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Cited by 615Genomics and Rare DiseasesGenetics and Neurodevelopmental DisordersGenomic variations and chromosomal abnormalities

Evidence for 28 genetic disorders discovered by combining healthcare and research data

Open access
Kaplanis, Joanna, Samocha, Kaitlin E., Wiel, Laurens, Zhang, Zhancheng, Arvai, Kevin J., Eberhardt, Ruth Y., Gallone, Giuseppe, Lelieveld, Stefan H. +274 more·2020·Nature
DOI 10.1038/s41586-020-2832-5PMC PMC7116826
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Abstract

De novo mutations in protein-coding genes are a well-established cause of developmental disorders1. However, genes known to be associated with developmental disorders account for only a minority of the observed excess of such de novo mutations1,2. Here, to identify previously undescribed genes associated with developmental disorders, we integrate healthcare and research exome-sequence data from 31,058 parent–offspring trios of individuals with developmental disorders, and develop a simulation-based statistical test to identify gene-specific enrichment of de novo mutations. We identified 285 genes that were significantly associated with developmental disorders, including 28 that had not previously been robustly associated with developmental disorders. Although we detected more genes associated with developmental disorders, much of the excess of de novo mutations in protein-coding genes remains unaccounted for. Modelling suggests that more than 1,000 genes associated with developmental disorders have not yet been described, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of genes associated with developmental disorders. By integrating healthcare and exome-sequencing data from parent–offspring trios of patients with developmental disorders, 28 genes that had not previously been associated with developmental disorders were identified.

Integrity signals

Registry

Crossref · 10.1038/s41586-020-2832-5

Cites

39 of 39 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 41 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    25.0% of the cohort has a nonsynonymous de novo mutation in a consensus or significant developmental-disorder-associated gene.

    “Taken together, 25.0% of our cohort has a nonsynonymous DNM in one of the consensus or significant DD-associated genes (Fig. 1d).”
    Quote in the paperNot a substantial claim
  • Findingown data

    11 of the 33 putative novel genes had a significant excess of synonymous variants in gnomAD.

    “We identified 11/33 genes with a significant excess of synonymous variants.”
    Quote in the paperSubstantial claim
  • Findingown data

    Patients with de novo mutations in the same novel gene were less phenotypically similar to each other than patients with mutations in a consensus gene (p = 2.3 × 10-11).

    “patients with DNMs in the same novel DD-associated gene were less phenotypically similar to each other, on average, than patients with DNMs in a consensus gene (p = 2.3 × 10-11, Wilcoxon rank-sum test; Fig. 2a; Supplementary Figure 9).”
    Quote in the paperSubstantial claim
  • Findingown data

    314 patients, 1.0% of the cohort, had nonsynonymous de novo mutations in the 28 novel genes.

    “There were 314 patients with nonsynonymous DNMs in these 28 genes (1.0% of our cohort); all these DNMs were inspected in IGV10 and, of 198 for which experimental validation was attempted, all were confirmed as DNMs.”
    • Also stated in: § Discussion · plain
      “These 28 novel genes account for 1.0% of our cohort, and their inclusion in diagnostic workflows will catalyse increased diagnosis of similar patients globally.”
    Quote in the paperSubstantial claim
  • Findingcitation

    Six of the 28 novel developmental-disorder-associated genes are corroborated by OMIM entries or publications, including TFE3.

    “Six of the 28 novel DD-associated genes are corroborated by OMIM entries or publications, including TFE3 11,12 which was described in two recent publications.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [11] Villegas, F. et al. Lysosomal signaling licenses embryonic stem cell differentiation via inactivation of Tfe3. Cell Stem Cell 24, 257–270 (2019). source

      Not checked in the free run.

    • cites [12] Diaz, J., Berger, S. & Leon, E. TFE3-associated neurodevelopmental disorder: a distinct recognizable syndrome. Am. J. Med. Genet. A 182, 584–590 (2020). source

      Not checked in the free run.

  • May combine two claims. 31
  • Classified as probably not a substantial claim. 10

  • May combine two claims.

    Findingown data

    Applying DeNovoWEST to undiagnosed patients identified 94 significant genes, of which 33 were putative novel developmental-disorder-associated genes.

    “To discover novel DD-associated genes with greater power, we applied DeNovoWEST to DNMs in patients without damaging DNMs in consensus genes (we refer to this subset as ‘undiagnosed’ patients) and identified 94 significant genes (Supplementary Fig. 7; Supplementary Table 2), of which 33 were putative ‘novel’ DD-associated genes.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The study identified 285 genes significantly associated with developmental disorders, including 28 not previously robustly associated.

    “We identified 285 significantly DD-associated genes, including 28 not previously robustly associated with DDs.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The synonymous SpliceAI enrichment corresponds to about 15 excess splice-disrupting synonymous de novo mutations, six of which are accounted for by a recurrent KAT6B synonymous mutation.

    “This enrichment corresponds to an excess of ~15 splice-disrupting synonymous DNMs in our cohort, of which six are accounted for by a recurrent synonymous DNM in KAT6B known to disrupt splicing14.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [14] Yilmaz, R. et al. A recurrent synonymous KAT6B mutation causes Say-Barber-Biesecker/Young-Simpson syndrome by inducing aberrant splicing. Am. J. Med. Genet. A 167, 3006–3010 (2015). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    After increasing the null mutation rate for the 11 genes with excess synonymous variants, five fell below significance, leaving 28 novel genes.

    “Five of these genes fell below our exome-wide significance threshold and were removed, leaving 28 novel genes, with a median of 10 nonsynonymous DNMs (Fig. 1b–c; Supplementary Table 3).”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The null mutation model used to calculate expected de novo mutation counts is adequate for genes without detected mutation-rate heterogeneity.

  • May combine two claims.

    Findingown data

    Nonsynonymous de novo mutations in more recently discovered developmental-disorder-associated genes are more likely to be missense and less likely to be protein-truncating than in consensus genes (p = 1.2 × 10-25).

    “Despite the high-level functional similarity between known and novel DD-associated genes, nonsynonymous DNMs in the more recently discovered DD-associated genes are much more likely to be missense DNMs, and less likely to be PTVs (discordant and novel; p = 1.2 × 10-25, chi-squared test).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    DeNovoWEST identified 281 significantly enriched genes in the full cohort, 18 more than the previous method.

    “We first applied DeNovoWEST to all individuals in our cohort and identified 281 significantly enriched genes, 18 more than when using our previous method1 (Supplementary Fig. 5; Fig. 1a).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [1] Deciphering Developmental Disorders Study. Prevalence and architecture of de novo mutations in developmental disorders. Nature 542, 433–438 (2017). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    All but two of these 16 de novo single nucleotide variants cause missense changes, all but two of the genes cause disease by an altered-function mechanism, and the mutations were depleted for CpGs relative to all recurrent mutations.

    “All but two of these 16 de novo SNVs cause missense changes, all but two of these genes cause disease by an altered-function mechanism, and these DNMs were depleted for CpGs relative to all recurrent mutations.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Recurrent nonsynonymous TCGA mutations were enriched 21-fold in the cohort (p < 10-50), while recurrent synonymous TCGA mutations were not significantly enriched (2.4-fold, p = 0.13).

    “we found that recurrent nonsynonymous mutations in TCGA are enriched 21-fold in our cohort (p < 10-50, Poisson test, Supplementary Fig. 11), whereas recurrent synonymous mutations in TCGA are not significantly enriched (2.4-fold, p = 0.13, Poisson test).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Clinical ascertainment, greater mutability at specific sites, and positive selection in the male germline all contribute to recurrent de novo mutations, not mutually exclusively.

    “We observed evidence that all three factors contribute, but not mutually exclusively.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    39 recurrent de novo mutations were identified in 11 known germline selection genes; 38 were missense and all were known to be activating in the germline.

    “We identified 39 recurrent DNMs in 11 of these genes, 38 of which are missense and all of which are known to be activating in the germline (see Supplement).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    64% of recurrent de novo single nucleotide variants occurred at hypermutable CpG dinucleotides, a 2.0-fold enrichment over mutations observed only once (p = 3.3 × 10-68).

    “Hypermutability underpins the observation that 64% of recurrent de novo SNVs occurred at hypermutable CpG dinucleotides24, a 2.0-fold enrichment over DNMs only observed once (p = 3.3 × 10-68, chi-square test).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [24] Duncan, B. K. & Miller, J. H. Mutagenic deamination of cytosine residues in DNA. Nature 287, 560–561 (1980). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Missense de novo mutations in protein domains were enriched 2.63-fold in consensus genes and 1.80-fold in novel genes, with no enrichment for synonymous mutations.

    “We observed a 2.63-fold enrichment (p = 2.2 × 10-68, G-test) of missense DNMs residing in protein domains among consensus genes and a 1.80-fold enrichment (p = 8.0 × 10-5, G-test) in novel DD-associated genes, but no enrichment for synonymous DNMs (Supplementary Table 6).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    65% of recurrent de novo mutations were in consensus genes, a 5.4-fold enrichment compared with mutations observed only once (p < 10-50).

    “Clinical ascertainment drives the observation that 65% of recurrent DNMs were in consensus genes, a 5.4-fold enrichment compared to DNMs only observed once (p < 10-50, proportion test).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Protein-truncating variant mutability was significantly lower in unassociated genes than in developmental-disorder-associated genes (p = 4.5 × 10-68), reducing power to detect enrichment in unassociated genes.

    “We observed that PTV mutability (estimated from a null germline mutation model) was significantly lower in unassociated genes compared to DD-associated genes (p = 4.5 × 10-68, Wilcox rank-sum test Fig. 3a), which leads to reduced statistical power to detect DNM enrichment in unassociated genes, consistent with our hypothesis that many more HI disorders await discovery.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The null mutation model used to calculate expected de novo mutation counts is adequate for genes without detected mutation-rate heterogeneity.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Developmental-disorder-associated genes are significantly more likely to be expressed in fetal brain.

    “For example, we observe that DD-associated genes are significantly more likely to be expressed in fetal brain (Supplementary Fig. 14).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The 285 developmental-disorder-associated genes significantly overlap 369 previously described cancer driver genes, with 70 genes overlapping (p = 1.7 × 10-49).

    “We observed a significant overlap between the 285 DNM-enriched DD-associated genes and a set of 369 previously described cancer driver genes19 (overlap of 70 genes; p = 1.7 × 10-49, logistic regression correcting for shet), as observed previously20,21, as well as a significant enrichment of nonsynonymous DNMs in both overlapping and non-overlapping cancer genes (Supplementary Table 9).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [19] Martincorena, I. et al. Universal patterns of selection in cancer and somatic tissues. Cell 171, 1029–1041 (2017). source

      Not checked in the free run.

  • May combine two claims.

    Findingreasoning

    Among about 19,000 non-developmental-disorder-associated genes, about 1,200 were more than three times more likely to have arisen from a 10-fold increased protein-truncating variant rate, while about 7,000 were three times more likely to have no de novo protein-truncating variant enrichment.

    “Among the ~19,000 non-DD-associated genes, ~1,200 were more than three times more likely to have arisen from a 10-fold increased PTV rate, whereas ~7,000 were three times more likely to have no de novo PTV enrichment.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    In developing DeNovoWEST, applying variant-level and gene-level weights in separate stages faced statistical challenges due to correlations between gene-level and variant-level metrics.

    “In developing DeNovoWEST, we explored applying both variant-level weights and gene-level weights in separate stages of the analysis, however, subtle but pervasive correlations between gene-level metrics (e.g. shet) and variant-level metrics (e.g. regional missense constraint, CADD) presents statistical challenges to implementation.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Extended Data Table 1 shows 16 de novo single nucleotide variants observed nine or more times, only two of which are in known germline selection genes.

    “Extended Data Table 1 shows the 16 de novo SNVs observed nine or more times in our cohort, only two of which are in known germline selection genes.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Modelling indicates that more than 1,000 novel developmental-disorder-associated genes remain to be discovered, many likely less penetrant than currently known genes.

    “Modelling suggests that over 1,000 novel DD-associated genes await discovery, many of which are likely to be less penetrant than the currently known genes.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The lower phenotypic similarity suggests that novel disorders less often produce distinctive and consistent clinical presentations, which may have made them harder to discover through phenotype-driven approaches.

    “This suggests that these novel disorders less often result in distinctive and consistent clinical presentations, which may have made these disorders harder to discover via a phenotype-driven approach.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    About 42-48% of patients with severe developmental disorder have a pathogenic de novo mutation in a protein-coding gene.

    “It has previously been estimated that ~42-48% of patients with a severe developmental disorder (DD) have a pathogenic de novo mutation (DNM) in a protein coding gene1,2.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [1] Deciphering Developmental Disorders Study. Prevalence and architecture of de novo mutations in developmental disorders. Nature 542, 433–438 (2017). source

      Not checked in the free run.

    • cites [2] Martin, H. C. et al. Quantifying the contribution of recessive coding variation to developmental disorders. Science 362, 1161–1164 (2018). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    De novo mutations in protein-coding genes are an established cause of developmental disorders.

    “De novo mutations (DNMs) in protein-coding genes are a well-established cause of developmental disorders (DD)1.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [1] Deciphering Developmental Disorders Study. Prevalence and architecture of de novo mutations in developmental disorders. Nature 542, 433–438 (2017). source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductown data

    The three cohorts had similar clinical characteristics, sex ratios, de novo mutation class enrichments, and prevalences of known disorders.

    “The three cohorts have similar clinical characteristics, male/female ratios, enrichments of DNMs by mutational class, and prevalences of known disorders (Supplementary Fig. 2).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    SHOC2 and PPP1CB encode interacting proteins that regulate the RAS-MAPK pathway, and pathogenic variants in these genes are associated with a Noonan-like syndrome.

    “Two of these genes with highly recurrent de novo SNVs, SHOC2 and PPP1CB, encode interacting proteins that regulate the RAS-MAPK pathway, and pathogenic variants in these genes are associated with a Noonan-like syndrome27.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [27] Young, L. C. et al. SHOC2–MRAS–PP1 complex positively regulates RAF activity and contributes to Noonan syndrome pathogenesis. Proc. Natl Acad. Sci. USA 115, E10576–E10585 (2018). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationnone given

    The FDR of individual genes depends on the significance of other genes tested, so FDR is not appropriate for assessing individual gene significance but rather for defining gene-sets.

    “The FDR of individual genes depends on the significance of other genes being tested, so are not appropriate for assessing the significance of individual genes, but rather for defining gene-sets.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    The residual protein-truncating burden is greatest in genes intolerant of protein-truncating variants in the general population, suggesting that more haploinsufficient disorders await discovery.

    “This residual burden of protein-truncating DNMs is greatest in genes that are intolerant of PTVs in the general population (Supplementary Fig. 12) suggesting that more haploinsufficient (HI) disorders await discovery.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    A significant negative correlation exists between protein-truncating variant enrichment in the cohort and the ratio of protein-truncating to synonymous variants in gnomAD, suggesting that incomplete penetrance lowers de novo protein-truncating enrichment.

    “We observed a significant negative correlation (p = 0.031, weighted linear regression) between PTV enrichment in our cohort and the ratio of PTV to synonymous variants in gnomAD6, suggesting that incomplete penetrance does lower de novo PTV enrichment in our cohort (Fig. 3c).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [6] Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationreasoning

    These candidate germline selection mutations should result in higher than expected disease incidence that increases dramatically with increased paternal age.

    “which should result in a higher than expected disease incidence that increases dramatically with increased paternal age.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    De novo mutations under germline selection should be more likely to be activating missense mutations and less enriched for CpG dinucleotides.

    “Based on the observations above, DNMs under germline selection should be more likely to be activating missense mutations, and should be less enriched for CpG dinucleotides.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The remaining protein-truncating variant burden is most likely spread across about 1,000 genes with about 10-fold protein-truncating variant enrichment.

    “We found that the remaining PTV burden is most likely spread across ~1,000 genes with ~10-fold PTV enrichment (Extended Data Fig 1b).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationown data

    The authors' analyses suggest that variant-level weights could be improved by incorporating other variant prioritisation metrics.

    “Our analyses also suggest that variant-level weights could be further improved by incorporating other variant prioritisation metrics, such as upweighting variants predicted to impact splicing, variants in particular protein domains, or variants that are somatic driver mutations during tumorigenesis.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationnone given

    Including more functional information may increase power to detect some novel disorders while decreasing power for disorders with different pathophysiology from known disorders.

    “As a cautionary note, including more functional information may increase power to detect some novel disorders while decreasing power for disorders with pathophysiology different from known disorders.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    This inferred fold enrichment is three times lower than in known haploinsufficient developmental-disorder-associated genes, suggesting that incomplete penetrance and/or pre/perinatal death is more prevalent among undiscovered haploinsufficient genes.

    “This fold enrichment is three times lower than in known HI DD-associated genes, suggesting that incomplete penetrance and/or pre/perinatal death is more prevalent among undiscovered HI genes.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Novel metrics based on gene co-regulation networks can predict whether genes function within a disease-relevant pathway.

    “Furthermore, novel metrics based on gene co-regulation networks can predict whether genes function within a disease-relevant pathway33.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [33] Deelen, P. et al. Improving the diagnostic yield of exome-sequencing by predicting gene–phenotype associations using large-scale gene expression analysis. Nat. Commun. 10, 2837 (2019). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    In two previous studies using the same significance threshold, 26 novel developmental-disorder-associated genes were identified, and all are now regarded as diagnostic and have entered routine clinical practice.

    “In two previous studies using the same significance threshold, we identified 26 novel DD-associated genes1,31. All 26 are now regarded as being diagnostic, and have entered routine clinical diagnostic practice.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [1] Deciphering Developmental Disorders Study. Prevalence and architecture of de novo mutations in developmental disorders. Nature 542, 433–438 (2017). source

      Not checked in the free run.

    • cites [31] Deciphering Developmental Disorders Study. Large-scale discovery of novel genetic causes of developmental disorders. Nature 519, 223–228 (2015). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Both incomplete penetrance and pre/perinatal death reduce power to detect novel developmental disorders postnatally.

    “We have shown that both incomplete penetrance and pre/perinatal death reduce our power to detect novel DDs postnatally, and hypothesise that one or both of these factors are operating more strongly among undiscovered DD-associated genes.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    These ascertainment biases will not affect the representation of novel developmental disorders in the cohort.

    “These ascertainment biases will not impact the representation of novel DDs in our cohort.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S1 (asserted). May combine two claims.

    Interpretationreasoning

    One or both of incomplete penetrance and pre/perinatal death are hypothesised to operate more strongly among undiscovered developmental-disorder-associated genes.

    “and hypothesise that one or both of these factors are operating more strongly among undiscovered DD-associated genes.”
    Quote in the paperNot a substantial claim
39 of 39

  • The paper relies on this without support.

    The null mutation model used to calculate expected de novo mutation counts is adequate for genes without detected mutation-rate heterogeneity.

    “To ensure robustness to potential mutation rate variation between genes, we determined whether any of the putative novel DD-associated genes had significantly more synonymous variants in the Genome Aggregation Database6 (gnomAD) of population variation than expected under our null mutation model (Supplementary Note).”

  • The paper relies on this without support.

    Synonymous de novo mutations are generally not pathogenic and can serve as a negative control for gene-specific enrichment.

    “Applying DeNovoWEST to synonymous DNMs, as a negative control analysis, identified no significantly enriched genes (Supplementary Fig. 6).”
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Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The recurrent WASF1 variants p.Leu455Pro and p.Leu535Pro were detected in a patient with autism and another patient with developmental delay, respectively.

    “The recurrent variants p.Leu455Pro and p.Leu535Pro were detected in a patient with autism and another patient with DD, respectively103,104.”

    From The WAVE complex in developmental and adulthood brain disorders (2025) · cites this paper as [103]

    The Introduction’s discussion of recurrent mutations and the Extended Data table describe other variants, but neither identifies the claimed WASF1 variants or links them to the two patients. Searches for WASF1, p.Leu455Pro, and p.Leu535Pro found no passage in our copy that verifies the patient-specific claim. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

  • Two missense WASF2 variants, c.113G > A (p.Arg38Gln) and c.494T > C (p.Leu165Pro), were identified in patients with autism and neurodevelopmental disorders.

    “Two missense WASF2 variants, c.113G > A (p.Arg38Gln) and c.494T > C (p.Leu165Pro), were identified in patients with autism and NDDs103–105, but the functional alterations associated with brain disorders remain to be studied (Table 2g).”

    From The WAVE complex in developmental and adulthood brain disorders (2025) · cites this paper as [103]

    The Introduction’s discussion of missense variants in developmental disorders and the Extended Data table do not identify WASF2 or either specified variant. Searches of our copy for WASF2, Arg38Gln, Leu165Pro, and the variant notation returned no passage linking them to patients with autism or neurodevelopmental disorders. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

  • A nonsense WASF3 variant, p.Glu88Ter, was identified in a patient with neurodevelopmental disorders.

    “A nonsense WASF3 variant, p.Glu88Ter, was identified in a patient with NDDs103,104,106 (Table 2h).”

    From The WAVE complex in developmental and adulthood brain disorders (2025) · cites this paper as [103]

    The Introduction discusses de novo variants in patients with developmental disorders, but the passages from our copy do not identify a WASF3 variant or a patient carrying p.Glu88Ter. Searches for “WASF3,” “Glu88Ter,” and the combined phrase found no passage addressing that specific claim. (LLM, conf=0.73)

    Experimental — accuracy not yet measured

  • Genes in which rare variants increase risk of autism spectrum disorder and developmental disorder are also enriched for schizophrenia common variant associations.

    “We tested for and found that genes in which rare variants increase risk of ASD and DD32,33 are also enriched for schizophrenia common variant associations.”

    From Mapping genomic loci implicates genes and synaptic biology in schizophrenia (2022) · cites this paper as [33]

  • Rare variant risk overlaps between schizophrenia, ASD, epilepsy, and severe neurodevelopmental disorders, although in some shared genes different mutation types are implicated.

    “We observe an overlap of rare variant risk between schizophrenia, autism spectrum disorders (ASD)1, epilepsy and severe neurodevelopmental disorders (DD/ID)2, though in some shared genes different mutation types are implicated.”

    From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [2]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Table caption excludes variants listed in the table

    Minor

    The caption says the table contains variants with more than nine recurrences, but several listed variants have exactly nine. The main text describes the threshold as nine or more.

  • Reported CpG percentage conflicts with the recurrence counts

    Minor

    The CpG comparison reports 6 of 39 and 425 of 692 recurrent mutations at CpGs. Those groups total 431 CpG mutations among 731 mutations; even if all five remaining recurrent SNVs were at CpGs, the share would be about 59%, not the stated 64%.

2 of 2

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Authors
Kaplanis, J., Samocha, K. E., Wiel, L., Zhang, Z., Arvai, K. J., Eberhardt, R. Y., Gallone, G., Lelieveld, S. H., Martin, H. C., McRae, J. F., Short, P. J., Torene, R. I., de Boer, E., Danecek, P., Gardner, E. J., Huang, N., Lord, J., Martincorena, I., Pfundt, R., Reijnders, M. R. F., Yeung, A., Yntema, H. G., Study, D. D. D., Borras, S., Clark, C., Dean, J., Miedzybrodzka, Z., Ross, A., Tennant, S., Dabir, T., Donnelly, D., Humphreys, M., Magee, A., McConnell, V., McKee, S., McNerlan, S., Morrison, P. J., Rea, G., Stewart, F., Cole, T., Cooper, N., Cooper-Charles, L., Cox, H., Islam, L., Jarvis, J., Keelagher, R., Lim, D., McMullan, D., Morton, J., Naik, S., O’Driscoll, M., Ong, K.-R., Osio, D., Ragge, N., Turton, S., Vogt, J., Williams, D., Bodek, S., Donaldson, A., Hills, A., Low, K., Newbury-Ecob, R., Norman, A. M., Roberts, E., Scurr, I., Smithson, S., Tooley, M., Abbs, S., Armstrong, R., Dunn, C., Holden, S., Park, S.-M., Paterson, J., Raymond, L., Reid, E., Sandford, R., Simonic, I., Tischkowitz, M., Woods, G., Bradley, L., Comerford, J., Green, A., Lynch, S., McQuaid, S., Mullaney, B., Berg, J., Goudie, D., Mavrak, E., McLean, J., McWilliam, C., Reavey, E., Azam, T., Cleary, E., Jackson, A., Lam, W., Lampe, A., Moore, D., Porteous, M., Baple, E., Baptista, J., Brewer, C., Castle, B., Kivuva, E., Owens, M., Rankin, J., Shaw-Smith, C., Turner, C., Turnpenny, P., Tysoe, C., Bradley, T., Davidson, R., Gardiner, C., Joss, S., Kinning, E., Longman, C., McGowan, R., Murday, V., Pilz, D., Tobias, E., Whiteford, M., Williams, N., Barnicoat, A., Clement, E., Faravelli, F., Hurst, J., Jenkins, L., Jones, W., Kumar, V. K. A., Lees, M., Loughlin, S., Male, A., Morrogh, D., Rosser, E., Scott, R., Wilson, L., Beleza, A., Deshpande, C., Flinter, F., Holder, M., Irving, M., Izatt, L., Josifova, D., Mohammed, S., Molenda, A., Robert, L., Roworth, W., Ruddy, D., Ryten, M., Yau, S., Bennett, C., Blyth, M., Campbell, J., Coates, A., Dobbie, A., Hewitt, S., Hobson, E., Jackson, E., Jewell, R., Kraus, A., Prescott, K., Sheridan, E., Thomson, J., Bradshaw, K., Dixit, A., Eason, J., Haines, R., Harrison, R., Mutch, S., Sarkar, A., Searle, C., Shannon, N., Sharif, A., Suri, M., Vasudevan, P., Canham, N., Ellis, I., Greenhalgh, L., Howard, E., Stinton, V., Swale, A., Weber, A., Banka, S., Breen, C., Briggs, T., Burkitt-Wright, E., Chandler, K., Clayton-Smith, J., Donnai, D., Douzgou, S., Gaunt, L., Jones, E., Kerr, B., Langley, C., Metcalfe, K., Smith, A., Wright, R., Bourn, D., Burn, J., Fisher, R., Hellens, S., Henderson, A., Montgomery, T., Splitt, M., Straub, V., Wright, M., Zwolinski, S., Allen, Z., Bernhard, B., Brady, A., Brooks, C., Busby, L., Clowes, V., Ghali, N., Holder, S., Ibitoye, R., Wakeling, E., Blair, E., Carmichael, J., Cilliers, D., Clasper, S., Gibbons, R., Kini, U., Lester, T., Nemeth, A., Poulton, J., Price, S., Shears, D., Stewart, H., Wilkie, A., Albaba, S., Baker, D., Balasubramanian, M., Johnson, D., Parker, M., Quarrell, O., Stewart, A., Willoughby, J., Crosby, C., Elmslie, F., Homfray, T., Jin, H., Lahiri, N., Mansour, S., Marks, K., McEntagart, M., Saggar, A., Tatton-Brown, K., Butler, R., Clarke, A., Corrin, S., Fry, A., Kamath, A., McCann, E., Mugalaasi, H., Pottinger, C., Procter, A., Sampson, J., Sansbury, F., Varghese, V., Baralle, D., Callaway, A., Cassidy, E. J., Daniels, S., Douglas, A., Foulds, N., Hunt, D., Kharbanda, M., Lachlan, K., Mercer, C., Side, L., Temple, I. K., Wellesley, D., Vissers, L. E. L. M., Juusola, J., Wright, C. F., Brunner, H. G., Firth, H. V., FitzPatrick, D. R., Barrett, J. C., Hurles, M. E., Gilissen, C., & Retterer, K.
Affiliations
  • Wellcome Sanger Institute (GB)
  • Radboud University Medical Center (NL)
  • Radboud University Nijmegen (NL)
  • Maastricht University Medical Centre (NL)
  • Victorian Clinical Genetics Services (AU)
  • National Health Service (GB)
  • Belfast Health and Social Care Trust (GB)
  • Birmingham Women's Hospital (GB)
  • University Hospitals Bristol NHS Foundation Trust (GB)
  • Cambridge University Hospitals NHS Foundation Trust (GB)
  • Children's Health Ireland at Crumlin (IE)
  • NHS Tayside (GB)
  • Western General Hospital (GB)
  • Royal Devon & Exeter NHS Foundation Trust (GB)
  • NHS Greater Glasgow and Clyde (GB)
  • Great Ormond Street Hospital (GB)
  • Guy's Hospital (GB)
  • Chapel Allerton Hospital (GB)
  • Nottingham University Hospitals NHS Trust (GB)
  • Leicester Royal Infirmary (GB)
  • Liverpool Womens NHS Foundation Trust (GB)
  • St Mary's Hospital (GB)
  • Newcastle upon Tyne Hospitals NHS Foundation Trust (GB)
  • London North West Healthcare NHS Trust (GB)
  • John Radcliffe Hospital (GB)
  • Sheffield Children's NHS Foundation Trust (GB)
  • St George's, University of London (GB)
  • Glan Clwyd Hospital (GB)
  • Salisbury District Hospital (GB)
  • University of Exeter (GB)
Corresponding author
Hurles, Matthew E.
ORCID
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2020-10-14
Volume
586
Issue
7831
Pages
757-762
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
DOI
10.1038/s41586-020-2832-5
PMC
PMC7116826
OpenAlex
W3093292403
Semantic Scholar
e174e0b283898598ca31068295c59c2db137a976
Cited by
615
References
39
Citations by year
2026: 85 · 2025: 122 · 2024: 116 · 2023: 92 · 2022: 125 · 2021: 67 · 2020: 7
FWCI
43.17
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • Discovery Research Portal (University of Dundee) (publishedVersion)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • ePrints Soton (University of Southampton) (acceptedVersion)
  • Open Research Exeter (University of Exeter) (acceptedVersion)
  • Research Publications (Maastricht University) (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (submittedVersion, cc-by-sa)
  • UCL Discovery (University College London) (submittedVersion)
  • Figshare (submittedVersion)
  • Research Explorer (The University of Manchester) (submittedVersion, other-oa)
  • Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion, other-oa)
  • Research Publications (Maastricht University) (submittedVersion)
  • Newcastle University ePrints (Newcastle Univesity)
Funders
  • Wellcome Trust
  • Bowel Cancer UK (18PG0019)
  • Cancer Research UK (21777)
  • National Institute for Health and Care Research (NF-SI-0515-10035, NF-SI-0510-10282, HICF-1009-003)
  • European Commission (HICF-1009-003, HORIZON2020, 779257)
  • Nederlandse Organisatie voor Wetenschappelijk Onderzoek (917-17-353)
  • Radboud Universitair Medisch Centrum
  • Medical Research Council (MC_UU_00007/3)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • 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
Keywords
de novo mutations, developmental disorders, genetic disorders, parent-offspring trios, exome sequencing, health data integration, penetrance
MeSH terms
Data Analysis, Developmental Disabilities, Delivery of Health Care, DNA Mutational Analysis, Europe, Female, Humans, Male, Cohort Studies, Germ-Line Mutation, Sample Size, Penetrance, Mutation, Missense, Genetic Diseases, Inborn, Databases, Genetic, DNA Copy Number Variations, Haploinsufficiency, Perinatal Death, Datasets as Topic

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