Abstract
The predisposition to neuropsychiatric disease involves a complex, polygenic, and pleiotropic genetic architecture. However, little is known about how genetic variants impart brain dysfunction or pathology. We used transcriptomic profiling as a quantitative readout of molecular brain-based phenotypes across five major psychiatric disorders—autism, schizophrenia, bipolar disorder, depression, and alcoholism—compared with matched controls. We identified patterns of shared and distinct gene-expression perturbations across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (single-nucleotide polymorphism–based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence and specificity.
Original language | English |
---|---|
Pages (from-to) | 693-697 |
Number of pages | 5 |
Journal | Science |
Volume | 359 |
Issue number | 6376 |
DOIs | |
State | Published - 9 Feb 2018 |
Externally published | Yes |
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In: Science, Vol. 359, No. 6376, 09.02.2018, p. 693-697.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap
AU - PsychENCODE Consortium
AU - iPSYCH-BROAD Working Group
AU - CommonMind Consortium
AU - Gandal, Michael J.
AU - Haney, Jillian R.
AU - Parikshak, Neelroop N.
AU - Leppa, Virpi
AU - Ramaswami, Gokul
AU - Hartl, Chris
AU - Schork, Andrew J.
AU - Appadurai, Vivek
AU - Buil, Alfonso
AU - Werge, Thomas M.
AU - Liu, Chunyu
AU - White, Kevin P.
AU - Horvath, Steve
AU - Geschwind, Daniel H.
N1 - Funding Information: The work is funded by the U.S. National Institute of Mental Health (NIMH) (grants P50-MH106438, D.H.G.; R01-MH094714, D.H.G.; U01-MH103339, D.H.G.; R01-MH110927, D.H.G.; R01-MH100027, D.H.G.; R01-MH110920, C.L.; and U01-MH103340, C.L.), the Simons Foundation for Autism Research Initiative (SFARI) (SFARI grant 206733, D.H.G., and SFARI Bridge to Independence Award, M.J.G.), and the Stephen R. Mallory schizophrenia research award at the University of California, Los Angeles, (UCLA) (M.J.G.). The study was supported by The Lundbeck Foundation Initiative for Integrative Psychiatric Research (grant R102-A9118) and by the Novo Nordisk Foundation. Published microarray data sets analyzed in this study are available on Gene Expression Omnibus (accession nos. GSE28521, GSE28475, GSE35978, GSE53987, GSE17612, GSE12649, GSE21138, GSE54567, GSE54568, GSE54571, GSE54572, GSE29555, and GSE11223), ArrayExpress (accession no. E-MTAB-184), or directly from the study authors (4). New RNA-seq data (available on Synapse with accession numbers syn4590909 and syn4587609, with access governed by NIMH Repository and Genomics Resource) were generated as part of the PsychENCODE Consortium, supported by grants U01MH103339, U01MH103365, U01MH103392, U01MH103340, U01MH103346, R01MH105472, R01MH094714, R01MH105898, R21MH102791, R21MH105881, R21MH103877, and P50MH106934 awarded to Schahram Akbarian (Icahn School of Medicine at Mount Sinai), Gregory Crawford (Duke), Stella Dracheva (Icahn School of Medicine at Mount Sinai), Peggy Farnham (USC), Mark Gerstein (Yale), Daniel Geschwind (UCLA), Thomas M. Hyde (LIBD), Andrew Jaffe (LIBD), James A. Knowles (USC), Chunyu Liu (UIC), Dalila Pinto (Icahn School of Medicine at Mount Sinai), Nenad Sestan (Yale), Pamela Sklar (Icahn School of Medicine at Mount Sinai), Matthew State (UCSF), Patrick Sullivan (UNC), Flora Vaccarino (Yale), Sherman Weissman (Yale), Kevin White (UChicago), and Peter Zandi (JHU). RNA-seq data from the CommonMind Consortium used in this study (Synapse accession no. syn2759792) was supported by funding from Takeda Pharmaceuticals Company, F. Hoffman-La Roche and NIH grants R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1-MH-075916, P50M096891, P50MH084053S1, R37MH057881, R37MH057881S1, HHSN271201300031C, AG02219, AG05138, and MH06692. Brain tissue for the study was obtained from the following brain bank collections: the Mount Sinai NIH Brain and Tissue Repository, the University of Pennsylvania Alzheimer’s Disease Core Center, the University of Pittsburgh NeuroBioBank and Brain and Tissue Repositories, the Harvard Brain Bank as part of the Autism Tissue Project (ATP), the Stanley Medical Research Institute, and the NIMH Human Brain Collection Core. Summary statistics for the ASD GWAS performed on data from the iPSYCH consortium are available in data table S5. Data and analysis code are available at https://github.com/mgandal/Shared-molecular-neuropathology-across-major-psychiatric-disorders-parallels-polygenic-overlap. The authors thank S. Parhami, H. Won, J. Stein, D. Poliodakis, J. Flint, R. Ophoff, and members of the D.H.G. laboratory for critical reading of earlier versions of this manuscript. The authors also thank B. Pasaniuc for his helpful comments and for assistance with module heritability analyses. Funding Information: The work is funded by the U.S. National Institute of Mental Health (NIMH) (grants P50-MH106438, D.H.G.; R01-MH094714, D.H.G.; U01-MH103339, D.H.G.; R01-MH110927, D.H.G.; R01-MH100027, D.H.G.; R01-MH110920, C.L.; and U01-MH103340, C.L.), the Simons Foundation for Autism Research Initiative (SFARI) (SFARI grant 206733, D.H.G., and SFARI Bridge to Independence Award, M.J.G.), and the Stephen R. Mallory schizophrenia research award at the University of California, Los Angeles, (UCLA) (M.J.G.). The study was supported by The Lundbeck Foundation Initiative for Integrative Psychiatric Research (grant R102-A9118) and by the Novo Nordisk Foundation. Published microarray data sets analyzed in this study are available on Gene Expression Omnibus (accession nos. GSE28521, GSE28475, GSE35978, GSE53987, GSE17612, GSE12649, GSE21138, GSE54567, GSE54568, GSE54571, GSE54572, GSE29555, and GSE11223), ArrayExpress (accession no. E-MTAB-184), or directly from the study authors (4). New RNA-seq data (available on Synapse with accession numbers syn4590909 and syn4587609, with access governed by NIMH Repository and Genomics Resource) were generated as part of the PsychENCODE Consortium, supported by grants U01MH103339, U01MH103365, U01MH103392, U01MH103340, U01MH103346, R01MH105472, R01MH094714, R01MH105898, R21MH102791, R21MH105881, R21MH103877, and P50MH106934 awarded to Schahram Akbarian (Icahn School of Medicine at Mount Sinai), Gregory Crawford (Duke), Stella Dracheva (Icahn School of Medicine at Mount Sinai), Peggy Farnham (USC), Mark Gerstein (Yale), Daniel Geschwind (UCLA), Thomas M. Hyde (LIBD), Andrew Jaffe (LIBD), James A. Knowles (USC), Chunyu Liu (UIC), Dalila Pinto (Icahn School of Medicine at Mount Sinai), Nenad Sestan (Yale), Pamela Sklar (Icahn School of Medicine at Mount Sinai), Matthew State (UCSF), Patrick Sullivan (UNC), Flora Vaccarino (Yale), Sherman Weissman (Yale), Kevin White (UChicago), and Peter Zandi (JHU). RNA-seq data from the CommonMind Consortium used in this study (Synapse accession no. syn2759792) was supported by funding from Takeda Pharmaceuticals Company, F. Hoffman-La Roche and NIH grants R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1-MH-075916, P50M096891, P50MH084053S1, R37MH057881, R37MH057881S1, HHSN271201300031C, AG02219, AG05138, and MH06692. Brain tissue for the study was obtained from the following brain bank collections: the Mount Sinai NIH Brain and Tissue Repository, the University of Pennsylvania Alzheimer’s Disease Core Center, the University of Pittsburgh NeuroBioBank and Brain and Tissue Repositories, the Harvard Brain Bank as part of the Autism Tissue Project (ATP), the Stanley Medical Research Institute, and the NIMH Human Brain Collection Core. Summary statistics for the ASD GWAS performed on data from the iPSYCH consortium are available in data table S5. Data and analysis code are available at https://github. com/mgandal/Shared-molecular-neuropathology-across-major-psychiatric-disorders-parallels-polygenic-overlap. The authors thank S. Parhami, H. Won, J. Stein, D. Poliodakis, J. Flint, R. Ophoff, and members of the D.H.G. laboratory for critical reading of earlier versions of this manuscript. The authors also thank B. Pasaniuc for his helpful comments and for assistance with module heritability analyses. Publisher Copyright: 2017 © The Authors.
PY - 2018/2/9
Y1 - 2018/2/9
N2 - The predisposition to neuropsychiatric disease involves a complex, polygenic, and pleiotropic genetic architecture. However, little is known about how genetic variants impart brain dysfunction or pathology. We used transcriptomic profiling as a quantitative readout of molecular brain-based phenotypes across five major psychiatric disorders—autism, schizophrenia, bipolar disorder, depression, and alcoholism—compared with matched controls. We identified patterns of shared and distinct gene-expression perturbations across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (single-nucleotide polymorphism–based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence and specificity.
AB - The predisposition to neuropsychiatric disease involves a complex, polygenic, and pleiotropic genetic architecture. However, little is known about how genetic variants impart brain dysfunction or pathology. We used transcriptomic profiling as a quantitative readout of molecular brain-based phenotypes across five major psychiatric disorders—autism, schizophrenia, bipolar disorder, depression, and alcoholism—compared with matched controls. We identified patterns of shared and distinct gene-expression perturbations across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (single-nucleotide polymorphism–based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence and specificity.
UR - http://www.scopus.com/inward/record.url?scp=85041925301&partnerID=8YFLogxK
U2 - 10.1126/science.aad6469
DO - 10.1126/science.aad6469
M3 - Article
C2 - 29439242
AN - SCOPUS:85041925301
SN - 0036-8075
VL - 359
SP - 693
EP - 697
JO - Science
JF - Science
IS - 6376
ER -