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Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights

Alexander Gusev, Nick Mancuso, Hilary K Finucane, Yakir Reshef, Lingyun Song, Alexias Safi, Edwin Oh, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Steven McCarroll, Benjamin Neale, Roel Ophoff, Michael C O’Donovan, Nicholas Katsanis, Gregory E Crawford, Patrick F Sullivan, Bogdan Pasaniuc, Alkes L Price
doi: https://doi.org/10.1101/067355
Alexander Gusev
1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
2Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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Nick Mancuso
3David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
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Hilary K Finucane
1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
4Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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Yakir Reshef
5Department of Computer Science, Harvard University, Cambridge, Massachusetts, USA
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Lingyun Song
6Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, USA
7Department of Pediatrics, Division of Medical Genetics, Duke University Medical Center, Durham, North Carolina, USA
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Alexias Safi
6Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, USA
7Department of Pediatrics, Division of Medical Genetics, Duke University Medical Center, Durham, North Carolina, USA
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Edwin Oh
8Center for Human Disease Modeling, Duke University Medical Center, Durham, North Carolina, United States
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Steven McCarroll
9Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
10Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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Benjamin Neale
2Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
10Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
11Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
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Roel Ophoff
12Center for Neurobehavioral Genetics, University of California, Los Angeles, Los Angeles, California, USA
13Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
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Michael C O’Donovan
14MRC Centre for Psychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
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Nicholas Katsanis
8Center for Human Disease Modeling, Duke University Medical Center, Durham, North Carolina, United States
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Gregory E Crawford
6Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, USA
7Department of Pediatrics, Division of Medical Genetics, Duke University Medical Center, Durham, North Carolina, USA
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Patrick F Sullivan
15Departments of Genetics and Psychiatry, University of North Carolina, Chapel Hill, North Carolina, USA
16Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Bogdan Pasaniuc
3David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
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Alkes L Price
1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
2Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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ABSTRACT

Genome-wide association studies (GWAS) have identified over 100 risk loci for schizophrenia, but the causal mechanisms remain largely unknown. We performed a transcriptome-wide association study (TWAS) integrating expression data from brain, blood, and adipose tissues across 3,693 individuals with schizophrenia GWAS of 79,845 individuals from the Psychiatric Genomics Consortium. We identified 157 genes with a transcriptome-wide significant association, of which 35 did not overlap a known GWAS locus; the largest number involved alternative splicing in brain. 42/157 genes were also associated to specific chromatin phenotypes measured in 121 independent samples (a 4-fold enrichment over background genes). This high-throughput connection of GWAS findings to specific genes, tissues, and regulatory mechanisms is an essential step toward understanding the biology of schizophrenia and moving towards therapeutic interventions.

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Posted August 02, 2016.
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Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights
Alexander Gusev, Nick Mancuso, Hilary K Finucane, Yakir Reshef, Lingyun Song, Alexias Safi, Edwin Oh, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Steven McCarroll, Benjamin Neale, Roel Ophoff, Michael C O’Donovan, Nicholas Katsanis, Gregory E Crawford, Patrick F Sullivan, Bogdan Pasaniuc, Alkes L Price
bioRxiv 067355; doi: https://doi.org/10.1101/067355
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Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights
Alexander Gusev, Nick Mancuso, Hilary K Finucane, Yakir Reshef, Lingyun Song, Alexias Safi, Edwin Oh, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Steven McCarroll, Benjamin Neale, Roel Ophoff, Michael C O’Donovan, Nicholas Katsanis, Gregory E Crawford, Patrick F Sullivan, Bogdan Pasaniuc, Alkes L Price
bioRxiv 067355; doi: https://doi.org/10.1101/067355

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