Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

doi:10.1016/j.cell.2019.12.036

. 2020 Feb 6;180(3):568-584.e23.

doi: 10.1016/j.cell.2019.12.036. Epub 2020 Jan 23.

Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

F Kyle Satterstrom¹, Jack A Kosmicki², Jiebiao Wang³, Michael S Breen⁴, Silvia De Rubeis⁴, Joon-Yong An⁵, Minshi Peng³, Ryan Collins⁶, Jakob Grove⁷, Lambertus Klei⁸, Christine Stevens⁹, Jennifer Reichert¹⁰, Maureen S Mulhern¹⁰, Mykyta Artomov⁹, Sherif Gerges⁹, Brooke Sheppard¹¹, Xinyi Xu¹⁰, Aparna Bhaduri¹², Utku Norman¹³, Harrison Brand¹⁴, Grace Schwartz¹¹, Rachel Nguyen¹⁵, Elizabeth E Guerrero¹⁶, Caroline Dias¹⁷; Autism Sequencing Consortium; iPSYCH-Broad Consortium; Catalina Betancur¹⁸, Edwin H Cook¹⁹, Louise Gallagher²⁰, Michael Gill²⁰, James S Sutcliffe²¹, Audrey Thurm²², Michael E Zwick²³, Anders D Børglum²⁴, Matthew W State¹¹, A Ercument Cicek²⁵, Michael E Talkowski¹⁴, David J Cutler²³, Bernie Devlin⁸, Stephan J Sanders²⁶, Kathryn Roeder²⁷, Mark J Daly²⁸, Joseph D Buxbaum²⁹

Collaborators, Affiliations

Collaborators

Branko Aleksic, Richard Anney, Mafalda Barbosa, Somer Bishop, Alfredo Brusco, Jonas Bybjerg-Grauholm, Angel Carracedo, Marcus C Y Chan, Andreas G Chiocchetti, Brian H Y Chung, Hilary Coon, Michael L Cuccaro, Aurora Curró, Bernardo Dalla Bernardina, Ryan Doan, Enrico Domenici, Shan Dong, Chiara Fallerini, Montserrat Fernández-Prieto, Giovanni Battista Ferrero, Christine M Freitag, Menachem Fromer, J Jay Gargus, Daniel Geschwind, Elisa Giorgio, Javier González-Peñas, Stephen Guter, Danielle Halpern, Emily Hansen-Kiss, Xin He, Gail E Herman, Irva Hertz-Picciotto, David M Hougaard, Christina M Hultman, Iuliana Ionita-Laza, Suma Jacob, Jesslyn Jamison, Astanand Jugessur, Miia Kaartinen, Gun Peggy Knudsen, Alexander Kolevzon, Itaru Kushima, So Lun Lee, Terho Lehtimäki, Elaine T Lim, Carla Lintas, W Ian Lipkin, Diego Lopergolo, Fátima Lopes, Yunin Ludena, Patricia Maciel, Per Magnus, Behrang Mahjani, Nell Maltman, Dara S Manoach, Gal Meiri, Idan Menashe, Judith Miller, Nancy Minshew, Eduarda M S Montenegro, Danielle Moreira, Eric M Morrow, Ole Mors, Preben Bo Mortensen, Matthew Mosconi, Pierandrea Muglia, Benjamin M Neale, Merete Nordentoft, Norio Ozaki, Aarno Palotie, Mara Parellada, Maria Rita Passos-Bueno, Margaret Pericak-Vance, Antonio M Persico, Isaac Pessah, Kaija Puura, Abraham Reichenberg, Alessandra Renieri, Evelise Riberi, Elise B Robinson, Kaitlin E Samocha, Sven Sandin, Susan L Santangelo, Gerry Schellenberg, Stephen W Scherer, Sabine Schlitt, Rebecca Schmidt, Lauren Schmitt, Isabela M W Silva, Tarjinder Singh, Paige M Siper, Moyra Smith, Gabriela Soares, Camilla Stoltenberg, Pål Suren, Ezra Susser, John Sweeney, Peter Szatmari, Lara Tang, Flora Tassone, Karoline Teufel, Elisabetta Trabetti, Maria Del Pilar Trelles, Christopher A Walsh, Lauren A Weiss, Thomas Werge, Donna M Werling, Emilie M Wigdor, Emma Wilkinson, A Jeremy Willsey, Timothy W Yu, Mullin H C Yu, Ryan Yuen, Elaine Zachi, Esben Agerbo, Thomas Damm Als, Vivek Appadurai, Marie Bækvad-Hansen, Rich Belliveau, Alfonso Buil, Caitlin E Carey, Felecia Cerrato, Kimberly Chambert, Claire Churchhouse, Søren Dalsgaard, Ditte Demontis, Ashley Dumont, Jacqueline Goldstein, Christine S Hansen, Mads Engel Hauberg, Mads V Hollegaard, Daniel P Howrigan, Hailiang Huang, Julian Maller, Alicia R Martin, Joanna Martin, Manuel Mattheisen, Jennifer Moran, Jonatan Pallesen, Duncan S Palmer, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Timothy Poterba, Jesper Buchhave Poulsen, Stephan Ripke, Andrew J Schork, Wesley K Thompson, Patrick Turley, Raymond K Walters

Affiliations

¹ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
² Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
³ Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA.
⁴ Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁵ Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, Republic of Korea.
⁶ Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA.
⁷ The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Center for Genomics and Personalized Medicine, Aarhus, Denmark; Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark.
⁸ Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
⁹ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
¹⁰ Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹¹ Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
¹² Department of Neurology, University of California, San Francisco, San Francisco, CA, USA; The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
¹³ Computer Engineering Department, Bilkent University, Ankara, Turkey.
¹⁴ Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
¹⁵ Center for Autism Research and Translation, University of California, Irvine, Irvine, CA, USA.
¹⁶ MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California, Davis, Davis, CA, USA.
¹⁷ Division of Genetics, Boston Children's Hospital, Boston, MA, USA; Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA.
¹⁸ Sorbonne Université, INSERM, CNRS, Neuroscience Paris Seine, Institut de Biologie Paris Seine, Paris, France.
¹⁹ Institute for Juvenile Research, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA.
²⁰ Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland.
²¹ Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA; Department of Molecular Physiology and Biophysics and Psychiatry, Vanderbilt University School of Medicine, Nashville, TN, USA.
²² National Institute of Mental Health, NIH, Bethesda, MD, USA.
²³ Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA.
²⁴ The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Center for Genomics and Personalized Medicine, Aarhus, Denmark; Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark; Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.
²⁵ Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA; Computer Engineering Department, Bilkent University, Ankara, Turkey.
²⁶ Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA. Electronic address: [email protected].
²⁷ Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA; Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA. Electronic address: [email protected].
²⁸ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. Electronic address: [email protected].
²⁹ Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Electronic address: [email protected].

PMID: 31981491
PMCID: PMC7250485
DOI: 10.1016/j.cell.2019.12.036

Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

F Kyle Satterstrom et al. Cell. 2020.

. 2020 Feb 6;180(3):568-584.e23.

doi: 10.1016/j.cell.2019.12.036. Epub 2020 Jan 23.

Authors

Collaborators

Branko Aleksic, Richard Anney, Mafalda Barbosa, Somer Bishop, Alfredo Brusco, Jonas Bybjerg-Grauholm, Angel Carracedo, Marcus C Y Chan, Andreas G Chiocchetti, Brian H Y Chung, Hilary Coon, Michael L Cuccaro, Aurora Curró, Bernardo Dalla Bernardina, Ryan Doan, Enrico Domenici, Shan Dong, Chiara Fallerini, Montserrat Fernández-Prieto, Giovanni Battista Ferrero, Christine M Freitag, Menachem Fromer, J Jay Gargus, Daniel Geschwind, Elisa Giorgio, Javier González-Peñas, Stephen Guter, Danielle Halpern, Emily Hansen-Kiss, Xin He, Gail E Herman, Irva Hertz-Picciotto, David M Hougaard, Christina M Hultman, Iuliana Ionita-Laza, Suma Jacob, Jesslyn Jamison, Astanand Jugessur, Miia Kaartinen, Gun Peggy Knudsen, Alexander Kolevzon, Itaru Kushima, So Lun Lee, Terho Lehtimäki, Elaine T Lim, Carla Lintas, W Ian Lipkin, Diego Lopergolo, Fátima Lopes, Yunin Ludena, Patricia Maciel, Per Magnus, Behrang Mahjani, Nell Maltman, Dara S Manoach, Gal Meiri, Idan Menashe, Judith Miller, Nancy Minshew, Eduarda M S Montenegro, Danielle Moreira, Eric M Morrow, Ole Mors, Preben Bo Mortensen, Matthew Mosconi, Pierandrea Muglia, Benjamin M Neale, Merete Nordentoft, Norio Ozaki, Aarno Palotie, Mara Parellada, Maria Rita Passos-Bueno, Margaret Pericak-Vance, Antonio M Persico, Isaac Pessah, Kaija Puura, Abraham Reichenberg, Alessandra Renieri, Evelise Riberi, Elise B Robinson, Kaitlin E Samocha, Sven Sandin, Susan L Santangelo, Gerry Schellenberg, Stephen W Scherer, Sabine Schlitt, Rebecca Schmidt, Lauren Schmitt, Isabela M W Silva, Tarjinder Singh, Paige M Siper, Moyra Smith, Gabriela Soares, Camilla Stoltenberg, Pål Suren, Ezra Susser, John Sweeney, Peter Szatmari, Lara Tang, Flora Tassone, Karoline Teufel, Elisabetta Trabetti, Maria Del Pilar Trelles, Christopher A Walsh, Lauren A Weiss, Thomas Werge, Donna M Werling, Emilie M Wigdor, Emma Wilkinson, A Jeremy Willsey, Timothy W Yu, Mullin H C Yu, Ryan Yuen, Elaine Zachi, Esben Agerbo, Thomas Damm Als, Vivek Appadurai, Marie Bækvad-Hansen, Rich Belliveau, Alfonso Buil, Caitlin E Carey, Felecia Cerrato, Kimberly Chambert, Claire Churchhouse, Søren Dalsgaard, Ditte Demontis, Ashley Dumont, Jacqueline Goldstein, Christine S Hansen, Mads Engel Hauberg, Mads V Hollegaard, Daniel P Howrigan, Hailiang Huang, Julian Maller, Alicia R Martin, Joanna Martin, Manuel Mattheisen, Jennifer Moran, Jonatan Pallesen, Duncan S Palmer, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Timothy Poterba, Jesper Buchhave Poulsen, Stephan Ripke, Andrew J Schork, Wesley K Thompson, Patrick Turley, Raymond K Walters

Affiliations

¹ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
² Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
³ Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA.
⁴ Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁵ Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, Republic of Korea.
⁶ Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA.
⁷ The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Center for Genomics and Personalized Medicine, Aarhus, Denmark; Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark.
⁸ Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
⁹ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
¹⁰ Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹¹ Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
¹² Department of Neurology, University of California, San Francisco, San Francisco, CA, USA; The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
¹³ Computer Engineering Department, Bilkent University, Ankara, Turkey.
¹⁴ Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
¹⁵ Center for Autism Research and Translation, University of California, Irvine, Irvine, CA, USA.
¹⁶ MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California, Davis, Davis, CA, USA.
¹⁷ Division of Genetics, Boston Children's Hospital, Boston, MA, USA; Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA.
¹⁸ Sorbonne Université, INSERM, CNRS, Neuroscience Paris Seine, Institut de Biologie Paris Seine, Paris, France.
¹⁹ Institute for Juvenile Research, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA.
²⁰ Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland.
²¹ Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA; Department of Molecular Physiology and Biophysics and Psychiatry, Vanderbilt University School of Medicine, Nashville, TN, USA.
²² National Institute of Mental Health, NIH, Bethesda, MD, USA.
²³ Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA.
²⁴ The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Center for Genomics and Personalized Medicine, Aarhus, Denmark; Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark; Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.
²⁵ Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA; Computer Engineering Department, Bilkent University, Ankara, Turkey.
²⁶ Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA. Electronic address: [email protected].
²⁷ Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA; Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA. Electronic address: [email protected].
²⁸ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. Electronic address: [email protected].
²⁹ Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Electronic address: [email protected].

PMID: 31981491
PMCID: PMC7250485
DOI: 10.1016/j.cell.2019.12.036

Abstract

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

Keywords: autism spectrum disorder; cell type; cytoskeleton; excitatory neurons; excitatory-inhibitory balance; exome sequencing; genetics; inhibitory neurons; liability; neurodevelopment.

PubMed Disclaimer

Conflict of interest statement

Declaration of Interests B.M.N. is a member of the scientific advisory board at Deep Genomics and consults for Biogen, Camp4 Therapeutics Corporation, Takeda Pharmaceutical, and Biogen. During the last 3 years, C.M. Freitag has been consultant to Desitin and Roche and receives royalties for books on ASD, ADHD, and MDD.

Figures

**Figure 1.. Distribution of Rare Autosomal Protein-Coding Variants in ASD Cases and Controls**
(A) The proportion of rare autosomal genetic variants split by predicted functional consequences, represented by color, is displayed for family-based (split into *de novo* and inherited variants) and case-control data. PTVs and missense variants are split into three tiers of predicted functional severity, represented by shade, based on the pLI and MPC metrics, respectively. (B) The relative difference in variant frequency (i.e., burden) between ASD cases and controls (top and bottom) or transmitted and untransmitted parental variants (center) is shown for the top two tiers of functional severity for PTVs (left and center) and the top tier of functional severity for missense variants (right). Next to the bar plot, the same data are shown divided by sex. (C) The relative difference in variant frequency shown in (B) is converted to a trait liability Z score, split by the same subsets used in (A). For context, a Z score of 2.18 would shift an individual from the population mean to the top 1.69% of the population (equivalent to an ASD threshold based on 1 in 68 children; Christensen et al., 2016). No significant difference in liability was observed between males and females for any analysis. Statistical tests: (B) and (C), binomial exact test (BET) for most contrasts; exceptions were “both” and “case-control,” for which Fisher’s method for combining BET p values for each sex and, for case-control, each population was used; p values corrected for 168 tests are shown.

**Figure 2.. Gene Discovery in the ASC Cohort**
(A) WES data from 35,584 samples are entered into a Bayesian analysis framework (TADA) that incorporates pLI score for PTVs and MPC score for missense variants. (B) The model identifies 102 autosomal genes associated with ASD at a false discovery rate (FDR) threshold of 0.1 or less, which is shown on the y axis of this Manhattan plot, with each point representing a gene. Of these, 78 pass the threshold FDR of 0.05 or less, and 26 pass the threshold family-wise error rate (FWER) of 0.05 or less. (C) Repeating our ASD trait liability analysis (Figure 1C) for variants observed within the 102 ASD-associated genes only. Statistical tests: (B), TADA; (C), BET for most contrasts; exceptions were “both” and “case-control,” for which Fisher’s method for combining BET p values for each sex and, for case-control, each population was used; p values corrected for 168 tests are shown.

**Figure 3.. Genetic Characterization of ASD Genes**
(A) Count of PTVs versus missensevariants(MPC ≥ 1) in cases for each ASD-associated gene (red points, selected genes labeled). These counts reflect the data used by TADA for association analysis: *de novo* and case-control data for PTVs; *de novo* only for missense. (B) Location of ASD *de novo* missense variants in *DEAF1*. The five ASD variants (marked in red) are in the SAND (Sp100, AIRE-1, NucP41/75, DEAF-1) DNA-binding domain (amino acids 193–273, spirals show α helices, arrows show β sheets, KDWK isthe DNA-binding motif) alongside 10 variants observed in NDD, several of which have been shown to reduce DNA binding, including Q264P and Q264R (Chen et al., 2017; Heyne et al., 2018; Vultovan Silfhout et al., 2014). (C) Location of ASD missensevariants in *KCNQ3*. All four ASD variants are located in the voltage sensor (fourth of six transmembrane domains), with three in the same residue (R230), including the gain-of-function R230C mutation observed in NDD (Heyne et al., 2018; Miceli et al, 2015). Five inherited variants observed in benign infantile seizures are shown in the pore loop (Landrum et al., 2014; Maljevic et al., 2016). (D) Location of ASD missense variants in *SCN1A* along side 17 *de novo* variants in NDD and epilepsy (Heyne et al., 2018). (E) Location of ASD missense variants in *SLC6A1* along side 31 *de novo* variants in NDD and epilepsy (Heyne et al., 2018; Johannesen et al., 2018). (F) Subtelomeric 2q37 deletions are associated with facial dysmorphisms, brachydactyly, high BMI, NDD, and ASD (Leroy et al., 2013). Although three genes within the locus have a pLI score of 0.995 or higher, only *HDLBP* is associated with ASD. (G) Deletions atthe 11q13.2–q13.4 locus have been observed in NDD, ASD, and otodental dysplasia (Coe et al., 2014; Cooperet al., 2011). Five genes within the locus have a pLI score of 0.995 or higher, including two ASD genes: *KMT5B* and *SHANK2*. (H) Assessment of gene-based enrichment, via MAGMA, of 102 ASD genes against genome-wide significant common variants from six GWASs. (I) Gene-based enrichment of 102 ASD genes in multiple GWASs as a function of effective cohort size. The GWAS used for each disorder in (I) has a black outline. Statistical tests: (F) and (G), TADA; (H) and (I), MAGMA.

**Figure 4.. Phenotypic and Functional Categories of ASD-Associated Genes**
(A) Frequency of disruptive *de novo* variants (e.g., PTVs or missense variants with MPC ≥ 1) in ASD-ascertained and NDD-ascertained cohorts (Table S4) is shown for the 102 ASD-associated genes (selected genes labeled). Fifty genes with a higher frequency in ASD are designated ASD-predominant (ASDp), whereas the 49 genes more frequently mutated in NDD are designated as ASD_NDD. Three genes marked with a star(*UBR1*, *MAP1A*, and *NUP155*) are included in the ASDP category on the basis of case-control data (Table S4), which are not shown here. Of the 26 FWER genes, 10 are ASDp and 16 are ASD_NDD. Of the 102 genes, 13 demonstrate nominally significant heterogeneity between samples ascertained for ASD versus NDD (Table S4). (B) ASD cases with disruptive *de novo* variants in ASD genes show delayed walking compared with ASD cases without such *de novo* variants, and the effect is greater for those with disruptive *de novo* variants in ASDNDD genes. (C) Similarly, cases with disruptive *de novo* variants in ASD_NDD genes and, to a lesser extent, ASD_P genes have a lower full-scale IQ (FSIQ) than other ASD cases. (D) Despite the association between *de novo* variants in ASD genes and cognitive impairment shown in (C), an excess of disruptive *de novo* variants is observed in cases without intellectual disability (FSIQ ≥ 70) or with an IQ above the cohort mean (FSIQ ≥ 82). (E) Along with the phenotypic division (A), genes can also be classified functionally into four groups (gene expression regulation [GER], neuronal communication [NC], cytoskeleton, and other) based on Gene Ontology and research literature. The 102 ASD risk genes are shown in a mosaic plot divided by gene function and, from (A), the ASD versus NDD variant frequency, with the area of each box proportional to the number of genes. Statistical tests: (B) and (C), t test; (D), chi-square test with 1° of freedom.

**Figure 5.. Analysis of 102 ASD-Associated Genes in the Context of Gene Expression Data**
(A) GTEx bulk RNA-seq data from 53 tissues were processed to identify genes enriched in specific tissues. Gene set enrichment was performed for the 102 ASD genes and four subsets (ASD_P, ASD_NDD, GER, and NC) for each tissue. Five representative tissues are shown here, including cortex, which has the greatest degree of enrichment (OR = 3.7; p = 2.6 × 10⁻⁶). (B) BrainSpan bulk RNA-seq data across 10 developmental stages was used to plot the normalized expression of the 101 cortically expressed ASD genes (excluding *PAX5*, which is not expressed in the cortex) across development, split by the four subsets. (C) A t-statistic was calculated, comparing prenatal with postnatal expression in the BrainSpan data. The t-statistic distribution of 101 ASD-associated genes shows a prenatal bias (p = 8 × 10⁻⁸) for GER genes (p = 9 × 10⁻¹⁵), whereas NC genes are postnatally biased (p = 0.03). (D) The cumulative number of ASD-associated genes expressed in RNA-seq data for 4,261 cells collected from human forebrain across prenatal development (Nowakowski et al., 2017). (E) t-SNE analysis identifies 19 clusters with unambiguous cell type in these single-cell expression data. (F) The enrichment of the 102 ASD-associated genes within cells of each type is represented by color. The most consistent enrichment is observed in maturing and mature excitatory (bottom center) and inhibitory (top right) neurons. (G) The developmental relationships of the 19 clusters are indicated by black arrows, with the inhibitory lineage shown on the left (cyan), excitatory lineage in the middle (magenta), and non-neuronal cell types on the right (gray). The proportion of the 102 ASD-associated genes observed in at least 25% of cells within the cluster is shown by the pie chart, whereas the log-transformed Bonferroni-corrected p value of gene set enrichment is shown by the size of the red circle. (H) The relationship between the number of cells in the cluster (x axis) and the p value for ASD gene enrichment (y axis) is shown for the 19 cell type clusters. Linear regression indicates that clusters with few expressed genes (e.g., C23 newborn inhibitory neurons) have higher p valuesthan clusters with many genes (e.g., C25 radial glia). (I) The relationship between the 19 cell type clusters using hierarchical clustering based on the 10% of genes with the greatest variability among cell types. Statistical tests: (A), t test; (C), Wilcoxon test; (E), (F), (H), and (I), FET.

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Comment in

High-Risk, High-Reward Genetics in ASD.
Castellani CA, Arking DE. Castellani CA, et al. Neuron. 2020 Feb 5;105(3):407-410. doi: 10.1016/j.neuron.2020.01.007. Neuron. 2020. PMID: 32027831 Free PMC article.
Autism Genetics: Over 100 Risk Genes and Counting.
Forrest MP, Penzes P. Forrest MP, et al. Pediatr Neurol Briefs. 2020 Dec 4;34:13. doi: 10.15844/pedneurbriefs-34-13. Pediatr Neurol Briefs. 2020. PMID: 33304087 Free PMC article.

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References

1. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, and Sunyaev SR (2010). A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249. - PMC - PubMed
1. Baio J, Wiggins L, Christensen DL, Maenner MJ, Daniels J, Warren Z, Kurzius-Spencer M, Zahorodny W, Robinson Rosenberg C, White T, et al. (2018). Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014. MMWR Surveill Summ. 67, 1–23. - PMC - PubMed
1. Battle A, Brown CD, Engelhardt BE, and Montgomery SB; GTEx Consortium; Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group; Statistical Methods groups—Analysis Working Group; Enhancing GTEx (eGTEx) groups; NIH Common Fund; NIH/NCI; NIH/NHGRI; NIH/NIMH; NIH/NIDA; Biospecimen Collection Source Site—NDRI; Biospecimen Collection Source Site—RPCI; Biospecimen Core Resource—VARI; Brain Bank Repository—University of Miami Brain Endowment Bank; Leidos Biomedical—Project Management; ELSI Study; Genome Browser Data Integration &Visualization — EBI; Genome Browser Data Integration &Visualization — UCSC Genomics Institute, University of California Santa Cruz; Lead analysts; Laboratory, Data Analysis &Coordinating Center (LDACC); NIH program management; Biospecimen collection; Pathology; eQTL manuscript working group (2017). Genetic effects on gene expression across human tissues. Nature 550, 204–213. - PubMed
1. Ben-Shalom R, Keeshen CM, Berrios KN, An JY, Sanders SJ, and Bender KJ (2017). Opposing effects on NaV1.2 function underlie differences between SCN2A variants observed in individuals with autism spectrum disorder or infantile seizures. Biol. Psychiatry 82, 224–232. - PMC - PubMed
1. Bernier R, Golzio C, Xiong B, Stessman HA, Coe BP, Penn O, Witherspoon K, Gerdts J, Baker C, Vulto-van Silfhout AT, et al. (2014). Disruptive CHD8 mutations define a subtype of autism early in development. Cell 158, 263–276. - PMC - PubMed

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[1] Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, and Sunyaev SR (2010). A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249. - PMC - PubMed

[2] Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, and Sunyaev SR (2010). A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249. - PMC - PubMed

[3] Baio J, Wiggins L, Christensen DL, Maenner MJ, Daniels J, Warren Z, Kurzius-Spencer M, Zahorodny W, Robinson Rosenberg C, White T, et al. (2018). Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014. MMWR Surveill Summ. 67, 1–23. - PMC - PubMed

[4] Baio J, Wiggins L, Christensen DL, Maenner MJ, Daniels J, Warren Z, Kurzius-Spencer M, Zahorodny W, Robinson Rosenberg C, White T, et al. (2018). Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014. MMWR Surveill Summ. 67, 1–23. - PMC - PubMed

[5] Battle A, Brown CD, Engelhardt BE, and Montgomery SB; GTEx Consortium; Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group; Statistical Methods groups—Analysis Working Group; Enhancing GTEx (eGTEx) groups; NIH Common Fund; NIH/NCI; NIH/NHGRI; NIH/NIMH; NIH/NIDA; Biospecimen Collection Source Site—NDRI; Biospecimen Collection Source Site—RPCI; Biospecimen Core Resource—VARI; Brain Bank Repository—University of Miami Brain Endowment Bank; Leidos Biomedical—Project Management; ELSI Study; Genome Browser Data Integration &Visualization — EBI; Genome Browser Data Integration &Visualization — UCSC Genomics Institute, University of California Santa Cruz; Lead analysts; Laboratory, Data Analysis &Coordinating Center (LDACC); NIH program management; Biospecimen collection; Pathology; eQTL manuscript working group (2017). Genetic effects on gene expression across human tissues. Nature 550, 204–213. - PubMed

[6] Battle A, Brown CD, Engelhardt BE, and Montgomery SB; GTEx Consortium; Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group; Statistical Methods groups—Analysis Working Group; Enhancing GTEx (eGTEx) groups; NIH Common Fund; NIH/NCI; NIH/NHGRI; NIH/NIMH; NIH/NIDA; Biospecimen Collection Source Site—NDRI; Biospecimen Collection Source Site—RPCI; Biospecimen Core Resource—VARI; Brain Bank Repository—University of Miami Brain Endowment Bank; Leidos Biomedical—Project Management; ELSI Study; Genome Browser Data Integration &Visualization — EBI; Genome Browser Data Integration &Visualization — UCSC Genomics Institute, University of California Santa Cruz; Lead analysts; Laboratory, Data Analysis &Coordinating Center (LDACC); NIH program management; Biospecimen collection; Pathology; eQTL manuscript working group (2017). Genetic effects on gene expression across human tissues. Nature 550, 204–213. - PubMed

[7] Ben-Shalom R, Keeshen CM, Berrios KN, An JY, Sanders SJ, and Bender KJ (2017). Opposing effects on NaV1.2 function underlie differences between SCN2A variants observed in individuals with autism spectrum disorder or infantile seizures. Biol. Psychiatry 82, 224–232. - PMC - PubMed

[8] Ben-Shalom R, Keeshen CM, Berrios KN, An JY, Sanders SJ, and Bender KJ (2017). Opposing effects on NaV1.2 function underlie differences between SCN2A variants observed in individuals with autism spectrum disorder or infantile seizures. Biol. Psychiatry 82, 224–232. - PMC - PubMed

[9] Bernier R, Golzio C, Xiong B, Stessman HA, Coe BP, Penn O, Witherspoon K, Gerdts J, Baker C, Vulto-van Silfhout AT, et al. (2014). Disruptive CHD8 mutations define a subtype of autism early in development. Cell 158, 263–276. - PMC - PubMed

[10] Bernier R, Golzio C, Xiong B, Stessman HA, Coe BP, Penn O, Witherspoon K, Gerdts J, Baker C, Vulto-van Silfhout AT, et al. (2014). Disruptive CHD8 mutations define a subtype of autism early in development. Cell 158, 263–276. - PMC - PubMed

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Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

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Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

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