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Nat Genet. 2014 Sep;46(9):944-50. doi: 10.1038/ng.3050. Epub 2014 Aug 3.

A framework for the interpretation of de novo mutation in human disease.

Author information

1
1] Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [2] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [3] Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [4] Program in Genetics and Genomics, Biological and Biomedical Sciences, Harvard Medical School, Boston, Massachusetts, USA.
2
1] Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [2] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [3] Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
3
1] Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA. [2] Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, USA.
4
1] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [2] Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
5
Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA.
6
Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
7
1] Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [2] Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA. [3] Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
8
1] Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. [2] Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK.
9
Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA.
10
1] Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [2] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
11
1] Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA. [2] Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
12
Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
13
Synapdx, Lexington, Massachusetts, USA.
14
1] Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [2] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [3] Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [4] Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA. [5] Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA. [6] Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
15
1] Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [2] Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. [3] Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK.
16
1] Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA. [2] Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, USA.
17
1] Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA. [2] Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA. [3] Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA. [4] Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, New York, USA. [5] Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA. [6] Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
18
Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois, USA.
19
Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
20
Center for Molecular Neuroscience, Vanderbilt University, Nashville, Tennessee, USA.
21
Department of Psychiatry, University of Pittsburgh Medical School, Pittsburgh, Pennsylvania, USA.
22
1] Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA. [2] Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.

Abstract

Spontaneously arising (de novo) mutations have an important role in medical genetics. For diseases with extensive locus heterogeneity, such as autism spectrum disorders (ASDs), the signal from de novo mutations is distributed across many genes, making it difficult to distinguish disease-relevant mutations from background variation. Here we provide a statistical framework for the analysis of excesses in de novo mutation per gene and gene set by calibrating a model of de novo mutation. We applied this framework to de novo mutations collected from 1,078 ASD family trios, and, whereas we affirmed a significant role for loss-of-function mutations, we found no excess of de novo loss-of-function mutations in cases with IQ above 100, suggesting that the role of de novo mutations in ASDs might reside in fundamental neurodevelopmental processes. We also used our model to identify ∼1,000 genes that are significantly lacking in functional coding variation in non-ASD samples and are enriched for de novo loss-of-function mutations identified in ASD cases.

PMID:
25086666
PMCID:
PMC4222185
DOI:
10.1038/ng.3050
[Indexed for MEDLINE]
Free PMC Article

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