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

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

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

2018
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Overview
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 a schizophrenia GWAS of 79,845 individuals from the Psychiatric Genomics Consortium with expression data from brain, blood, and adipose tissues across 3,693 primarily control individuals. We identified 157 TWAS-significant genes, of which 35 did not overlap a known GWAS locus. Of these 157 genes, 42 were associated with specific chromatin features measured in independent samples, thus highlighting potential regulatory targets for follow-up. Suppression of one identified susceptibility gene, mapk3 , in zebrafish showed a significant effect on neurodevelopmental phenotypes. Expression and splicing from the brain captured most of the TWAS effect across all genes. This large-scale connection of associations to target genes, tissues, and regulatory features is an essential step in moving toward a mechanistic understanding of GWAS. A transcriptome-wide association study integrating genome-wide association data with expression data from brain, blood and adipose tissues identifies new candidate susceptibility genes for schizophrenia, providing a step toward understanding the underlying biology.