Cited by 998Autism Spectrum Disorder ResearchGenetics and Neurodevelopmental DisordersGenomic variations and chromosomal abnormalities

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Convergence of Genes and Cellular Pathways Dysregulated in Autism Spectrum Disorders

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Pinto, Dalila, Delaby, Elsa, Merico, Daniele, Barbosa, Mafalda, Merikangas, Alison, Klei, Lambertus, Thiruvahindrapuram, Bhooma, Xu, Xiao, Ziman, Robert, Wang, Zhuozhi, Vorstman, Jacob A.S., Thompson, Ann, Regan, Regina, Pilorge, Marion, Pellecchia, Giovanna, Pagnamenta, Alistair T., Oliveira, Bárbara, Marshall, Christian R., Magalhaes, Tiago R., Lowe, Jennifer K., Howe, Jennifer L., Griswold, Anthony J., Gilbert, John, Duketis, Eftichia, Dombroski, Beth A., De Jonge, Maretha V., Cuccaro, Michael, Crawford, Emily L., Correia, Catarina T., Conroy, Judith, Conceição, Inês C., Chiocchetti, Andreas G., Casey, Jillian P., Cai, Guiqing, Cabrol, Christelle, Bolshakova, Nadia, Bacchelli, Elena, Anney, Richard, Gallinger, Steven, Cotterchio, Michelle, Casey, Graham, Zwaigenbaum, Lonnie, Wittemeyer, Kerstin, Wing, Kirsty, Wallace, Simon, van Engeland, Herman, Tryfon, Ana, Thomson, Susanne, Soorya, Latha, Rogé, Bernadette, Roberts, Wendy, Poustka, Fritz, Mouga, Susana, Minshew, Nancy, McInnes, L. Alison, McGrew, Susan G., Lord, Catherine, Leboyer, Marion, Le Couteur, Ann S., Kolevzon, Alexander, Jiménez González, Patricia, Jacob, Suma, Holt, Richard, Guter, Stephen, Green, Jonathan, Green, Andrew, Gillberg, Christopher, Fernandez, Bridget A., Duque, Frederico, Delorme, Richard, Dawson, Geraldine, Chaste, Pauline, Café, Cátia, Brennan, Sean, Bourgeron, Thomas, Bolton, Patrick F., Bölte, Sven, Bernier, Raphael, Baird, Gillian, Bailey, Anthony J., Anagnostou, Evdokia, Almeida, Joana, Wijsman, Ellen M., Vieland, Veronica J., Vicente, Astrid M., Schellenberg, Gerard D., Pericak-Vance, Margaret, Paterson, Andrew D., Parr, Jeremy R., Oliveira, Guiomar, Nurnberger, John I., Monaco, Anthony P., Maestrini, Elena, Klauck, Sabine M., Hakonarson, Hakon, Haines, Jonathan L., Geschwind, Daniel H., Freitag, Christine M., Folstein, Susan E., Ennis, Sean, Coon, Hilary, Battaglia, Agatino, Szatmari, Peter, Sutcliffe, James S., Hallmayer, Joachim, Gill, Michael, Cook, Edwin H., Buxbaum, Joseph D., Devlin, Bernie, Gallagher, Louise, Betancur, Catalina, Scherer, Stephen W.·2014·The American Journal of Human Genetics

Abstract

Rare copy-number variation (CNV) is an important source of risk for autism spectrum disorders (ASDs). We analyzed 2,446 ASD-affected families and confirmed an excess of genic deletions and duplications in affected versus control groups (1.41-fold, p = 1.0 × 10(-5)) and an increase in affected subjects carrying exonic pathogenic CNVs overlapping known loci associated with dominant or X-linked ASD and intellectual disability (odds ratio = 12.62, p = 2.7 × 10(-15), ∼3% of ASD subjects). Pathogenic CNVs, often showing variable expressivity, included rare de novo and inherited events at 36 loci, implicating ASD-associated genes (CHD2, HDAC4, and GDI1) previously linked to other neurodevelopmental disorders, as well as other genes such as SETD5, MIR137, and HDAC9. Consistent with hypothesized gender-specific modulators, females with ASD were more likely to have highly penetrant CNVs (p = 0.017) and were also overrepresented among subjects with fragile X syndrome protein targets (p = 0.02). Genes affected by de novo CNVs and/or loss-of-function single-nucleotide variants converged on networks related to neuronal signaling and development, synapse function, and chromatin regulation.

Overview

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Written from the paper’s full text.

TL;DR

This study analyzed rare copy-number variation (CNV) in 2,446 autism spectrum disorder (ASD)-affected families and 2,640 controls, confirming excess genic CNV burden and enrichment of pathogenic CNVs at ASD/intellectual disability loci. Genes affected by de novo CNVs and loss-of-function single-nucleotide variants converged on neuronal signaling, synapse, and chromatin-regulation networks.

Key findings

  • Affected subjects showed a 1.41-fold increase in genes affected by rare CNVs versus controls (empirical p = 1 × 10−5). Pathogenic CNVs overlapping autosomal-dominant or X-linked ASD/ID genes and loci were found in 2.8% (60/2,147) of European-ancestry affected subjects (OR = 12.62, 95% CI = 5.44–29.27, p = 2.74 × 10−15); across all ancestries, pathogenic CNVs were identified in ∼3.3% (82/2,446).
  • Among 2,096 trios, 102 rare de novo CNVs were found in 99 affected subjects, with 4.7% of trios having at least one de novo CNV. De novo events averaged 1.17 Mb versus 0.67 Mb in unaffected siblings (p = 0.01) and 0.55 Mb in control trios (p = 0.01), and affected 3.8-fold more genes than control de novo CNVs.
  • Females were more likely to carry highly penetrant pathogenic CNVs (male-to-female ratio 2:1 versus 6:1 among all affected subjects; p = 0.017) and were overrepresented among subjects with exonic deletions overlapping FMRP targets (17 females in 73 affected subjects, 1.98-fold more than males, p = 0.022).
  • Network analyses linked de novo CNVs and de novo LoF SNVs to neuronal signaling and development, synapse function, and chromatin regulation: a NETBAG network of 113 genes (global cluster p = 0.02) and a DAPPLE protein-protein interaction network of 151 genes with 1.5-fold more direct interactions than expected (p < 0.001).

Methods

  • The Autism Genome Project sample included 2,446 ASD-affected families passing QC (from 2,845 families and 9,050 individuals) and 2,640 unrelated European-ancestry controls; all were genotyped on Illumina 1M arrays and analyzed with the same QC and CNV pipeline.
  • CNV burden was compared between affected subjects and controls with Fisher’s exact tests, PLINK, R, and custom scripts; de novo and clinically relevant CNVs were validated by quantitative PCR, MLPA, and/or long-range PCR.
  • Analyses included gene-list burden tests (ASD/ID loci, BrainSpan brain-expressed genes, postsynaptic density genes, FMRP targets, HPO/MPO neurological genes, haploinsufficiency probability), logit models for multigene burden, and functional enrichment/network analyses using NETBAG and DAPPLE.

Limitations

  • The paper states that many subjects were assessed with clinical diagnostic methods and excluded if positive, and individuals with known congenital malformations or dysmorphic features were not enrolled, so the etiologic yield is likely an underestimate.
  • The paper notes that some CNVs were seen in a small fraction of controls, consistent with variable expressivity and/or incomplete penetrance.
  • Evident from the text: main analyses were restricted to European-ancestry subjects, and CNV detection relied on array-based calls rather than sequence data.

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Integrity signals

Registry

Crossref · 10.1016/j.ajhg.2014.03.018

Cites

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Statistics

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Figures

Figure 1 CNV Burden in Genes and Loci Implicated in ASD and/or ID CNV data from 2,147 European affected subjects and 2,640 European control subjects were analyzed for overlap with genes and loci implicated in ASD and/or ID (results including non-European affected and control subjects are shown in Figure S1). Only CNVs affecting autosomal-dominant and X-linked dominant genes or loci in both genders (132 genes, 56 loci), as well as X-linked recessive genes or loci in males (52 genes, 2 loci), were considered (“all CNV”). Exonic ≥30 kb CNVs affecting an ASD- and/or ID-associated gene or overlapping at least 50% of the target loci were selected for further analysis. Rare CNVs were divided into three categories—pathogenic, uncertain clinical significance, or benign—without regard to affected status. (A) Percentage of individuals with CNVs overlapping genes and loci implicated in ASD and/or ID (“all CNV”), pathogenic CNVs, uncertain CNVs, or benign CNVs; and OR in affected and control subjects. (B) Percentage of individuals with pathogenic deletions or duplications and OR in affected and control subjects. (C) Fraction of de novo CNVs in each category of affected subjects.
Figure 1 CNV Burden in Genes and Loci Implicated in ASD and/or ID CNV data from 2,147 European affected subjects and 2,640 European control subjects were analyzed for overlap with genes and loci implicated in ASD and/or ID (results including non-European affected and control subjects are shown in Figure S1). Only CNVs affecting autosomal-dominant and X-linked dominant genes or loci in both genders (132 genes, 56 loci), as well as X-linked recessive genes or loci in males (52 genes, 2 loci), were considered (“all CNV”). Exonic ≥30 kb CNVs affecting an ASD- and/or ID-associated gene or overlapping at least 50% of the target loci were selected for further analysis. Rare CNVs were divided into three categories—pathogenic, uncertain clinical significance, or benign—without regard to affected status. (A) Percentage of individuals with CNVs overlapping genes and loci implicated in ASD and/or ID (“all CNV”), pathogenic CNVs, uncertain CNVs, or benign CNVs; and OR in affected and control subjects. (B) Percentage of individuals with pathogenic deletions or duplications and OR in affected and control subjects. (C) Fraction of de novo CNVs in each category of affected subjects.CC BY-NC-ND · PubMed Central
Figure 2 All Pathogenic CNVs Identified in Affected Subjects CNVs overlapping genes and loci implicated in ASD and/or ID in 2,446 affected subjects irrespective of ancestry, plus chromosomal abnormalities, other large rare de novo events, and further experimentally validated CNVs < 30 kb. Pathogenic CNVs identified in affected subjects (84 CNVs in 82 probands) were divided into different categories: CNVs disrupting genes implicated in ASD and/or ID, genomic disorders with recurrent breakpoints, genomic disorders with nonrecurrent breakpoints, chromosomal abnormalities, and other rare, large de novo CNVs. (A) Pie chart displaying the proportion for each of these categories. The number of events and inheritance are in parentheses. (B) Percentage of probands with no ID or with nonsyndromic ASD among carriers of pathogenic CNVs. (C) Distribution of de novo and inherited deletions and duplications in all CNVs versus in pathogenic CNVs in affected subjects. (D) Size distribution of pathogenic CNVs. (E) Gender distribution in all probands (n = 2,446) versus in probands with autosomal pathogenic CNVs (n = 72). Autosomal pathogenic CNVs were partitioned into two categories: highly penetrant CNVs (n = 21) and pathogenic CNVs with variable expressivity and/or incomplete penetrance (n = 48). The male-to-female ratio is shown above each group. The number of affected subjects is shown at the bottom of each bar. The proportion of females was increased among carriers of pathogenic CNVs associated with high penetrance.
Figure 2 All Pathogenic CNVs Identified in Affected Subjects CNVs overlapping genes and loci implicated in ASD and/or ID in 2,446 affected subjects irrespective of ancestry, plus chromosomal abnormalities, other large rare de novo events, and further experimentally validated CNVs < 30 kb. Pathogenic CNVs identified in affected subjects (84 CNVs in 82 probands) were divided into different categories: CNVs disrupting genes implicated in ASD and/or ID, genomic disorders with recurrent breakpoints, genomic disorders with nonrecurrent breakpoints, chromosomal abnormalities, and other rare, large de novo CNVs. (A) Pie chart displaying the proportion for each of these categories. The number of events and inheritance are in parentheses. (B) Percentage of probands with no ID or with nonsyndromic ASD among carriers of pathogenic CNVs. (C) Distribution of de novo and inherited deletions and duplications in all CNVs versus in pathogenic CNVs in affected subjects. (D) Size distribution of pathogenic CNVs. (E) Gender distribution in all probands (n = 2,446) versus in probands with autosomal pathogenic CNVs (n = 72). Autosomal pathogenic CNVs were partitioned into two categories: highly penetrant CNVs (n = 21) and pathogenic CNVs with variable expressivity and/or incomplete penetrance (n = 48). The male-to-female ratio is shown above each group. The number of affected subjects is shown at the bottom of each bar. The proportion of females was increased among carriers of pathogenic CNVs associated with high penetrance.CC BY-NC-ND · PubMed Central
Figure 3 Enrichment of Functional Gene Sets Affected by Rare Exonic CNVs in Affected versus Control Subjects Overrepresentation of deletions (A) and duplications (B) in various functional gene sets. ORs, with 95% CIs, and the percentages of affected subjects (n = 1,486) and control subjects (n = 1,820) with exonic CNVs overlapping genes are given for the following gene sets: (1) highly-brain-expressed genes (log(RPKM) > 4.5, BrainSpan; n = 5,610); (2) functionally characterized control genes not expressed in the brain (log(RPKM) < 1, BrainSpan; n = 5,410); (3) PSD genes (n = 1,453);33 (4) FMRP interactors (n = 842);34 (5) genes associated with neurological phenotypes compiled from the HPO and MPO (n = 3,112); (6) genes as described in (5) but filtered for autosomal-dominant genes (n = 739); and (7) genes grouped by their pHI35 into three subgroups: pHI > 0.15 (n = 8,862), pHI > 0.35 (n = 4,136,) and pHI > 0.55 (n = 2,214). Genes with a pHI > 0.35 were considered haploinsufficient. The p values for affected and control subjects were estimated with two-tailed Fisher’s exact tests (∗p < 0.01, ∗∗p < 0.001, ∗∗∗p < 0.0001). (C–D) Pattern of increased burden as the number of brain-expressed genes affected by deletions (C) or duplications (D) increased. The percentages of affected and control subjects with CNVs overlapping genes are shown for deletions and duplications separately. For estimating the expected ORs (stars), a logit model of case status (affected or control) was fit to covariates, namely CNV status, the number of genes covered by each CNV, and their average brain expression levels (neocortex, BrainSpan). See Tables S11A–S11E for the results of alternative models, all of which showed that ASD risk increased as a function of the number of brain-expressed genes affected by a CNV, even after within-subject dependency of CNVs was accounted for.
Figure 3 Enrichment of Functional Gene Sets Affected by Rare Exonic CNVs in Affected versus Control Subjects Overrepresentation of deletions (A) and duplications (B) in various functional gene sets. ORs, with 95% CIs, and the percentages of affected subjects (n = 1,486) and control subjects (n = 1,820) with exonic CNVs overlapping genes are given for the following gene sets: (1) highly-brain-expressed genes (log(RPKM) > 4.5, BrainSpan; n = 5,610); (2) functionally characterized control genes not expressed in the brain (log(RPKM) < 1, BrainSpan; n = 5,410); (3) PSD genes (n = 1,453);33 (4) FMRP interactors (n = 842);34 (5) genes associated with neurological phenotypes compiled from the HPO and MPO (n = 3,112); (6) genes as described in (5) but filtered for autosomal-dominant genes (n = 739); and (7) genes grouped by their pHI35 into three subgroups: pHI > 0.15 (n = 8,862), pHI > 0.35 (n = 4,136,) and pHI > 0.55 (n = 2,214). Genes with a pHI > 0.35 were considered haploinsufficient. The p values for affected and control subjects were estimated with two-tailed Fisher’s exact tests (∗p < 0.01, ∗∗p < 0.001, ∗∗∗p < 0.0001). (C–D) Pattern of increased burden as the number of brain-expressed genes affected by deletions (C) or duplications (D) increased. The percentages of affected and control subjects with CNVs overlapping genes are shown for deletions and duplications separately. For estimating the expected ORs (stars), a logit model of case status (affected or control) was fit to covariates, namely CNV status, the number of genes covered by each CNV, and their average brain expression levels (neocortex, BrainSpan). See Tables S11A–S11E for the results of alternative models, all of which showed that ASD risk increased as a function of the number of brain-expressed genes affected by a CNV, even after within-subject dependency of CNVs was accounted for.CC BY-NC-ND · PubMed Central
Figure 4 Functional ASD Maps (A) Gene-set enrichment for rare exonic deletions (de novo and inherited) in affected versus control subjects. Enrichment results were mapped as a network of gene sets (nodes) related by mutual overlap (edges). Node size is proportional to the gene-set size, and edge thickness scales with the number of genes overlapping between sets. Only gene sets enriched in affected subjects with a FDR ≤ 20% are shown; gene sets are colored by different red intensity scales on the basis of their FDR. The node stroke color (orange or purple) indicates whether the gene set is also enriched with genes known to cause ASD and/or ID. Groups of functionally related gene sets are circled and labeled (groups are filled green or blue circles; subgroups are dashed lines), and the functions of prominent clusters are shown. (B) Network of genes affected by rare de novo CNVs in affected subjects. Shown are NETBAG results from the analysis of 102 rare de novo CNVs (11 large de novo chromosome abnormalities were not considered; Table S1C), representing 75 nonredundant genic CNV regions. Nodes in the network correspond to genes, and edges correspond to interactions. Node sizes are proportional to the gene’s contribution to the overall cluster score. Edge widths are proportional to the prior likelihood that the two corresponding genes contribute to a shared genetic phenotype. Nodes are colored on the basis of whether genes show prenatal- or postnatal-biased brain expression, or have no biased expression, in an analysis of 12 developmental stages of the BrainSpan data set (Figure S4). Shaded ovals represent enriched biological functions (Tables S14A–S14E), and their colors represent functional themes shared among Figures 4A, 4B, and 5B.
Figure 4 Functional ASD Maps (A) Gene-set enrichment for rare exonic deletions (de novo and inherited) in affected versus control subjects. Enrichment results were mapped as a network of gene sets (nodes) related by mutual overlap (edges). Node size is proportional to the gene-set size, and edge thickness scales with the number of genes overlapping between sets. Only gene sets enriched in affected subjects with a FDR ≤ 20% are shown; gene sets are colored by different red intensity scales on the basis of their FDR. The node stroke color (orange or purple) indicates whether the gene set is also enriched with genes known to cause ASD and/or ID. Groups of functionally related gene sets are circled and labeled (groups are filled green or blue circles; subgroups are dashed lines), and the functions of prominent clusters are shown. (B) Network of genes affected by rare de novo CNVs in affected subjects. Shown are NETBAG results from the analysis of 102 rare de novo CNVs (11 large de novo chromosome abnormalities were not considered; Table S1C), representing 75 nonredundant genic CNV regions. Nodes in the network correspond to genes, and edges correspond to interactions. Node sizes are proportional to the gene’s contribution to the overall cluster score. Edge widths are proportional to the prior likelihood that the two corresponding genes contribute to a shared genetic phenotype. Nodes are colored on the basis of whether genes show prenatal- or postnatal-biased brain expression, or have no biased expression, in an analysis of 12 developmental stages of the BrainSpan data set (Figure S4). Shaded ovals represent enriched biological functions (Tables S14A–S14E), and their colors represent functional themes shared among Figures 4A, 4B, and 5B.CC BY-NC-ND · PubMed Central
Figure 5 Genes Affected by CNVs and SNVs Converge on Functional Gene Networks (A) Venn diagram showing the overview of 151 genes resulting from a DAPPLE analysis of 336 unique genes. A similar diagram of DAPPLE input genes is shown in Figure S5. For the DAPPLE analysis, we compiled the following lists of genes: (1) 113 genes identified from our de novo CNVs by NETBAG; (2) 122 genes with de novo LoF SNVs from four published exome sequencing studies;7–10 (3) 31 genes with hemizygous LoF SNVs on the X chromosome of male ASD subjects and not observed in male control subjects;16 and (4) 92 ASD-implicated genes previously described as autosomal dominant, X-linked dominant, or X-linked recessive in males.18 (B) A DAPPLE network of 151 genes (Table S15) from the genes in (A) shows direct interactions between associated proteins according to the InWeb database. Nodes represent genes and are colored according to gene-set membership depicted in (A): genes identified from our de novo CNVs by NETBAG (red nodes), genes affected by de novo LoF SNVs from published exome sequencing studies (blue nodes), genes affected by hemizygous LoF SNVs on the X chromosome of males (white nodes), and genes known to be implicated in ASD (yellow nodes). Other node colors (orange, purple, green, dark yellow, or dark purple) correspond to genes present in two or more lists. Edges represent significant direct protein-protein interactions (as defined by a common interactor binding degree of 2) in the InWeb database. Shaded ovals represent enriched biological functions common among 10% or more genes in the network, and their colors represent functional themes shared among Figures 4A, 4B, and 5B.
Figure 5 Genes Affected by CNVs and SNVs Converge on Functional Gene Networks (A) Venn diagram showing the overview of 151 genes resulting from a DAPPLE analysis of 336 unique genes. A similar diagram of DAPPLE input genes is shown in Figure S5. For the DAPPLE analysis, we compiled the following lists of genes: (1) 113 genes identified from our de novo CNVs by NETBAG; (2) 122 genes with de novo LoF SNVs from four published exome sequencing studies;7–10 (3) 31 genes with hemizygous LoF SNVs on the X chromosome of male ASD subjects and not observed in male control subjects;16 and (4) 92 ASD-implicated genes previously described as autosomal dominant, X-linked dominant, or X-linked recessive in males.18 (B) A DAPPLE network of 151 genes (Table S15) from the genes in (A) shows direct interactions between associated proteins according to the InWeb database. Nodes represent genes and are colored according to gene-set membership depicted in (A): genes identified from our de novo CNVs by NETBAG (red nodes), genes affected by de novo LoF SNVs from published exome sequencing studies (blue nodes), genes affected by hemizygous LoF SNVs on the X chromosome of males (white nodes), and genes known to be implicated in ASD (yellow nodes). Other node colors (orange, purple, green, dark yellow, or dark purple) correspond to genes present in two or more lists. Edges represent significant direct protein-protein interactions (as defined by a common interactor binding degree of 2) in the InWeb database. Shaded ovals represent enriched biological functions common among 10% or more genes in the network, and their colors represent functional themes shared among Figures 4A, 4B, and 5B.CC BY-NC-ND · PubMed Central
Figure 6 Functional Metrics for Various Gene Sets Derived from CNV and SNV Studies, as well as HI Scores for Genic Deletions (A) Box plots of pHIs for various genes sets. Boxes correspond to the spread between the upper and lower quartiles; medians are indicated by a solid horizontal line, and whiskers extend up to 1.5× the interquartile range. “Genome” indicates all 16,781 genes with an available pHI from an imputed data set, excluding seed genes. Only genes implicated in dominant, recessive, or X-linked disorders with neurological phenotypes in the HPO database (“HPO het,” “HPO hom,” “HPO X,” respectively) and mouse genes whose homozygous, heterozygous, or X-linked knockout (“MPO het,” “MPO hom,” “MPO X,” respectively) causes various abnormal phenotypes were considered. The median pHI for HPO het was selected as the threshold to differentiate between dominant and recessive genes (red horizontal line). Genes implicated in ASD and ID were further annotated into dominant (dom), recessive (rec), or X-linked (XL) genes. Other abbreviations are as follows: dn, de novo; allg; all genes; DEL, deletion; “1g-NBG 69g,” 69 genes selected by NETBAG analysis of 102 de novo CNVs with up to one gene per each CNV region; “2g-NBG 113g,” 113 genes selected by NETBAG analysis with up to two genes per CNV (as depicted in Figure 4B); “2g-NBG DEL/disr 80g,” subset of NETBAG genes completely overlapped or disrupted by deletions (no duplications were considered); “ASD (CompStudies) dn SNV 122g,” 122 genes affected by de novo LoF SNVs from ASD exome sequencing studies; “ID (CompStudies) dn SNV 32g,” 32 genes affected by de novo LoF SNVs from ID exome sequencing studies; “SCZ (Xu2012) dn SNV 22g,” 22 genes affected by de novo LoF SNVs from schizophrenia exome sequencing studies; “ASD (Lim2013) rec SNV 49g,” 49 genes affected by hemizygous LoF SNVs on the X chromosome of ASD males; “ID (Najmabadi2011) rec SNV 73g,” 73 genes hit by recessive SNVs in consanguineous ID-affected families; “pre-DAPPLE ASD input 336g,” 336 DAPPLE input genes; “336g minus 151g excluded 185g,” 185 genes not used by DAPPLE; “DAPPLE ASD direct-PPI 151g,” 151 genes depicted in the network of Figure 5B; “DAPPLE minus 54 known genes 97g,” 97 genes depicted in the network of Figure 5B (and listed in Table S16), not including the 54 genes previously implicated in ASD (yellow nodes); and “DAPPLE known genes only 54g,” 54 genes known to be involved in ASD. (B) LOD scores of the probability that at least one gene within a rare deletion will cause haploinsufficiency were calculated for affected and control subjects. Deletion-based LOD scores are plotted as a function of the number of genes in each event for rare genic deletions in affected and control subjects. The p value for the difference in the slope of the two regression lines is indicated. (C) Box plots with the distribution of predicted functional indispensability scores for gene categories from Khurana et al.55 (LoF-tolerant genes, neutral genes, genes with known mutations as listed in the Human Genome Mutation Database, and essential genes [i.e., genes in which LoF mutations result in infertility or death before puberty]) and CNV or SNV genes from our DAPPLE analysis (185 genes excluded by DAPPLE, 151 genes selected by DAPPLE, 54 known ASD-implicated genes selected by DAPPLE, and 97 genes selected by DAPPLE after exclusion of the 54 ASD-implicated genes). (D) Box plots with the distributions of degree centrality in Multinet55 for the same gene categories as in (C). (E) Box plots with the distributions of the number of networks in which a gene is involved in Multinet for the same gene categories as in (C) and (D).
Figure 6 Functional Metrics for Various Gene Sets Derived from CNV and SNV Studies, as well as HI Scores for Genic Deletions (A) Box plots of pHIs for various genes sets. Boxes correspond to the spread between the upper and lower quartiles; medians are indicated by a solid horizontal line, and whiskers extend up to 1.5× the interquartile range. “Genome” indicates all 16,781 genes with an available pHI from an imputed data set, excluding seed genes. Only genes implicated in dominant, recessive, or X-linked disorders with neurological phenotypes in the HPO database (“HPO het,” “HPO hom,” “HPO X,” respectively) and mouse genes whose homozygous, heterozygous, or X-linked knockout (“MPO het,” “MPO hom,” “MPO X,” respectively) causes various abnormal phenotypes were considered. The median pHI for HPO het was selected as the threshold to differentiate between dominant and recessive genes (red horizontal line). Genes implicated in ASD and ID were further annotated into dominant (dom), recessive (rec), or X-linked (XL) genes. Other abbreviations are as follows: dn, de novo; allg; all genes; DEL, deletion; “1g-NBG 69g,” 69 genes selected by NETBAG analysis of 102 de novo CNVs with up to one gene per each CNV region; “2g-NBG 113g,” 113 genes selected by NETBAG analysis with up to two genes per CNV (as depicted in Figure 4B); “2g-NBG DEL/disr 80g,” subset of NETBAG genes completely overlapped or disrupted by deletions (no duplications were considered); “ASD (CompStudies) dn SNV 122g,” 122 genes affected by de novo LoF SNVs from ASD exome sequencing studies; “ID (CompStudies) dn SNV 32g,” 32 genes affected by de novo LoF SNVs from ID exome sequencing studies; “SCZ (Xu2012) dn SNV 22g,” 22 genes affected by de novo LoF SNVs from schizophrenia exome sequencing studies; “ASD (Lim2013) rec SNV 49g,” 49 genes affected by hemizygous LoF SNVs on the X chromosome of ASD males; “ID (Najmabadi2011) rec SNV 73g,” 73 genes hit by recessive SNVs in consanguineous ID-affected families; “pre-DAPPLE ASD input 336g,” 336 DAPPLE input genes; “336g minus 151g excluded 185g,” 185 genes not used by DAPPLE; “DAPPLE ASD direct-PPI 151g,” 151 genes depicted in the network of Figure 5B; “DAPPLE minus 54 known genes 97g,” 97 genes depicted in the network of Figure 5B (and listed in Table S16), not including the 54 genes previously implicated in ASD (yellow nodes); and “DAPPLE known genes only 54g,” 54 genes known to be involved in ASD. (B) LOD scores of the probability that at least one gene within a rare deletion will cause haploinsufficiency were calculated for affected and control subjects. Deletion-based LOD scores are plotted as a function of the number of genes in each event for rare genic deletions in affected and control subjects. The p value for the difference in the slope of the two regression lines is indicated. (C) Box plots with the distribution of predicted functional indispensability scores for gene categories from Khurana et al.55 (LoF-tolerant genes, neutral genes, genes with known mutations as listed in the Human Genome Mutation Database, and essential genes [i.e., genes in which LoF mutations result in infertility or death before puberty]) and CNV or SNV genes from our DAPPLE analysis (185 genes excluded by DAPPLE, 151 genes selected by DAPPLE, 54 known ASD-implicated genes selected by DAPPLE, and 97 genes selected by DAPPLE after exclusion of the 54 ASD-implicated genes). (D) Box plots with the distributions of degree centrality in Multinet55 for the same gene categories as in (C). (E) Box plots with the distributions of the number of networks in which a gene is involved in Multinet for the same gene categories as in (C) and (D).CC BY-NC-ND · PubMed Central

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  • The paper relies on this without support.

    Unrelated control subjects from SAGE, the Ontario Colorectal Cancer Case-Control Study, and HABC, who had no obvious psychiatric history, are valid controls for ASD CNV burden analyses.

    “Unrelated control subjects were assembled from three studies in which individuals had no obvious psychiatric history: the Study of Addiction Genetics and Environment (SAGE),26 the Ontario Colorectal Cancer Case-Control Study,27,28 and Health, Aging, and Body Composition (HABC) (Table S1B).29”
  • The paper relies on this without support.

    The published control de novo CNV datasets (unaffected siblings from the Simons Simplex Collection and Icelandic control trios) are comparable to the AGP affected subjects for CNV size and gene-content comparisons.

    “Secondary analyses included comparisons of CNV number, length, and intersected gene number between our 102 de novo CNVs identified in affected subjects and the 76 de novo CNVs in control subjects of two published data sets: (1) 17 de novo CNVs identified in 15 unaffected siblings from 872 families with a single ASD-affected offspring and an unaffected sibling from the Simons Simplex Collection4”
  • The authors state this as an assumption.

    If genomic regions are perturbed by genetic variants associated with the same phenotype, they will contain genes forming connected clusters.

    “NETBAG identifies networks of genes under the premise that if genomic regions are perturbed by genetic variants associated with the same phenotype, they will contain genes forming connected clusters.”
  • The authors state this as an assumption.

    Different genes harboring suspected causative mutations for the same disorder often physically interact.

    “Under the assumption that different genes harboring suspected causative mutations for the same disorder often physically interact, we sought to evaluate protein-protein interactions (PPIs) encoded by genes known to be implicated in ASD and genes affected by rare CNVs or SNVs”
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Percentages, sums and reported differences re-computed from the paper’s own numbers.

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Metadata

Authors
Pinto, D., Delaby, E., Merico, D., Barbosa, M., Merikangas, A., Klei, L., Thiruvahindrapuram, B., Xu, X., Ziman, R., Wang, Z., Vorstman, J. A. S., Thompson, A., Regan, R., Pilorge, M., Pellecchia, G., Pagnamenta, A. T., Oliveira, B., Marshall, C. R., Magalhaes, T. R., Lowe, J. K., Howe, J. L., Griswold, A. J., Gilbert, J., Duketis, E., Dombroski, B. A., De Jonge, M. V., Cuccaro, M., Crawford, E. L., Correia, C. T., Conroy, J., Conceição, I. C., Chiocchetti, A. G., Casey, J. P., Cai, G., Cabrol, C., Bolshakova, N., Bacchelli, E., Anney, R., Gallinger, S., Cotterchio, M., Casey, G., Zwaigenbaum, L., Wittemeyer, K., Wing, K., Wallace, S., van Engeland, H., Tryfon, A., Thomson, S., Soorya, L., Rogé, B., Roberts, W., Poustka, F., Mouga, S., Minshew, N., McInnes, L. A., McGrew, S. G., Lord, C., Leboyer, M., Le Couteur, A. S., Kolevzon, A., Jiménez González, P., Jacob, S., Holt, R., Guter, S., Green, J., Green, A., Gillberg, C., Fernandez, B. A., Duque, F., Delorme, R., Dawson, G., Chaste, P., Café, C., Brennan, S., Bourgeron, T., Bolton, P. F., Bölte, S., Bernier, R., Baird, G., Bailey, A. J., Anagnostou, E., Almeida, J., Wijsman, E. M., Vieland, V. J., Vicente, A. M., Schellenberg, G. D., Pericak-Vance, M., Paterson, A. D., Parr, J. R., Oliveira, G., Nurnberger, J. I., Monaco, A. P., Maestrini, E., Klauck, S. M., Hakonarson, H., Haines, J. L., Geschwind, D. H., Freitag, C. M., Folstein, S. E., Ennis, S., Coon, H., Battaglia, A., Szatmari, P., Sutcliffe, J. S., Hallmayer, J., Gill, M., Cook, E. H., Buxbaum, J. D., Devlin, B., Gallagher, L., Betancur, C., & Scherer, S. W.
Affiliations
  • Icahn School of Medicine at Mount Sinai (US)
  • Centre National de la Recherche Scientifique (FR)
  • Hospital for Sick Children (CA)
  • Trinity College Dublin (IE)
  • University of Pittsburgh (US)
  • University Medical Center Utrecht (NL)
  • McMaster University (CA)
  • University College Dublin (IE)
  • Centre for Human Genetics (GB)
  • University of Lisbon (PT)
  • University of Toronto (CA)
  • University of California, Los Angeles (US)
  • University of Miami (US)
  • Goethe University Frankfurt (DE)
  • University of Pennsylvania (US)
  • Vanderbilt University (US)
  • University of Bologna (IT)
  • Cancer Care Ontario (CA)
  • University of Southern California (US)
  • University of Alberta (CA)
  • University of Birmingham (GB)
  • Warneford Hospital (GB)
  • Laboratoire de NeuroPsychoLinguistique (FR)
  • Unidade Local de Saúde de Coimbra (PT)
  • Weill Cornell Medical Center (US)
  • Inserm (FR)
  • University of Minnesota (US)
  • University of Illinois Chicago (US)
  • Manchester Academic Health Science Centre (GB)
  • University of Gothenburg (SE)
  • Memorial University of Newfoundland (CA)
  • King's College London (GB)
  • University of Washington (US)
  • Nationwide Children's Hospital (US)
  • Newcastle University (GB)
  • Tufts University (US)
  • German Cancer Research Center (DE)
  • Children's Hospital of Philadelphia (US)
  • University of Utah (US)
  • Stanford Medicine (US)
Corresponding author
  • Betancur, Catalina
  • Scherer, Stephen W.
Venue
The American Journal of Human Genetics
Publisher
Elsevier BV
Published
2014-05
Volume
94
Issue
5
Pages
677-694
ISSN
0002-9297 (ISSN-L)
OpenAlex
W2129867386
Cited by
969
References
66
Citations by year
2026: 26 · 2025: 35 · 2024: 62 · 2023: 63 · 2022: 80 · 2021: 98 · 2020: 100 · 2019: 91 · 2018: 80 · 2017: 100 · 2016: 102 · 2015: 92 · 2014: 40
FWCI
62.30
Type
journal article
Language
en
Open access
Locations
  • The American Journal of Human Genetics (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion)
  • Arrow@dit (Dublin Institute of Technology) (submittedVersion)
  • HAL (submittedVersion, other-oa)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
  • Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
  • ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
  • Research Portal (King's College London) (submittedVersion, other-oa)
  • Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) (submittedVersion, cc-by-nc-nd)
  • Research Explorer (The University of Manchester) (submittedVersion)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion)
  • IUScholarWorks (Indiana University) (submittedVersion, cc-by-nc-nd)
  • PMC
  • Newcastle University ePrints (Newcastle Univesity) (cc-by-nc-nd)
Funders
  • Brain and Behavior Research Foundation
  • Medical Research Council
  • Genome Canada
  • Hospital for Sick Children
  • National Alliance for Research on Schizophrenia and Depression
  • Health Research Board (AUT/2006/1, AUT/2006/2, PD/2006/48)
  • Ontario Genomics Institute
  • Canadian Institutes of Health Research
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
Keywords
autism spectrum disorder, copy number variation, de novo CNVs, intellectual disability, CHD2, HDAC4, GDI1, SETD5, microRNA-137, HDAC9, neuronal signaling, synaptic function, chromatin regulation, gene networks
MeSH terms
Child, Child Development Disorders, Pervasive, Female, Multigene Family, Humans, Male, Pedigree, Sequence Deletion, Gene Regulatory Networks, Metabolic Networks and Pathways, DNA Copy Number Variations

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.

A language model drew the claims from the paper on 2026-10-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-10-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

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 ›

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