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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Our CMC-derived DLPFC prediction models are publicly available at https://github.com/laurahuckins/CMC_DLPFC_prediXcan.
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We dedicate this manuscript to the memory of Pamela Sklar, whose guidance and wisdom we miss daily. We strive to continue her legacy of thoughtful, innovative, and collaborative science. Data were generated as part of the CommonMind Consortium supported by funding from Takeda Pharmaceuticals Company Limited, F. Hoffman-La Roche Ltd and NIH grants R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1-MH-075916, P50M096891, P50MH084053S1, R37MH057881 and 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 and the NIMH Human Brain Collection Core. CMC Leadership: P. Sklar, J. Buxbaum (Icahn School of Medicine at Mount Sinai), B. Devlin, D. Lewis (University of Pittsburgh), R. Gur, C.-G. Hahn (University of Pennsylvania), K. Hirai, H. Toyoshiba (Takeda Pharmaceuticals Company Limited), E. Domenici, L. Essioux (F. Hoffman-La Roche Ltd), L. Mangravite, M. Peters (Sage Bionetworks), T. Lehner, B. Lipska (NIMH).
ROSMAP study data were provided by the Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago. Data collection was supported through funding by NIA grants P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG36836, U01AG32984, U01AG46152, the Illinois Department of Public Health, and the Translational Genomics Research Institute.
The iPSYCH-GEMS team acknowledges funding from the Lundbeck Foundation (grant no. R102-A9118 and R155-2014-1724), the Stanley Medical Research Institute, an Advanced Grant from the European Research Council (project no. 294838), the Danish Strategic Research Council the Novo Nordisk Foundation for supporting the Danish National Biobank resource, and grants from Aarhus and Copenhagen Universities and University Hospitals, including support to the iSEQ Center, the GenomeDK HPC facility, and the CIRRAU Center.
The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The data used for the analyses described in this manuscript were obtained from the GTEx Portal on September 5, 2016. BrainSpan: Atlas of the Developing Human Brain (Internet). Funded by ARRA Awards 1RC2MH089921-01, 1RC2MH090047-01, and 1RC2MH089929-01.
H.K.I. was supported by R01 MH107666-01.
E.D. has received research support from Roche during 2016–2018. T.W. has acted as advisor and lecturer to H. Lundbeck A/S. All other authors declare no conflicts of interest.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Note and Supplementary Figures 1–12
Forward stepwise conditional analysis results.
MAGMA based pathway association results.
Mutant mouse lines lacking expression of SCZ-associated genes
Gene set membership of SCZ-associated genes, according to BRAINSPAN clusters
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Huckins, L.M., Dobbyn, A., Ruderfer, D.M. et al. Gene expression imputation across multiple brain regions provides insights into schizophrenia risk. Nat Genet 51, 659–674 (2019). https://doi.org/10.1038/s41588-019-0364-4
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