Visualising Multiple Hits in Autism Spectrum Disorders Using Whole Genome Sequencing and Protein-Protein Interaction Networks

Thursday, May 11, 2017: 12:00 PM-1:40 PM
Golden Gate Ballroom (Marriott Marquis Hotel)
F. Cliquet1, C. Carton1,2, T. Kergrohen1, A. Mathieu1, A. Ziegler3, J. Van-Gils4, J. Buratti5, F. Amsellem1,6, T. Rolland1, C. S. Leblond1,2, D. Bonneau3, B. Schwikowski1, R. Delorme1,6 and T. Bourgeron2,7, (1)Institut Pasteur, Paris, France, (2)Université Paris Diderot, Paris, France, (3)CHU Angers, Angers, France, (4)CHU Bordeaux, Bordeaux, France, (5)Hôpital Pitié-Salpêtrière, Paris, France, (6)Hôpital Robert-Debré, Paris, France, (7)Neuroscience, Institut Pasteur, Paris, France
Background: The biological causes of autism spectrum disorders (ASD) remain largely unknown mostly because of the high clinical and genetic heterogeneity. Furthermore, many studies indicated that, in a single patient, multiple hits affecting different genes/pathways might underlie the increased risk to have ASD. Several tools, such as Cytoscape, exist to visualize protein-protein interactions networks, but no application was designed to visualise variants affecting these networks.

Objectives: We aimed at developing a tool to help geneticists to visualise both protein-protein interactions and whole genome/exome data. This tool should help identifying multiple hits in individuals with ASD and providing a very precise characterization of each variants.

Methods: We sequenced the whole genome of 152 individuals from simplex and multiplex families with autism (57 patients, 68 parents and 51 relatives). We then designed GRAVITY a new Cytoscape App to rapidly visualise variants affecting ASD-risk genes (for example the SFARI gene list) or pathways (for example the glutamatergic, the GABAergic or the FMRP pathways). The tool can help filter the data on various user-defined criteria, such as the quality of the base calling, the type of mutation (synonymous, missense, stopgain…), the inheritance (de novo, recessive, dominant), the allele frequency as well as various scores to predict the deleteriousness impact of the variants (CADD, polyphen, SIFT).

Results: We first identified patients carrying a “first hit” affecting a known ASD-risk gene (SHANK2, SHANK3, NLGN4X, CNTNAP2, CNTNAP4, TBC1D5, KCNB1, HYDIN, MEF2C) or new compelling candidate genes (EPHA4, SMG1). Using GRAVITY, we could also visualize additional hits in known ASD-risk gene and providing an estimation of the burden of multiple hits for each affected and unaffected individuals.

Conclusions: GRAVITY is a new tool simplifying the discovery of multiple hit in patients, saving a lot of time in the process. Thanks to GRAVITY, we were able to analyse the genetic architecture of 152 individuals revealing new candidate genes and confirming that multiple hits are frequently observed in patients with ASD. Further studies are warranted to ascertain if the burden of multiple hits contribute to the severity of the symptoms in the patients.

See more of: Genetics
See more of: Genetics