The contribution of de novo coding mutations to autism spectrum disorder

By I. Iossifov, Brian J. O'Roak, Stephan J Sanders, M. Ronemus, Niklas Krumm, D. Levy, H. Stessman, Kali T. Witherspoon, Laura Vives, Karynne E. Patterson and 37 more. Nature, 2014

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Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females.

Subfields: Cognitive Neuroscience, Genetics

View Paper: https://www.semanticscholar.org/paper/56793ee97ea91d14b5f397846abe9980eff93222

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Citations in the corpus

Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder (2017, neutral): “To move forward toward the goal of understanding all of the genetic factors involved in ASD, we recognize the need to scan the genome in its entirety using whole genome sequencing (WGS) 14,18,20,21 on thousands of samples, if not tens of thousands (or more) 13,22–24 .”
Predicting Splicing from Primary Sequence with Deep Learning. (2019, methodology): “These included 3,953 probands with autism spectrum disorder (Iossifov et al., 2014; De Rubeis et al., 2014), 4,293 probands from the Deciphering Developmental Disorders cohort (McRae et al.”
Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism (2019, methodology): “Of the 102 ASDassociated genes, 60 were not discovered by our earlier analyses (De Rubeis et al., 2014; Iossifov et al., 2014; Sanders et al., 2015).”
A SPECTRAL APPROACH INTEGRATING FUNCTIONAL GENOMIC ANNOTATIONS FOR CODING AND NONCODING VARIANTS (2016, background): “In total for ASD, we have n = 2,027 such mutations among which 1, 753 are missense [22, 23, 24, 25, 26].”
Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism (2016, neutral): “Extended Data Figure 2 | Transcriptome-wide DGE analysis. a , We applied a classification method robust to overfitting (elastic net model 47 ) by training on the RNA-seq data from samples previously analysed in ref.”
Ultra-rare disruptive and damaging mutations influence educational attainment in the general population (2016, neutral): “” Nature neuroscience 19 (12): 1563-1565.”
Modelling learning and memory in Drosophila to understand Intellectual Disabilities. (2020, neutral): “IDshaveastronggenetic basis, with the bulk of risk arising from de novo mutations and inherited genetic variation (De Rubeis et al., 2014; Iossifov et al., 2014).”
ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social-communication difficulties (2017, neutral): “Both, ASD and schizophrenia, are highly heritable10,11 and recent studies have linked different types of genetic variation including common variants10,12,13, as well as rare inherited14,15 and de novo variation16,17 to risk of illness in both conditions.”
Regional missense constraint improves variant deleteriousness prediction (2017, methodology): “Taking the combined scores from 5620 cases with a neurodevelopmental disorder 1-6 and 2078 controls 10,11 , we took the top ~10% of scores and determined the fraction of those variants that came from the cases.”
Advancing the understanding of autism disease mechanisms through genetics (2016, neutral): “Furthermore, estimates of the influence of de novo mutation on risk for ASD have been derived mostly from a sample of simplex families ( Box 1 ), which may inflate the contribution of de novo mutations 40,44,45,47,49 .”