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

Journal: Translational psychiatry
Published Date: Mar 6, 2018

Abstract

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 function (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.

Authors

  • Marlena Duda
    Department of Pediatrics, Division of Systems Medicine, Stanford University, Stanford, CA USA.
  • Hongjiu Zhang
    Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • Hong-Dong Li
    Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • Dennis P Wall
    Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California; Department of Biomedical Data Science, Stanford University, Stanford, California; Department of Psychiatry and Behavioral Sciences (by courtesy), Stanford University, Stanford, California. Electronic address: dpwall@stanford.edu.
  • Margit Burmeister
    Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • Yuanfang Guan
    Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA. gyuanfan@umich.edu.

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