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Neurodevelopmental disease genes implicated by de novo mutation and copy number variation morbidity
Open accessAbstract
We combined de novo mutation (DNM) data from 10,927 individuals with developmental delay and autism to identify 253 candidate neurodevelopmental disease genes with an excess of missense and/or likely gene-disruptive (LGD) mutations. Of these genes, 124 reach exome-wide significance (P < 5 × 10-7) for DNM. Intersecting these results with copy number variation (CNV) morbidity data shows an enrichment for genomic disorder regions (30/253, likelihood ratio (LR) +1.85, P = 0.0017). We identify genes with an excess of missense DNMs overlapping deletion syndromes (for example, KIF1A and the 2q37 deletion) as well as duplication syndromes, such as recurrent MAPK3 missense mutations within the chromosome 16p11.2 duplication, recurrent CHD4 missense DNMs in the 12p13 duplication region, and recurrent WDFY4 missense DNMs in the 10q11.23 duplication region. Network analyses of genes showing an excess of DNMs highlights functional networks, including cell-specific enrichments in the D1+ and D2+ spiny neurons of the striatum.
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“Large scale genetic screenings have revealed that many of the identified top-ranking autism risk factors are genes implicated in synaptic homeostasis, transcriptional regulation and chromatin remodeling pathways 140–142.”
From Mechanisms of synaptic transmission dysregulation in the prefrontal cortex: pathophysiological implications (2022) · cites this paper as [142]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“To date, no genes have been identified that, when mutated, confer only ASD risk and not risk for ID or other NDDs.”
From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [12]
Experimental — accuracy not yet measuredIn the citing paper
“In fact, 72% of genes predicted to be significant by the two statistical models showed evidence of excess de novo variants in both ASD and ID/DD cohorts.”
From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [12]
In the citing paper
“Although pragmatic in terms of data availability, a significant problem with the cohort-ascertainment-based approach used in the Satterstrom et al.11 and Coe et al.12 studies is the potential bias introduced by the unequal opportunity for each participant to receive each diagnosis (i.e., ASD and ID) due to the lack of uniform phenotyping across studies.”
From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [12]
In the citing paper
“Coe et al.12 also compared the distribution of likely gene-disruptive mutations between ASD- and ID/DD-ascertained cohorts but did not find evidence of ASD specificity for any of the 253 genes they identified as candidate NDD genes based on evidence of excess of de novo mutations through the use of two statistical models.”
From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [12]
In the citing paper
“For example, standardized ASD diagnostic measures were frequently utilized in the ASD cohorts but not in the ID/DD cohorts.11,12”
From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [12]
In the citing paper
“Because of this bias, the phenotypic overlap between the groups is unclear; the prevalence of ASD in several of the ID/DD-ascertained cohorts is not quantified,13, 14, 15,18,19 and the prevalence of ID in the ASD-ascertained cohorts is known only for a minority subset of participants.11,12”
From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [12]
In the citing paper
“In fact, the ID/DD cohorts evaluated in these two studies overlapped almost completely; each study used samples from five previously published studies, and four of the five were the same studies, accounting for 99% of the samples.11, 12, 13, 14, 15, 16”
From Insufficient Evidence for “Autism-Specific” Genes (2020) · cites this paper as [12]
In the citing paper
“Our study is approximately three times larger than a recent meta-analysis of DNMs from a collection of individuals with autism spectrum disorder, intellectual disability, and/or a developmental disorder28.”
From Evidence for 28 genetic disorders discovered by combining healthcare and research data (2020) · cites this paper as [28]
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Integration of single cell gene expression data in Bayesian association analysis of rare variantsPreprint
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acorn: an R package for de novo variant analysisPreprint
Turner, T. N. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.11.536422
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Additional file 3 of Acorn: an R package for de novo variant analysis
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Additional file 1 of Acorn: an R package for de novo variant analysis
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Metadata
- Authors
- Coe, B. P., Stessman, H. A. F., Sulovari, A., Geisheker, M. R., Bakken, T. E., Lake, A. M., Dougherty, J. D., Lein, E. S., Hormozdiari, F., Bernier, R. A., & Eichler, E. E.
- Affiliations
- University of Washington (US)
- Creighton University (US)
- Allen Institute for Brain Science (US)
- Washington University in St. Louis (US)
- University of California, Davis (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Eichler, Evan E.
- ORCID
- Venue
- Nature Genetics
- Published
- 2018-12-17
- Volume
- 51
- Issue
- 1
- Pages
- 106-116
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC6309590
- OpenAlex
- W2903850738
- Cited by
- 330
- References
- 108
- Citations by year
- 2026: 19 · 2025: 34 · 2024: 43 · 2023: 36 · 2022: 45 · 2021: 78 · 2020: 50 · 2019: 19 · 2018: 3
- FWCI
- 24.07
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Foundation for the National Institutes of Health
- Howard Hughes Medical Institute
- Brain and Behavior Research Foundation
- Brain Research Foundation
- National Alliance for Research on Schizophrenia and Depression
- Simons Foundation Autism Research Initiative
- Nature
- National Institute of Mental Health (R01MH107515, R01MH101221)
- National Institute of General Medical Sciences (T32GM007266)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (U54HD087011)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- de novo mutations, copy number variation, developmental delay, autism spectrum disorder, missense mutations, genomic disorders, KIF1A, ERK1, 16p11.2 duplication, CHD4, gene regulatory networks
- MeSH terms
- Animals, Autistic Disorder, Developmental Disabilities, Chromosome Aberrations, Humans, Intellectual Disability, Mutation, Phenotype, Polymorphism, Single Nucleotide, Intracellular Signaling Peptides and Proteins, Mice, Mi-2 Nucleosome Remodeling and Deacetylase Complex, DNA Copy Number Variations, Exome, Neurodevelopmental Disorders
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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