Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

CommonMind Consortium, Francis O'Neill

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

Original languageEnglish
Pages (from-to)659-674
Number of pages16
JournalNature Genetics
Volume51
Issue number4
Early online date25 Mar 2019
DOIs
Publication statusPublished - 01 Apr 2019

Fingerprint

Genome-Wide Association Study
Prefrontal Cortex
Schizophrenia
Tay-Sachs Disease
Gene Expression
Brain
Genes
Genotype
Conditioning (Psychology)

Keywords

  • Brain/physiopathology
  • Case-Control Studies
  • Gene Expression/genetics
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study/methods
  • Genotype
  • Humans
  • Polymorphism, Single Nucleotide/genetics
  • Quantitative Trait Loci/genetics
  • Risk
  • Schizophrenia/genetics
  • Transcriptome/genetics

Cite this

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title = "Gene expression imputation across multiple brain regions provides insights into schizophrenia risk",
abstract = "Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.",
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Gene expression imputation across multiple brain regions provides insights into schizophrenia risk. / CommonMind Consortium ; O'Neill, Francis.

In: Nature Genetics, Vol. 51, No. 4, 01.04.2019, p. 659-674.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

AU - CommonMind Consortium

AU - Huckins, Laura M

AU - Dobbyn, Amanda

AU - Ruderfer, Douglas M

AU - Hoffman, Gabriel

AU - Wang, Weiqing

AU - Pardiñas, Antonio F

AU - Rajagopal, Veera M

AU - Als, Thomas D

AU - T Nguyen, Hoang

AU - Girdhar, Kiran

AU - Boocock, James

AU - Roussos, Panos

AU - Fromer, Menachem

AU - Kramer, Robin

AU - Domenici, Enrico

AU - Gamazon, Eric R

AU - Purcell, Shaun

AU - Demontis, Ditte

AU - Børglum, Anders D

AU - Walters, James T R

AU - O'Donovan, Michael C

AU - Sullivan, Patrick

AU - Owen, Michael J

AU - Devlin, Bernie

AU - Sieberts, Solveig K

AU - Cox, Nancy J

AU - Im, Hae Kyung

AU - Sklar, Pamela

AU - Stahl, Eli A

AU - O'Neill, Francis

PY - 2019/4/1

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N2 - Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

AB - Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

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KW - Case-Control Studies

KW - Gene Expression/genetics

KW - Genetic Predisposition to Disease

KW - Genome-Wide Association Study/methods

KW - Genotype

KW - Humans

KW - Polymorphism, Single Nucleotide/genetics

KW - Quantitative Trait Loci/genetics

KW - Risk

KW - Schizophrenia/genetics

KW - Transcriptome/genetics

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DO - 10.1038/s41588-019-0364-4

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VL - 51

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JO - Nature Genetics

JF - Nature Genetics

SN - 1061-4036

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ER -