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. 2014 May 1;94(5):677-94.
doi: 10.1016/j.ajhg.2014.03.018. Epub 2014 Apr 24.

Convergence of genes and cellular pathways dysregulated in autism spectrum disorders

Dalila Pinto  1 Elsa Delaby  2 Daniele Merico  3 Mafalda Barbosa  4 Alison Merikangas  5 Lambertus Klei  6 Bhooma Thiruvahindrapuram  3 Xiao Xu  7 Robert Ziman  3 Zhuozhi Wang  3 Jacob A S Vorstman  8 Ann Thompson  9 Regina Regan  10 Marion Pilorge  2 Giovanna Pellecchia  3 Alistair T Pagnamenta  11 Bárbara Oliveira  12 Christian R Marshall  13 Tiago R Magalhaes  10 Jennifer K Lowe  14 Jennifer L Howe  3 Anthony J Griswold  15 John Gilbert  15 Eftichia Duketis  16 Beth A Dombroski  17 Maretha V De Jonge  8 Michael Cuccaro  15 Emily L Crawford  18 Catarina T Correia  12 Judith Conroy  19 Inês C Conceição  12 Andreas G Chiocchetti  16 Jillian P Casey  10 Guiqing Cai  20 Christelle Cabrol  2 Nadia Bolshakova  5 Elena Bacchelli  21 Richard Anney  5 Steven Gallinger  22 Michelle Cotterchio  23 Graham Casey  24 Lonnie Zwaigenbaum  25 Kerstin Wittemeyer  26 Kirsty Wing  11 Simon Wallace  27 Herman van Engeland  8 Ana Tryfon  28 Susanne Thomson  18 Latha Soorya  28 Bernadette Rogé  29 Wendy Roberts  30 Fritz Poustka  16 Susana Mouga  31 Nancy Minshew  6 L Alison McInnes  28 Susan G McGrew  32 Catherine Lord  33 Marion Leboyer  34 Ann S Le Couteur  35 Alexander Kolevzon  36 Patricia Jiménez González  37 Suma Jacob  38 Richard Holt  11 Stephen Guter  39 Jonathan Green  40 Andrew Green  41 Christopher Gillberg  42 Bridget A Fernandez  43 Frederico Duque  31 Richard Delorme  44 Geraldine Dawson  45 Pauline Chaste  46 Cátia Café  47 Sean Brennan  5 Thomas Bourgeron  48 Patrick F Bolton  49 Sven Bölte  50 Raphael Bernier  51 Gillian Baird  52 Anthony J Bailey  27 Evdokia Anagnostou  53 Joana Almeida  47 Ellen M Wijsman  54 Veronica J Vieland  55 Astrid M Vicente  12 Gerard D Schellenberg  17 Margaret Pericak-Vance  15 Andrew D Paterson  56 Jeremy R Parr  57 Guiomar Oliveira  31 John I Nurnberger  58 Anthony P Monaco  59 Elena Maestrini  21 Sabine M Klauck  60 Hakon Hakonarson  61 Jonathan L Haines  18 Daniel H Geschwind  14 Christine M Freitag  16 Susan E Folstein  62 Sean Ennis  41 Hilary Coon  63 Agatino Battaglia  64 Peter Szatmari  9 James S Sutcliffe  18 Joachim Hallmayer  65 Michael Gill  5 Edwin H Cook  39 Joseph D Buxbaum  66 Bernie Devlin  6 Louise Gallagher  5 Catalina Betancur  67 Stephen W Scherer  68
Affiliations

Convergence of genes and cellular pathways dysregulated in autism spectrum disorders

Dalila Pinto et al. Am J Hum Genet. .

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.

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Figures

Figure 1
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 2
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 3
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); (4) FMRP interactors (n = 842); (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 pHI 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 4
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 5
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; (3) 31 genes with hemizygous LoF SNVs on the X chromosome of male ASD subjects and not observed in male control subjects; and (4) 92 ASD-implicated genes previously described as autosomal dominant, X-linked dominant, or X-linked recessive in males. (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 6
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. (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 Multinet 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).

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