PPI 网络分析显示了鉴定基因之间的功能关系。对遗传变异的分析表明，稀有变异占主导地位，且具有数据库特异性的分布模式。研究结果提供了对 ASD 遗传图谱的宝贵见解，并概述了涉及该疾病的基因和生物学过程，同时考虑到该研究仅依赖于计算机模拟分析，这可能受到数据库方法学固有的偏见影响。需要进一步进行包含多组学数据和实验验证的研究，以增强我们对非综合征 ASD 遗传学的理解，并促进有针对性的研究、干预和治疗的发展。
