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      Integrating de novo and inherited variants in 42,607 autism cases identifies mutations in new moderate-risk genes

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      1 , 2 , 3 , 1 , 2 , 4 , 5 , 6 , 3 , 3 , 1 , 2 , 3 , 4 , 7 , 3 , 8 , 8 , 3 , 3 , 3 , 3 , 3 , 9 , 10 , 4 , 11 , 11 , 9 , The SPARK Consortium, 8 , 3 , 4 , 7 , 2 , 12 , 1 , 3 , 13 ,
      Nature Genetics
      Nature Publishing Group US
      Autism spectrum disorders, Neuroscience, Sequencing

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          Abstract

          To capture the full spectrum of genetic risk for autism, we performed a two-stage analysis of rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new cases recruited online by SPARK. We identified 60 genes with exome-wide significance ( P < 2.5 × 10 −6), including five new risk genes ( NAV3, ITSN1, MARK2, SCAF1 and HNRNPUL2). The association of NAV3 with autism risk is primarily driven by rare inherited loss-of-function (LoF) variants, with an estimated relative risk of 4, consistent with moderate effect. Autistic individuals with LoF variants in the four moderate-risk genes ( NAV3, ITSN1, SCAF1 and HNRNPUL2; n = 95) have less cognitive impairment than 129 autistic individuals with LoF variants in highly penetrant genes ( CHD8, SCN2A, ADNP, FOXP1 and SHANK3) (59% vs 88%, P = 1.9 × 10 −6). Power calculations suggest that much larger numbers of autism cases are needed to identify additional moderate-risk genes.

          Abstract

          An integrated analysis of de novo and inherited coding variants in 42,607 individuals with autism spectrum disorder identifies 60 risk genes of which five have not previously been associated with neurodevelopmental disorders.

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          Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

          Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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            STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

            Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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              The mutational constraint spectrum quantified from variation in 141,456 humans

              Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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                Author and article information

                Contributors
                wkc15@columbia.edu
                Journal
                Nat Genet
                Nat Genet
                Nature Genetics
                Nature Publishing Group US (New York )
                1061-4036
                1546-1718
                18 August 2022
                18 August 2022
                2022
                : 54
                : 9
                : 1305-1319
                Affiliations
                [1 ]GRID grid.239585.0, ISNI 0000 0001 2285 2675, Department of Pediatrics, , Columbia University Medical Center, ; New York, NY USA
                [2 ]GRID grid.239585.0, ISNI 0000 0001 2285 2675, Department of Systems Biology, , Columbia University Medical Center, ; New York, NY USA
                [3 ]GRID grid.430264.7, ISNI 0000 0004 4648 6763, Simons Foundation, ; New York, NY USA
                [4 ]GRID grid.34477.33, ISNI 0000000122986657, Department of Genome Sciences, , University of Washington School of Medicine, ; Seattle, WA USA
                [5 ]GRID grid.11135.37, ISNI 0000 0001 2256 9319, Department of Medical Genetics, , Center for Medical Genetics, School of Basic Medical Sciences, Peking University Health Science Center, ; Beijing, China
                [6 ]GRID grid.11135.37, ISNI 0000 0001 2256 9319, Neuroscience Research Institute, , Department of Neurobiology, School of Basic Medical Sciences, Peking University Health Science Center; Key Laboratory for Neuroscience, Ministry of Education of China & National Health Commission of China, ; Beijing, China
                [7 ]GRID grid.34477.33, ISNI 0000000122986657, Howard Hughes Medical Institute, , University of Washington, ; Seattle, WA USA
                [8 ]GRID grid.214572.7, ISNI 0000 0004 1936 8294, Department of Psychiatry, , University of Iowa Carver College of Medicine, ; Iowa City, IA USA
                [9 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, , University of California, Los Angeles, ; Los Angeles, CA USA
                [10 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Department of Genetics, , Washington University, ; St. Louis, MO USA
                [11 ]GRID grid.5288.7, ISNI 0000 0000 9758 5690, Department of Molecular & Medical Genetics, , Oregon Health & Science University, ; Portland, OR USA
                [12 ]GRID grid.239585.0, ISNI 0000 0001 2285 2675, Department of Biomedical Informatics, , Columbia University Medical Center, ; New York, NY USA
                [13 ]GRID grid.239585.0, ISNI 0000 0001 2285 2675, Department of Medicine, , Columbia University Medical Center, ; New York, NY USA
                [14 ]GRID grid.240684.c, ISNI 0000 0001 0705 3621, Department of Psychiatry and Behavioral Sciences, , Rush University Medical Center, ; Chicago, IL USA
                [15 ]GRID grid.223827.e, ISNI 0000 0001 2193 0096, Department of Pediatrics, , University of Utah, ; Salt Lake City, UT USA
                [16 ]GRID grid.412807.8, ISNI 0000 0004 1936 9916, Vanderbilt Kennedy Center, , Vanderbilt University Medical Center, ; Nashville, TN USA
                [17 ]GRID grid.240023.7, ISNI 0000 0004 0427 667X, Center for Autism and Related Disorders, , Kennedy Krieger Institute, ; Baltimore, MD USA
                [18 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Department of Psychiatry and Biobehavioral Sciences, , University of California, Los Angeles, ; Los Angeles, CA USA
                [19 ]PreventionGenetics, Marshfield, WI USA
                [20 ]GRID grid.134936.a, ISNI 0000 0001 2162 3504, Thompson Center for Autism and Neurodevelopmental Disorders, , University of Missouri, ; Columbia, MO USA
                [21 ]GRID grid.17635.36, ISNI 0000000419368657, Department of Pediatrics, , University of Minnesota, ; Minneapolis, MN USA
                [22 ]GRID grid.47100.32, ISNI 0000000419368710, Child Study Center, , Yale School of Medicine, ; New Haven, CT USA
                [23 ]GRID grid.240023.7, ISNI 0000 0004 0427 667X, Department of Neurogenetics, , Kennedy Krieger Institute, ; Baltimore, MD USA
                [24 ]GRID grid.214458.e, ISNI 0000000086837370, Department of Psychiatry, , University of Michigan, ; Ann Arbor, MI USA
                [25 ]GRID grid.26790.3a, ISNI 0000 0004 1936 8606, Department of Psychology, , University of Miami’s Center for Autism and Related Disabilities (UM-CARD), ; Coral Gables, FL USA
                [26 ]GRID grid.168010.e, ISNI 0000000419368956, Department of Psychiatry and Behavioral Sciences, , Stanford University, ; Stanford, CA USA
                [27 ]GRID grid.240344.5, ISNI 0000 0004 0392 3476, Division of Pediatric Psychology and Neuropsychology, , Nationwide Children’s Hospital (Child Development Center), ; Columbus, OH USA
                [28 ]GRID grid.26790.3a, ISNI 0000 0004 1936 8606, John P. Hussman Institute for Human Genomics, , University of Miami Miller School of Medicine, ; Miami, FL USA
                [29 ]GRID grid.17635.36, ISNI 0000000419368657, Department of Psychiatry, , University of Minnesota, ; Minneapolis, MN USA
                [30 ]GRID grid.239573.9, ISNI 0000 0000 9025 8099, Department of Psychiatry and Behavioral Neuroscience, , Cincinnati Children’s Hospital Medical Center - Research Foundation, ; Cincinnati, OH USA
                [31 ]GRID grid.412807.8, ISNI 0000 0004 1936 9916, Department of Pediatrics, , Vanderbilt University Medical Center, ; Nashville, TN USA
                [32 ]GRID grid.5288.7, ISNI 0000 0000 9758 5690, Department of Psychiatry, , Oregon Health & Science University, ; Portland, OR USA
                [33 ]GRID grid.67105.35, ISNI 0000 0001 2164 3847, Department of Pediatrics, , JFK Partners/University of Colorado School of Medicine, ; Aurora, CO USA
                [34 ]Department of Neurosciences, University of California, San Diego and SARRC Phoenix, La Jolla, CA USA
                [35 ]GRID grid.2515.3, ISNI 0000 0004 0378 8438, Department of Pediatrics, , Boston Children’s Hospital, ; Boston, MA USA
                [36 ]GRID grid.240283.f, ISNI 0000 0001 2152 0791, Department of Pediatrics, , Montefiore Medical Center and The Albert Einstein College of Medicine, ; Bronx, NY USA
                [37 ]GRID grid.5386.8, ISNI 000000041936877X, Department of Psychiatry, , Weill Cornell Medicine, ; White Plains, NY USA
                [38 ]GRID grid.259828.c, ISNI 0000 0001 2189 3475, Department of Pediatrics, , Medical University of South Carolina, ; Charleston, SC USA
                [39 ]GRID grid.416975.8, ISNI 0000 0001 2200 2638, Department of Pediatrics, , Texas Children’s Hospital (Baylor College of Medicine), ; Houston, TX USA
                [40 ]GRID grid.2515.3, ISNI 0000 0004 0378 8438, Department of Medicine, , Boston Children’s Hospital, ; Boston, MA USA
                [41 ]GRID grid.27860.3b, ISNI 0000 0004 1936 9684, MIND Institute and Department of Psychiatry and Behavioral Sciences, , University of California, Davis, ; Sacramento, CA USA
                [42 ]GRID grid.428220.e, ISNI 0000 0004 0455 6823, Children’s Specialized Hospital, ; Toms River, NJ USA
                [43 ]GRID grid.410711.2, ISNI 0000 0001 1034 1720, Department of Psychiatry, , University of North Carolina (UNC, TEACCH, CIDD), ; Chapel Hill, NC USA
                [44 ]GRID grid.428158.2, ISNI 0000 0004 0371 6071, Department of Psychiatry and Behavioral Sciences, , Emory University and Marcus Autism Center, ; Atlanta, GA USA
                [45 ]GRID grid.428158.2, ISNI 0000 0004 0371 6071, Department of Pediatrics, , Emory University and Marcus Autism Center, ; Atlanta, GA USA
                [46 ]GRID grid.476963.9, Geisinger Autism & Developmental Medicine Institute, ; Lewisburg, PA USA
                [47 ]GRID grid.240684.c, ISNI 0000 0001 0705 3621, Department of Pediatrics, , Rush University Medical Center, ; Chicago, IL USA
                [48 ]GRID grid.410721.1, ISNI 0000 0004 1937 0407, Department of Pediatrics, , University of Mississippi Medical Center, ; Jackson, MS USA
                [49 ]GRID grid.34477.33, ISNI 0000000122986657, Department of Psychiatry and Behavioral Sciences, , University of Washington/Seattle Children’s Autism Center, ; Seattle, WA USA
                [50 ]GRID grid.214458.e, ISNI 0000000086837370, Department of Psychology, , University of Michigan, ; Ann Arbor, MI USA
                [51 ]GRID grid.239552.a, ISNI 0000 0001 0680 8770, Center for Autism Research, , Children’s Hospital of Philadelphia, ; Philadelphia, PA USA
                [52 ]GRID grid.152326.1, ISNI 0000 0001 2264 7217, Department of Molecular Physiology and Biophysics, , Vanderbilt University, ; Nashville, TN USA
                [53 ]GRID grid.239585.0, ISNI 0000 0001 2285 2675, Department of Psychiatry, , Columbia University Medical Center, ; New York, NY USA
                [54 ]GRID grid.259828.c, ISNI 0000 0001 2189 3475, Department of Psychiatry and Behavioral Sciences, , Medical University of South Carolina, ; Charleston, SC USA
                [55 ]GRID grid.2515.3, ISNI 0000 0004 0378 8438, Department of Neurology, , Boston Children’s Hospital, ; Boston, MA USA
                [56 ]GRID grid.416311.0, ISNI 0000 0004 0433 3945, Maine Medical Center Research Institute, ; Scarborough, ME USA
                [57 ]GRID grid.27860.3b, ISNI 0000 0004 1936 9684, Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, , University of California, Davis, ; Sacramento, CA USA
                [58 ]GRID grid.2515.3, ISNI 0000 0004 0378 8438, Translational Neuroscience Center, , Boston Children’s Hospital, ; Boston, MA USA
                [59 ]GRID grid.5386.8, ISNI 000000041936877X, Center for Autism and the Developing Brain (CADB), , Weill Cornell Medicine, ; White Plains, NY USA
                [60 ]GRID grid.134936.a, ISNI 0000 0001 2162 3504, Department of Health Psychology, , University of Missouri, ; Columbia, MO USA
                [61 ]GRID grid.418307.9, ISNI 0000 0000 8571 0933, Greenwood Genetic Center, ; Greenwood, SC USA
                [62 ]Department of Pediatrics, University of California, San Diego and SARRC Phoenix, La Jolla, CA USA
                Author information
                http://orcid.org/0000-0003-4266-1301
                http://orcid.org/0000-0002-3730-5102
                http://orcid.org/0000-0002-5179-087X
                http://orcid.org/0000-0001-5328-4631
                http://orcid.org/0000-0002-9240-789X
                http://orcid.org/0000-0002-9225-9874
                http://orcid.org/0000-0001-8246-6477
                http://orcid.org/0000-0003-2896-3450
                http://orcid.org/0000-0001-9713-0992
                http://orcid.org/0000-0002-1299-5979
                http://orcid.org/0000-0003-3438-5685
                Article
                1148
                10.1038/s41588-022-01148-2
                9470534
                35982159
                334f2d37-52e5-4948-8a93-4ba5b33b88c6
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 26 September 2021
                : 28 June 2022
                Funding
                Funded by: Simons Foundation Autism Research Initiative
                Funded by: Simons Foundation Autism Research Initiative #644038
                Funded by: FundRef https://doi.org/10.13039/100000011, Howard Hughes Medical Institute (HHMI);
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: R01GM120609
                Award Recipient :
                Funded by: Simons Foundation Autism Research Initiative SIMONS606450
                Categories
                Article
                Custom metadata
                © The Author(s), under exclusive licence to Springer Nature America, Inc. 2022

                Genetics
                autism spectrum disorders,neuroscience,sequencing
                Genetics
                autism spectrum disorders, neuroscience, sequencing

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