A framework for the interpretation of de novo mutation in human disease

Samocha, Kaitlin E.; Robinson, Elise; Sanders, Stephan; Stevens, Christine; Sabo, Aniko; McGrath, Lauren M.; Kosmicki, Jack A.; Rehnström, Karola; Mallick, Swapan; Kirby, Andrew; Wall, Dennis P.; MacArthur, Daniel G.; Gabriel, Stacey; DePristo, Mark A.; Purcell, Shaun; Palotie, Aarno; Boerwinkle, Eric; Buxbaum, Joseph D.; Cook, Edwin H.; Gibbs, Richard A.; Schellenberg, Gerard D.; Sutcliffe, James S.; Devlin, Bernie; Roeder, Kathryn; Neale, Benjamin M.; Daly, Mark J.

doi:10.1038/ng.3050

Cited by 941 publications

(1,251 citation statements)

References 25 publications

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“…That autism candidate genes have a reduced load of damaging mutation has been reported earlier by others using different methods for measuring tolerance of mutation based largely on missense mutation and/or overlapping autism sample sets (13,14,16). Our results strengthen this finding with somewhat stronger statistics by using a larger set of target genes divided by severity, by using a larger control population to hone the tolerance score, or both.…”

Section: Discussionsupporting

confidence: 80%

“…Because people with ASD have lower fecundity than the general population, a disruptive mutation in an autism gene will be under strong purifying selection and quickly eliminated from the population (11). A clear prediction is that autism genes will have a smaller load of disruptive mutations than "typical" genes, as we first observed for fragile X mental retardation protein (FMRP)-associated genes (5, 12).Indeed, recent reports indicate that the targets of disruptive DN mutation in affected children do have a lighter load of disruptive mutation in the human population (13,14). The methods used for measuring the load used missense mutations as well as LGD mutations, in fairly complex formulations termed the "residual variation intolerance score" (RVIS) or gene constraint.…”

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confidence: 80%

“…Indeed, recent reports indicate that the targets of disruptive DN mutation in affected children do have a lighter load of disruptive mutation in the human population (13,14). The methods used for measuring the load used missense mutations as well as LGD mutations, in fairly complex formulations termed the "residual variation intolerance score" (RVIS) or gene constraint.…”

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confidence: 99%

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Low load for disruptive mutations in autism genes and their biased transmission

Iossifov

Levy

Allen

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

141

144

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We previously computed that genes with de novo (DN) likely gene-disruptive (LGD) mutations in children with autism spectrum disorders (ASD) have high vulnerability: disruptive mutations in many of these genes, the vulnerable autism genes, will have a high likelihood of resulting in ASD. Because individuals with ASD have lower fecundity, such mutations in autism genes would be under strong negative selection pressure. An immediate prediction is that these genes will have a lower LGD load than typical genes in the human gene pool. We confirm this hypothesis in an explicit test by measuring the load of disruptive mutations in wholeexome sequence databases from two cohorts. We use information about mutational load to show that lower and higher intelligence quotients (IQ) affected individuals can be distinguished by the mutational load in their respective gene targets, as well as to help prioritize gene targets by their likelihood of being autism genes. Moreover, we demonstrate that transmission of rare disruptions in genes with a lower LGD load occurs more often to affected offspring; we show transmission originates most often from the mother, and transmission of such variants is seen more often in offspring with lower IQ. A surprising proportion of transmission of these rare events comes from genes expressed in the embryonic brain that show sharply reduced expression shortly after birth.autism spectrum disorder | gene vulnerability | disruptive mutations | biased transmission | autism genes T he past decade has seen remarkable progress in understanding genetic causation of autism spectrum disorders (ASD), confirmatory of predictions made by a "unified" genetic theory of autism proposed in 2007 (1). This theory proposes that much of ASD is caused by new mutation, sometimes directly contributing to the disorder through germ-line mutation, or transmitted by parents, especially females, who carry a variant of recent vintage without experiencing severe consequences. The theory was based largely on three sets of observations: (i) low ASD incidence in females compared with males (2), (ii) apparently dominant transmission to male children in multiplex families (1), and (iii) greater incidence of de novo (DN) copy number mutation in children with ASD than in their siblings in simplex families (3, 4). Since then, evidence for causal DN mutation has accumulated (5-8). These damaging mutations generally affect only one allele, suggesting that gene targets are dosage-sensitive, prone to dominant negative mutation, or some combination of these factors.A widely held genetic model for autism is that combinations of common variation are the major driving force. As we argue, there is little evidence for this belief. Damaging DN mutation contributes to at least 30% of ASD in simplex families (9). Among such damaging mutations are those mutations that are likely gene-disruptive (LGD) in that they create nonsense, splice-site, or small frame-shift variants (5). The estimates of contribution from DN mutations derive from the statistical...

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Section: Discussionsupporting

confidence: 80%

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confidence: 80%

mentioning

confidence: 99%

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Low load for disruptive mutations in autism genes and their biased transmission

Iossifov

Levy

Allen

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

141

144

View full text Add to dashboard Cite

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“…This finding is consistent with genetic reports of strong de novo influences on severe intellectual disability (26,27) and suggests that the IQ distribution within ASDs could follow a similar trend. Second, studies have associated de novo copy number variants (CNVs) and point mutations with reductions in average IQ in ASD (20,28,29), although the extent to which this pattern extends to broader patterns of genetic architecture or case severity is unclear. Symptom severity, which can include impairments in social, communication, and daily living abilities, are associated with IQ in ASD but are likely, in many cases, to provide an independent route to reproductive disadvantage.…”

Section: Identifying Variables That Index Differences In Genetic Archmentioning

confidence: 99%

Autism spectrum disorder severity reflects the average contribution of de novo and familial influences

Robinson

Samocha

Kosmicki

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

129

118

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Autism spectrum disorders (ASDs) are a highly heterogeneous group of conditions-phenotypically and genetically-although the link between phenotypic variation and differences in genetic architecture is unclear. This study aimed to determine whether differences in cognitive impairment and symptom severity reflect variation in the degree to which ASD cases reflect de novo or familial influences. Using data from more than 2,000 simplex cases of ASD, we examined the relationship between intelligence quotient (IQ), behavior and language assessments, and rate of de novo loss of function (LOF) mutations and family history of broadly defined psychiatric disease (depressive disorders, bipolar disorder, and schizophrenia; history of psychiatric hospitalization). Proband IQ was negatively associated with de novo LOF rate (P = 0.03) and positively associated with family history of psychiatric disease (P = 0.003). Female cases had a higher frequency of sporadic genetic events across the severity distribution (P = 0.01). High rates of LOF mutation and low frequencies of family history of psychiatric illness were seen in individuals who were unable to complete a traditional IQ test, a group with the greatest degree of language and behavioral impairment. These analyses provide strong evidence that familial risk for neuropsychiatric disease becomes more relevant to ASD etiology as cases become higher functioning. The findings of this study reinforce that there are many routes to the diagnostic category of autism and could lead to genetic studies with more specific insights into individual cases.neuropsychiatric genetics | epidemiology | heterogeneity | phenotype

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“…None have been reported in public databases (gnomAD Browser), and one mutation (YWHAG c.394C>T) is recurrent in three subjects (B, E, and F). We used denovolyzeR 24 to evaluate the excess of de novo mutations in YWHAG. Assuming that 6,869 individuals were included, we observed a highly significant enrichment of heterozygotes (0.2 expected versus 7 observed; p ¼ 5.1 3 10 À9 ; 30.83; Table 1).…”

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confidence: 99%

De Novo Mutations in YWHAG Cause Early-Onset Epilepsy

Guella

McKenzie

Evans

et al. 2017

The American Journal of Human Genetics

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Massively parallel sequencing has revealed many de novo mutations in the etiology of developmental and epileptic encephalopathies (EEs), highlighting their genetic heterogeneity. Additional candidate genes have been prioritized in silico by their co-expression in the brain. Here, we evaluate rare coding variability in 20 candidates nominated with the use of a reference gene set of 51 established EE-associated genes. Variants within the 20 candidate genes were extracted from exome-sequencing data of 42 subjects with EE and no previous genetic diagnosis. We identified 7 rare non-synonymous variants in 7 of 20 genes and performed Sanger sequence validation in affected probands and parental samples. De novo variants were found only in SLC1A2 (aka EAAT2 or GLT1) (c.244G>A [p.Gly82Arg]) and YWHAG (aka 14-3-3g) (c.394C>T [p.Arg132Cys]), highlighting the potential cause of EE in 5% (2/42) of subjects. Seven additional subjects with de novo variants in SLC1A2 (n ¼ 1) and YWHAG (n ¼ 6) were subsequently identified through online tools. We identified a highly significant enrichment of de novo variants in YWHAG, establishing their role in early-onset epilepsy, and we provide additional support for the prior assignment of SLC1A2. Hence, in silico modeling of brain co-expression is an efficient method for nominating EE-associated genes to further elucidate the disorder's etiology and genotype-phenotype correlations.

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A framework for the interpretation of de novo mutation in human disease

Cited by 941 publications

References 25 publications

Low load for disruptive mutations in autism genes and their biased transmission

Low load for disruptive mutations in autism genes and their biased transmission

Autism spectrum disorder severity reflects the average contribution of de novo and familial influences

De Novo Mutations in YWHAG Cause Early-Onset Epilepsy

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