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This Item Is the Archived Peer-Reviewed Author-Version Of This item is the archived peer-reviewed author-version of: Targeted sequencing identifies 91 neurodevelopmental-disorder risk genes with autism and developmental-disability biases Reference: Stessman Holly A. F., Xiong Bo, Coe Bradley P., Wang Tianyun, Hoekzema Kendra, Fenckova Michaela, Kvarnung Malin, Gerdts Jennifer, Trinh Sandy, Cosemans Nele, ....- Targeted sequencing identifies 91 neurodevelopmental-disorder risk genes with autism and developmental-disability biases Nature genetics - ISSN 1061-4036 - 49:4(2017), p. 515-526 Full text (Publisher's DOI): http://dx.doi.org/doi:10.1038/NG.3792 To cite this reference: http://hdl.handle.net/10067/1424230151162165141 Institutional repository IRUA 1 Targeted sequencing identifies 91 neurodevelopmental disorder risk genes with autism 2 and developmental disability biases 3 4 Holly A. F. Stessman1,Ψ,α, Bo Xiong1,2,Ψ, Bradley P. Coe1,β, Tianyun Wang3,β, Kendra 5 Hoekzema1, Michaela Fenckova4,5, Malin Kvarnung6,7, Jennifer Gerdts8, Sandy Trinh8, Nele 6 Cosemans9, Laura Vives1, Janice Lin1, Tychele N. Turner1, Gijs Santen10, Claudia 7 Ruivenkamp10, Marjolein Kriek10, Arie van Haeringen10, Emmelien Aten10, Kathryn Friend11,12, 8 Jan Liebelt13, Christopher Barnett13, Eric Haan11,13, Marie Shaw11, Jozef Gecz11,14, Britt-Marie 9 Anderlid6,7, Ann Nordgren6,7, Anna Lindstrand6,7, Charles Schwartz15, R. Frank Kooy16, Geert 10 Vandeweyer16, Celine Helsmoortel16, Corrado Romano17, Antonino Alberti17, Mirella Vinci17, 11 Emanuela Avola17, Stefania Giusto18, Eric Courchesne19, Tiziano Pramparo19, Karen Pierce19, 12 Srinivasa Nalabolu19, David Amaral20, Ingrid E. Scheffer21,22,23, Martin B. Delatycki21,24,25, Paul J. 13 Lockhart21,25, Fereydoun Hormozdiari26, Benjamin Harich4,5, Anna Castells-Nobau4,5, Kun Xia3, 14 Hilde Peeters9, Magnus Nordenskjöld6,7, Annette Schenck4,5, Raphael A. Bernier8, Evan E. 15 Eichler1,27 16 17 1Department of Genome Sciences, University of Washington, Seattle, WA, USA; 2Department of 18 forensic medicine and Institute of Brain Research, Tongji Medical College, Huazhong University 19 of Science and Technology, Wuhan, Hubei, China; 3The State Key Laboratory of Medical 20 Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China; 21 4Department of Human Genetics, Radboud university medical center, Nijmegen, The 22 Netherlands; 5Donders Institute for Brain, Cognition and Behaviour, Radboud university medical 23 center, Nijmegen, The Netherlands; 6Department of Molecular Medicine and Surgery, Center for 24 Molecular Medicine, Karolinska Institutet, Stockholm, Sweden; 7Department of Clinical Genetics, 25 Karolinska University Hospital, Stockholm, Sweden; 8Department of Psychiatry and Behavioral 26 Sciences, University of Washington, Seattle, WA, USA; 9Centre for Human Genetics, KU 27 Leuven and Leuven Autism Research (LAuRes), Leuven, Belgium; 10Department of Clinical 28 Genetics, Leiden University Medical Center (LUMC), Leiden, The Netherlands; 11Robinson 29 Research Institute and the University of Adelaide at the Women’s and Children’s Hospital, North 30 Adelaide, Australia; 12SA Pathology, Adelaide, Australia; 13South Australian Clinical Genetics 31 Service, SA Pathology (at Women’s and Children’s Hospital), Adelaide, Australia, Australia; 32 14South Australian Health and Medical Research Institute, Adelaide, Australia; 15Center for 33 Molecular Studies, J.C. Self Research Institute of Human Genetics, Greenwood Genetic Center, 34 Greenwood, South Carolina, USA; 16Department of Medical Genetics, University of Antwerp, 1 35 Antwerp, Belgium; 17Unit of Pediatrics & Medical Genetics and 18Unit of Neurology, IRCCS 36 Associazione Oasi Maria Santissima, Troina, Italy; 19UCSD, Autism Center of Excellence, La 37 Jolla, CA, USA; 20MIND Institute and the University of California Davis School of Medicine, 38 Sacramento, CA, USA; 21Department of Paediatrics, University of Melbourne, Royal Children's 39 Hospital, Melbourne, Victoria, Australia; 22Department of Medicine, University of Melbourne, 40 Austin Health, Melbourne, Australia; 23The Florey Institute of Neuroscience and Mental Health, 41 Parkville, Victoria, Australia; 24Victorian Clinical Genetics Services, Parkville, Victoria, Australia; 42 25Bruce Lefroy Centre for Genetic Health Research, Murdoch Children’s Research Institute, 43 Parkville, Victoria, Australia; 26Department of Biochemistry and Molecular Medicine, University of 44 California at Davis, Davis, CA, USA; 27Howard Hughes Medical Institute, Seattle, WA, USA. 45 46 α Present address: Department of Pharmacology, Creighton University School of Medicine, 47 Omaha, NE, USA. 48 49 Ψ Shared first authors. β Authors contributed equally. 50 51 Corresponding author: 52 Evan E. Eichler, Ph.D. 53 Department of Genome Sciences 54 University of Washington School of Medicine 55 Foege S-413A, Box 355065 56 3720 15th Ave NE 57 Seattle, WA 98195-5065 58 E-mail: [email protected] 59 Tel 001-(1)2066857336 60 Fax 001-(1)2062215795 61 62 63 2 64 ABSTRACT 65 Gene-disruptive mutations contribute to the biology of neurodevelopmental disorders (NDDs), 66 but most pathogenic genes are not known. We sequenced 208 candidate genes from >11,730 67 patients and >2,867 controls. We report 91 genes with an excess of de novo mutations or 68 private disruptive mutations in 5.7% of patients, including 38 novel NDD genes. Drosophila 69 functional assays of a subset bolster their involvement in NDDs. We identify 25 genes that show 70 a bias for autism versus intellectual disability and highlight a network associated with high- 71 functioning autism (FSIQ>100). Clinical follow-up for NAA15, KMT5B, and ASH1L reveals novel 72 syndromic and non-syndromic forms of disease. 73 74 Abbreviations: ASD: autism spectrum disorders; CNV: copy number variant; ID: intellectual 75 disability; DD: developmental delay; NDD: neurodevelopmental disorder; DN: de novo; LGD: 76 likely gene-disruptive; smMIP: single-molecule molecular inversion probe; CADD: combined 77 annotation dependent depletion; MIS30: missense mutations with a CADD score > 30; SSC: 78 Simons Simplex Collection; FDR: false discovery rate; NMJ: neuromuscular junction; TTC: trials 79 to no-jump criterion. 80 81 3 82 Neurodevelopmental disorders (NDDs) are a heterogeneous collection of psychiatric and 83 clinical diagnoses that encompass autism spectrum disorders (ASD), intellectual 84 disability/developmental delay (ID/DD), attention-deficit/hyperactivity, motor and tic disorders, 85 and language communication disorders1. Although each diagnosis is distinctive based on the 86 Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5)1, NDDs often co- 87 occur. Twin studies have shown that NDDs have a heritable component2. In addition to 88 phenotypic overlaps, copy number variant (CNV) studies have shown that risk genotypes 89 overlap between NDDs3. While these data strongly suggest that common genetic etiologies 90 underlie a subset of broadly defined NDDs, there has been criticism that gene discovery efforts 91 have failed to distinguish ID/DD genes from those contributing to ASD without ID4. 92 Large numbers of potentially pathogenic mutations have been identified based on 93 exome sequencing of NDD cohorts, but in most cases only a single occurrence of a DN 94 mutation in a particular gene has been discovered. Significantly larger numbers of cases and 95 controls are required to prove the statistical significance of individual genes. Leveraging 96 samples and data from multiple comorbid conditions, in principle, can increase our sensitivity to 97 identify risk genes. Phenotypic follow-up of cases broadly drawn from NDDs has previously 98 allowed us to explore specific clinical phenotypes in a genotype-first manner5, such as in the 99 case of genes like CHD86, DYRK1A7, and ADNP8. 100 Using single-molecule molecular inversion probes (smMIPs)9,10, we sequenced the 101 coding and splicing portions of 208 potential NDD risk genes in over 11,730 ASD, ID, and DD 102 cases. smMIPs provide a highly sensitive, specific, and inexpensive approach to target 103 sequence the protein-coding portions of a moderate number of candidate genes in a large 104 number of patients. Samples were collected as part of an international consortium termed the 105 ASID (Autism Spectrum/Intellectual Disability) network that involved 15 centers across seven 106 countries and four continents. The collection has the advantage over many others in that 107 subsequent phenotypic follow-up is possible for a large fraction of the patients. 108 109 RESULTS 110 Mutation discovery 111 We selected 208 candidate NDD (ASD, ID and DD) disease-risk genes based on 112 published sequencing studies11-17 (Supplementary Tables 1-3) using denovo-db (http://denovo- 113 db.gs.washington.edu)18. Genes were selected and ranked based on the number of published 114 DN recurrences, overlap with a CNV morbidity map19, pathway connectivity20, and absence of 115 DN variants in 1,909 published unaffected sibling control exomes12,13. We designed 12,016 4 116 smMIPs distributed across four smMIP pools to cover all annotated RefSeq coding exons as 117 well as five base pairs of flanking intronic sequence (Supplementary Tables 4-7; Methods). We 118 targeted these genes for sequencing in 15 large cohorts of patients (some including unaffected 119 siblings) with a primary ascertainment diagnosis of ASD, ID, or DD where exome sequencing 120 had not previously been performed (Supplementary Tables 8 and 9). The set includes 6,342 121 patients with a primary diagnosis of
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