Gandal, M. J. | Search bioRxiv

bioRxiv2018

Whole genome sequencing in multiplex families reveals novel inherited and de novo genetic risk in autism

Genetic studies of autism spectrum disorder (ASD) have revealed a complex, heterogeneous architecture, in which the contribution of rare inherited variation remains relatively un-explored. We performed whole-genome sequencing (WGS) in 2,308 individuals from families containing multiple affected children, including analysis of single nucleotide variants (SNV) and structural variants (SV). We identified 16 new ASD-risk genes, including many supported by inherited variation, and provide statistical support for 69 genes in total, including previously implicated genes. These risk genes are enriched in pathways involving negative regulation of synaptic transmission and organelle organization. We identify a significant protein-protein interaction (PPI) network seeded by inherited, predicted damaging variants disrupting highly constrained genes, including members of the BAF complex and established ASD risk genes. Analysis of WGS also identified SVs effecting non-coding regulatory regions in developing human brain, implicating NR3C2 and a recurrent 2.5Kb deletion within the promoter of DLG2. These data lend support to studying multiplex families for identifying inherited risk for ASD. We provide these data through the Hartwell Autism Research and Technology Initiative (iHART), an open access cloud-computing repository for ASD genetics research.

genomics↗

bioRxiv2018

Spatial gene-by-environment mapping for schizophrenia reveals locale of upbringing effects beyond urban-rural differences

Identification of mechanisms underlying the incidence of psychiatric disorders has been hampered by the difficulty in discovering highly-predictive environmental risk factors. For example, prior efforts have failed to establish environmental effects predicting geospatial clustering of schizophrenia incidence beyond urban-rural differences. Here, we employ a novel statistical framework for decomposing the geospatial risk for schizophrenia based on locale of upbringing (place of residence, ages 0-7 years) and its synergistic effects with genetic liabilities (polygenic risk for schizophrenia). We use this statistical framework to analyze unprecedented geolocation and genotyping data in a case-cohort study of n=24,028 subjects, drawn from the 1.47 million Danish persons born between 1981 and 2005. Using this framework we estimate the effects of upbringing locale (E) and gene-by-locale interactions (GxE). After controlling for potential confounding variables, upbringing at high-risk locales increases the risk for schizophrenia on average by 122%, while GxE modulates genetic risk for schizophrenia on average by 78%. Within the boundaries of Copenhagen (the largest and most densely populated city of Denmark) specific locales vary substantially in their E and GxE effects, with hazard ratios ranging from 0.26 to 9.26 for E and from 0.20 to 5.95 for GxE. This study provides insight into the degree of geospatial clustering of schizophrenia risk, and our novel analytic procedure provides a framework for decomposing variation in geospatial risk into G, E, and GxE components.

epidemiology↗