Brain-specific functional relationship networks inform autism spectrum disorder gene prediction

作者：Duda, Marlena; Zhang, Hongjiu; Li, Hong-Dong; Wall, Dennis P.; Burmeister, Margit; Guan, Yuanfang^*

来源：Translational Psychiatry, 2018, 8(1): 56.

DOI：10.1038/s41398-018-0098-6

• DE-NOVO MUTATIONS
• MOLECULAR INTERACTION DATABASE
• RESOURCE
• IMPLICATE
• PATHWAYS
• REVEAL

Autism spectrum disorder (ASD) is a neuropsychiatric disorder with strong evidence of genetic contribution, and increased research efforts have resulted in an ever-growing list of ASD candidate genes. However, only a fraction of the hundreds of nominated ASD-related genes have identified de novo or transmitted loss of LOF) mutations that can be directly attributed to the disorder. For this reason, a means of prioritizing candidate genes for ASD would help filter out false-positive results and allow researchers to focus on genes that are more likely to be causative. Here we constructed a machine learning model by leveraging a brain-specific functional relationship network (FRN) of genes to produce a genome-wide ranking of ASD risk genes. We rigorously validated our gene ranking using results from two independent sequencing experiments, together representing over 5000 simplex and multiplex ASD families. Finally, through functional enrichment analysis on our highly prioritized candidate gene network, we identified a small number of pathways that are key in early neural development, providing further support for their potential role in ASD.

• 出版日期2018-3-6
• 单位上海生物信息技术研究中心; 中南大学