Low load for disruptive mutations in autism genes and their biased transmission
Open accessAbstract
Significance: Gene targets of de novo mutation in autistic children have a lighter load of rare disruptive variation than typical human genes. This finding suggests such mutations are under negative selection and autism genes are highly vulnerable to mutation. Disruptive variants in these genes have biased transmission: They are more frequently transmitted to affected children, and more often from mothers than from fathers. Targets of mutation in lower intelligence quotient (IQ) affected children have a lower load of disruptive mutations than targets of mutation in higher IQ affected children. Biased transmission is seen more frequently to affected children of lower IQ. These observations are consistent with a correlation between severity of mutations and phenotype, and based on them, we list candidate autism genes ordered by likelihood.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 26 cited sources checked · 0 supported · 0 flagged
- Findingown data
De novo target gene sets from lower-IQ affected children have significantly lower LGD ratios than sibling targets (P = 0.0011).
“Judging by this measure, DN target gene sets from affected children with lower IQ have significantly lower LGD ratios than DN targets from siblings (P = 0.0011).”
Quote in the paperSubstantial claim - Findingown data
After posterior probabilities including transmission adjustment, scores of target genes in various classes are bimodal.
“After posterior probabilities are calculated, including adjustment for transmission, the scores of target genes in the various classes become bimodal (Fig. 2, Right).”
- Also stated in: § Discussion · boosted
“Moreover, we show a bimodal distribution in mutational load in the proportion predicted by theory for candidate autism genes and bystander target genes.”
Quote in the paperSubstantial claim- The authors state this as an assumption: Autism vulnerable genes and intolerant (protected) genes are treated as the same set.
- The authors state this as an assumption: DN and rare parental data are independent.
- The authors state this as an assumption: A protected gene has only 10% of typical share of UR LGD mutations.
- Also stated in: § Discussion · boosted
- Findingown data
Ultrarare missense accumulation is proportional to ultrarare synonymous accumulation.
“By contrast, UR missense accumulation proportionately follows UR synonymous accumulation (Fig. 1B).”
Quote in the paperSubstantial claim - Findingnone given
No ascertainment differential is observed for non-disruptive mutations such as synonymous variants.
“An ascertainment differential is not seen for mutations that are not disruptive, such as synonymous variants.”
Quote in the paperSubstantial claim - Findingown data
Ultrarare LGD variant load is not linear with ultrarare synonymous variant load.
“The load of UR LGD variants is not linear with the load of UR synonymous variants.”
Quote in the paperSubstantial claim
- Findingreasoning
About one in five people carries one de novo mutation that lowers fecundity.
“We estimate that one in five individuals is burdened with one DN mutation that reduces fecundity.”
Quote in the paperNot a substantial claim- Rests on an assumption: The majority of LGD mutations, and the subset of nonsense mutations, are harmful.
- Findingown data
The transmission signal is significant only for longer genes.
“We separately calculate the P value of the signal from both sources, and observe great significance only from the longer genes.”
Quote in the paperSubstantial claim - Findingown data§ Low load for disruptive mutations in autism genes and their biased transmission
Autism genes carry a lower burden of disruptive mutations 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.”
- Also stated in: § autism spectrum disorder | gene vulnerability | disruptive mutations | biased transmission | autism genes · plain
“Gene targets of de novo mutation in autistic children have a lighter load of rare disruptive variation than typical human genes.”
Quote in the paperSubstantial claim - Also stated in: § autism spectrum disorder | gene vulnerability | disruptive mutations | biased transmission | autism genes · plain
- Findingcitation
There is a strong signal of biased transmission in functional categories of genes previously linked to autism spectrum disorder.
“We also find a strong signal for biased transmission in the functional categories of genes previously associated with ASD (10).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] source
Not checked in the free run.
- Findingown data
The lower LGD ratio of de novo targets in higher-IQ males is not statistically significant (P = 0.1066).
“On the other hand, the lower LGD ratio of the DN targets of higher IQ males does not reach standard statistical significance (P = 0.1066).”
Quote in the paperNot a substantial claim - Findingown data
Unaffected-sibling DN mutation targets show a higher LGD variant burden.
“In strong contrast, the targets of DN mutation in unaffected siblings have a greater accumulation of LGD variants (Table 4).”
Quote in the paperSubstantial claim - Findingown data
Most recurrent DN LGD target genes, including several long genes, show no accumulation of LGD mutations as anticipated.
“The majority of these genes, such as ANKRD11, ASH1L, CHD8, GRIN2B, MED13L, and SCN2A, are long but have not accumulated LGD mutations despite expectations.”
Quote in the paperSubstantial claim - Findingown data
Five of twelve genes are promoted to causal because their LGD variants are transmitted to affected child.
“On the other hand, five of these 12 genes (KMT2C, KATNAL2, ADNP, DIP2A, and PTEN) are “promoted” to be causal, because we observe that LGD variants found in these genes are also transmitted to the affected child.”
Quote in the paperSubstantial claim - Findingown data
Eleven DN LGD targets are demoted because they have LGD variants.
“Eleven DN LGD targets are “demoted” by virtue of having LGD variants, including RIMS1 and KDM5B.”
Quote in the paperSubstantial claim - Findingreasoning
LGD accumulation in a population roughly follows the square root of synonymous accumulation.
“Indeed, LGD accumulation in a population follows roughly the square root of synonymous accumulation as revealed by the similarity to the LOWESS fit.”
Quote in the paperSubstantial claim - Findingown data
239 autism candidates have posterior probability above 0.8.
“The posterior probabilities for all genes can be found in Dataset S1, and the 239 autism candidates with a posterior probability above 0.8 are summarized in Dataset S2.”
- Also stated in: § Discussion · plain
“With a likelihood model based on tolerance for disruption, we obtain a clear bimodal distribution of likelihood among all DN missense and LGD targets in affected individuals (Fig. 2), and we list the 239 most likely causal genes (Dataset S2).”
Quote in the paperSubstantial claim- The authors state this as an assumption: Autism vulnerable genes and intolerant (protected) genes are treated as the same set.
- The authors state this as an assumption: DN and rare parental data are independent.
- The authors state this as an assumption: A protected gene has only 10% of typical share of UR LGD mutations.
- Also stated in: § Discussion · plain
- Findingown data
Genes with exactly one LGD variant show significant transmission bias to affected children (809 vs. 708; P = 0.0101).
“On the other hand, we see clear significance in transmission (Table 3) for the set of genes with only a single LGD variant (809 vs. 708; P = 0.0101).”
Quote in the paperSubstantial claim - Findingown data
Every de novo target gene set from affected children has a lower LGD ratio than de novo target gene sets from unaffected siblings.
“All DN target gene sets derived from affected children have lower LGD ratios than the DN target gene sets derived from unaffected siblings.”
Quote in the paperSubstantial claim - Findingown data
Among all de novo variants, the ratio of LGD to synonymous mutations is higher in children than in parents.
“Relative to the proportion of LGD variants to synonymous variants in parents, the proportion of LGD mutations to synonymous mutations among all DN variants is increased in all children.”
Quote in the paperSubstantial claim - Findingown data
All ultrarare LGD variants show a nonsignificant bias toward transmission to affected rather than unaffected children (4,921 vs. 4,813; P = 0.1398).
“Although we see bias for transmission of all UR LGD variants to affected rather than unaffected children (4,921 vs. 4,813 variants, respectively), it is not significant (P = 0.1398).”
Quote in the paperSubstantial claim - Findingown data
Disruptive mutations in rarely disrupted genes are preferentially transmitted from mothers to children with severe autism spectrum disorder.
“Using the LGD score, we obtain strong statistical evidence for low disruptive loads in autism genes, especially in the autism genes affecting children of lower IQ, and for preferential transmission of disruptive mutations in rarely disrupted genes from mothers to children with severe ASD.”
Quote in the paperSubstantial claim - Findingown data
The SSC and EVS databases have comparable variation parameters.
“We examined the parameters of variation between the two databases, and found them comparable (Table 1).”
Quote in the paperSubstantial claim - Findingreasoning
32 (>80%) of original 39 recurrent gene targets remain excellent causal candidates.
“Overall, 32 (>80%) of the original 39 recurrent gene targets remain as excellent causal candidates.”
Quote in the paperSubstantial claim - Findingown data
Combining prior with likelihood of observed UR LGD load under two models yields global ranking of DN target genes across classes.
“Combining the prior with the likelihood of the observed load of UR LGD mutations under the two models provides a global ranking of DN target genes for the classes of recurrent LGD targets, recurrent missense targets, and LGD targets in lower and higher IQ affected individuals (Fig. 2, x axis).”
Quote in the paperSubstantial claim- The authors state this as an assumption: Autism vulnerable genes and intolerant (protected) genes are treated as the same set.
- The authors state this as an assumption: DN and rare parental data are independent.
- The authors state this as an assumption: A protected gene has only 10% of typical share of UR LGD mutations.
- Findingcitation
Substantial signal from transmission seen in embryonic genes.
“First, a substantial signal from transmission is seen in the set of “embryonic” genes (10).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] source
Not checked in the free run.
- Findingnone given
Lower-IQ affected children carry transmitted and DN events in highly vulnerable genes.
“We know that transmitted and DN events in highly vulnerable genes occur in lower IQ affected children.”
Quote in the paperSubstantial claim - Findingown data
Embryonic genes' involvement in transmission greater than predicted.
“Although our previous work had shown that embryonic genes were enriched as DN targets (10), their involvement in transmission is greater than we would have predicted.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] source
Not checked in the free run.
- Findingreasoning
An estimated 36% of genes with at least one DN LGD mutation are causal targets.
“Taking this fact into account, we estimate that 36% of the genes hit by one or more DN LGD mutations are causal target genes.”
Quote in the paperSubstantial claim- The authors state this as an assumption: Noncontributory DN LGD mutations in affected children occur at same rate as DN LGD mutations in unaffected individuals, and their target genes have similar UR LGD loads.
- The authors state this as an assumption: Vulnerability of noncausal genes is 1, i.e., they have same load as targets of DN LGD mutation in unaffected siblings.
- Findingnone given
Signal mainly seen in severely affected children.
“Moreover, the signal is mainly seen in severely affected children.”
Quote in the paperNot a substantial claim - Findingown data
Our tolerance method and RVIS are strongly but not perfectly correlated.
“Our method of determining tolerance, based on UR LGD mutations and normalized by UR synonymous mutations, and the RVIS method are strongly but far from perfectly correlated (Fig. S3).”
Quote in the paperNot a substantial claim - Findingown data
Except targets of DN mutation in unaffected children, all gene classes have significantly decreased UR LGD load.
“With the exception of the targets of DN mutation in unaffected children, all classes have a significantly decreased UR LGD mutational load.”
Quote in the paperSubstantial claim - Findingown data
Disruptive mutations in vulnerable genes are transmitted more often to lower-IQ affected children.
“Moreover, most of the biased transmission of disruptive mutation in vulnerable genes occurs in children of lower IQ.”
Quote in the paperSubstantial claim - Findingown data
Biased transmission of UR disruptive variants in very low load genes to affected sibling only vs typical sibling only (P=0.01).
“Indeed, we observe that there is biased transmission of UR disruptive variants within genes with very low load to the affected sibling only, compared with variants transmitted to the typical sibling only (P = 0.01, by permuting labels).”
Quote in the paperSubstantial claim - Findingcitation
Increase in DN LGD rate in affected vs unaffected used to estimate 0.42 of 391 DN variants contribute to affected status.
“The increase in the rate of DN LGD mutation in affected children compared with the rate in their unaffected siblings was used to estimate the proportion (0.42) of 391 observed DN variants in the affected children that contribute to affected status (10).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] source
Not checked in the free run.
- Findingnone given
Targets of DN mutation in higher IQ show higher mutational load than lower IQ.
“Second, the targets of DN mutation in higher IQ affected individuals show higher mutational load than the targets in affected individuals with lower IQ.”
Quote in the paperSubstantial claim - Findingown data
Affected-child DN LGD mutation targets show lower UR LGD burden than sibling DN LGD targets.
“We observe that the targets of all DN LGD mutations in affected children have a decreased load of UR LGD mutations compared with the targets of DN LGD mutations in siblings.”
Quote in the paperSubstantial claim- The authors state this as an assumption: Noncontributory DN LGD mutations in affected children occur at same rate as DN LGD mutations in unaffected individuals, and their target genes have similar UR LGD loads.
- The authors state this as an assumption: Vulnerability of noncausal genes is 1, i.e., they have same load as targets of DN LGD mutation in unaffected siblings.
- Findingown data
Most of the transmission bias for UR LGD variants in vulnerable genes traces to the maternal side.
“In support of these reports, we find that the majority of the signal of biased transmission of UR LGD variants in vulnerable genes comes from the maternal line.”
Quote in the paperSubstantial claim - Study design and conductcitation
Target genes in affected and unaffected individuals have closely matched length distributions.
“Moreover, the target genes in affected and unaffected individuals have length distributions that are closely matched (10).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] source
Not checked in the free run.
- Interpretationown data
The IQ decomposition agrees with greater gene vulnerability in de novo targets of lower-IQ affected individuals than in higher-IQ targets.
“This result is in keeping with finding more gene vulnerability in the DN targets of the lower IQ affected individuals than in the targets from the higher IQ affected individuals.”
Quote in the paperSubstantial claim - Premisecitation
Damaging de novo mutation accounts for at least 30% of autism spectrum disorder in simplex families.
“Damaging DN mutation contributes to at least 30% of ASD in simplex families (9).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [9] source
Not checked in the free run.
- Premisecitation
In males, a de novo likely gene-disruptive mutation in an autism gene produces severe autism spectrum disorder about half the time.
“We computed that roughly half of the time in males, a DN LGD mutation within an autism gene will produce severe ASD (10).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] source
Not checked in the free run.
- Interpretationown data
Causal targets in higher-IQ affected individuals appear less vulnerable as a class.
“Thus, causal targets in higher IQ affected individuals seem to be less vulnerable as a class.”
Quote in the paperSubstantial claim - Premisecitation
Nearly half of simplex families are estimated to belong to the high-risk class where transmission causes most cases.
“we estimate that nearly half of simplex families are actually of the high-risk class in which causation by transmission predominates (9).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [9] source
Not checked in the free run.
- Premisecitation
Recent reports show that targets of disruptive de novo mutation in affected children have a lighter load of disruptive mutation in the human population.
“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).”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisenone given
90% of 65 variants in 27 recurrently hit genes expected causal.
“Ninety percent of the 65 variants that fell within the 27 recurrently hit genes are expected to be causal.”
Quote in the paperSubstantial claim - Interpretationreasoning
Inverse correlation between phenotypic severity and tolerance of genetic target.
“Overall, we can say there is an inverse correlation between phenotypic severity and the tolerance of the genetic target for disruptive mutation.”
Quote in the paperSubstantial claim - Premisecitation
About 40% of SSC families are high risk with strong transmission genetics.
“Although the SSC is composed mainly of simplex families, we have previously calculated that about 40% of families are “high risk,” in which transmission genetics play a strong causative role (9).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [9] source
Not checked in the free run.
- Premisecitation
Endophenotypes in high-functioning children mainly seen in mothers.
“Interestingly, endophenotypes in high-functioning children are mainly seen in their mothers (21).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [21] source
Not checked in the free run.
- May combine two claims. 28
- Classified as probably not a substantial claim. 13
May combine two claims.
Findingown dataBy affected IQ, the transmission differential is 70 from lower-IQ families and 30 from higher-IQ families (P = 0.0071 and P = 0.1489).
“Almost as striking is the decomposition by affected IQ: A differential of 70 comes from precisely half of the families with an affected child of lower IQ, and 30 come from families with an affected child of higher IQ (P = 0.0071 and P = 0.1489, respectively).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe transmission ascertainment differential for genes with one LGD variant is 101, which may explain about 5.4% of SSC families.
“The ascertainment differential of transmission of UR LGD variants in the genes with a single LGD variant is 101, contributing to diagnosis in perhaps 5.4% of families from the SSC.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataEmbryonic category shows differential transmission of UR LGD variants to affected children over siblings; 31 more transmitted only to affected child among 298 opportunities (P=0.0073).
“The embryonically expressed category shows a surprising differential transmission of UR LGD variants to affected children over siblings.With 298 opportunities, 31 more are transmitted only to the affected child rather than to the unaffected sibling among quad families (P = 0.0073 by permutation test).”
Quote in the paperSubstantial claimMay combine two claims.
FindingcitationAll gene classes enriched for autism targets show decreased load of UR LGD variants, especially FMRP-associated.
“All gene classes enriched for autism targets show a decreased load of UR LGD variants, especially the FMRP-associated class, as previously noted (10).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] source
Not checked in the free run.
May combine two claims.
Findingown dataDifferential transmission is 76 from mothers and 25 from fathers, with P = 0.0031 and P = 0.1890, respectively.
“We observe differential transmission of 76 from the mother compared with 25 from the father with P = 0.0031 and P = 0.1890, respectively.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe two databases have similar total numbers of ultrarare synonymous variants and similar ratios of missense, synonymous, nonsense, and LGD mutations, as well as similar transition/transversion ratios.
“The total number of UR synonymous variants is similar, as are the ratios of missense, synonymous, nonsense, and LGD mutations, as well as the ratios of transition and transversion UR variants.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataCausal class vulnerability estimates for true autism genes based on recurrent, lower-IQ, and all affected classes are close (0.17, 0.19, and 0.15) and quite low.
“The estimates of the causal class vulnerability for the true autism genes based on the rec in aut, autL, and aut values are close (0.17, 0.19 and 0.15, respectively) and quite low.”
Quote in the paperSubstantial claimMay combine two claims.
FindingreasoningThe tolerance index is 1.0 for unaffected siblings and 0.15 for affected children.
“The indices are 1.0 for unaffected siblings, by definition, and 0.15 for affected children.”
Quote in the paperSubstantial claimMay combine two claims.
FindingreasoningAfter adjusting for recurrently hit genes, 44% of the lower-IQ affected gene set and 30% of the higher-IQ gene set are estimated to be causal targets.
“Adjusting for recurrently hit genes (Methods), we estimate that 44% of the gene set for lower IQ affected individuals and 30% for higher IQ individuals are causal targets.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataAffected-child target classes have a markedly lower load of ultrarare LGD variants than sibling classes, though the difference is not significant for higher-IQ affected children.
“Target classes from affected children show a markedly lower load for UR LGD variants than the class from siblings, although this difference is not significant for the affected children of higher IQ.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataFor four of these genes transmissions mainly from mother; for KMT2C all four from father.
“For four of these genes, the transmissions are mainly from the mother, but for one, the histone methyltransferase KMT2C, each of the four transmissions is from the father (Fig. S2).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataNearly all differential transmission signal comes from longer genes, with a differential of 93 in longer genes and 8 in shorter genes.
“Despite this even split, nearly all the signal in differential transmission comes from the longer genes: the differential is 93 in the longer genes and 8 in the shorter genes.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataProportion of genes with reduced load matches ascertainment differential, with target genes in two classes.
“Moreover, the proportion of genes with a reduced load matches expectations based on the ascertainment differential in DN mutation frequency between affected and unaffected siblings, with target genes falling into two classes: those genes with reduced mutational load and those genes without (Fig. 2).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataRecently published RVIS findings show maternal transmission for lower half of RVIS-tolerant genes, and our result is similar (P=0.003 all, P>0.0005 long).
“Recently published findings using the RVIS (16) present evidence for maternal transmission within the SSC of “private” LGD mutations for the lower half of RVIS-tolerant genes, and our result on maternal transmission based purely on genes with UR LGD mutations is very similar (statistically significant with a P = 0.003 for all, and P > 0.0005 for the more vulnerable long genes).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [16] source
Not checked in the free run.
May combine two claims.
Findingown dataProportion of causal genes in lower IQ is 44%, higher IQ 30%.
“Similarly, we computed the proportion of causal genes in the targets of DN LGD mutations in affected children with lower (44%) and higher (30%) nonverbal IQs.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: Noncontributory DN LGD mutations in affected children occur at same rate as DN LGD mutations in unaffected individuals, and their target genes have similar UR LGD loads.
- The authors state this as an assumption: Vulnerability of noncausal genes is 1, i.e., they have same load as targets of DN LGD mutation in unaffected siblings.
May combine two claims.
Findingown dataLOWESS fit agrees with square root model for UR LGD vs synonymous, linear for missense.
“The LOWESS fit agrees closely with the square root model for the number of UR LGD mutations as a function of the number of UR synonymous variants, but it aligns better with the linear fit for the number of UR missense as a function of UR synonymous variants.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductown dataThe affected and unaffected target classes were found on the same sequencing platforms, at the same depth, through identical pipelines, and in full siblings matched for germ-line background.
“These two target classes were discovered on the same sequencing platforms, sequenced to the same depth, and processed through identical informatics pipelines, and they arise in children matched for germ-line background by being full siblings.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductown dataTransmission significance was assessed by permuting affected labels.
“We determined significance by permuting”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationcitationBecause ASD individuals have reduced fecundity, target genes should be under severe purifying selection and have reduced load of disruptive variants.
“Because individuals with ASD have drastically reduced fecundity (11), the net prediction is that these target genes should be under severe purifying selection, and hence have a reduced load of disruptive variants in the human gene pool.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [11] source
Not checked in the free run.
May combine two claims.
PremisecitationThere are 39 recurrent DN LGD targets in affected children, and about 90% are true causal targets.
“There are 39 such targets (10,18), and we previously estimated that ∼90% of these targets are true causal targets.”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
Premisecitation§ Low load for disruptive mutations in autism genes and their biased transmissionGenes that carry de novo likely gene-disruptive mutations in children with autism spectrum disorder are highly vulnerable, and a disruptive mutation in many vulnerable autism genes is likely to lead to autism spectrum disorder.
“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.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] source
Not checked in the free run.
May combine two claims.
PremisecitationRecurrence and overlap analysis of de novo likely gene-disruptive targets estimates about 500 causative autism spectrum disorder target genes in lower-IQ affected individuals, enriched in certain functional classes.
“From recurrence and overlap analysis of DN LGD targets, we estimate ∼500 causative ASD target genes in the affected individuals with lower intelligence quotients (IQ), and these targets are enriched in certain functional classes (10).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] source
Not checked in the free run.
May combine two claims.
Interpretationcitation§ Low load for disruptive mutations in autism genes and their biased transmissionDisruptive mutations in autism genes face strong negative selection and are rapidly removed from the population.
“Because individuals with ASD have lower fecundity, such mutations in autism genes would be under strong negative selection pressure.”
- Also stated in: § autism spectrum disorder | gene vulnerability | disruptive mutations | biased transmission | autism genes · boosted
“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).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [11] source
Not checked in the free run.
- Also stated in: § autism spectrum disorder | gene vulnerability | disruptive mutations | biased transmission | autism genes · boosted
Classified as probably not a substantial claim. May combine two claims.
Study design and conductnone givenSome SSC parents may carry autism-contributing variation, so statistics from these families may overestimate rare variation in candidate autism genes.
“Obviously, some of these parents may be carriers of variation contributing to ASD, so statistics extracted from these families may overestimate the rare variation seen in candidate autism genes.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductnone givenSome SSC parents may carry ultrarare LGD mutations ascertained because they caused autism in their affected children after transmission.
“It is possible that some SSC parents carry UR LGD mutations that have been ascertained because they caused autism in their affected children upon transmission.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
InterpretationreasoningBecause most missense mutations are weakly selected or neutral, missense accumulation should be proportional to synonymous mutation.
“Because the great majority of missense mutations will be under weak to neutral selection, we expect accumulation of missense will be proportional to synonymous mutation (Fig. 1B).”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductown dataSignificance of LGD ratio differences was assessed with 10,000 permutations that randomly swapped genes between sets while keeping set sizes fixed.
“To determine if these lower ratios were significant, we performed 10,000 permutations, randomly swapping genes between sets while keeping the size of sets fixed, and computed the LGD ratio.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationHalf siblings sharing the maternal germ line have fourfold greater concordance than those sharing the paternal germ line.
“for example, that there is a fourfold greater concordance in half siblings sharing the maternal rather than paternal germ-line (17).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [17] source
Not checked in the free run.
May combine two claims.
Study design and conductown dataSSC exome data came from similar capture and sequencing platforms, a uniform analysis pipeline, and known coverage at every nucleotide position in targeted regions.
“The advantage of using the SSC is that the WES data were obtained with similar capture and sequencing platforms and were subject to a uniform analysis pipeline, and the coverage is known for every nucleotide position in every gene in every person within the targeted regions.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Interpretationnone givenAssociation of load with causation provides tool to study transmission of causative factors.
“The association of load with causation provides us with a tool by which we can study transmission of causative factors.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
InterpretationreasoningPower of using gene tolerance should be of general value in genetic disorders that reduce fecundity.
“The power of using gene tolerance for disruptive mutation should be of general value in the analysis of genetic disorders that reduce fecundity.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
Interpretationown dataOur results strengthen this finding with stronger statistics.
“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.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationEarlier population studies indicated importance of shared maternal bloodline in sibling risk.
“Earlier population studies have indicated the importance of a shared maternal bloodline in sibling risk (19,20).”
Quote in the paperNot a substantial claim0 of 2 sources checkedClassified as probably not a substantial claim. May combine two claims.
PremisereasoningWe relied solely on LGD variants because their presence in interior of well-annotated gene will almost certainly disrupt function.
“We have relied solely on LGD variants because, unlike missense variants that are hard to interpret, their presence in the interior of a well-annotated gene (Fig. S1) will almost certainly cause disruption of gene function.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningUR variants of vulnerable genes would be short-lived and not detectable by population association studies.
“By this theory, UR variants of vulnerable genes would be short-lived in the population, and therefore not detectable by population association studies.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenScore should not be treated as absolute probability; it is heuristic.
“Such a score should not be treated as absolute probability for a gene to be an autism gene.It is a heuristic that allows us to prioritize genes and has several useful properties.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: Autism vulnerable genes and intolerant (protected) genes are treated as the same set.
- The authors state this as an assumption: DN and rare parental data are independent.
- The authors state this as an assumption: A protected gene has only 10% of typical share of UR LGD mutations.
Classified as probably not a substantial claim.
PremisecitationAutism candidate genes have reduced load of damaging mutation, reported earlier.
“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).”
Quote in the paperSubstantial claim0 of 3 sources checked
The paper relies on this without support.
The majority of LGD mutations, and the subset of nonsense mutations, are harmful.
“The majority of LGD mutations (and the subset of nonsense) will be harmful, but this scenario is not so for missense mutations.”
The authors state this as an assumption.
Noncontributory DN LGD mutations in affected children occur at same rate as DN LGD mutations in unaffected individuals, and their target genes have similar UR LGD loads.
“The rate of noncontributory DN LGD mutations per affected individual should match the rate of DN LGD mutations in unaffected individuals; moreover, the genes targeted by noncontributory DN LGD mutations in affected and unaffected siblings should have similar loads of UR LGD mutations.”
The authors state this as an assumption.
Vulnerability of noncausal genes is 1, i.e., they have same load as targets of DN LGD mutation in unaffected siblings.
“where the vulnerability of noncausal genes is set to 1, reflecting the assumption that they have the same load as the targets of DN LGD mutation in unaffected siblings.”
The authors state this as an assumption.
Autism vulnerable genes and intolerant (protected) genes are treated as the same set.
“We developed a simple heuristic gene score based on the naive assumption that the set of autism vulnerable genes and the set of intolerant (protected) genes are the same.”
The authors state this as an assumption.
DN and rare parental data are independent.
“Using the Bayes rule, and further assuming that the DN and rare parental data are independent, we can rewrite this conditional probability as:”
The authors state this as an assumption.
A protected gene has only 10% of typical share of UR LGD mutations.
“To define pðRjAÞ, we assume that a protected gene has only 10% of the typical share of UR LGD mutations:”
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?
Exome sequencing of families has found evidence that inherited protein-truncating variants contribute to ASD.
“Evidence for the contribution of inherited protein truncating variants to ASD has also been found by exome sequencing of families (Iossifov et al., 2015; Krumm et al., 2015)”
From Getting to the cores of autism (2019) · cites this paper as Iossifov et al., 2015
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.
Higher-IQ transmission difference is reported as both 30 and 31
MinorThe prose gives a transmission difference of 30 for higher-IQ families, while Table 3 gives 31 for the same group.
“A differential of 70 comes from precisely half of the families with an affected child of lower IQ, and 30 come from families with an affected child of higher IQ”
“| Higher IQ | 1,528 | 1,528 | 374 | 403 | 391 | 360 | 31 | 0.1489 |”
Long-gene P value conflicts with the stated inequality
MinorThe discussion says the P value for the more vulnerable long genes is greater than 0.0005, but Table 3 reports it as equal to 0.0005.
“P > 0.0005 for the more vulnerable long genes”
“| Long | 1,557 | 1,557 | 384 | 412 | 427 | 334 | 93 | 0.0005 |”
Count of demoted recurrent targets changes from 11 to 12
MinorThe text says 11 targets were demoted, then refers to five of those targets as being among 12 genes.
“Eleven DN LGD targets are "demoted" by virtue of having LGD variants, including RIMS1 and KDM5B.”
“On the other hand, five of these 12 genes (KMT2C, KATNAL2, ADNP, DIP2A, and PTEN) are "promoted" to be causal”
Causal vulnerability for all affected targets has two values
MinorThe text reports 0.16 for causal targets across all affected individuals, whereas Table 2 reports 0.15 for that same class.
“0.16 over all affected individuals”
“| aut | 509 | 0.36 | 24,758 | 2,062 | 0.08 | 0.0009 | 2,959 | 0.70 | 0.15 |”
Cites
Synaptic, transcriptional and chromatin genes disrupted in autism
Study, T. D., De Rubeis, S., Autism, H. M. C. F., UK10K Consortium, The Autism Sequencing Consortium, He, X., Goldberg, A. P., Poultney, C. S., Samocha, K., Ercument Cicek, A., et al. (2014) · Nature · doi:10.1038/nature13772 · Cited by 2,746 · see citing works
The contribution of de novo coding mutations to autism spectrum disorder
Iossifov, I., O’Roak, B. J., Sanders, S. J., Ronemus, M., Krumm, N., Levy, D., Stessman, H. A., Witherspoon, K. T., Vives, L., Patterson, K. E., et al. (2014) · Nature · doi:10.1038/nature13908 · Cited by 2,585 · see citing works
Self-citationSporadic autism exomes reveal a highly interconnected protein network of de novo mutations
O’Roak, B. J., Vives, L., Girirajan, S., Karakoc, E., Krumm, N., Coe, B. P., Levy, R., Ko, A., Lee, C., Smith, J. D., et al. (2012) · Nature · doi:10.1038/nature10989 · Cited by 2,165 · cited 1× · see citing works
“They apply their particular tolerance score on targets from a subset of the Simons Simplex Collection (SSC), a collection of simplex autism families (5, 7, 8, 15).”
BackgroundDe novo mutations revealed by whole-exome sequencing are strongly associated with autism
Sanders, S. J., Murtha, M. T., Gupta, A. R., Murdoch, J. D., Raubeson, M. J., Willsey, A. J., Ercan-Sencicek, A. G., DiLullo, N. M., Parikshak, N. N., Stein, J. L., et al. (2012) · Nature · doi:10.1038/nature10945 · Cited by 2,084 · see citing works
FMRP Stalls Ribosomal Translocation on mRNAs Linked to Synaptic Function and Autism
Darnell, J. C., Van Driesche, S. J., Zhang, C., Hung, K. Y. S., Mele, A., Fraser, C. E., Stone, E. F., Chen, C., Fak, J. J., Chi, S. W., et al. (2011) · Cell · doi:10.1016/j.cell.2011.06.013 · Cited by 2,072 · see citing works
Patterns and rates of exonic de novo mutations in autism spectrum disorders
Neale, B. M., Kou, Y., Liu, L., Ma’ayan, A., Samocha, K. E., Sabo, A., Lin, C.-F., Stevens, C., Wang, L.-S., Makarov, V., et al. (2012) · Nature · doi:10.1038/nature11011 · Cited by 1,734 · see citing works
De Novo Gene Disruptions in Children on the Autistic Spectrum
Iossifov, I., Ronemus, M., Levy, D., Wang, Z., Hakker, I., Rosenbaum, J., Yamrom, B., Lee, Y.-H., Narzisi, G., Leotta, A., et al. (2012) · Neuron · doi:10.1016/j.neuron.2012.04.009 · Cited by 1,446 · see citing works
Self-citationSanders, S. J., Ercan-Sencicek, A. G., Hus, V., Luo, R., Murtha, M. T., Moreno-De-Luca, D., Chu, S. H., Moreau, M. P., Gupta, A. R., Thomson, S. A., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.05.002 · Cited by 1,263 · see citing works
Sandin, S., Lichtenstein, P., Kuja-Halkola, R., Larsson, H., Hultman, C. M., & Reichenberg, A. (2014) · JAMA · doi:10.1001/jama.2014.4144 · Cited by 1,073 · cited 1× · see citing works
“Earlier population studies have indicated the importance of a shared maternal bloodline in sibling risk (19, 20).”
BackgroundA framework for the interpretation of de novo mutation in human disease
Samocha, K. E., Robinson, E. B., Sanders, S. J., Stevens, C., Sabo, A., McGrath, L. M., Kosmicki, J. A., Rehnström, K., Mallick, S., Kirby, A., et al. (2014) · Nature Genetics · doi:10.1038/ng.3050 · Cited by 979 · see citing works
Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes
Petrovski, S., Wang, Q., Heinzen, E. L., Allen, A. S., & Goldstein, D. B. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003709 · Cited by 901 · see citing works
The Simons Simplex Collection: a resource for identification of autism genetic risk factors
Fischbach, G. D., & Lord, C. (2010) · Neuron · doi:10.1016/j.neuron.2010.10.006 · Cited by 725 · see citing works
Rare de novo and transmitted copy-number variation in autistic spectrum disorders
Levy, D., Ronemus, M., Yamrom, B., Lee, Y.-H., Leotta, A., Kendall, J., Marks, S., Lakshmi, B., Pai, D., Ye, K., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.05.015 · Cited by 712 · see citing works
Self-citationDisentangling the heterogeneity of autism spectrum disorder through genetic findings
Jeste, S. S., & Geschwind, D. H. (2014) · Nature Reviews Neurology · doi:10.1038/nrneurol.2013.278 · Cited by 644 · see citing works
Excess of rare, inherited truncating mutations in autism
Krumm, N., Turner, T. N., Baker, C., Vives, L., Mohajeri, K., Witherspoon, K., Raja, A., Coe, B. P., Stessman, H. A., He, Z.-X., et al. (2015) · Nature Genetics · doi:10.1038/ng.3303 · Cited by 587 · see citing works
The role of de novo mutations in the genetics of autism spectrum disorders
Ronemus, M., Iossifov, I., Levy, D., & Wigler, M. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3585 · Cited by 390 · see citing works
Self-citationPower, R. A., Kyaga, S., Uher, R., MacCabe, J. H., Långström, N., Landen, M., McGuffin, P., Lewis, C. M., Lichtenstein, P., & Svensson, A. C. (2013) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.268 · Cited by 336 · see citing works
A unified genetic theory for sporadic and inherited autism
Zhao, X., Leotta, A., Kustanovich, V., Lajonchere, C., Geschwind, D. H., Law, K., Law, P., Qiu, S., Lord, C., Sebat, J., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0705803104 · Cited by 319 · see citing works
Self-citationRethinking the nature of genetic vulnerability to autistic spectrum disorders
Skuse, D. H. (2007) · Trends in Genetics · doi:10.1016/j.tig.2007.06.003 · Cited by 147 · see citing works
Familial Recurrence of Autism Spectrum Disorder: Evaluating Genetic and Environmental Contributions
Risch, N., Hoffmann, T. J., Anderson, M., Croen, L. A., Grether, J. K., & Windham, G. C. (2014) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2014.13101359 · Cited by 144 · see citing works
Autism recurrence in half siblings: strong support for genetic mechanisms of transmission in ASD
Constantino, J. N., Todorov, A., Hilton, C., Law, P., Zhang, Y., Molloy, E., Fitzgerald, R., & Geschwind, D. (2013) · Molecular Psychiatry · doi:10.1038/mp.2012.9 · Cited by 134 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder
Gandal, M. J., Zhang, P., Hadjimichael, E., Walker, R. L., Chen, C., Liu, S., Won, H., van Bakel, H., Varghese, M., Wang, Y., et al. (2018) · Science · doi:10.1126/science.aat8127 · Cited by 1,247 · see citing works
“(1 and 2) genes from SFARI Gene database; vulnerable ASD genes (105);”
Heritability of autism spectrum disorders: a meta-analysis of twin studies
Tick, B., Bolton, P., Happé, F., Rutter, M., & Rijsdijk, F. (2016) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12499 · Cited by 1,150 · see citing works
“There is evidence for the contribution of both common variants and rare mutations (Gaugler et al., 2014; Iossifov et al., 2015) and at this point it is simply not possible to definitively decide on one model over the other.”
BackgroundHippocampal GABAergic Inhibitory Interneurons
Pelkey, K. A., Chittajallu, R., Craig, M. T., Tricoire, L., Wester, J. C., & McBain, C. J. (2017) · Physiological Reviews · doi:10.1152/physrev.00007.2017 · Cited by 889 · see citing works
Neurodevelopmental Disorders: From Genetics to Functional Pathways
Parenti, I., Rabaneda, L. G., Schoen, H., & Novarino, G. (2020) · Trends in Neurosciences · doi:10.1016/j.tins.2020.05.004 · Cited by 634 · see citing works
“Variants in these genes are not under negative selective pressure and are frequently transmitted in families for generations [2,14].”
BackgroundEmerging Roles for the Gut Microbiome in Autism Spectrum Disorder
Vuong, H. E., & Hsiao, E. Y. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.08.024 · Cited by 595 · see citing works
“It is estimated that the de novo mutations, common variants, and short nucleotide polymorphisms identified across numerous ASD cases altogether account for approximately 50% of the disorder (14,15).”
BackgroundStessman, H. A. F., Xiong, B., Coe, B. P., Wang, T., Hoekzema, K., Fenckova, M., Kvarnung, M., Gerdts, J., Trinh, S., Cosemans, N., et al. (2017) · Nature Genetics · doi:10.1038/ng.3792 · Cited by 559 · see citing works
“Of interest are the 13 genes without DN mutation significance (SMARCC2, CTNND2, SIN3A, SCN1A, NFIA, CDKL5, DNAJC6, IQSEC2, IQGAP3, ADGRL2, ERBIN, NAV2, and AGPA2; Table 2) suggesting potential inherited risk factors 13,31,52 .”
New insights into the generation and role of de novo mutations in health and disease
Acuña‐Hidalgo, R., Veltman, J. A., & Hoischen, A. (2016) · Genome biology · doi:10.1186/s13059-016-1110-1 · Cited by 451 · see citing works
“For these milder phenotypes that have less impact on fitness, the exact contribution of de novo mutations to the disease burden is not yet firmly established, and inherited variation is likely to be at least as important in the expression of the phenotype [120–122].”
BackgroundKrishnan, A., Zhang, R., Yao, V., Theesfeld, C. L., Wong, A. K., Tadych, A., Volfovsky, N., Packer, A. I., Lash, A., & Troyanskaya, O. G. (2016) · Nature Neuroscience · doi:10.1038/nn.4353 · Cited by 427 · see citing works
“Further, in agreement with recent findings 28 , genes we predicted to be highly linked to ASD tended to be more evolutionarily constrained than all the other genes (permutation test P = 1 × 10 −6 ; Supplementary Fig.”
ResultA comprehensive transcriptional map of primate brain development
Bakken, T. E., Miller, J. A., Ding, S., Sunkin, S. M., Smith, K. A., Ng, L., Szafer, A., Dalley, R. A., Royall, J. J., Lemon, T. A., et al. (2016) · Nature · doi:10.1038/nature18637 · Cited by 376 · see citing works
Liu, F., Li, J., Wu, F., Zheng, H., Peng, Q., & Zhou, H. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0389-6 · Cited by 336 · see citing works
Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk
Zhou, J., Park, C. Y., Theesfeld, C. L., Wong, A. K., Yuan, Y., Scheckel, C., Fak, J. J., Funk, J., Yao, K., Tajima, Y., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0420-0 · Cited by 287 · see citing works
Exome sequencing of 457 autism families recruited online provides evidence for autism risk genes
Feliciano, P., Zhou, X., Astrovskaya, I., Turner, T. N., Wang, T., Brueggeman, L., Barnard, R., Hsieh, A., Snyder, L. G., Muzny, D. M., et al. (2019) · npj Genomic Medicine · doi:10.1038/s41525-019-0093-8 · Cited by 247 · see citing works
Getting to the cores of autism
Iakoucheva, L. M., Muotri, A. R., & Sebat, J. (2019) · Cell · doi:10.1016/j.cell.2019.07.037 · Cited by 260 · see citing works
“Evidence for the contribution of inherited protein truncating variants to ASD has also been found by exome sequencing of families (Iossifov et al., 2015; Krumm et al., 2015) Thus, a portion of the genetic architecture consists of rare coding variants with incomplete penetrance that are inherited fromparentswho do notm…”
BackgroundPaternally inherited cis-regulatory structural variants are associated with autism
Brandler, W. M., Antaki, D., Gujral, M., Kleiber, M. L., Whitney, J., Maile, M. S., Hong, O., Chapman, T. R., Tan, S., Tandon, P., et al. (2018) · Science · doi:10.1126/science.aan2261 · Cited by 209 · see citing works
Pizzo, L., Jensen, M., Polyak, A., Rosenfeld, J. A., Mannik, K., Krishnan, A., McCready, E., Pichon, O., Le Caignec, C., Van Dijck, A., et al. (2019) · Genetics in Medicine · doi:10.1038/s41436-018-0266-3 · Cited by 193 · see citing works
Exonic Mosaic Mutations Contribute Risk for Autism Spectrum Disorder
Krupp, D. R., Barnard, R. A., Duffourd, Y., Evans, S. A., Mulqueen, R. M., Bernier, R., Rivière, J.-B., Fombonne, E., & O’Roak, B. J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.07.016 · Cited by 204 · see citing works
Recent ultra-rare inherited variants implicate new autism candidate risk genes
Wilfert, A. B., Turner, T. N., Murali, S. C., Hsieh, P., Sulovari, A., Wang, T., Coe, B. P., Guo, H., Hoekzema, K., Bakken, T. E., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00899-8 · Cited by 138 · see citing works
An autism spectrum disorder-related de novo mutation hotspot discovered in the GEF1 domain of Trio
Sadybekov, A., Tian, C., Arnesano, C., Katritch, V., & Herring, B. E. (2017) · Nature Communications · doi:10.1038/s41467-017-00472-0 · Cited by 111 · see citing works
Kosillo, P., & Bateup, H. S. (2021) · Frontiers in Neural Circuits · doi:10.3389/fncir.2021.700968 · Cited by 110 · see citing works
Mutation and Human Exceptionalism: Our Future Genetic Load
Lynch, M. (2016) · Genetics · doi:10.1534/genetics.115.180471 · Cited by 105 · see citing works
“At least 30% of individuals with autism spectrum disorders appear to acquire such behaviors by de novo mutation (Iossifov et al. 2015).”
BackgroundMethodKataoka, M., Matoba, N., Sawada, T., Kazuno, A.-A., Ishiwata, M., Fujii, K., Matsuo, K., Takata, A., & Kato, T. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.69 · Cited by 104 · see citing works
Genetic Associations between Voltage-Gated Calcium Channels and Psychiatric Disorders
Andrade, A., Brennecke, A., Mallat, S., Brown, J., Gomez-Rivadeneira, J., Czepiel, N., & Londrigan, L. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20143537 · Cited by 127 · see citing works
“Four missense variations (R212C, R902W, W962C and A1874V) were identified in a study of 461 probands with ASD and 480 ethnically matched individuals by targeted sequencing of the CACNA1H genomic region [254,255].”
BackgroundInfluentialDapas, M., Sisk, R. K., Legro, R. S., Urbanek, M., Dunaif, A. E., & Hayes, M. G. (2019) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2018-02496 · Cited by 92 · see citing works
Autism Spectrum Disorder: Focus on Glutamatergic Neurotransmission
Montanari, M., Martella, G., Bonsi, P., & Meringolo, M. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23073861 · Cited by 105 · see citing works
Spence, E. F., Dube, S., Uezu, A., Locke, M., Soderblom, E. J., & Soderling, S. H. (2019) · Nature Communications · doi:10.1038/s41467-019-08288-w · Cited by 88 · see citing works
Cederquist, G., Tchieu, J. H., Callahan, S. J., Ramnarine, K., Ryan, S. D., Zhang, C., Rittenhouse, C. A., Zeltner, N., Chung, S. Y., Zhou, T., et al. (2020) · Cell stem cell · doi:10.1016/j.stem.2020.06.004 · Cited by 85 · see citing works
Developmental Gene Expression Differences between Humans and Mammalian Models
Cardoso-Moreira, M., Sarropoulos, I., Velten, B., Mort, M. E., Cooper, D. N., Huber, W. K., & Kaessmann, H. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108308 · Cited by 75 · see citing works
Guo, D., Yang, X., & Shi, L. (2020) · Cells · doi:10.3390/cells9040835 · Cited by 73 · see citing works
Liu, Z., Mao, X., Zhou, D., Pei, Y., Xu, R., Guo, M., Liu, K., Zhang, F., Chen, J., Su, C., et al. (2021) · Gut Microbes · doi:10.1080/19490976.2020.1854967 · Cited by 74 · see citing works
“However, the de novo mutations, common variants, and short nucleotide polymorphisms identified across numerous ASD cases altogether only account for approximately 50% of the cases.(5,6) As such, many studies highlight the possibility of environmental risk factors and associated medical co-morbidities that may contribu…”
BackgroundThe Role of De Novo Noncoding Regulatory Mutations in Neurodevelopmental Disorders
Turner, T. N., & Eichler, E. E. (2018) · Trends in Neurosciences · doi:10.1016/j.tins.2018.11.002 · Cited by 69 · see citing works
TBR1 regulates autism risk genes in the developing neocortex
Notwell, J. H., Heavner, W. E., Darbandi, S. F., Katzman, S., McKenna, W. L., Ortiz-Londono, C. F., Tastad, D., Eckler, M. J., Rubenstein, J. L. R., McConnell, S. K., et al. (2016) · Genome Research · doi:10.1101/gr.203612.115 · Cited by 74 · see citing works
“www.genome.org A recent study showed that LoF variants in KATNAL2 were passed from an unaffected mother to their unaffected male child, reinforcing this point (Iossifov et al. 2015).”
BackgroundDamaging de novo mutations diminish motor skills in children on the autism spectrum
Buja, A., Volfovsky, N., Krieger, A. M., Lord, C., Lash, A. E., Wigler, M., & Iossifov, I. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1715427115 · Cited by 64 · see citing works
“Nevertheless, in a previous study we still found that affected children in the SSC with dn LGDs in highly vulnerable genes had significantly lower IQ than in affected children with LGDs in less vulnerable genes (7).”
Self-citationPrediction of response to drug therapy in psychiatric disorders
Stern, S., Linker, S. B., Vadodaria, K. C., Marchetto, M. C., & Gage, F. H. (2018) · Open Biology · doi:10.1098/rsob.180031 · Cited by 65 · see citing works
Shin, W., Kim, K., Serraz, B., Cho, Y. S., Kim, D., Kang, M., Lee, E., Lee, H., Bae, Y. C., Paoletti, P., et al. (2020) · PLoS Biology · doi:10.1371/journal.pbio.3000717 · Cited by 62 · see citing works
Dendritic spine actin cytoskeleton in autism spectrum disorder
Joensuu, M., Lanoue, V., & Hotulainen, P. (2018) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2017.08.023 · Cited by 65 · see citing works
Qin, L., Williams, J. B., Tan, T., Liu, T., Cao, Q., Ma, K., & Yan, Z. (2021) · Nature Communications · doi:10.1038/s41467-021-26972-8 · Cited by 62 · see citing works
Increased burden of deleterious variants in essential genes in autism spectrum disorder
Ji, X., Kember, R. L., Brown, C. D., & Bućan, M. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1613195113 · Cited by 52 · see citing works
“Several groups reported an enrichment of de novo and rare inherited single-nucleotide loss-of-function variants in ASD probands (8, 26), although there is a depletion of damaging mutations in ASD risk genes in population controls (12, 27, 28).”
BackgroundResultKinzina, E., Podolskiy, D. I., Dmitriev, S. E., & Gladyshev, V. N. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.11.091 · Cited by 55 · see citing works
Lin, Y., Afshar, S., Rajadhyaksha, A. M., Potash, J. B., & Han, S. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.500064 · Cited by 59 · see citing works
“In addition to having functional relationships, ASD genes affected by de novo mutations tend to be intolerant of variations (Samocha et al., 2014; Iossifov et al., 2015).”
BackgroundGozes, I., Patterson, M. C., Dijck, A. V., Kooy, R. F., Peeden, J., Eichenberger, J. A., Zawacki-Downing, A., & Bedrosian‐Sermone, S. (2017) · Frontiers in Endocrinology · doi:10.3389/fendo.2017.00107 · Cited by 50 · see citing works
A systematic variant annotation approach for ranking genes associated with autism spectrum disorders
Larsen, E., Menashe, I., Ziats, M. N., Pereanu, W., Packer, A. I., & Banerjee‐Basu, S. (2016) · Molecular Autism · doi:10.1186/s13229-016-0103-y · Cited by 50 · see citing works
“corresponding posterior probabilities [23] (Fig.”
ResultLeveraging large genomic datasets to illuminate the pathobiology of autism spectrum disorders
Searles, V. B., Wang, B., & State, M. W. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-0768-y · Cited by 52 · see citing works
Rates of contributory de novo mutation in high and low-risk autism families
Yoon, S. C., Muñoz, A., Yamrom, B., Lee, Y.-H., Andrews, P., Marks, S., Wang, Z., Reeves, C., Winterkorn, L. H., Krieger, A. Μ., et al. (2021) · Communications Biology · doi:10.1038/s42003-021-02533-z · Cited by 42 · see citing works
Self-citationThe Yin and Yang of Autism Genetics: How Rare De Novo and Common Variations Affect Liability
Chaste, P., Roeder, K., & Devlin, B. (2017) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-083115-022647 · Cited by 49 · see citing works
“Still, given the results from analysis of data from WES and from microarrays for CNV detection, some have concluded that de novo variation, possibly then inherited for a few generations, is the fundamental genetic driver of ASD liability (67, 68, 116).”
BackgroundThe chemistry of gut microbiome in health and diseases
Lau, A., Tan, L. T., Mutalib, N. A., Wong, S. H., Letchumanan, V., & Lee, L. (2021) · Progress In Microbes & Molecular Biology · doi:10.36877/pmmb.a0000175 · Cited by 52 · see citing works
“The exact cause of autism spectrum disorder is still unknown despite strong genetic evidence([231,232])and environmental factors.”
BackgroundMunz, M., Bharioke, A., Kosche, G., Moreno‐Juan, V., Brignall, A. C., Rodrigues, T. M., Graff-Meyer, A., Ulmer, T., Haeuselmann, S., Pavlinić, D., et al. (2023) · Cell · doi:10.1016/j.cell.2023.03.025 · Cited by 49 · see citing works
Chau, K. K., Zhang, P., Urresti, J., Amar, M., Pramod, A. B., Chen, J., Thomas, A. E., Corominas, R., Lin, G. N., & Iakoucheva, L. M. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109631 · Cited by 42 · see citing works
“For example, two LoF-affected isoforms of KMT2C histone lysine methyltransferase, a high-confidence ASD risk gene (De Rubeis et al., 2014; Iossifov et al., 2015; O’Roak et al., 2011) were highly expressed prenatally and had opposing temporal trajectories compared with non-affected isoforms that…”
Gupta, C., Chandrashekar, P. B., Jin, T., He, C., Khullar, S., Chang, Q., & Wang, D. (2022) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-022-09438-w · Cited by 64 · see citing works
“Furthermore, IDDs may involve changes in multiple genes, each conferring a small risk, and hundreds of autism risk genes have been cataloged through genomic assays [52–55].”
BackgroundBrown, E., Lautz, J. D., Davis, T. R., Gniffke, E. P., VanSchoiack, A., Neier, S. C., Tashbook, N., Nicolini, C., Fahnestock, M. L., Schrum, A. G., et al. (2018) · Molecular Autism · doi:10.1186/s13229-018-0229-1 · Cited by 40 · see citing works
The link between autism spectrum disorder and gut microbiota: A scoping review
Nitschke, A. S., Deonandan, R., & Konkle, A. T. M. (2020) · Autism · doi:10.1177/1362361320913364 · Cited by 45 · see citing works
“It is estimated that de novo mutations, common variants, and single nucleotide polymorphisms are overall responsible for approximately 50% of the disorder (Gaugler et al., 2014; Iossifov et al., 2015).”
BackgroundStructural insights into the human NuA4/TIP60 acetyltransferase and chromatin remodeling complex
Yang, Z., Mameri, A., Cattoglio, C., Lachance, C., Ariza, A. J. F., Luo, J., Humbert, J., Sudarshan, D., Banerjea, A., Galloy, M., et al. (2024) · Science · doi:10.1126/science.adl5816 · Cited by 44 · see citing works
Unified inference of missense variant effects and gene constraints in the human genome
Huang, Y.-F. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1008922 · Cited by 31 · see citing works
Zhao, G., Walsh, K., Long, J., Gui, W., & Denisova, K. (2018) · PLoS ONE · doi:10.1371/journal.pone.0196964 · Cited by 32 · see citing works
Rhine, C. L., Neil, C. R., Wang, J., Maguire, S., Buerer, L., Salomon, M., Meremikwu, I. C., Kim, J. E., Strande, N. T., & Fairbrother, W. G. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1009884 · Cited by 31 · see citing works
Thongkorn, S., Kanlayaprasit, S., Kasitipradit, K., Lertpeerapan, P., Panjabud, P., Hu, V. W., Jindatip, D., & Sarachana, T. (2023) · Biology of Sex Differences · doi:10.1186/s13293-023-00496-w · Cited by 33 · see citing works
Non-complicit: Revisiting Hans Asperger’s Career in Nazi-era Vienna
Falk, D. (2019) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-019-03981-7 · Cited by 30 · see citing works
Southwell, D. G., Seifikar, H., Malik, R., Lavi, K., Vogt, D. L., Rubenstein, J. L. R., & Sohal, V. S. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.1063-19.2019 · Cited by 23 · see citing works
“1-Cre; Pten conditional knock-out mice (hereafter also referred to as “Pten mice”), disruption of Pten, a phosphatase implicated in human ASD (Roak et al., 2012; De Rubeis et al., 2014; Iossifov et al., 2015; Geisheker et al., 2017), alters the subtype composition of interneurons derived from the medial ganglionic emi…”
BackgroundMethodInfluentialSchmeißer, K., Fardghassemi, Y., & Parker, J. A. (2017) · Experimental Neurology · doi:10.1016/j.expneurol.2017.03.022 · Cited by 23 · see citing works
“Its human orthologue, GRIN2B, has been strongly associated with ASD and other neurological disorders (Iossifov et al., 2015; Myers et al., 2011; O'Roak et al., 2011; Yoo et al., 2012).”
Genetic Associations between Voltage-Gated Calcium Channels and Psychiatric DisordersPreprint
Andrade, A., Brennecke, A., Mallat, S., et al. (2019) · Preprints.org · doi:10.20944/preprints201906.0192.v1 · Cited by 27 · see citing works
Giant ankyrin-B mediates transduction of axon guidance and collateral branch pruning factor sema 3A
Creighton, B. A., Afriyie, S., Ajit, D., Casingal, C. R., Voos, K. M., Reger, J., Burch, A. M., Dyne, E. D., Bay, J., Huang, J. K., et al. (2021) · eLife · doi:10.7554/elife.69815 · Cited by 23 · see citing works
A Whole-Exome Sequencing Study of Tourette Disorder in a Chinese Population
Zhao, X., Wang, S., Hao, J., Zhu, P., Zhang, X., & Wu, M. (2019) · DNA and Cell Biology · doi:10.1089/dna.2019.4746 · Cited by 21 · see citing works
“For example, Iossifov et al. showed that LGD variants occur at significantly higher rates in ASD probands compared to their unaffected siblings (Iossifov et al. , 2014, 2015).”
Pizzo, L., Lasser, M. C., Yusuff, T., Jensen, M., Ingraham, P., Huber, E., Singh, M. D., Monahan, C., Iyer, J. S., Desai, I., et al. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009112 · Cited by 24 · see citing works
“2 genes were enriched for genes intolerant to functional variation (Fig 7E and 7G), such 499 as ASH1L, a histone methyltransferase activator and autism candidate gene (75), and CAMK2B, a 500”
BackgroundStrain differences in behaviour and immunity in aged mice: Relevance to Autism
O’Connor, R., van de Wouw, M., Moloney, G. M., Ventura‐Silva, A. P., O’Riordan, K. J., Golubeva, A. V., Dinan, T. G., Schellekens, H., & Cryan, J. F. (2020) · Behavioural Brain Research · doi:10.1016/j.bbr.2020.113020 · Cited by 25 · see citing works
Exploring the heterogeneity of neural social indices for genetically distinct etiologies of autism
Hudac, C. M., Stessman, H. A. F., DesChamps, T. D., Kresse, A., Faja, S., Neuhaus, E., Webb, S. J., Eichler, E. E., & Bernier, R. (2017) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-017-9199-4 · Cited by 23 · see citing works
“Although this study is limited by a small sample size and thus should be considered exploratory, the analysis of neural social phenotypes based on functional clustering offers a promising approach for narrowing in on convergent pathways that may reflect shared phenotypes and provide insight for targeted treatment [5,…”
BackgroundMethodInfluentialBio-collections in autism research
Reilly, J., Gallagher, L., Chen, J. L., Leader, G., & Shen, S. (2017) · Molecular Autism · doi:10.1186/s13229-017-0154-8 · Cited by 23 · see citing works
Meili, F., Wei, W., Sin, W., Meyers, W. M., Dascalu, I., Callaghan, D. B., Rogić, S., Pavlidis, P., & Haas, K. Z. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.11.011 · Cited by 22 · see citing works
Exonic Mosaic Mutations Contribute Risk for Autism Spectrum DisorderPreprint
Krupp, D. R., Barnard, R., Duffourd, Y., et al. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/083428 · Cited by 23 · see citing works
“Moreover, we found missense PMMs in some of the highest-confidence ASD risk genes identified in the SSC or other combined studies, for example: CHD2, CTNNB1, KMT2C, SCN2A, and SYNGAP1 (Table 4).(30,32,33,67) Interestingly, small de novo deletions targeting CHD2, SYNGAP1, CTNNB1, and KMT2C have been reported in the SSC…”
BackgroundInfluentialGenetic factors contributing to autism spectrum disorder in Williams-Beuren syndrome
Codina‐Solà, M., Costa‐Roger, M., Pérez-García, D., Flores, R., Palacios-Verdú, M. G., Cuscó, I., & Jurado, L. A. P. (2019) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2019-106080 · Cited by 22 · see citing works
Transcriptional consequences of MBD5 disruption in mouse brain and CRISPR-derived neurons
Seabra, C. M., Aneichyk, T., Erdin, S., Tai, D. J. C., de Esch, C. E. F., Razaz, P., An, Y., Manavalan, P., Ragavendran, A., Stortchevoi, A., et al. (2020) · Molecular Autism · doi:10.1186/s13229-020-00354-1 · Cited by 20 · see citing works
Jaini, R., Wolf, M. R., Yu, Q., King, A. T., Frazier, T. W., & Eng, C. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01472-x · Cited by 21 · see citing works
Ritchie, F. D., & Lizarraga, S. B. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.989109 · Cited by 21 · see citing works
Enhanced LTP of population spikes in the dentate gyrus of mice haploinsufficient for neurobeachin
Muellerleile, J., Blistein, A., Rohlmann, A., Scheiwe, F., Missler, M., Schwarzacher, S. W., & Jedlička, P. (2020) · Scientific Reports · doi:10.1038/s41598-020-72925-4 · Cited by 18 · see citing works
Guerreiro, S. R., & Maciel, P. (2023) · Cells · doi:10.3390/cells12040538 · Cited by 20 · see citing works
“Mutations in one of these genes are rare but are associated with high disease risk and penetrance, likely inducing a disease phenotype even in the absence of additional mutations and therefore leading to monogenic NDDs; often resulting from de novo mutational events, they are therefore associated with sporadic cases o…”
BackgroundBeversdorf, D. Q., Shah, A., Jhin, A., Noel‐MacDonnell, J., Hecht, P. M., Ferguson, B. J., Bruce, D., Tilley, M. R., & Talebizadeh, Z. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.668577 · Cited by 18 · see citing works
Contribution of CACNA1H Variants in Autism Spectrum Disorder Susceptibility
Viggiano, M., D’Andrea, T., Cameli, C., Posar, A., Visconti, P., Scaduto, M. C., Colucci, R., Rochat, M. J., Ceroni, F., Milazzo, G., et al. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.858238 · Cited by 14 · see citing works
Tang, W., Beckley, J. T., Zhang, J., Song, R., Xu, Y., Kim, S., Quirk, M. C., Robichaud, A. J., Diaz, E. S., Myers, S. J., et al. (2023) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04667-7 · Cited by 17 · see citing works
Recent ultra-rare inherited mutations identify novel autism candidate risk genesPreprint
Wilfert, A. B., Turner, T. N., Murali, S. C., Hsieh, P., Sulovari, A., Wang, T., Coe, B. P., Guo, H., Hoekzema, K., Bakken, T. E., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.10.932327 · Cited by 14 · see citing works
“This estimate is in line with other 5 studies (3, 26) and suggests that this understudied class of mutation may confer almost as much risk as de novo SNVs and indels (6-9% of cases using the same population attributable risk estimator)(2, 3).”
MethodResultIntegrating genomic and resting State fMRI for efficient autism spectrum disorder classification
Lu, P., Li, X., Hu, L., & Lu, L. J. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-020-10473-9 · Cited by 17 · see citing works
Neuronal knockdown of Cullin3 as a Drosophila model of autism spectrum disorder
Tener, S. J., Lin, Z., Park, S. J., Oraedu, K., Ulgherait, M., van Beek, E., Martínez-Muñiz, A., Pantalia, M., Gatto, J. A., Volpi, J., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-51657-9 · Cited by 15 · see citing works
Neurodevelopmental functions of CHD8: new insights and questions
Basson, M. A. (2024) · Biochemical Society Transactions · doi:10.1042/bst20220926 · Cited by 17 · see citing works
Jiménez-Romero, M. S., Salas, P. C., & Benítez‐Burraco, A. (2018) · Molecular Syndromology · doi:10.1159/000485638 · Cited by 14 · see citing works
“We found that MED13L is a candidate for ASD [Iossifov et al., 2012, 2014, 2015], a condition characterized by a distinctive abnormal language profile [for review, see Benítez-Burraco and Murphy, 2016].”
BackgroundThiffault, I., Cadieux‐Dion, M., Farrow, E., Caylor, R. C., Miller, N., Soden, S. E., & Saunders, C. (2018) · Human Mutation · doi:10.1002/humu.23646 · Cited by 13 · see citing works
Mehinovic, E., Gray, T., Campbell, M. C., Ekholm, J. M., Wenger, A. M., Rowell, W. J., Grudo, A., Grimwood, J., Korlach, J., Gurnett, C. A., et al. (2022) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.62743 · Cited by 14 · see citing works
“Several other types of rare genetic variants have been implicated in autism including rare inherited variants (Iossifov et al., 2015; Krumm et al., 2015; Wilfert et al., 2021), recessive variants (Doan et al.”
BackgroundHuang, H., Cheng, S., Ding, M., Wen, Y. F., Ma, M., Zhang, L., Li, P., Cheng, B., Liang, X., Liu, L., et al. (2018) · Autism Research · doi:10.1002/aur.2048 · Cited by 14 · see citing works
“suggested that ANK2 was a strong candidate risk gene to ASD [Iossifov et al., 2015].”
BackgroundAnkyrin B promotes developmental spine regulation in the mouse prefrontal cortex
Murphy, K. E., Duncan, B. W., Sperringer, J. E., Zhang, E. Y., Haberman, V. A., Wyatt, E. V., & Maness, P. F. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad311 · Cited by 12 · see citing works
The DCIDE framework: systematic investigation of evolutionary hypotheses, exemplified with autism
Hunt, A., & Jaeggi, A. V. (2025) · Biological reviews/Biological reviews of the Cambridge Philosophical Society · doi:10.1111/brv.70010 · Cited by 14 · see citing works
Rethinking the fast-slow continuum of individual differencesPreprint
Giudice, M. D. (2019) · doi:10.31234/osf.io/4uhz8 · Cited by 92 · see citing works
“This distinction is consistent with the genetic evidence on the role of mutations in autism (Gardner et al., 2019; Iossifov et al., 2014, 2015; Ronemus et al., 2014), and is supported by convergent epidemiological data on paternal/maternal age, socioeconomic status, and so forth (details in Del…”
ResultCornejo, K. G., Venegas, A., Sono, M. H., Door, M., Gutierrez-Ruiz, B., Karabedian, L. B., Nandi, S. G., Hadisurya, M., Tao, W. A., Dykhuizen, E. C., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114877 · Cited by 15 · see citing works
Neurobiology of cognitive abilities in early childhood autism
Denisova, K. (2024) · JCPP Advances · doi:10.1002/jcv2.12214 · Cited by 13 · see citing works
“(Note, GABRB3 was identified by Iossifov and colleagues (Iossifov et al., 2015) to have a low LGD (likely gene disruptive) score of 0.08 ( < 0.1) (scores range between 0 and 1), indicating that a DN mutation on that gene is particularly likely; GABRB2 hasanLGDscoreof0.”
BackgroundInfluentialJURNAK, F. A. (2015) · Nutrition and Metabolic Insights · doi:10.4137/nmi.s29531 · Cited by 10 · see citing works
Enrichment of factors regulating canonical Wnt signaling among autism risk genes
Packer, A. I. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.228 · Cited by 9 · see citing works
Failure to attune to language predicts autism in high risk infants
Denisova, K. (2019) · Brain and Language · doi:10.1016/j.bandl.2019.04.002 · Cited by 9 · see citing works
“Guilt by association” is not competitive with genetic association for identifying autism risk genes
Gunning, M., & Pavlidis, P. (2021) · Scientific Reports · doi:10.1038/s41598-021-95321-y · Cited by 11 · see citing works
Measuring shared variants in cohorts of discordant siblings with applications to autism
Ye, K. Q., Iossifov, I. H., Levy, D., Yamrom, B., Buja, A., Krieger, A. Μ., & Wigler, M. H. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1700439114 · Cited by 9 · see citing works
“This hypothesis has statistical support from two recent analyses of the SSC (9, 10).”
BackgroundResultSelf-citationLin, Y., Rajadhyaksha, A. M., Potash, J. B., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/463547 · Cited by 10 · see citing works
Chen, L., Wang, W., Cai, W., Song, W., Qian, W., & Lin, G. N. (2021) · Scientific Reports · doi:10.1038/s41598-021-87632-x · Cited by 9 · see citing works
Developmental Gene Expression Differences between Humans and Mammalian ModelsPreprint
Cardoso-Moreira, M., Sarropoulos, I., Velten, B., et al. (2019) · bioRxiv · doi:10.1101/747782 · Cited by 76 · see citing works
“We also performed the analysis of genes associated with autism spectrum disorders using a larger dataset of autism associated genes (164 with dynamic temporal profiles out of 233; Iossifov et al., 2015) and obtained the same result (i.”
ResultPrediction of Response to Drug Therapy in Psychiatric Disorders
Stern, S., Linker, S. B., Vadodaria, K. C., Marchetto, M. C., & Gage, F. H. (2019) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.17304 · Cited by 8 · see citing works
Zhang, P., Omanska, A., Ander, B. P., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.29.486259 · Cited by 8 · see citing works
“99 as reported by 378 the Exome Aggregation Consortium (28), mutationally constrained genes(27), vulnerable ASD 379 genes(79), CHD8 targets(29), FMRP targets (80), syndromic and highly ranked (1 and 2) genes 380 from SFARI Gene database.”
BackgroundThe Unique Evolutionary Signature of Genes Associated with Autism Spectrum Disorder
Tsur, E., Friger, M. D., & Menashe, I. (2016) · Behavior Genetics · doi:10.1007/s10519-016-9804-4 · Cited by 8 · see citing works
“During the past decade, genetic studies have suggested hundreds of ASDsusceptibility genes, but only a few of these genes have been robustly associated with the disorder (Abrahams et al. 2013; Iossifov et al. 2015; Sanders et al. 2015) and mutations in these genes can explain ASD in only a portion of affected individu…”
Background
- Authors
- Iossifov, I., Levy, D., Allen, J., Ye, K., Ronemus, M., Lee, Y.-H., Yamrom, B., & Wigler, M.
- Affiliations
- Cold Spring Harbor Laboratory (US)
- Albert Einstein College of Medicine (US)
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724;
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2015-09-23
- Volume
- 112
- Issue
- 41
- Pages
- E5600-7
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4611648
- OpenAlex
- W1961487924
- Semantic Scholar
- 72f81b98f4b3861f39ce50b51ba3e5ca838b57a4
- Cited by
- 156
- References
- 21
- Citations by year
- 2026: 11 · 2025: 7 · 2024: 13 · 2023: 11 · 2022: 11 · 2021: 18 · 2020: 23 · 2019: 18 · 2018: 16 · 2017: 14 · 2016: 11 · 2015: 2
- FWCI
- 8.52
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
- Funders
- SFARI (SF235988, SF362665)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Keywords
- autism spectrum disorder, de novo mutations, mutational load, mother-to-child transmission, fecundity, intelligence quotient, exome sequencing
- MeSH terms
- Autistic Disorder, Child, Child, Preschool, Female, Gene Pool, Humans, Male, Models, Genetic, Mutation, Databases, Genetic, Exome
About these checks
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.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review