Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p.

Humans Autistic Disorder / genetics DNA Copy Number Variations Chromosomes Chromosome Deletion Chromosomes, Human, Pair 16 / genetics

Journal

Nature genetics
ISSN: 1546-1718
Titre abrégé: Nat Genet
Pays: United States
ID NLM: 9216904

Informations de publication

Date de publication:
11 2022
Historique:
received: 11 03 2022
accepted: 15 09 2022
pubmed: 26 10 2022
medline: 15 11 2022
entrez: 25 10 2022
Statut: ppublish

Résumé

The canonical paradigm for converting genetic association to mechanism involves iteratively mapping individual associations to the proximal genes through which they act. In contrast, in the present study we demonstrate the feasibility of extracting biological insights from a very large region of the genome and leverage this strategy to study the genetic influences on autism. Using a new statistical approach, we identified the 33-Mb p-arm of chromosome 16 (16p) as harboring the greatest excess of autism's common polygenic influences. The region also includes the mechanistically cryptic and autism-associated 16p11.2 copy number variant. Analysis of RNA-sequencing data revealed that both the common polygenic influences within 16p and the 16p11.2 deletion were associated with decreased average gene expression across 16p. The transcriptional effects of the rare deletion and diffuse common variation were correlated at the level of individual genes and analysis of Hi-C data revealed patterns of chromatin contact that may explain this transcriptional convergence. These results reflect a new approach for extracting biological insight from genetic association data and suggest convergence of common and rare genetic influences on autism at 16p.

Identifiants

DOI: 10.1038/s41588-022-01203-y PMID: 36280734 PMC: PMC9649437
pubmed: 36280734
doi: 10.1038/s41588-022-01203-y
pii: 10.1038/s41588-022-01203-y
pmc: PMC9649437
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1630-1639

Subventions

Organisme : NIMH NIH HHS
ID : R01 MH099134
Pays : United States
Organisme : NLM NIH HHS
ID : T15 LM007092
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH100027
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM144273
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH069359
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH122412
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH111813
Pays : United States
Organisme : NIMH NIH HHS
ID : F30 MH129009
Pays : United States
Organisme : NHGRI NIH HHS
ID : T32 HG002295
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM007753
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS093200
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH094400
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH124851
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH123619
Pays : United States
Organisme : NICHD NIH HHS
ID : R01 HD096326
Pays : United States

Investigateurs

Preben B Mortensen (PB)
Thomas Werge (T)
Ditte Demontis (D)
Ole Mors (O)
Merete Nordentoft (M)
Thomas D Als (TD)
Marie Baekvad-Hansen (M)
Anders Rosengren (A)
Alexandra Havdahl (A)
Anne Hedemand (A)
Aarno Palotie (A)
Aravinda Chakravarti (A)
Dan Arking (D)
Arvis Sulovari (A)
Anna Starnawska (A)
Bhooma Thiruvahindrapuram (B)
Christiaan de Leeuw (C)
Caitlin Carey (C)
Christine Ladd-Acosta (C)
Celia van der Merwe (C)
Bernie Devlin (B)
Edwin H Cook (EH)
Evan Eichler (E)
Elisabeth Corfield (E)
Gwen Dieleman (G)
Gerard Schellenberg (G)
Hakon Hakonarson (H)
Hilary Coon (H)
Isabel Dziobek (I)
Jacob Vorstman (J)
Jessica Girault (J)
James S Sutcliffe (JS)
Jinjie Duan (J)
John Nurnberger (J)
Joachim Hallmayer (J)
Joseph Buxbaum (J)
Joseph Piven (J)
Lauren Weiss (L)
Lea Davis (L)
Magdalena Janecka (M)
Manuel Mattheisen (M)
Matthew W State (MW)
Michael Gill (M)
Mark Daly (M)
Mohammed Uddin (M)
Ole Andreassen (O)
Peter Szatmari (P)
Phil Hyoun Lee (PH)
Richard Anney (R)
Stephan Ripke (S)
Kyle Satterstrom (K)
Susan Santangelo (S)
Susan Kuo (S)
Ludger Tebartz van Elst (LT)
Thomas Rolland (T)
Thomas Bougeron (T)
Tinca Polderman (T)
Tychele Turner (T)
Jack Underwood (J)
Veera Manikandan (V)
Vamsee Pillalamarri (V)
Varun Warrier (V)
Alexandra Philipsen (A)
Andreas Reif (A)
Anke Hinney (A)
Bru Cormand (B)
Claiton H D Bau (CHD)
Diego Luiz Rovaris (DL)
Edmund Sonuga-Barke (E)
Elizabeth Corfield (E)
Eugenio Horacio Grevet (EH)
Giovanni Salum (G)
Henrik Larsson (H)
Jan Buitelaar (J)
Jan Haavik (J)
James McGough (J)
Jonna Kuntsi (J)
Josephine Elia (J)
Klaus-Peter Lesch (KP)
Marieke Klein (M)
Mark Bellgrove (M)
Martin Tesli (M)
Patrick W L Leung (PWL)
Pedro M Pan (PM)
Soren Dalsgaard (S)
Sandra Loo (S)
Sarah Medland (S)
Stephen V Faraone (SV)
Ted Reichborn-Kjennerud (T)
Tobias Banaschewski (T)
Ziarih Hawi (Z)

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2022. The Author(s).

Références

Tam, V. et al. Benefits and limitations of genome-wide association studies. Nat. Rev. Genet. 20, 467–484 (2019).
pubmed: 31068683 doi: 10.1038/s41576-019-0127-1
Fachal, L. et al. Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes. Nat. Genet. 52, 56–73 (2020).
pubmed: 31911677 pmcid: 6974400 doi: 10.1038/s41588-019-0537-1
Huang, H. et al. Fine-mapping inflammatory bowel disease loci to single-variant resolution. Nature 547, 173–178 (2017).
pubmed: 28658209 pmcid: 5511510 doi: 10.1038/nature22969
GTEx Consortium. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369, 1318–1330 (2020).
doi: 10.1126/science.aaz1776
Fulco, C. P. et al. Activity-by-contact model of enhancer-promoter regulation from thousands of CRISPR perturbations. Nat. Genet. 51, 1664–1669 (2019).
pubmed: 31784727 pmcid: 6886585 doi: 10.1038/s41588-019-0538-0
Claussnitzer, M. et al. FTO obesity variant circuitry and adipocyte browning in humans. N. Engl. J. Med. 373, 895–907 (2015).
pubmed: 26287746 pmcid: 4959911 doi: 10.1056/NEJMoa1502214
Bulik-Sullivan, B. K. et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
pubmed: 25642630 pmcid: 4495769 doi: 10.1038/ng.3211
Fu, J. M. et al. Rare coding variation provides insight into the genetic architecture and phenotypic context of autism. Nat. Genet. https://doi.org/10.1038/s41588-022-01104-0 (2022).
Wilfert, A. B. et al. Recent ultra-rare inherited variants implicate new autism candidate risk genes. Nat. Genet. 53, 1125–1134 (2021).
pubmed: 34312540 pmcid: 8459613 doi: 10.1038/s41588-021-00899-8
Zhou, J. et al. Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk. Nat. Genet. 51, 973–980 (2019).
pubmed: 31133750 pmcid: 6758908 doi: 10.1038/s41588-019-0420-0
Grove, J. et al. Identification of common genetic risk variants for autism spectrum disorder. Nat. Genet. 51, 431–444 (2019).
pubmed: 30804558 pmcid: 6454898 doi: 10.1038/s41588-019-0344-8
Weiner, D. J. et al. Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders. Nat. Genet. 49, 978–985 (2017).
pubmed: 28504703 pmcid: 5552240 doi: 10.1038/ng.3863
Sanders, S. J. et al. Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci. Neuron 87, 1215–1233 (2015).
pubmed: 26402605 pmcid: 4624267 doi: 10.1016/j.neuron.2015.09.016
Krumm, N. et al. Excess of rare, inherited truncating mutations in autism. Nat. Genet. 47, 582–588 (2015).
pubmed: 25961944 pmcid: 4449286 doi: 10.1038/ng.3303
Gaugler, T. et al. Most genetic risk for autism resides with common variation. Nat. Genet. 46, 881–885 (2014).
pubmed: 25038753 pmcid: 4137411 doi: 10.1038/ng.3039
Collins, R. L. et al. A cross-disorder dosage sensitivity map of the human genome. Cell 185, 3041–3055.e25 (2022).
pubmed: 35917817 doi: 10.1016/j.cell.2022.06.036
Pinto, D. et al. Functional impact of global rare copy number variation in autism spectrum disorders. Nature 466, 368–372 (2010).
pubmed: 20531469 pmcid: 3021798 doi: 10.1038/nature09146
Sebat, J. et al. Strong association of de novo copy number mutations with autism. Science 316, 445–449 (2007).
pubmed: 17363630 pmcid: 2993504 doi: 10.1126/science.1138659
Niarchou, M. et al. Psychiatric disorders in children with 16p11.2 deletion and duplication. Transl. Psychiatry 9, 8 (2019).
pubmed: 30664628 pmcid: 6341088 doi: 10.1038/s41398-018-0339-8
Blumenthal, I. et al. Transcriptional consequences of 16p11.2 deletion and duplication in mouse cortex and multiplex autism families. Am. J. Hum. Genet. 94, 870–883 (2014).
pubmed: 24906019 pmcid: 4121471 doi: 10.1016/j.ajhg.2014.05.004
Golzio, C. et al. KCTD13 is a major driver of mirrored neuroanatomical phenotypes of the 16p11.2 copy number variant. Nature 485, 363–367 (2012).
pubmed: 22596160 pmcid: 3366115 doi: 10.1038/nature11091
Iyer, J. et al. Pervasive genetic interactions modulate neurodevelopmental defects of the autism-associated 16p11.2 deletion in Drosophila melanogaster. Nat. Commun. 9, 2548 (2018).
pubmed: 29959322 pmcid: 6026208 doi: 10.1038/s41467-018-04882-6
Urresti, J. et al. Cortical organoids model early brain development disrupted by 16p11.2 copy number variants in autism. Mol. Psychiatry 26, 7560–7580 (2021).
pubmed: 34433918 pmcid: 8873019 doi: 10.1038/s41380-021-01243-6
Luo, R. et al. Genome-wide transcriptome profiling reveals the functional impact of rare de novo and recurrent CNVs in autism spectrum disorders. Am. J. Hum. Genet. 91, 38–55 (2012).
pubmed: 22726847 pmcid: 3397271 doi: 10.1016/j.ajhg.2012.05.011
Sun, J. H. et al. Disease-associated short tandem repeats co-localize with chromatin domain boundaries. Cell 175, 224–238.e15 (2018).
pubmed: 30173918 pmcid: 6175607 doi: 10.1016/j.cell.2018.08.005
Zhang, X. et al. Local and global chromatin interactions are altered by large genomic deletions associated with human brain development. Nat. Commun. 9, 5356 (2018).
pubmed: 30559385 pmcid: 6297223 doi: 10.1038/s41467-018-07766-x
Maury, E. A. et al. Schizophrenia-associated somatic copy number variants from 12,834 cases reveal contribution to risk and recurrent, isoform-specific NRXN1 disruptions. Preprint at medRxiv https://doi.org/2021.12.24.21268385 (2022).
Gorkin, D. U. et al. Common DNA sequence variation influences 3-dimensional conformation of the human genome. Genome Biol. 20, 255 (2019).
pubmed: 31779666 pmcid: 6883528 doi: 10.1186/s13059-019-1855-4
Fischbach, G. D. & Lord, C. The Simons Simplex Collection: a resource for identification of autism genetic risk factors. Neuron 68, 192–195 (2010).
pubmed: 20955926 doi: 10.1016/j.neuron.2010.10.006
SPARK Consortium. SPARK: a US cohort of 50,000 families to accelerate autism research. Neuron 97, 488–493 (2018).
doi: 10.1016/j.neuron.2018.01.015
Berisa, T. & Pickrell, J. K. Approximately independent linkage disequilibrium blocks in human populations. Bioinformatics 32, 283–285 (2016).
pubmed: 26395773
Satterstrom, F. K. et al. Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Cell 180, 568–584.e23 (2020).
pubmed: 31981491 pmcid: 7250485 doi: 10.1016/j.cell.2019.12.036
Reilly, S. K. et al. Evolutionary genomics. Evolutionary changes in promoter and enhancer activity during human corticogenesis. Science 347, 1155–1159 (2015).
pubmed: 25745175 pmcid: 4426903 doi: 10.1126/science.1260943
Gandal, M. J. et al. Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science 362, eaat8127 (2018).
pubmed: 30545856 pmcid: 6443102 doi: 10.1126/science.aat8127
Mi, H., Muruganujan, A., Casagrande, J. T. & Thomas, P. D. Large-scale gene function analysis with the PANTHER classification system. Nat. Protoc. 8, 1551–1566 (2013).
pubmed: 23868073 pmcid: 6519453 doi: 10.1038/nprot.2013.092
Ashburner, M. et al. Gene ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000).
pubmed: 10802651 pmcid: 3037419 doi: 10.1038/75556
Tai, D. J. C. et al. Tissue and cell-type specific molecular and functional signatures of 16p11.2 reciprocal genomic disorder across mouse brain and human neuronal models. Am. J. Hum. Genet. 109, 1-25 (2022).
Pagnamenta, A. T. et al. A 15q13.3 microdeletion segregating with autism. Eur. J. Hum. Genet. 17, 687–692 (2009).
pubmed: 19050728 doi: 10.1038/ejhg.2008.228
Kogan, J. H. et al. Mouse model of chromosome 15q13.3 microdeletion syndrome demonstrates features related to autism spectrum disorder. J. Neurosci. 35, 16282–16294 (2015).
pubmed: 26658876 pmcid: 6605504 doi: 10.1523/JNEUROSCI.3967-14.2015
Ziats, M. N. et al. The complex behavioral phenotype of 15q13.3 microdeletion syndrome. Genet. Med. 18, 1111–1118 (2016).
pubmed: 26963284 doi: 10.1038/gim.2016.9
Zhang, Y. et al. Rapid single-step induction of functional neurons from human pluripotent stem cells. Neuron 78, 785–798 (2013).
pubmed: 23764284 pmcid: 3751803 doi: 10.1016/j.neuron.2013.05.029
Hoffman, G. E. et al. CommonMind Consortium provides transcriptomic and epigenomic data for schizophrenia and bipolar disorder. Sci Data 6, 180 (2019).
pubmed: 31551426 pmcid: 6760149 doi: 10.1038/s41597-019-0183-6
Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).
pubmed: 19815776 pmcid: 2858594 doi: 10.1126/science.1181369
Won, H. et al. Chromosome conformation elucidates regulatory relationships in developing human brain. Nature 538, 523–527 (2016).
pubmed: 27760116 pmcid: 5358922 doi: 10.1038/nature19847
Loviglio, M. N. et al. Chromosomal contacts connect loci associated with autism, BMI and head circumference phenotypes. Mol. Psychiatry 22, 836–849 (2017).
pubmed: 27240531 doi: 10.1038/mp.2016.84
Gusev, A. et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat. Genet. 48, 245–252 (2016).
pubmed: 26854917 pmcid: 4767558 doi: 10.1038/ng.3506
Pintacuda, G. et al. Interaction studies of risk proteins in human induced neurons reveal convergent biology and novel mechanisms underlying autism spectrum disorders. Preprint at medRxiv https://doi.org/2021.10.07.21264575 (2021).
Vilhjálmsson, B. J. et al. Modeling linkage disequilibrium increases accuracy of polygenic risk scores. Am. J. Hum. Genet. 97, 576–592 (2015).
pubmed: 26430803 pmcid: 4596916 doi: 10.1016/j.ajhg.2015.09.001
Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015).
pubmed: 25722852 pmcid: 4342193 doi: 10.1186/s13742-015-0047-8
Wigdor, E. M. et al.The female protective effect against autism spectrum disorder. Cell Genom. https://doi.org/10.1016/j.xgen.2022.100134 (2022).
Navarro Gonzalez, J. et al. The UCSC Genome Browser database: 2021 update. Nucleic Acids Res. 49, D1046–D1057 (2021).
pubmed: 33221922 doi: 10.1093/nar/gkaa1070
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
pubmed: 20110278 pmcid: 2832824 doi: 10.1093/bioinformatics/btq033
Demontis, D. et al. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat. Genet. 51, 63–75 (2019).
pubmed: 30478444 doi: 10.1038/s41588-018-0269-7
1000 Genomes Project Consortium et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).
doi: 10.1038/nature15393
Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020).
pubmed: 32461654 pmcid: 7334197 doi: 10.1038/s41586-020-2308-7
Finucane, H. K. et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat. Genet. 50, 621–629 (2018).
pubmed: 29632380 pmcid: 5896795 doi: 10.1038/s41588-018-0081-4
Hafemeister, C. & Satija, R. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. Genome Biol. 20, 296 (2019).
pubmed: 31870423 pmcid: 6927181 doi: 10.1186/s13059-019-1874-1
Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).
pubmed: 29608179 pmcid: 6700744 doi: 10.1038/nbt.4096
Lajoie, B. R., Dekker, J. & Kaplan, N. The hitchhiker’s guide to Hi-C analysis: practical guidelines. Methods 72, 65–75 (2015).
pubmed: 25448293 doi: 10.1016/j.ymeth.2014.10.031

Auteurs

Daniel J Weiner (DJ)

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA. dweiner@broadinstitute.org.
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. dweiner@broadinstitute.org.
ORCID: 0000-0002-3744-6853

Emi Ling (E)

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Genetics, Harvard Medical School, Boston, MA, USA.
ORCID: 0000-0001-5287-0284

Serkan Erdin (S)

Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
ORCID: 0000-0001-6587-2625

Derek J C Tai (DJC)

Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.

Rachita Yadav (R)

Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.

Jakob Grove (J)

Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark.
Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, Denmark.
Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.
The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
ORCID: 0000-0003-2284-5744

Jack M Fu (JM)

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.
Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.

Ajay Nadig (A)

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.

Caitlin E Carey (CE)

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.

Nikolas Baya (N)

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Jonas Bybjerg-Grauholm (J)

The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark.
ORCID: 0000-0003-1705-4008

Sabina Berretta (S)

Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
McLean Hospital, Belmont, MA, USA.

Evan Z Macosko (EZ)

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.

Jonathan Sebat (J)

Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.

Luke J O'Connor (LJ)

Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
ORCID: 0000-0003-2730-9668

David M Hougaard (DM)

The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark.
ORCID: 0000-0001-5928-3517

Anders D Børglum (AD)

Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark.
Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, Denmark.
The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
ORCID: 0000-0001-8627-7219

Michael E Talkowski (ME)

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.
Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
ORCID: 0000-0003-2889-0992

Steven A McCarroll (SA)

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Genetics, Harvard Medical School, Boston, MA, USA.

Elise B Robinson (EB)

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA. erob@broadinstitute.org.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. erob@broadinstitute.org.
Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. erob@broadinstitute.org.
ORCID: 0000-0003-2314-2792

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Classifications MeSH

questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Statistical and functional convergence of...
questionsmedicales.fr › Troubles mentaux › Troubles du développement neurologique › Troubles généralisés du développement de l'enfant › Trouble du spectre autistique › Trouble autistique › Statistical and functional convergence of...
questionsmedicales.fr › Phénomènes génétiques › Variation génétique › Polymorphisme génétique › Variation structurale du génome › Variations de nombre de copies de segment d'ADN › Statistical and functional convergence of...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Chromosomes › Statistical and functional convergence of...
questionsmedicales.fr › Phénomènes génétiques › Ploïdies › Aneuploïdie › Monosomie › Délétion de segment de chromosome › Statistical and functional convergence of...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Chromosomes › Chromosomes de mammifère › Chromosomes humains › Chromosomes humains 16-18 › Chromosomes humains de la paire 16 › Statistical and functional convergence of...