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Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis
GWAS have identified 108 schizophrenia risk loci, but risk mechanisms for individual loci are largely unknown. Using developmental, genetic, and illness-based RNA sequencing expression analysis in human brain, we characterized the human brain transcriptome around these loci and found enrichment for...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6438700/ https://www.ncbi.nlm.nih.gov/pubmed/30050107 http://dx.doi.org/10.1038/s41593-018-0197-y |
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author | Jaffe, Andrew E. Straub, Richard E. Shin, Joo Heon Tao, Ran Gao, Yuan Collado-Torres, Leonardo Kam-Thong, Tony Xi, Hualin S. Quan, Jie Chen, Qiang Colantuoni, Carlo Ulrich, William S. Maher, Brady J. Deep-Soboslay, Amy Cross, Alan J. Brandon, Nicholas J. Leek, Jeffrey T. Hyde, Thomas M. Kleinman, Joel E. Weinberger, Daniel R. |
author_facet | Jaffe, Andrew E. Straub, Richard E. Shin, Joo Heon Tao, Ran Gao, Yuan Collado-Torres, Leonardo Kam-Thong, Tony Xi, Hualin S. Quan, Jie Chen, Qiang Colantuoni, Carlo Ulrich, William S. Maher, Brady J. Deep-Soboslay, Amy Cross, Alan J. Brandon, Nicholas J. Leek, Jeffrey T. Hyde, Thomas M. Kleinman, Joel E. Weinberger, Daniel R. |
author_sort | Jaffe, Andrew E. |
collection | PubMed |
description | GWAS have identified 108 schizophrenia risk loci, but risk mechanisms for individual loci are largely unknown. Using developmental, genetic, and illness-based RNA sequencing expression analysis in human brain, we characterized the human brain transcriptome around these loci and found enrichment for developmentally regulated genes with novel examples of shifting isoform usage across pre- and post-natal life. Across the genome, we found widespread expression quantitative trait loci (eQTLs), including many with transcript specificity and previously unannotated sequence that were independently replicated. We leveraged this general eQTL database to show that 48.1% of risk variants for schizophrenia associated with nearby expression. We lastly found 237 genes significantly differentially expressed between patients and controls which replicated in an independent dataset, implicated synaptic processes and were strongly regulated in early development. These findings together offer genetic- and diagnosis-related targets for better modeling schizophrenia risk. This publicly-available resource is available at: http://eqtl.brainseq.org/phase1 |
format | Online Article Text |
id | pubmed-6438700 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
record_format | MEDLINE/PubMed |
spelling | pubmed-64387002019-03-28 Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis Jaffe, Andrew E. Straub, Richard E. Shin, Joo Heon Tao, Ran Gao, Yuan Collado-Torres, Leonardo Kam-Thong, Tony Xi, Hualin S. Quan, Jie Chen, Qiang Colantuoni, Carlo Ulrich, William S. Maher, Brady J. Deep-Soboslay, Amy Cross, Alan J. Brandon, Nicholas J. Leek, Jeffrey T. Hyde, Thomas M. Kleinman, Joel E. Weinberger, Daniel R. Nat Neurosci Article GWAS have identified 108 schizophrenia risk loci, but risk mechanisms for individual loci are largely unknown. Using developmental, genetic, and illness-based RNA sequencing expression analysis in human brain, we characterized the human brain transcriptome around these loci and found enrichment for developmentally regulated genes with novel examples of shifting isoform usage across pre- and post-natal life. Across the genome, we found widespread expression quantitative trait loci (eQTLs), including many with transcript specificity and previously unannotated sequence that were independently replicated. We leveraged this general eQTL database to show that 48.1% of risk variants for schizophrenia associated with nearby expression. We lastly found 237 genes significantly differentially expressed between patients and controls which replicated in an independent dataset, implicated synaptic processes and were strongly regulated in early development. These findings together offer genetic- and diagnosis-related targets for better modeling schizophrenia risk. This publicly-available resource is available at: http://eqtl.brainseq.org/phase1 2018-07-26 2018-08 /pmc/articles/PMC6438700/ /pubmed/30050107 http://dx.doi.org/10.1038/s41593-018-0197-y Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Jaffe, Andrew E. Straub, Richard E. Shin, Joo Heon Tao, Ran Gao, Yuan Collado-Torres, Leonardo Kam-Thong, Tony Xi, Hualin S. Quan, Jie Chen, Qiang Colantuoni, Carlo Ulrich, William S. Maher, Brady J. Deep-Soboslay, Amy Cross, Alan J. Brandon, Nicholas J. Leek, Jeffrey T. Hyde, Thomas M. Kleinman, Joel E. Weinberger, Daniel R. Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis |
title | Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis |
title_full | Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis |
title_fullStr | Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis |
title_full_unstemmed | Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis |
title_short | Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis |
title_sort | developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6438700/ https://www.ncbi.nlm.nih.gov/pubmed/30050107 http://dx.doi.org/10.1038/s41593-018-0197-y |
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