Genotype to Phenotype Relationships in Autism Spectrum Disorders

© 2014 Nature America, Inc. All rights reserved. us us with genes complementary in sets enriched causal ASD mutations. provided approaches independent two These studies. recent several computational approach and on all on by a of our that network-based set were implicated analyses genes our We focused scores. phenotypic social and intelligence including have assembled a large compendium of ASD-related phenotypic data, Correspondence should Correspondence be addressed to D.V. ( 4 and Columbia Bioinformatics, University, New York, New York, USA. 1 (SSC) Collection Simplex Simons the as such resources addition, stages developmental and regions brain anatomical distinct comprehensive database of gene expression across different cell types, genetic a include These are accumulated. resources rapidly being phenotypic disease-associated and of functional brain-related of sets data complementary identification variations, the with parallel In networks that are involved in neurogenesis and synaptic function biological several on converge disorders psychiatric other and ASDs with associated variations genetic that found recently others and we variants genetic disease- of associated collection diverse a using networks biological cohesive for searches that (NETBAG+) approach computational a developed ASDs. in role have a causal to are likely CNVs large and mutations) frameshift and site splice nonsense, as (such SNVs truncating that single nucleotide variations (SNVs) associated with ASDs, including copy number variations (CNVs) of collection large a identified have studies recent genes target of number large a of result a as substantial be to likely is cases ASD sporadic to contribution collective but their tant phenotypes related and autism to contribute abnormalities behavioral and cognitive of range wide a with associated are ASDs social and behavioral ASD phenotypes. ASD high-functioning cases. Overall, we find that stronger functional insults usually lead to more severe intellectual, expression than in males. Our results also suggest that truncating and brain corticostriatal circuits. In females, truncating ASD mutations on average affect genes with 50–100% higher brain be strongest in cortical pyramidal interneurons, neurons and the medium spiny neurons of the striatum, implicating cortical likely to be Multiple cell haploinsufficient. types and brain areas are affected, but the impact of ASD mutations appears to truncating mutations in early embryonic development. We find that functional mutations are observed preferentially in genes perturbed in ASD suggests that both truncating and nontruncating Autism spectrum disorders (ASDs) are by characterized phenotypic and genetic heterogeneity. Our analysis of functional networks Jonathan Chang spectrum disorders Genotype to phenotype relationships in autism nature nature Received 12 August; accepted 26 November; published online 22 December 2014; Department Department of Psychiatry, Department of Genetics, Yale University, New Haven, Connecticut, USA. Department of Biomedical Informatics, Columbia University, New York, New York, USA. To explore the underlying biological pathways, we previously previously we pathways, biological underlying the explore To de novo de NEUR mutations associated with ASDs are individually rare, rare, individually are ASDs with associated mutations 1 OSCI , 2 . It is estimated that many hundreds of genes may may genes of hundreds many that estimated is It . EN 1 , 2 C , 5 E

, Sarah , R Sarah Gilman advance online publication online advance 12 , 1 3 . Using network-based approaches, approaches, network-based Using . de novo 3 , 7 , 8 , [email protected] 1 1 . These studies demonstrated truncating mutations from 2 , 1 3 . Functionally impor Functionally . , 2 , 5 de novo de , , Andrew H Chiang 3– 3 mutations mutations ). 1 Department Department of Psychiatry, University of California, San Francisco, California, USA.

0 . Several Several . 16 , 1 12– 6 7 and . In . 1 1 5 8 - .

doi:10.1038/nn.390 de de novo (GO) terms that were significantly enriched among network gene gene network among enriched significantly were that terms (GO) DAVID used we network, implicated siblings. in identified non-synonymous 368 the with associated genes using detected were networks significant no Notably, connectivity. sets that matched the real data in terms of protein length and network The CNVs. network’s using random was input estimated significance by affected were genes 131 which ( genes 159 taining The network Methods). NETBAG+ con a search revealed functional (Online network phenotypic underlying the in connected strongly are that genes input the of subset a identify to NETBAG+ Weused of analysis previous our in con sidered loci 47 the than larger considerably was used loci genomic of novo de loci, genomic independent 624 with genes unique 580 including from genes unique 991 contained of data total input a combined The etiology. ASD of hypotheses genome- using by any preexisting biased obtained not are therefore and were methodologies wide analyses our for input the as used SSC the from patients autistic in observed by applied affected we genes of ASD, set in a to NETBAG+ perturbed networks functional elucidate To Functional gene networks affected by RESULTS phenotypes. ASD affect genes autism-associated of properties files of implicated genes. We also explored Wehow investigatedexpression the temporal, spatial and expression cell-specific pro and functional de de novo To explore the biological functions associated with the the with associated functions biological the explore To 1 2 , Department Department of Systems Biology, Center for Biology Computational 2 , , Stephan J Sanders CNVs ( CNVs mutations play a smaller role in the etiology of mutations contribute to autism, with a bias against 5 These These authors contributed equally to this work. Supplementary Table 1 Table Supplementary 7 P = 0.036; = 0.036; 3 Fig. Fig. , 4 & Dennis Vitkup de de novo 1 de novo de de novo de and and 1 9 Supplementary Table 2 Supplementary to identify Gene Ontology Ontology Gene identify to de novo SNVs and 434 genes within within and SNVs genes 434 ); we note that the number number the that note we ); de novo de 3 SNVs and 31 by by 31 and SNVs CNV events in autism in events CNV , 6– 8 . All of the mutations mutations the of All . mutations de novo de t r a CNVs and SNVs SNVs and CNVs

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© 2014 Nature America, Inc. All rights reserved. ronal projections and actin cytoskeleton ( cytoskeleton actin and projections ronal LIMK1 PRKCA, CTNNB1, MDM2, EPHA1/B2 DCC, genes that are associated with neuronal signaling and migration ( memory and learning in important are which channels, calcium dependent ( CACNA1D genes contained cluster This receptors. ion of and set channels diverse a included cluster related A synapses. excitatory ( ( neurexin contained cluster This and function. formation for synapse ( functions biological non-overlapping and distinct with associated each clusters, network a as network ( phenotypic metric the in interactions of strength the using genes network the of clustering hierarchical performed we network, the in genes between relationships functional the understand better To activity. channel calcium and modification chromatin function, synaptic including network, with the implicated associated functions ( annotations Table 3 ( clustering hierarchical using by colors) node (indicated clusters functional cohesive four into was divided The network types. by mutation both affected genes represent and CNVs diamonds from genes represent squares SNVs, from genes represent circles mutations: of types the corresponding indicate shapes Node shown. For clarity,are for gene each edges Methods). the only two strongest (Online phenotype to the genetic same contributes pair gene the that corresponding P 1 Figure t r a FLNA, ACTN4 NRXN SHANK2

= 0.036). Node sizes are proportional to the contributions of each gene to the overall network score and edge widths are proportional to the likelihood to the likelihood are proportional and widths edge score network of to gene each the overall to the contributions are proportional sizes Node = 0.036). CACNA1E One cluster in our network ( network our in cluster One for a complete list of GO terms associated with each cluster). Gray nodes represent genes that are not members of the network clusters. of the network are that not members genes represent nodes Gray cluster). each with of list GO associated for a terms complete Channel CACNA1B

) and neuroligin ( neuroligin and ) activity C I Supplementary Fig. 1) Fig. Supplementary The network implicated by NETBAG+ based on ASD-associated on based ASD-associated by NETBAG+ implicated The network 2 CACNA1S 0 KCNC1 and and . The largest cluster of the implicated network contained contained network implicated the of cluster largest The . SCN2 , , e l CACNA1E Postsynapti ATP2B CHRND Table Table ). As we have previously demonstrated, ASD-associated CACNA1D A density CASK DLG2/DLG4 GABRB3 MPP6 OPRL1 s TRPV5 4 ), intracellular signaling ( signaling intracellular ), HRH2 RYR1 CHRNA 1 Supplementary Fig. 1 Fig. Supplementary Supplementary Table 3 Supplementary DLG1 DLG2 GRIN2B GRM5 ). This analysis identified a diverse set of of set diverse a identified analysis This ). , , c GRM7 CACNA1S NRLG 7 SHANK2 SPTAN ) of the postsynaptic density (PSD) of of (PSD) density postsynaptic the of ) MYH DLG4 GNAS CYFIP1 ABI2 IQGAP2 . This analysis identified four major major four identified analysis This . Fig. Fig. 9 AP1GBP1 ), as well as important components components important as well as ), 1 RIMS1 FANCA ITPR1 MYH11 LLGL1 ADCY ) for subunits of several voltage- several of subunits for ) A2 ), and the development of neu of development the and ), NLGN 1 CRK M PFKM ) contained genes responsible responsible genes contained ) NLGN 5 BAIAP2 L MYH10 SYNE1 3 MYO9 ); general biological functions of these clusters, determined using DAVID,using (see are shown determined of clusters, these functions biological ); general SDH 1 CYFIP1, TRIO, SPTAN1, SPTAN1, TRIO, CYFIP1, NF PMM2 NRXN1 MAPK3, EGFR, PTEN, PTEN, EGFR, MAPK3, AK1 B MAPT 1 A ). DS ACTN LRP2 T ITGB3 PIK3R2 PDGFD CA 4 MAD CLPB D FLN ACAC PTEN LRP1 D APAF1 A CACNA1B B TTN PSEN1 TLK2 PPM1 TSC2 TCF7L1 PRKG1 EGFR MDM2 DNMT3A JU NF1, NF1, D PRKC CTNNA P GRK5 de de novo - CTNNB1 MSH ,

STK1 A 3 AXIN DCC 6 EPHB2 MST1R studies have revealed recurrent truncating mutations in several several in mutations ( truncating genes recurrent revealed have studies functional properties of the network genes. Recent exome-sequencing work and gene that subsets specific may the highlight phenotypic and above, we there investigated was whether an overlap the net between discussed categories GO biological and molecular the to addition In Association of the implicated genes with specific functional subsets EIF3G ( interference RNA ASDs: in implicated have been that processes other in involved develop ment, neuroplasticityneural andof learning stages various affect crucially mechanisms tory Notably,regulation. there is that growing evidence chromatin regula and transcriptional remodeling chromatin modifications, chromatin with associated functions to related primarily was cluster final The our in implicated schizophrenia and ASDs in insults been genetic of have analyses previous which spines, dendritic of function and growth the to related proteins encode above described clusters projections neuronal of the and development adhesion cell-cell migration, neuron for required are that on the of regulation processes and cytoskeleton actin other structural converge that pathways signaling multiple perturb often mutations WNK2 1 CDH5 SNVs and CNVs from recent studies (network is comprised of 159 genes, is comprised (network studies and recent SNVs from CNVs TRI 1 UBE3C O MAPK13 TNK ROS1 DDR2 ) and splicing ( splicing and ) PTPR MAPK3 SMAD ADNP, ANK2, ARID1B, CHD8, CUL3, DYRK1A, GRIN2B, GRIN2B, DYRK1A, CUL3, CHD8, ARID1B, ANK2, ADNP, S STK1 EPHA1 advance online publication online advance CUL5 M PTK DYRK1A NAV2 PTPR 2 CI 9 DICER1, DICER1, AGO1/EIF2C1 T 7 VPS4A CUL3 K RUVBL1 LIMK RPS6KA3 SNRK DDB1 CDC42BP ABCA2 VC 1 SFPQ, TRA2B SFPQ, STK36 P RPS6KB2 TRRA ZMYND11 IKBKAP B SMC3 TBL1XR1 P TSSK2 NUAK1 BRSK2 NOLC1 BRD1 HDAC9 L3MBTL WDR4 2 cytoskeleton 3 KIF18A NCOR1 signaling/ Neuronal . This cluster also contained genes ) 2 EP400 ), ), translation ( 4 UIMC . TRA2B GTF3C1 BRD4 ARID1B 12 CHD3 TADA2L SUPT16H ,

1 21 SFPQ modification/ nature nature , HTATIP2 Chromatin 2 regulation CBX 2 MYBBP1A HNRNP SRCA . Many genes in the the in genes Many . EIF2C1 SMARCA2 4 CHD8 P Supplementary Supplementary F EIF4A1, EIF4G1, EIF4G1, EIF4A1, NEUR HNRNPUL1 DHX SF EIF3 DICER1 1 9 G EIF4G1 OSCI DDX20 EIF4A1 POL EN 12 Q , C 1 3 E - - - .

© 2014 Nature America, Inc. All rights reserved. harboring SNVs with potentially stronger functional effect. functional stronger potentially with SNVs harboring mutations, this analysis demonstrates that damaging NETBAG predominantly more genes selects to correspond scores GERP higher As one tail, Wilcoxon rank-sum are 4.0 and respectively; 3.3, scores GERP non-network and network (average network the into was significantly higher than the genes average GERP score of network genes not of selected score Online GERP (see average the mutations Notably, SNV Methods). of severity the characterize to scores We also considered the Genomic Evolutionary Rate Profiling (GERP) are 0.69 and 0.39, respectively; Wilcoxon rank-sum two tail, with recurrent truncating mutationsgenes andfor unaffected sibling probability SNV genes (median mutations truncating recurrent with test, two-tail rank-sum Wilcoxon respectively; 0.32, and 0.57 are genes network bynot selected NETBAG+ probability (median for network and non- were that genes than haploinsufficient to be more likely significantly study a recent from probabilities haploinsufficiency using Indeed, genes. sufficient haploin target preferentially would mutations causal true that likely Because ASD is of a enrichment causal genes substantial in the implicated network. network (Fisher’s exact one-tail test, 6 network, mutations of are 11 truncating in genes with recurrent the 580 (~23%) of all genes harboring missense SNVs form the implicated KATNAL2,SCN2A POGZ, ( background as genes brain-expressed using obtained also were results enrichment similar genes; human all of set background default the using performed were calculations cluster, see network each with associated terms GO of list a For shown. not are terms redundant and genes, human 400 than more with associated terms is, that terms, Nonspecific component. cellular for CC and function molecular for MF process, biological for BP domain: GO indicates column DAVID. ontology in The procedure Benjamini-Hochberg the using testing hypotheses david.abcc.ncifcrf.go ( network implicated the in enriched terms GO GO ID Table 1 nature nature genes harboring truncating ASD GO:003042 G GO:001406 GO: GO:000593 GO:00 GO:000761 GO:0044 GO:004521 GO:000591 GO:001 GO:003003 GO:001562 GO:00 GO:003125 GO:000526 GO:005101 GO: GO:004520 O:004300 Notably, a recent exome study showed a significant overlap between 000591 001656 3002 0438 688

45 NEUR GO GO terms associated with the implicated network Supplementary Table 4 Supplementary 5 5 9 1 8 9 1 6 1 3 7 6 9 6 2 2 5 8 2

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and advance online publication online advance ). de novo TBR1 Supplementary Table 3 Supplementary Term Dendrite Neuron projection density Postsynaptic Cell-cell junction Cell cortex based process Actin filament- Learning or memory Synapse part membrane Postsynaptic junction Cell-cell adherens ATPase activity organization Actin cytoskeleton Actin cytoskeleton Helicase activity Cell leading edge activity Calcium channel binding Actin filament modification Chromatin Synapse P Fig. Fig. = 0.02). This suggests that there ) 3 SNVs and targets of the fragile X , 7 1 , 8 ), as identified by DAVID by identified as ), , 11 , 2 5 . Although only 131 of 131 only . Although . The enrichment enrichment The . 8 8 × 10 8 × 10 7 × 10 7 × 10 6 × 10 3 × 10 2 × 10 1 × 10 7 × 10 6 × 10 3 × 10 0.0002 0.0001 0.0001 0.0001 0.0001 P 0.004 0.004 0.002 P value P

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of humangeneticvariation of theproportionraresynonymousvariants observedinarecentlarge-scalesurvey implicated genes.Theexpectednumbers ofFMRPtargetswereobtainedonthebasis The expectedandobservednumberofFMRP targets Sibling SNV genes Non-network SNV genes Channel activity cluster genes Postsynaptic density cluster genes Chromatin modification/regulation Neuronal signaling/cytoskeleton Network SNV non-truncating genes Truncating SNV genes Network genes Gene set Table 2 each of the four functional clusters of the implicated network ( for FMRP targets remained significant when we separately considered ( siblings unaffected from genes ( network the to selected not were that In contrast, there was no significant enrichment for proband SNV genes FMRP targets from another recent study ( 1:2.67, = (enrichment SNVs non-truncating harboring genes network only P two- test, 1:2.13, binomial enrichment tail gene SNV (truncating targets FMRP for enriched significantly were network implicated the in genes genes, ( sets gene ASD various in number observed the with compared then was study exome-sequencing large a from mutabilities gene inferring by genes ASD for targets FMRP of number expected the calculated we SNVs, analysis autistic previous by a accompanied Following often symptoms. disabilities cognitive of spectrum in a resulting X disorder a syndrome, genetic can FMRP fragile cause learning and plasticity synaptic ing protein that is for essential a wide array of includ cognitive functions (FMRP) protein retardation mental of theoverlapswere established usingatwo-tailbinomialtest. recent studyofFMRP targets genes ASD-implicated the of expression brain investigated Thus, next we function. gene of contexts developmental and physiological for clues unde important provide patterns expression Gene genes implicated of patterns expression brain spatial and Temporal 1:0.58, (enrichment under-represented significantly P 1:1.05, (enrichment siblings unaffected in SNVs harboring for genes 1:1.9, (enrichment probands 5 Table (enrichment 1:3.4, two-tail binomial test, network implicated the in genes PSD-associated of to enrichment cant crucial is plasticity and and communication synapses synaptic excitatory of membrane postsynaptic disorders psychiatric other and non-truncating with genes of fraction for a substantial role a causal suggest and etiology autism for important are targets FMRP that confirm analyses these Overall, = 3 × 10 = 0.8). For genes not selected to the network, PSD genes were were genes PSD network, the to selected not genes For 0.8). = cluster cluster genes cluster genes Genes forming the PSD are also likely to be important in ASDs ASDs in important be to likely also are PSD the forming Genes Table 3 0 P (Online Methods); the expected number of FMRP targets targets FMRP of number expected the Methods); (Online

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© 2014 Nature America, Inc. All rights reserved. sion (less than 8 post-conception weeks) was substantially lower lower substantially was weeks) post-conception 8 than (less sion truncating with P 0.18, test, one-tail 0.16, (bias P genes network for significant highly was harboring gene every peri for ods developmental postnatal and prenatal during expression between the difference the calculated we bias, expression prenatal the Toquantify composition. cellular brain in changes or cells brain genes in ASD-related of activity higher of result a as possibly weeks), during the early fetal to early mid-fetal periods (8–19 post-conception ( periods ( levels lower at significantly brain the in expressed are connectivity network or length equivalent with con human in genes the or randomly network; selected nectivity phenotypic length their of consequence a simply not is genes of network expression brain high significantly Notably, is genes. brain-related network in implicated enriched the that confirms result ( This network the to selected not were that higher than was the significantly expression of SNV-containing genes size (Online Methods). The brain expression of network genes of equal ( sets probe random in bias a greater of observing probability samples biological and test a (P permutation-based of sets between difference of expression the significance the estimate with genes for truncating as well as network, implicated the formed that sets gene various the for periods developmental across levels expression average the mined brain multiple We stages. deter and developmental regions across expression mRNA of map comprehensive a provides database HBT the individuals, healthy from samples analysis of transcriptional postmortem tissue (HBT, base Human Transcriptome data the Brain using s.e.m. represent bars Error stages. developmental postnatal and prenatal separate lines dashed Vertical (purple). genes SNV truncating male and (blue) genes network male (green), genes network female (red), genes SNV truncating female genes: SNV female/male truncating and network for profiles ( (blue). genes activity channel and (green) genes signaling/cytoskeleton (red), genes modification/regulation chromatin (cyan), genes density postsynaptic network: ( clusters functional ( probands. in observed mutations (red) non-truncating and (cyan) truncating with genes network for ( (purple). genes SNV non-network and (blue) genes SNV truncating all (green), CNVs from genes network (red), genes network all (orange), network the in ( set. a given in genes all using calculated were stage developmental each at levels expression average database; HBT the from obtained were (log data Expression sets. gene implicated for stages developmental across brain human the 2 Figure t r a test, (two-tail periods developmental later in that with compared as a

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© 2014 Nature America, Inc. All rights reserved. the Bonferroni procedure. Bias s.e.m. was calculated separately for each brain region. BG, basal ganglia. The significances of the expression biases were evaluated using the Wilcoxon rank-sum one-tail test and corrected using log bias for each brain region, we calculated the difference between the average log The biases were calculated using human expression data obtained from the HBT database. To quantify the expression Frontal Thalamus Hippocampus Temporal Parietal Occipital Cerebellum Striatum/BG Amygdala Brain region Table 3 P log truncating ing harbor genes for higher significantly was expression brain average test, compared Fisher’sone-tail in males; 13% exact with truncating are females in mutations SNV of (30% work net implicated the in genes the for stronger even was dimorphism greater a had test, one-tail collection exact (Fisher’s SSC males than the mutations truncating in of burden females that observed also males in than females in ASDs trigger to insults genetic of old thresh a higher requires that effect protective of a female a result be ASDs in findings notable and consistent most the of one is individuals, high-functioning for clusters. functional corresponding of profiles expression average the with consistent generally were genes vidual ( requirements of genes. expression Normalized trajectories dosage individual different by explained partially least at be to likely is ability ( profiles expression cluster average the around genes individual the of expression the in variability substantial was there Notably, stages. developmental all in presented are figure All (*). asterisk an with indicated are meta-analyses both for cutoff significance the passing types cell the and combined The methods. meta-analysis Stouffer’s and Fisher’s using combined were (blue), mutations truncating recurrent by affected genes on based other the and (red) genes network on based one approaches, the addition, In blue. red and light in shown are types non-significant and blue, and red dark in shown are types cell significant 10%; of rate discovery false a procedure with Benjamini-Hochberg the using testing hypothesis multiple for corrected and test one-tail rank-sum Wilcoxon the using was evaluated biases expression the of significance The (red). genes network for bias expression type cell the of magnitude the by ordered are with genes human log average the and genes human log average the between difference the type cell each for calculated we biases, expression the described previously using calculated were biases The (blue). SNVs truncating recurrent with genes 11 for and red) in (shown genes network implicated for CNS the of types cell 25 across computed were biases expression sibling unaffected versus Proband mutations. truncating recurrent 3 Figure nature nature Supplementary Fig. 3 Fig. Supplementary WT 2 A high male-to-female incidence ratio, estimated at 4:1 more than estimated ratio, incidence male-to-female A high postnatal expression, such that positive values in the table indicate higher expression levels in the prenatal periods. 2 expression for genes: females, 7.98; males, 7.40; one-tail test, test, one-tail 7.40; males, 7.98; females, genes: for expression < 10 < P = 0.07), which is consistent with this hypothesis. This gender gender This hypothesis. this with consistent is which 0.07), =

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0.03 0.03 0.02 0.05 0.05 0.04 0.07 0.04 0.02 Bias of truncating mutations on protein function, which makes the expres effect of severe the a is consequence likely result This genes. network versus for implicated than SNVs truncating with for genes females larger was males in mutations harboring genes for expression brain in difference relative the that note We also respectively. difference), and in were brain levels females males expression 7.42 and 7.39 (<3% average the probands male in SNVs truncating with genes for respec tively; difference), (<5% 7.95 and 8.02 were males and females in expression truncating SNV mutationswith in female genes probands normal For the average brain expressionfemales. by levels and males explained between differences be cannot patterns observed the expression Notably, females. in ASDs with associated erentially is, that mutations are in brain expression, genes with higher pref truncating perturbations, genetic stronger relatively data that expression suggest the also Thus, males. and females in SNVs truncating harboring genes of expression average the in stages developmental across 50–100% of differences level expression absolute to translate Mature oligodendrocytes,progenitors(cerebellum) Granule celllayerinterneurons(innerGolgicells Sibling SNVs Cholinergic projectionneurons(basalforebrain) Mature oligodendrocytes,progenitors(cortex Motor neurons,midbraincholinergicneurons S.e.m. 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 Layer 6corticothalamicpyramidalneurons Layer 5acorticostriatalpyramidalneurons Motor neurons,cholinergicinterneurons Drd1+ mediumspinyneurons(striatum) Drd2+ mediumspinyneurons(striatum) Unipolar brushcells(mGluR1subtype) Mature oligodendrocytes(cerebellum) Cholinergic neurons(corpusstriatum) Granule cells,deepcerebellarnucle Astroglia (includesBergmannglia Mature oligodendrocytes(cortex Significant, recurrenttruncating Significant, network P value 1.0 1.0 1.0 1.0 0.7 1.0 0.1 1.0 1.0 Mixed neurons(cortex Astroglia (JD133line) Astroglia (JD130line) Interneurons (cortex Stellate, basketcells Layer 5bneurons Neurons (cortex ASDs. Furthermore, we investigated the the investigated we in Furthermore, observed ASDs. abnormalities phenotypic of spectrum wide the with consistent is which ( regions brain all genes network showed significantly higher expression across controls, with Compared siblings. unaffected in SNVs levels with genes expression of the to genes network of levels expression average the compared we region, brain each For database. HBT the in data available expression spatial we analyzed regions, brain specific affect preferentially patients. across phenotypes ASD of variability the explaining in factor important an genes corresponding of sion Bergman glia Purkinje cells To investigate whether ASD mutations mutations ASD whether investigate To –0. ) ) ) ) ) ) ) i –1 * * * * * * 2 for recurrenttruncatingmutations 0 0 0 0 Non-significant, recurrenttruncating Non-significant, network Cell-type expressionbias Supplementary Table 7 Table Supplementary Cell-type expressionbias for networkmutations .5 .1 1 1 0. t r a 0 2 .5 .3 C I 2 0. 0 4 e l 2. 5 .5 s ), ), - - -

© 2014 Nature America, Inc. All rights reserved. types were also independently implicated by considering expression expression considering by implicated independently also were types and ( striatum the of neurons neurons spiny medium pyramidal interneurons, cortical expres especially neurons, cortical significant in observed and were genes network strong implicated for biases sion particularly cell affected, multiple were Although types types. cell diverse across pathways neural and structural signaling, common of usage shared by partially, least 8 Table ( genes network the in mutations ASD by affected were likely types cell and non-neuronal neuronal that multiple revealed analysis This siblings. in mutations unaffected harboring genes for orthologs of expression the with genes network for each cell type, the expression of mouse orthologs for the compared, implicated we biases, expression cell-specific To assess CNS. mouse set contains gene expression profiles for 25 distinct cell types from the (TRAP) purification affinity ribosome translating generated using expression gene cell-specific of set data used independent we an question, this explore To types. cell specific toward genes implicated of biases possible investigate to sought we and types, cell areas. brain across functions gene of sharing the however,regions. Overall, the lack underscores of regional specificity numerically, although not significantly, larger prenatal bias than other stimuli processing in emotional role crucial a have to known is which amygdala, the ( regions brain all for significant Wesiblings. in found and that statistically similar the prenatal bias was generally SNVs with genes for bias prenatal the with these pared com and genes truncating and network for bias expression prenatal s.e.m. represent bars Error siblings. unaffected all for individual per mutations of numbers average corresponding the represent lines dashed Horizontal individual. per (orange) SNVs synonymous and (purple) SNVs non-truncating of ( individual. per (green) CNVs and (blue) SNVs ( IQs. different with probands 4 Figure t r a ( ( stages. developmental postnatal and prenatal separate lines dashed Vertical blue. in phenotypes severe less and red in shown are phenotypes severe more with probands in affected genes for Profiles lines. dashed as SNVs truncating for profiles and lines solid as displayed are genes network for profiles Expression s.e.m. represent bars error and subset a given in genes all using calculated were stage developmental each at levels expression average database; HBT the from obtained were (log data Expression scores. phenotypic median corresponding the to relative low) and (high groups two into divided were Probands scores. phenotypic 5 Figure c

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© 2014 Nature America, Inc. All rights reserved. a substantial fraction of non-truncating non-truncating of fraction substantial a truncating ASD. in behaviors tive repeti and stereotypical may mediate that circuits neural functional Consequently, our unbiased genome-wide analysis implicates ASD specific in perturbed often are that behaviors habit-forming and cognitive emotional, motor, diverse mediate to known are circuits cortico-striatal-thalamic often corresponding 6 the thalamus; the to layer project and striatum the to project often neurons pyramidal striatum, seemed to be more strongly the affected. Notably, cortical of neuron layer as spiny 5 cortical medium such and neurons types, pyramidal some interneurons, types, cell multiple across processes and active are genes implicated the Although function. brain and synaptogenesis mobility, neuron neurogenesis, of stages multiple in important be to likely therefore are and profiles expression mental develop diverse disorder. had Wethe genes with affected that found is matched by the diversity of genetic and functional insults associated of heterogeneity ASD Our that results suggest the pathophysiological DISCUSSION 10 × 1.5 P test, one-tail tions: P test, P ally had significantly higher brain expression (network genes: one-tail or higher ADIR scores (both indicating more severe phenotypes) usu scores IQ lower with associated genes affected that revealed analysis ( subset phenotype each in identified genes implicated scores. Wephenotype the average then calculated expression levels of high-scoring phenotypic subsets relative to the corresponding median and low- into cases ASD the divided we phenotypes, corresponding and genes affected of level expression average the between tionship (ADIR-R) behaviors repetitive/restrictive and parents and patterns reflect in proband reciprocal interactions social (ADIR-S) with interviews structured on scores. based are scores behavior ADIR The repetitive and interaction social (ADIR) Interview- Revised Diagnostic Autism and IQ full-scale the considered analysis, we this For outcomes. phenotypic different with average, on is associated, genes for affected of expression brain level the whether dosage. in increase an than effect functional stronger substantially P test, one-tail rank-sum (Wilcoxon respectively 83.9, and 64.8 were duplications. duplications and and deletions CNV with probands for IQs deletions average The CNV by affected genes network with probands. ASD high-functioning for mutations recent study to play a ASD less Another prominent cases. role in likely high-functioning are mutations truncating that test, suggest analyses one-tail these exact Overall, (Fisher’s 70 > IQ ratio) with (3.3:1 probands mutations in synonymous IQ 110 mutations with and probands non-truncating synonymous in 330 72 observed were and ratio) (2.2:1 non-truncating 160 70: below signifi were those with compared 70 IQs above with probands in enriched cantly non-truncating non-synonymous mutations, mous for 0.46 100, < IQ for IQ (0.43 probands ASD high-functioning for relatively constant across IQs ( nature nature we Notably, disorder. the to contributes also probands in observed = 6 × 10 WT Although previous studies have primarily emphasized the role of role the emphasized primarily have studies previous Although asked we patterns, expression diverse exhibited genes that Given Notably, there was a significant difference in IQs between probands ≥ < 10 < 100; Fisher’s exact two-tail test, test, two-tail exact Fisher’s 100; WT −3 NEUR < 10 −15 −3 for ADIR-S, P ADIR-S, for de novo de ). ). This result that suggests a in decrease gene dosage has a 4 /P 1 −15 also demonstrated no excess of OSCI PT /P = 0.024 for ADIR-R; genes with truncating muta truncating with genes ADIR-R; for 0.024 = PT mutations in ASD in mutations EN WT = 0.01 for IQ, P C < 10 E

WT advance online publication online advance < 10 < −15 Fig. Fig. 4 /P −15 PT /P < 10 b WT ), ), without a prominent decrease PT 3 , P < 10 7 = 0.08 for ADIR-R; ADIR-R; for 0.08 = , = 0.7). Relative to synony to Relative 0.7). = −4 de novo de 8 , our analysis suggests that that suggests analysis our , for IQ, P −15 de novo 4 /P 2 . . To rela the explore missense mutations mutations missense PT = 0.3 for ADIR-S, WT loss-of-function ≤ < 10 70, whereas whereas 70, Fig. Fig. P

−15 = 0.04). 0.04). = Fig. Fig. 5 ). This This ). /P 43– PT 5 4 ). = 6 ------.

function in the brain. Functional gain and other types of genetic genetic of types other and gain Functional brain. the in function phen autism high-functioning that suggests result this function, of loss a with high-functioning associated are mutations usually truncating in Because ASD cases. role smaller a play mutations truncating that elucidated. be to remain effect this of mechanisms the females, although in effect protective a suggest evidence of sources pendent sizes autism CNVs of analyses in through demonstrated perturbations previously were females functional Stronger phenotypes. autistic female with are associated expression, brain higher substantially with genes of perturbation as such insults, functional stronger that hypothesis disorders. two the in and affected pathways genes specific than autism may lie primarily in the degree of overall functional and disability effect ratherintellectual between distinction the Thus, phenotypes. tions. Stronger functional insults lead, on average, to more severe ASD of consequences phenotypic observed the ence influ to likely are levels, expression brain as such genes, affected of We mechanisms. characteristics for disease the found that functional loinsufficient genes, which confirms that dosage effects are important in hap observed mutations were preferentially found that functional 2. 1. reprints/index.htm at online available is information permissions and Reprints The authors declare no competing interests.financial the results. J.C., A.H.C. andS.R.G., D.V. wrote the manuscript. analysis. functional D.V. the designed study, the project supervised and interpreted results. S.J.S. contributed data, interpreted the results and contributed to the J.C., andS.R.G. A.H.C. performed computational analysis and interpreted the Howard Hughes Medical Institute International Student Research Fellowship. in part by US NIGMS training grant T32 GM082797. S.J.S. was supported by a (MAGNet) grant to U54CA121852 Columbia University. was S.R.G. supported SFARI# 308962 to D.V. and US National Centers for Biomedical Computing discussions. This work was supported by a grant from the Simons Foundation G. Fischbach and all of the members of the Vitkup laboratory for helpful We would like to sincerely thank M. Wigler, M. State, D. Geschwind, A. Packer, online version of the pape Note: Any Supplementary Information and Source Data files are available in the the in v available are references associated any and Methods M therapies. ASD targeted to and, and predictions ultimately,prognostic diagnostic individualized to lead may cancer, in practice common a now stratification, patient Such types. cell and functions biological pathways, affected of basis the on stratified be can patients ASD individual which to extent the investigate to important be will it future, the In severity. phenotypic ASD predicting in useful be may genes target and mutations of ties cases. ASD high-functioning to contributors primary the be may regions, regulatory non-coding in mutations or morphisms such variations, as non-truncating COM AUTH Acknowledgmen ersion of the pape the of ersion

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© 2014 Nature America, Inc. All rights reserved. expected and the observed fractions of SNVs events in various ASD disease gene andPSDgenes.domSNVmutationWeFMRP in occur to comparedthen the calculated fractions represent the background (expected) probabilities for a ran entries were determined using the variant chromosomal position and allele. The ESP variant data was downloaded from only once, that affect FMRP target genes and genes associated with PSD. NHLBI study the in synonymousmutationssynonymous mutations,is,observed that sequencing data of about 6,500 individuals, we calculated the fractions of all rare forNHLBIthe ESPpurpose this exome-sequencing study used we synonymousrare study; ofsequencingexomelarge mutations a from targets FMRP between overlap the using ments approach described ously F largest network before a considerable decrease in network significance. of various network sizes random gene sets while also accounting for multiple hypothesis testing as a networkresult ASD mutations were allowed to participate in the randomization sets. byThe final affected genes genes; long or connected highly by driven not was the top five edge scores) and protein lengths to ensure that network significance match the input genes in terms of network connectivity (based on the average of random gene sets. The random gene sets used in the calculations were chosen to obtained using real input data to the distributionnetwork the of score comparingthe and sets generandom of 5,000 to algorithm network scores obtained using with five or fewer genes were ignored during the network searches. was constrained to contribute at most one gene to the network. Small networks of all pairwise likelihood scores between the network genes connected to the growing network.strongly most Networksgenes the addsare consecutively algorithmscored greedy based the gene, inputon a weighted sum find strongly interconnected networks among the input genes; startingphenotypic ofthe nodes network.togreedysearch from algorithmused A then was each associated with 132 different genetic phenotypes. of human genes compiled by a previous study genomes MINT and MIPS), phylogenetic profiles and chromosomal co-clustering across DIP,BiGG,BioGRID, IntAct,InNetDB,(BIND, HPRD, databases of number a in partners interaction sharedprotein-protein interactions, direct database, protein domains from the InterPro database, tissue expression from the TiGER tations, shared pathways in Kyoto Encyclopedia of Genes and GenomesBayesian (KEGG),integration of various descriptors of protein function: shared GOphenotype geneticsame the utetoanno genes are assigned a score proportional to the likelihood ratio that genes contribrelies on the previously described phenotypic network in Phenotypicwhich networkall andpairs the of human obtained from the original studies weremutations SNV of severity evolutionary the assess to used scores GERP in various tests comparing mutations and corresponding functional properties. SNV) each for (once times multiplecounted were probands these mutations; as input in our analysis. 11 probands considered in our study had multiple SNV duplicate genes resulted in 991 genes at 624 distinct genomic loci that were used removingoverlapsCombiningandevent. separate a as considered were CNV event, the SNV gene was considered individually and the remaining genes in the 5 Mb were ignored. When a gene thanaffected larger CNVs and byevent single ana intocombined SNVwere CNVs Overlappingwas also contained in a CNV studies of families in the SSC and included AS ONLINE MET doi: M Network significance was determined by applying the same greedy search greedy same the applying by determined was significance Network The 991 genes affected by D RP and PS and RP 10.1038/nn.3907 associated P 5 0 value reflects the probability of finding a higher scoring network using . The likelihood network was constructed using a carefully curated set D enrichment among implicatedsets. gene H de novo de ODS 12 variants. 3 , 1 and other similar studies, we estimated the enrich estimatedthe westudies, similar other and 3 de novo . The final network of 159 genes was selected as the NE TBA 4 12 mutations were mapped to the corresponding Variants recentwereobtainedseveral from 9 . , 1 G 3 . This ratio was calculated using a naivea usingcalculated ratiowas This . http:// + algorithm. de novo evs.gs.washington.ed 5 1 that contains 476 human genes 27 CNVs , 3 1 The NETBAG+ algorithm or PSD genes PSD or 6 and 12 3 0 , 1 Following previa . Using. exome-the 3 de novo . Each CNV event u 3 and unique 2 SNVs and a set set a and de novo de 3 , 7 , 8 - - - - - .

significance of various expression differences using a method based on randomly with a Bonferroni correction to account for multiple hypothesis testing. of regional and prenatal biases was evaluated using the Wilcoxon rank-sum test log average log the differencebetween the calculatingquantified bybrainregionwas eachfor log ference between the average log the post-mortem brain samples from healthy individuals. representsquantile-normalized log and Brain Transcriptome database (GEO accession ID, Humanthe from obtained wasregions brainand developmental acrossstages expression. brain human of analysis temporal and Spatial scores were used as the clustering metric. ( hierarchical clustering to divide the implicated network into functional clusters Hierarchical clustering of the implicated network. to the genes affected by ASD mutations ( random sets of human genes matched by protein length targetand networkgenes with connectivityvarious ASD gene sets to FMRP theof overlapoverlap the comparing by resultsof enrichment FMRPFMRP target the confirmed genes with sets using a two-tail binomial test ( 51. 50. 49. P Fisher’scombinedusing Stouffer’sandcombined The methods. meta-analysis onandgenesother thebased affected by recurrent truncating mutations, were genes network on based approaches,oneindependent two the from obtained multiple hypothesis testing using the Benjamini-Hochberg procedure. expressionWilcoxonusingthebiases rank-sumone-tailcorrectedandtestfor genes with cated human genes and the average log the difference between the average log in probands compared to siblings were quantified for each cell providedtype by by calculatingAffymetrix for the Mouse Genome 430 Array. human-mouseorthologs ofThe list the expression used we data, genetichuman biasesthe and data ferent cell types from the GSE1337 previouslyobtained data expression mouse considered we types, cell specific toward genes cated C taking the difference between the corresponding expression averages. median expression value of probe sets; expression biases were then calculated by the taking computedexpressiontranscript-levelbywe data, HBT original the in corresponding original gene sets. Analogous to the procedure used to process sampled in each of 10,000 random trials were equal to the numbers of biasprobes greater or equal to the bias insets the original data. The numbers of probe sets P generated expression probe sets ( Supplementary Fig. 1 Fig. Supplementary values were corrected using the Bonferroni method. values (P ell type–specific expression analysis. Complementary to the Wilcoxon rank-sum test (P To quantify the expression biases for each brain region, we calculated the dif A 2 2

eda, . Rhtk, . Vtu, . ewr poete o gns harboring genes of properties Network D. Vitkup, & using A. activities Rzhetsky, metabolic I., orphan Feldman, for genes Predicting D. Vitkup, & L. Chen, G.M. Cooper, (2008). mutations. disease inherited profiles. phylogenetic sequence. postnatal expression (early infancy to late adulthood stages). The significance expression of genes harboring SNVs in siblings. The prenatal expression bias Supplementary 9 ). The considered data set contains expression information for 25 dif 2 PT de novo of prenatal expression (embryonic to late fetal stages) and the average ) obtained with the random trials reflect the probability to obtain a Genome Res. Genome et al. et SNVs in unaffected siblings. We evaluated significances of the 1 Distribution and intensity of constraint in mammalian genomic mammalian in constraint of intensity and Distribution 7 M using ribosome affinity purification (GEO accession ID accessionpurification(GEO affinity ribosome using ethods Genome Biol. Genome ). The inverses of the phenotypic network likelihood likelihood network phenotypic the of inverses The ). Mus musculus

15 , 901–913 (2005). 901–913 , C 2 expression of implicated genes and the average Supplementary Table 9 rc Nt. cd Si USA Sci. Acad. Natl. Proc. hecklist Table

7 2 2 , R17 (2006). R17 , expression of mouse orthologs for impli expression of mouse ortholog for human To evaluate expression bias of the impli CNS. To connect the mouse expression 2 2 Supplementary Table 6 -transformedexpressions fromvalues and is available. Supplementary Table 5 nature nature GSE2521 We used the average linkage WT ), we also estimated the ). The permutation test 9

NEUR ) 105 Expression data Expression 1 6 ; the HBT data ). 4323–4328 , OSCI ). We also P values EN C E - - - -