Gene expression imputation across multiple brain regions provides insights into schizophrenia risk
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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.
Originalsprog | Engelsk |
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Tidsskrift | Nature Genetics |
Vol/bind | 51 |
Sider (fra-til) | 659-674 |
ISSN | 1061-4036 |
DOI | |
Status | Udgivet - 2019 |
Links
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7034316/pdf/nihms-1067544.pdf
Accepteret manuskript
ID: 238959486