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

Laura M. Huckins; Amanda Dobbyn; Douglas M. Ruderfer; Gabriel Hoffman; Weiqing Wang; Antonio F. Pardinas; Veera M. Rajagopal; Thomas D. Als; Hoang T. Nguyen; Kiran Girdhar; James Boocock; Panos Roussos; Menachem Fromer; Robin Kramer; Enrico Domenici; Eric R. Gamazon; Shaun Purcell; Ditte Demontis; Anders D. Borglum; James T. R. Walters; Michael C. O'Donovan; Patrick Sullivan; Michael J. Owen; Bernie Devlin; Solveig K. Sieberts; Nancy J. Cox; Hae Kyung Im; Pamela Sklar; Eli A. Stahl; Jessica S. Johnson; Hardik R. Shah; Lambertus L. Klein; Kristen K. Dang; Benjamin A. Logsdon; Milind C. Mahajan; Lara M. Mangravite; Hiroyoshi Toyoshiba; Raquel E. Gur; Chang-Gyu Hahn; Eric Schadt; David A. Lewis; Vahram Haroutunian; Mette A. Peters; Barbara K. Lipska; Joseph D. Buxbaum; Keisuke Hirai; Wiepke Cahn; Rene S. Kahn; Jim Van Os; Roel A. Ophoff

doi:10.1038/s41588-019-0364-4

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

Laura M. Huckins, Amanda Dobbyn, Douglas M. Ruderfer, Gabriel Hoffman, Weiqing Wang, Antonio F. Pardinas, Veera M. Rajagopal, Thomas D. Als, Hoang T. Nguyen, Kiran Girdhar, James Boocock, Panos Roussos, Menachem Fromer, Robin Kramer, Enrico Domenici, Eric R. Gamazon, Shaun Purcell, Ditte Demontis, Anders D. Borglum, James T. R. WaltersMichael C. O'Donovan, Patrick Sullivan, Michael J. Owen, Bernie Devlin, Solveig K. Sieberts, Nancy J. Cox, Hae Kyung Im, Pamela Sklar, Eli A. Stahl, Jessica S. Johnson, Hardik R. Shah, Lambertus L. Klein, Kristen K. Dang, Benjamin A. Logsdon, Milind C. Mahajan, Lara M. Mangravite, Hiroyoshi Toyoshiba, Raquel E. Gur, Chang-Gyu Hahn, Eric Schadt, David A. Lewis, Vahram Haroutunian, Mette A. Peters, Barbara K. Lipska, Joseph D. Buxbaum, Keisuke Hirai, Wiepke Cahn, Rene S. Kahn, Jim Van Os, Roel A. Ophoff

Research output: Contribution to journal › Article › Academic › peer-review

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 language	English
Pages (from-to)	659-674
Number of pages	16
Journal	Nature Genetics
Volume	51
Issue number	4
DOIs	https://doi.org/10.1038/s41588-019-0364-4 https://doi.org/10.1038/s41588-019-0364-4
Publication status	Published - Apr 2019

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

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Huckins, L. M., Dobbyn, A., Ruderfer, D. M., Hoffman, G., Wang, W., Pardinas, A. F., Rajagopal, V. M., Als, T. D., Nguyen, H. T., Girdhar, K., Boocock, J., Roussos, P., Fromer, M., Kramer, R., Domenici, E., Gamazon, E. R., Purcell, S., Demontis, D., Borglum, A. D., ... Ophoff, R. A. (2019). Gene expression imputation across multiple brain regions provides insights into schizophrenia risk. Nature Genetics, 51(4), 659-674. https://doi.org/10.1038/s41588-019-0364-4, https://doi.org/10.1038/s41588-019-0364-4

@article{6a320d46944743a7b89173ffd7b20d00,

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.",

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",

author = "Huckins, \{Laura M.\} and Amanda Dobbyn and Ruderfer, \{Douglas M.\} and Gabriel Hoffman and Weiqing Wang and Pardinas, \{Antonio F.\} and Rajagopal, \{Veera M.\} and Als, \{Thomas D.\} and Nguyen, \{Hoang T.\} and Kiran Girdhar and James Boocock and Panos Roussos and Menachem Fromer and Robin Kramer and Enrico Domenici and Gamazon, \{Eric R.\} and Shaun Purcell and Ditte Demontis and Borglum, \{Anders D.\} and Walters, \{James T. R.\} and O'Donovan, \{Michael C.\} and Patrick Sullivan and Owen, \{Michael J.\} and Bernie Devlin and Sieberts, \{Solveig K.\} and Cox, \{Nancy J.\} and Im, \{Hae Kyung\} and Pamela Sklar and Stahl, \{Eli A.\} and Johnson, \{Jessica S.\} and Shah, \{Hardik R.\} and Klein, \{Lambertus L.\} and Dang, \{Kristen K.\} and Logsdon, \{Benjamin A.\} and Mahajan, \{Milind C.\} and Mangravite, \{Lara M.\} and Hiroyoshi Toyoshiba and Gur, \{Raquel E.\} and Chang-Gyu Hahn and Eric Schadt and Lewis, \{David A.\} and Vahram Haroutunian and Peters, \{Mette A.\} and Lipska, \{Barbara K.\} and Buxbaum, \{Joseph D.\} and Keisuke Hirai and Wiepke Cahn and Kahn, \{Rene S.\} and \{Van Os\}, Jim and Ophoff, \{Roel A.\}",

note = "Publisher Copyright: {\textcopyright} 2019, The Author(s), under exclusive licence to Springer Nature America, Inc.",

year = "2019",

month = apr,

doi = "10.1038/s41588-019-0364-4",

language = "English",

volume = "51",

pages = "659--674",

journal = "Nature Genetics",

issn = "1061-4036",

publisher = "Nature Research",

number = "4",

}

Huckins, LM, Dobbyn, A, Ruderfer, DM, Hoffman, G, Wang, W, Pardinas, AF, Rajagopal, VM, Als, TD, Nguyen, HT, Girdhar, K, Boocock, J, Roussos, P, Fromer, M, Kramer, R, Domenici, E, Gamazon, ER, Purcell, S, Demontis, D, Borglum, AD, Walters, JTR, O'Donovan, MC, Sullivan, P, Owen, MJ, Devlin, B, Sieberts, SK, Cox, NJ, Im, HK, Sklar, P, Stahl, EA, Johnson, JS, Shah, HR, Klein, LL, Dang, KK, Logsdon, BA, Mahajan, MC, Mangravite, LM, Toyoshiba, H, Gur, RE, Hahn, C-G, Schadt, E, Lewis, DA, Haroutunian, V, Peters, MA, Lipska, BK, Buxbaum, JD, Hirai, K, Cahn, W , Kahn, RS , Van Os, J & Ophoff, RA 2019, 'Gene expression imputation across multiple brain regions provides insights into schizophrenia risk', Nature Genetics, vol. 51, no. 4, pp. 659-674. https://doi.org/10.1038/s41588-019-0364-4, https://doi.org/10.1038/s41588-019-0364-4

TY - JOUR

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

AU - Huckins, Laura M.

AU - Dobbyn, Amanda

AU - Ruderfer, Douglas M.

AU - Hoffman, Gabriel

AU - Wang, Weiqing

AU - Pardinas, Antonio F.

AU - Rajagopal, Veera M.

AU - Als, Thomas D.

AU - Nguyen, Hoang T.

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 - Borglum, 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 - Johnson, Jessica S.

AU - Shah, Hardik R.

AU - Klein, Lambertus L.

AU - Dang, Kristen K.

AU - Logsdon, Benjamin A.

AU - Mahajan, Milind C.

AU - Mangravite, Lara M.

AU - Toyoshiba, Hiroyoshi

AU - Gur, Raquel E.

AU - Hahn, Chang-Gyu

AU - Schadt, Eric

AU - Lewis, David A.

AU - Haroutunian, Vahram

AU - Peters, Mette A.

AU - Lipska, Barbara K.

AU - Buxbaum, Joseph D.

AU - Hirai, Keisuke

AU - Cahn, Wiepke

AU - Kahn, Rene S.

AU - Van Os, Jim

AU - Ophoff, Roel A.

PY - 2019/4

Y1 - 2019/4

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.

KW - Brain/physiopathology

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

U2 - 10.1038/s41588-019-0364-4

DO - 10.1038/s41588-019-0364-4

M3 - Article

C2 - 30911161

SN - 1061-4036

VL - 51

SP - 659

EP - 674

JO - Nature Genetics

JF - Nature Genetics

IS - 4

ER -

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

Abstract

Keywords

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