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

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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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Huckins, L. M., Dobbyn, A., Ruderfer, D. M., Hoffman, G., Wang, W., Pardiñas, A. F., … Im, H. K. (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

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