Getting to the cores of autism

Recessive variants account for up to 30% of cases in consanguineous families.

“Recessive variants account for a small fraction of idiopathic ASD (Gamsiz et al., 2013) and developmental delay, but they account for a larger proportion (up to 30%) of cases in consanguineous families (Martin et al., 2018).”

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Some ASD genetic risk comes from rare variants inherited from a mother or father.

“A portion of genetic risk for ASD consists of rare variants that are inherited from a mother or father (Fig. 1A).”

Large CNVs such as duplications of 15q11-13 and 16p11.2 and deletions of 15q11.2 can be transmitted from a parent with mild or no symptoms.

“These include duplications of 15q11–13 and 16p11.2 and deletions of 15q11.2 (Doornbos et al., 2009).”

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A portion of ASD genetic architecture consists of rare coding variants with incomplete penetrance inherited from parents who do not meet ASD criteria.

“Thus, a portion of the genetic architecture consists of rare coding variants with incomplete penetrance that are inherited from parents who do not meet criteria for ASD.”

A combined sample of 35,584 individuals, including 11,986 with ASD, raised the number of high-confidence ASD genes to 102.

“A recent study in a combined sample of 35,584 samples (11,986 with ASD), has brought the number of high confidence genes to 102 (Satterstrom et al., 2018).”

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Whole-genome analysis of structural variants in large samples has captured inherited variants including deletions disrupting individual genes or cis-regulatory elements.

“Recently, whole genome analysis of SVs in large samples has succeeded in capturing a broader array of inherited variants including deletions that disrupt individual genes or cis-regulatory elements (Brandler et al., 2018).”

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Genes such as GIGYF1, KDM6B, PTEN, ANK2, KMT5B, KMT2C, and CHD8 may have a more direct influence on social behavior.

“Fifty three genes had a greater frequency in ASD than in the broader category of Neurodevelopmental Disorders (NDDs), suggesting that genes such as GIGYF1, KDM6B, PTEN, ANK2, KMT5B, KMT2C, and CHD8 might have a more direct influence on social behavior.”

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Fifty-three genes were more frequent in ASD than in the broader category of neurodevelopmental disorders.

“Fifty three genes had a greater frequency in ASD than in the broader category of Neurodevelopmental Disorders (NDDs), suggesting that genes such as GIGYF1, KDM6B, PTEN, ANK2, KMT5B, KMT2C, and CHD8 might have a more direct influence on social behavior.”

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ASD susceptibility genes are interconnected within transcriptional and protein interaction networks.

“ASD susceptibility genes are interconnected at the level of transcriptional and protein networks, and many function as genetic regulators of neurodevelopment or synaptic proteins that regulate neural activity.”

• Also stated in: § The nature of gene action in ASDs · plain

  “As will be discussed in detail in the following section, multiple ASD genes are connected within transcriptional and protein interaction networks.”

Most germline mutations occur during mitotic division of spermatogonial cells, a process with a constant rate in the gonad.

“Most germline mutations happen during mitotic cell division of spermatogonial cells, a process that occurs at a constant rate in the gonad (Crow, 2000).”

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Applying TADA to exomes or whole genomes in large family samples is the most effective strategy for identifying ASD susceptibility genes.

“The application of this approach to exomes or whole genomes in large family samples has since become the most effective strategy for identifying ASD susceptibility genes (De Rubeis et al., 2014; Iossifov et al., 2014; Sanders et al., 2015; Satterstrom et al., 2018).”

• cites De Rubeis et al., 2014 sourceNot checked yet

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• cites Iossifov et al., 2014 sourceNot checked yet

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• cites Sanders et al., 2015 sourceNot checked yet

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Individuals carrying de novo mutations have lower non-verbal IQ than those who do not carry them.

“As would be expected for variants with large effects, subjects that carry de novo mutations have lower non-verbal IQs than subjects who do not (Iossifov et al., 2014).”

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Many ASD susceptibility genes act as regulators of neurodevelopment or encode synaptic proteins that control neural activity.

“ASD susceptibility genes are interconnected at the level of transcriptional and protein networks, and many function as genetic regulators of neurodevelopment or synaptic proteins that regulate neural activity.”

Recessive variants account for a small fraction of idiopathic ASD and developmental delay.

“Recessive variants account for a small fraction of idiopathic ASD (Gamsiz et al., 2013) and developmental delay, but they account for a larger proportion (up to 30%) of cases in consanguineous families (Martin et al., 2018).”

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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)”

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• cites Krumm et al., 2015 sourceNot checked yet

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These results support a joint contribution of multiple rare variants to risk for ASD and other neurodevelopmental disorders.

“These results are consistent with a joint contribution of multiple rare variants to risk for ASD and other NDDs.”

Bergen et al. showed that polygenic contribution in CNV carriers is inversely proportional to the effect size of the CNV.

“Bergen et al has shown that the polygenic contribution in CNV carriers is inversely proportional to the effect size of the CNV (Bergen et al., 2018), consistent with an attenuated contribution of common variation in subjects who carry a highly-penetrant rare variant.”

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Current GWAS data are consistent with a liability threshold model in which many risk alleles contribute additively to overall risk.

“Current data from GWAS is consistent with a liability threshold model, in which many risk alleles contribute additively to the overall risk.”

Individuals with ASD carrying de novo mutations have significantly increased ASD PRS compared to typically developing controls.

“A recent study reported that individuals with ASD that carry de novo mutations have significantly increased PRS for ASD compared to typically developing controls (Weiner et al., 2017).”

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Analysis of rare variants supports an oligogenic model in which clinical severity of known pathogenic mutations is influenced by the burden of additional rare variants.

“Analysis of rare variants in ASD and NDD cohorts has found evidence for an oligogenic model in which variation in the clinical severity of known pathogenic mutations is influenced by the genomic burden of additional rare variants.”

The determinants of psychiatric traits are multifactorial even when a large-effect variant is present.

“This suggests that the determinants of psychiatric traits are multifactorial even in the context of a large-effect variant.”

Estimates of ASD heritability explained by common SNPs range from 17% to 52%.

“Estimates of the heritability of ASD explained by common SNPs range from 17% (Autism Spectrum Disorders Working Group of The Psychiatric Genomics, 2017; Cross-Disorder Group of the Psychiatric Genomics et al., 2013) to 52% (Gaugler et al., 2014).”

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• cites Cross-Disorder Group of the Psychiatric Genomics et al., 2013Not checked yet

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• cites Gaugler et al., 2014 sourceNot checked yet

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There are likely thousands of loci with very small effects on ASD.

“However, there are likely to be thousands of loci with very small effects.”

For a 500 kb deletion of 16p12.1, carriers with developmental delay had an increased burden of secondary CNVs compared to controls.

“Deletion carriers with developmental delay had an increased burden of secondary CNVs compared to deletion carriers in controls.”

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The inverse relationship between polygenic contribution and CNV effect size is consistent with an attenuated contribution of common variation in carriers of highly penetrant rare variants.

“Bergen et al has shown that the polygenic contribution in CNV carriers is inversely proportional to the effect size of the CNV (Bergen et al., 2018), consistent with an attenuated contribution of common variation in subjects who carry a highly-penetrant rare variant.”

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A genetic effect from a single gene mutation can influence the function of other ASD genes and spread broadly through a gene regulatory network.

“Consequently, a genetic effect that originates from a single gene mutation has the potential to influence the function of other ASD genes, and can thereby fan out broadly through a gene regulatory network.”

Some ASD susceptibility genes encode RNA-binding proteins involved in posttranscriptional regulation of mRNA abundance, splicing, or translation.

“Some ASD susceptibility genes encode RBPs that are involved in posttranscriptional regulation of messenger RNA abundance, splicing or translation.”

Similar correlation between clinical severity and secondary rare variant number is observed for ASD subjects carrying gene-disrupting de novo mutations.

“Subsequent studies have shown that the clinical severity of subjects who carry CNVs at 1q21.1, 7q11.23 and 16p11.2 correlates with the number of secondary rare variants, and similar results have been observed for ASD subjects who carry gene disrupting de novo mutations (Pizzo et al., 2018).”

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Clinical severity of carriers of CNVs at 1q21.1, 7q11.23, and 16p11.2 correlates with the number of secondary rare variants.

“Subsequent studies have shown that the clinical severity of subjects who carry CNVs at 1q21.1, 7q11.23 and 16p11.2 correlates with the number of secondary rare variants, and similar results have been observed for ASD subjects who carry gene disrupting de novo mutations (Pizzo et al., 2018).”

Clinical outcomes of rare genetic disorders are influenced by rare variants in the genetic background.

“A series of studies have demonstrated that the clinical outcomes of rare genetic disorders are influenced by rare variants in the genetic background.”

Inactivating BCKDK mutations were identified in consanguineous families with autism, epilepsy, and intellectual disability.

“For example Novarino et al identified inactivating mutations in the gene Branched Chain Ketoacid Dehydrogenase Kinase (BCKDK) in consanguineous families with autism, epilepsy, and intellectual disability (Novarino et al., 2012).”

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Sequencing of consanguineous families has identified novel candidate genes associated with autism.

“Sequencing of consanguineous families has identified novel candidate genes associated with autism (Yu et al., 2013).”

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A mutation affecting a brain gene-expression regulator can have many downstream effects mediated by other regulatory genes in trans.

“For example, a mutation that impacts a protein that regulates gene expression in the brain can have numerous downstream effects that are mediated through other regulatory genes in trans (Fig 2A).”

Individuals with neurodevelopmental disorders carrying a reportable clinical diagnostic variant have significantly increased PRS.

“This study reported that individuals with NDDs who carry a reportable clinical diagnostic variant have a significantly increased PRS.”

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ASD genes show significant functional convergence within gene networks, synaptic function, and signaling pathways.

“Here we describe how ASD genes show significant functional convergence within the context of gene networks, synaptic function and signaling pathways, see Figure 3.”

DNA sequencing in consanguineous families is an effective approach for identifying ASD attributable to rare homozygous variants.

“DNA sequencing in such families is an effective approach for identifying cases of ASD that are attributable to rare homozygous variants (Morrow et al., 2008; Scott et al., 2016).”

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• cites Scott et al., 2016 sourceNot checked yet

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These observations support the view that developmental phenotypes associated with a CNV are attributable to dosage effects of multiple genes.

“These observations are consistent with developmental phenotypes associated with a CNV being attributable to the dosage effects of multiple genes.”

All three categories of genetic risk can have effects broadly distributed across a gene regulatory network.

“However, all 3 categories of genetic risk are similar in that their effects can also broadly distributed across a gene regulatory network.”

A subset of ASD susceptibility genes encode DNA-binding proteins and RNA-binding proteins.

“A subset of ASD susceptibility genes encode proteins that bind directly to DNA or RNA and are involved in the regulation of gene expression, referred to as DNA binding proteins (DBPs) and RNA binding proteins (RBPs).”

For most large CNVs, studies have not found evidence for a single driver gene.

“However, for the majority of large CNVs, studies have not found evidence for the existence of a single driver gene (De Rubeis et al., 2014; Iossifov et al., 2014).”

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• cites Iossifov et al., 2014 sourceNot checked yet

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A few known microdeletion syndromes have clinical features attributable to a major driver gene within the deleted region.

“There are a few known microdeletion syndromes where clinical features are attributable to a major driver gene within the region.”

The clinical outcome of individuals carrying a rare large-effect variant can be influenced by common polygenic variation.

“The clinical outcome of individuals that carry a rare variant of large effect can also be influenced by the background of common polygenic variation.”

ChIP-Seq of TBR1 in developing neocortex found that it binds next to high-confidence ASD genes more frequently than other brain-expressed transcription factors.

“Chromatin Immunoprecipitation Sequencing (ChIP-Seq) of TBR1 in the developing neocortex found that this protein binds next to high-confidence ASD genes more frequently than other transcription factors that are expressed in the brain (Notwell et al., 2016).”

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Polygenic risk is fundamentally different from rare variants of large effect.

“The nature of polygenic risk is fundamentally different from that of rare variants of large effect.”

ASD PRS correlates with higher educational attainment and IQ in the population.

“Surprisingly, multiple studies have found that PRS for ASD correlates with higher educational attainment and IQ in the population (Brainstorm Consortium et al., 2018), opposite to what has been reported for PRS of other neurodevelopmental disorders (Niemi et al., 2018; Sniekers et al., 2017).”

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Transgenic model organisms suggest that developmental phenotypes associated with CNVs are influenced by dosage effects of multiple genes.

“Evidence from transgenic model organisms suggests that developmental phenotypes associated with CNVs are influenced by the dosage effects of multiple genes.”

The correlation of ASD PRS with higher educational attainment and IQ is opposite to what has been reported for PRS of other neurodevelopmental disorders.

“Surprisingly, multiple studies have found that PRS for ASD correlates with higher educational attainment and IQ in the population (Brainstorm Consortium et al., 2018), opposite to what has been reported for PRS of other neurodevelopmental disorders (Niemi et al., 2018; Sniekers et al., 2017).”

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• cites Sniekers et al., 2017 sourceNot checked yet

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CHD8 binds and positively regulates other ASD genes.

“Similarly, the chromatin remodeling factor CHD8, binds and positively regulates other ASD genes (Cotney et al.; Sugathan et al.).”

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• cites Sugathan et al.Not checked yet

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Large pathogenic CNVs typically affect the copy number of dozens of genes.

“Large pathogenic CNVs typically affect the copy number of dozens of genes.”

If a CNV's influence on a trait is due to multiple genes, its effects on genetic regulatory networks are more complex than those of a monogenic mutation.

“If the influence of a CNV on a trait is attributable to multiple genes, this suggests that effects of the CNV on genetic regulatory networks could be to some degree more complex than the monogenic example described above.”

A large CNV contributes multiple rare hits that are distributed broadly across a gene regulatory network.

“In contrast to gene mutation in which the network level effects radiate outward from a single point, a large CNV contributes multiple rare “hits” that have direct effects that are distributed more broadly across a gene regulatory network (Fig 2B).”

A PRS constructed from previous ASD GWAS is significantly associated with ASD cases in independent cohorts.

“A PRS constructed from previous GWAS of ASD has been shown to be significantly associated with cases in independent cohorts (Grove et al., 2017).”

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Traits such as social motivation, anxiety, and aggression do not emerge directly from a handful of gene products.

“Traits like social motivation, anxiety and aggression don’t emerge directly from a handful of gene products.”

Upregulation of immune genes and downregulation of synaptic genes was observed in postmortem brain from idiopathic ASD.

“Upregulation of immune genes and downregulation of synaptic genes was observed in postmortem brain from idiopathic ASD (Voineagu et al., 2011), and this finding has been replicated in a larger ASD sample (Gupta et al., 2014).”

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Evidence for enrichment of ASD genes among genes dysregulated in iPSC models of CHD8 or FOXP1 was strongest for genes dysregulated in trans.

“Indeed, evidence for the enrichment of ASD genes amongi genes that are dysregulated in iPSC models of CHD8 (Sugathan et al., 2014) or FOXP1 (Araujo et al., 2015) was strongest for genes that were dysregulated in trans.”

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• cites Araujo et al., 2015 sourceNot checked yet

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A study compiling binding sites for 26 ASD-associated regulatory proteins reported that ASD genes enriched among these targets consist of other regulatory genes.

“By compiling the binding sites for 26 regulatory proteins associated with ASD, a recent study reported that the ASD genes that are enriched among these regulatory targets consist of other regulatory genes.”

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Mutations disrupting DNA-binding or RNA-binding proteins can directly affect regulation of many target genes in cis.

“The studies described above suggest that gene mutations that disrupt DBPs or RBPs can directly affect the regulation of numerous target genes in cis.”

Transcriptomic analysis of developing brain in transgenic mouse models of SETD5, FOXP1, and TBR1 suggests that mutations in these genes lead to dysregulation of ASD genes in trans.

“Similarly transcriptomic analysis of developing brain in transgenic mouse models of SETD5 (Pizzo et al., 2018), FOXP1 (Araujo et al., 2015), TBR1 (Notwell et al., 2016) suggests that mutations in these genes leads to the dysregulation of ASD genes in trans.”

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• cites Araujo et al., 2015 sourceNot checked yet

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• cites Notwell et al., 2016 sourceNot checked yet

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The same study did not find significant enrichment for ASD genes involved in neuronal communication.

“By contrast, they did not find a significant enrichment for ASD genes involved in “neuronal communication” (Satterstrom et al., 2018).”

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Current knowledge of the neurobiological basis of ASD is derived almost exclusively from studies of rare variants.

“Our current knowledge of the neurobiological basis of ASD is derived almost exclusively from studies of rare variants.”

Diversity of clinical phenotypes across the autism spectrum is in part a reflection of underlying genetic heterogeneity.

“The diversity of clinical phenotypes across the autism spectrum is in part a reflection of the underlying genetic heterogeneity of ASD (McClellan and King, 2010).”

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Coexpression of genes within ASD CNVs is enriched in the developing cortex.

“Likewise coexpression of genes within ASD CNVs was reported to be enriched in the developing cortex (Lin et al., 2015).”

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Transcriptome analysis of NPCs from idiopathic ASD with macrocephaly found differentially expressed genes enriched for ASD genes and genes within ASD-associated CNVs.

“Transcriptome analysis of NPCs derived from idiopathic ASD with macrocephaly found that differentially expressed genes were significantly enriched for ASD genes and genes within ASD-associated CNVs (Marchetto et al., 2017).”

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Loss of SETD5 results in activation of neuronal genes and Wnt signaling in mouse fetal tissue and human cells.

“Recent studies of SETD5 in mouse fetal tissue and human cells have reported that loss of SETD5 results in the activation of neuronal genes and Wnt signaling (Deliu et al., 2018).”

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Syndromes caused by disruption of mTOR signaling genes including PTEN, TSC1, TSC2, and NF1 are frequently associated with brain overgrowth and ASD.

“Early studies made the observation that syndromes caused by the disruption of genes involved in mTOR signaling, including PTEN, TSC1, TSC2, and NF1 were frequently associated with brain overgrowth and ASD (Wang and Doering, 2013).”

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Common variation in ASD preferentially impacts genes expressed in the fetal cortex during embryonic development.

“Thus, common variation in ASD also preferentially impacts genes expressed in the fetal cortex during embryonic development.”

These observations highlight the relevance of early fetal brain development in ASD pathophysiology.

“Taken together, these observations highlight the relevance of early fetal brain development in the pathophysiology of ASD.”

Psychiatric traits cannot be easily reduced to dysfunction in a single biological pathway.

“Unlike some other complex traits, for example serum lipid levels which are controlled by a set of proteins involved in lipid transport and metabolism (Cox and Garcia-Palmieri, 1990), psychiatric traits cannot be easily reduced to dysfunction in a single biological pathway.”

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Current understanding of ASD genetics is generally compatible with the omnigenic model.

“From the perspective of both rare variants and common variants, our current understanding of the genetics of ASD is generally compatible with an “omnigenic” model of gene action recently proposed by Boyle and Pritchard (Boyle et al.).”

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The finding of immune gene upregulation and synaptic gene downregulation in idiopathic ASD was replicated in a larger ASD sample.

“Upregulation of immune genes and downregulation of synaptic genes was observed in postmortem brain from idiopathic ASD (Voineagu et al., 2011), and this finding has been replicated in a larger ASD sample (Gupta et al., 2014).”

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It seems unlikely that common variant associations in ASD will tell a different story from rare variants.

“However, it is not yet clear whether common variant associations in ASD will tell a different story. Indeed this seems unlikely.”

From the perspective of ASD, major predictions of the omnigenic model hold true.

“From the perspective of ASD, major predictions of the model hold true.”

Regulation of cell-proliferation pathways in the developing brain is another point of convergence in ASD, specifically mTOR, MAPK, and Wnt signaling.

“The regulation of cell-proliferation pathways in the developing brain has become another point of convergence in ASD (Ernst, 2016), specifically mammalian target of rapamycin (mTOR), mitogen activated protein kinase (MAPK) and Wnt signaling.”

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Dysregulation of Wnt signaling has been reported in multiple transgenic models of ASD genes.

“Dysregulation of Wnt signaling has been reported in multiple transgenic models of ASD genes.”

Gene expression alterations in idiopathic ASD overlap with developmentally regulated genes implicated in cortical patterning, cell cycle, proliferation, and neural differentiation.

“Gene expression alterations from in idiopathic ASD overlap with developmentally regulated genes implicated on cortical patterning, cell cycle, proliferation and neural differentiation.”

The effects of a rare gene mutation can be propagated further by regulatory proteins.

“The effects of a rare gene mutation can be propagated further by regulatory proteins.”

Brain organoids can be used to dynamically study neural proliferation of progenitor cells, migration, differentiation, and maturation.

“Brain organoids can be used to dynamically study neural proliferation of progenitor cells, migration, differentiation and maturation (Trujillo et al., 2018).”

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Past decade efforts to define genetic underpinnings of psychiatric endophenotypes were largely unsuccessful in mapping genes to endophenotypes.

“During the past decade, significant efforts were undertaken to define the genetic underpinnings of psychiatric “endophenotypes” (Iacono et al., 2014). These studies, which were large for studies that apply biometrics like electroencephalography (EEG) but small by GWAS standards, were largely unsuccessful in achieving the goal of mapping genes to endophenotypes.”

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Gene discoveries have sped up progress toward precision psychiatric medicine by supplying knowledge that can support clinical sequencing and new ASD treatments.

“Gene discoveries have accelerated this process, by providing a foundation of knowledge that will form the basis for clinical sequencing and the development of new treatment strategies for ASD.”

Such differences may provide a way to identify distinct molecular subtypes of ASD.

“At the same time there are measurable differences in phenotypic expression between different genetic disorders, which can serve as windows into distinct molecular subtypes of ASD.”

The International Brain Behavior Consortium has started systematically using a set of dimensional psychopathology measures across several genetic disorders, especially high-risk CNVs.

“For instance, the International Brain Behavior Consortium (IBBC) has begun to apply a battery of dimensional measures of psychopathology systematically across multiple genetic disorders (Gur et al., 2017), with a particular focus on CNVs that carry significant risk.”

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At multiple loci, reciprocal deletions and duplications are linked to opposite brain phenotypes in circuits for social cognition, language, and reward.

“For example, reciprocal deletions of duplications of multiple loci associate with opposing brain phenotypes in neural circuits involved in social cognition, language and reward (Deshpande and Weiss, 2018; Lin et al., 2017; Maillard et al., 2015).”

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Studies of cognition and language in 16p11.2 reciprocal deletion and duplication carriers report opposite effects on particular language skills: deletion carriers perform worse and duplication carriers perform better than IQ-matched controls.

“Cognitive and language studies in carriers of the reciprocal deletions and duplication of 16p11.2 have reported mirror effects on specific linguistic skills, deletion carriers having reduced performance and and duplication carriers having greater performance than IQ-matched controls (Hippolyte et al., 2016).”

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Reductions in neurite outgrowth, dendritic arborization, and excitatory synapses are commonly observed in cellular models of gene mutation, including SHANK3, FMR1, and CACNA1C.

“Reductions in neurite outgrowth, dendritic arborization and excitatory synapses are neuronal phenotypes that have been commonly observed in cellular models of gene mutation, including models of SHANK3 (Shcheglovitov et al., 2013; Yi et al., 2016), FMR1 (Doers et al., 2014) and CACNA1C (Krey et al., 2013).”

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• cites Yi et al., 2016Not checked yet

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• cites Doers et al., 2014 sourceNot checked yet

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Reciprocal deletions and duplications at 1q21.1 and 16p11.2 have opposite effects on brain growth.

“For example for CNVs at two loci, 1q21.1 and 16p11.2, reciprocal deletions and duplications have opposite effects on brain growth (Malhotra and Sebat, 2012).”

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Different genetic disorders show measurable differences in how phenotypes are expressed.

“At the same time there are measurable differences in phenotypic expression between different genetic disorders, which can serve as windows into distinct molecular subtypes of ASD.”

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• cites Maillard et al., 2015 sourceNot checked yet

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Cellular models of MECP2 gain of function exhibit opposite effects of increased synapses and dendrites.

“Importantly, cellular models of the reciprocal MECP2 gain of function (MECP2 duplication syndrome, (Lugtenberg et al., 2009) exhibit the opposite effects of increased synapses and dendrites (Nageshappa et al., 2016).”

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The lack of success in mapping genes to psychiatric endophenotypes is unsurprising because endophenotypes themselves are complex traits.

“This is unsurprising in retrospect given that the endophenotypes themselves were complex traits.”

Existing large-scale neuroimaging and health-record cohorts, along with projects measuring dimensional psychiatric traits in large and rare-disorder samples, make reverse-genetic studies feasible.

“Large cohort studies of neuroimaging (Franke et al., 2016) and medical health information (Collins and Varmus, 2015) and efforts to define dimensional psychiatric traits in large samples (https://bit.ly/2qTsged) and in rare genetic disorders (https://bit.ly/2VYSk1O) are providing opportunities conduct such studies.”

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• cites Collins and Varmus, 2015 sourceNot checked yet

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Human clinical studies have robustly found significantly accelerated brain overgrowth during the first three years of life in a subset of ASD cases.

“A robust finding from human clinical studies of ASD has been the observation of significantly accelerated brain overgrowth during the first three years of life in a subset of cases (Courchesne et al.).”

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A major difficulty for rare mutations is recruiting enough participants who share a particular genetic disorder.

“For rare mutations, a key challenge is in obtaining a large sample of subjects with a specific genetic disorder.”

Large cohorts are being assembled for the most common genetic disorders.

“Recruitment of large cohorts is being achieved for the most frequent genetic disorders (D’Angelo et al.; Gur et al.; Simons VIP Consortium).”

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Electrophysiological behavior of neurons is a readout that could potentially distinguish genes with different effects on neural activity.

“Electrophysiological behavior of neurons thus represent a readout that could potentially distinguish genes with different effects on neural activity.”

The genotype-phenotype specificity seen in pathways and in molecular and cellular phenotypes may also apply to human psychiatric traits.

“This finding highlights the importance of fine-grained dimensional phenotyping, and further suggests that the specificity of genotype-phenotype relationships, which are evident at the level of pathways and molecular and cellular phenotypes can be extended to human psychiatric traits.”

Neuronal models of SHANK2, CNTNAP5, and EHMT1 display hyperconnectivity.

“Other studies have reported that neuronal models of SHANK2 (Zaslavsky et al., 2019), CNTNAP5 and EHMT1 (Deneault et al., 2019a) display hyperconnectivity.”

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• cites Deneault et al., 2019aNot checked yet

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In a systematic screen of ten ASD susceptibility genes using CRISPR/Cas9 iPSC lines and isogenic controls, patch-clamp recordings detected reduced EPSPs in a subset including ATRX, AFF2, KCNQ2, SCN2A, and ASTN2.

“In a systematic screen of ten ASD susceptibility genes (AFF2/FMR2, ANOS1, ASTN2, ATRX, CACNA1C, CHD8, DLGAP2, KCNQ2, SCN2A, TENM1) using CRISPR/Cas9-created iPSC lines and isogenic controls (Deneault et al., 2018), patch-clamp recordings detected reduced excitatory postsynaptic potentials (EPSPs) in a subset of gene models including ATRX, AFF2, KCNQ2, SCN2A, and ASTN2.”

• cites Deneault et al., 2018 sourceNot checked yet

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A key advantage of human cellular models is the ability to model CNVs or gene mutations in isogenic cell lines or naturally occurring variation in patient-derived lines.

“A key advantage of human cellular models is the ability to model the effects of CNVs or gene mutations in isogenic cell lines (Deneault et al., 2019b) or to model naturally occurring variation in cell lines derived from patients (Chailangkarn et al.).”

• cites Deneault et al., 2019bNot checked yet

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• cites Chailangkarn et al.Not checked yet

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The way clinical phenotypes unfold over development in CNV carriers appears similar to that in idiopathic populations.

“Results suggest that the developmental course of clinical phenotypic expression of CNV carriers resembles that of idiopathic populations (Monks et al., 2014).”

• cites Monks et al., 2014 sourceNot checked yet

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These results suggest that standard assays for cell proliferation and differentiation could detect genetic effects on development in specific gene models.

“These results suggest that standard assays for cell proliferation and differentiation could detect genetic effects on development in specific gene models.”