Person:

Howrigan, Daniel

Summary Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. We describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of truncating variants with 72% having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human “knockout” variants in protein-coding genes.

Disruptive and damaging ultra-rare variants (URVs) in highly constrained (HC) genes are enriched in individuals with neurodevelopmental disorders. In the general population, this class of variants was associated with a decrease in years of education (YOE; −3.1 months; P-value=3.3×10−8). This effect was stronger among high brain-expressed genes and explained more YOE variance than pathogenic copy number variation, but less than common variants. Disruptive and damaging URVs in HC genes influence the determinants of YOE in the general population.

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 ASD cases and 27,969 controls that identifies five genome-wide significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), seven additional loci shared with other traits are identified at equally strict significance levels. Dissecting the polygenic architecture we find both quantitative and qualitative polygenic heterogeneity across ASD subtypes, in contrast to what is typically seen in other complex disorders. These results highlight biological insights, particularly relating to neuronal function and corticogenesis and establish that GWAS performed at scale will be much more productive in the near term in ASD, just as it has been in a broad range of important psychiatric and diverse medical phenotypes.

Recent research has uncovered a significant role for de novo variation in neurodevelopmental disorders. Using aggregated data from 9246 families with autism spectrum disorder, intellectual disability, or developmental delay, we show ~1/3 of de novo variants are independently observed as standing variation in the Exome Aggregation Consortium’s cohort of 60,706 adults, and these de novo variants do not contribute to neurodevelopmental risk. We further use a loss-of-function (LoF)-intolerance metric, pLI, to identify a subset of LoF-intolerant genes that contain the observed signal of associated de novo protein truncating variants (PTVs) in neurodevelopmental disorders. LoF-intolerant genes also carry a modest excess of inherited PTVs; though the strongest de novo impacted genes contribute little to this, suggesting the excess of inherited risk resides lower-penetrant genes. These findings illustrate the importance of population-based reference cohorts for the interpretation of candidate pathogenic variants, even for analyses of complex diseases and de novo variation.

Protein-coding de novo mutations (DNMs) are significant risk factors in many neurodevelopmental disorders, whereas association with schizophrenia (SCZ) risk thus far has been modest. We analyze whole-exome sequence from 1,695 SCZ affected trios along with DNMs from 1,077 published SCZ trios to better understand their contribution to SCZ risk. Among 2,772 SCZ probands, exome-wide DNM burden remains modest. Gene set analyses reveal that SCZ DNMs are significantly concentrated in genes either highly brain expressed, under strong evolutionary constraint, and/or overlap with genes identified in other neurodevelopmental disorders. No single gene surpasses exome-wide significance, however sixteen genes are recurrently hit by protein-truncating DNMs, a 3.15-fold higher rate than the mutation model expectation (permuted 95% CI=1-10 genes, permuted p=3e-5). Overall, DNMs explain only a small fraction of SCZ risk, and larger samples are needed to identify individual risk genes, as coding variation across many genes confer risk for SCZ in the population.